Author: Dana Lewis

Understanding Fecal Elastase Test Results Including Sensitivity And Specificity And What It Means For Exocrine Pancreatic Insufficiency (EPI or PEI)

by Dana Lewis

One of the challenges related to diagnosing exocrine pancreatic insufficiency (known as EPI or PEI) is that there is no perfect test.

With diabetes, we can see in several different ways what glucose is doing: via fasting glucose levels, HbA1c (an average of 3 months glucose), and/or continuous glucose monitoring. We can also test for c-peptide to see if insulin production is ongoing.

Yet for EPI, the tests for assessing whether and how much the pancreas is producing digestive enzymes are much less direct, more invasive, or both.

Some of the tests include a breath test; an invasive secretin pancreatic function test; a 72-hour fecal fat collection test, or a single sample fecal elastase test.

  • A breath test is an indirect test, which assesses the end-product of digestion rather than digestion itself, and other conditions (like SIBO) can influence the results of this test. It’s also not widely available or widely used.
  • The secretin pancreatic function test is an invasive test involving inserting a tube into the small intestine after giving secretin, which is a hormone that stimulates the pancreas. The tube collects digestive juices produced by the pancreas, which are tested. It’s invasive, costly, and therefore not ideal.
  • For reliability, the 72-hour fecal fat collection test might be ideal, because it’s checking the amount of fat in the stool. It requires stopping enzymes, if someone is taking them already, and consuming a high fat diet. But that includes collecting stool samples for 3 days – ugh. (The “ugh” is my personal opinion, clearly).
  • The fecal elastase test, in contrast, does not require stopping enzymes. It measures human elastase, whereas digestive enzymes are typically pig-based, so you don’t have to stop enzymes when doing this test. It’s also a single stool sample (so you’re not collecting poop for 3 days in a row). The sensitivity and specificity are different based on the diagnostic threshold, which I’ll talk about below, and the accuracy can be influenced by the sample. Diarrhea, meaning watery poop, can make this test even less reliable. But that’s why it’s good that you can take enzymes while doing this test. Someone with diarrhea and suspected EPI could go on enzymes, reduce their diarrhea so they could have a formed (non-watery) sample for the elastase test, and get a better answer from the fecal elastase test.

The fecal elastase test is often commonly used for initial screening or diagnosis of EPI. But over the last two years, I’ve observed a series of problems with how it is being used clinically, based on reading hundreds of research and clinical practice articles and reading thousands of posts of people with EPI describing how their doctor is ordering/reviewing/evaluating this test.

Frequent problems include:

  • Doctors refuse to test elastase, because they don’t believe the test indicates EPI due to the sensitivity/specificity results for mild/moderate EPI.
  • Doctors test elastase, but won’t diagnose EPI when test results are <200 (especially if 100-200).
  • Doctors test elastase, but won’t diagnose EPI even when test results are <100!
  • Doctors test elastase, diagnose EPI, but then do not prescribe enzymes because of the level of elastase (even when <200).
  • Doctors test elastase, diagnose EPI, but prescribe a too-low level of enzymes based on the level of elastase, even though there is no evidence indicating elastase should be used to determine dosing of enzymes.

Some of the problems seem to result from the fact that the elastase test has different sensitivity and specificity at different threshold levels of elastase.

When we talk about “levels” of elastase or “levels” or “types” of EPI (PEI), that usually means the following thresholds / ranges:

  • Elastase <= 200 ug/g indicates EPI
  • Elastase 100-200 ug/g indicates “mild” or “mild/moderate” or “moderate” EPI
  • Elastase <100 ug/g often is referred to as “severe” EPI

You should know that:

  • People with severe EPI (elastase <100) could have no symptoms
  • People with mild/moderate EPI (elastase 100-200) could have a very high level of symptoms and be malnourished
  • People with any level of elastase indicating EPI (elastase <=200) can have EPI even if they don’t have malnourishment (usually meaning blood vitamin levels like A, D, E, or K are below range).

So let’s talk about sensitivity and specificity at these different levels of elastase.

First, let’s grab some sensitivity and specificity numbers for EPI.

  1. One paper that is widely cited, albeit old, is of sensitivity and specificity of fecal elastase for EPI in people with chronic pancreatitis. You’ll see me talk in other posts about how chronic pancreatitis and cystic fibrosis-related research is over-represented in EPI research, and it may or may not reflect the overarching population of people with EPI.But since it’s widely used, I’ll use it in the below examples, especially because this may be what is driving clinician misunderstanding about this test.With a cut off of <200 ug/g, they found that the sensitivity in detecting moderate/severe EPI is 100%, and 63% sensitivity for detecting mild EPI. At that <200 ug/g threshold, the specificity is 93% (which doesn’t distinguish between severities). With a cut off of <100 ug/g, the sensitivity for detecting mild EPI drops to 50%, but the specificity increases to 98%.This means that:
    1. 63% of people with mild EPI would be correctly diagnosed using an elastase threshold of 200 ug/g (vs. only 50% at 100 ug/g).
    2. 100% of people with moderate/severe EPI would be correctly diagnosed using an elastase threshold of 200 ug/g (compared to only 93% or 96% for moderate/severe at 100 ug/g).
    3. Only 7% of people testing <200 ug/g would be incorrectly diagnosed with EPI, and only 2% of people testing <100 ug/g.
  2. For comparison, a systematic review evaluated a bunch of studies (428 people from 14 studies) and found an average sensitivity of 77% (95% CI of 58-89%) and average specificity of 88% (95% CI of 78-93%).This sensitivity is a little higher than the above number, which I’ll discuss at the end for some context.

So what does sensitivity and specificity mean and why do we care?

At an abstract level, I personally find it hard to remember what sensitivity and specificity mean.

  • Sensitivity means: how often does it correctly identify the thing we want to identify?

This means a true positive. (Think about x-ray screening at airport security: how often do they find a weapon that is there?)

  • Specificity means: how often does it avoid mistakenly identifying the thing we want to identify? In other words, how often is a positive a true positive rather than a false positive?

(Think about x-ray screening at airport security: how often does it correctly identify that there are no weapons in the bag? Or how often do they accidentally think that your jam-packed bag of granola and snacks might be a weapon?)

Here is how we apply this to fecal elastase testing for EPI.

For those with moderate/severe EPI, the test is 100% sensitive at correctly detecting those cases if you use an elastase cut off of <200 ug/g. For those with mild EPI, the test drops to only being 63% sensitive at correctly detecting all of those cases. And 93% of the time, the test correctly excludes EPI when it doesn’t exist (at a <200 ug/g cut off, vs. 98% of the time at a <100 ug/g cut off). Conversely, 7% (which we get from subtracting 93% from 100%) of people with elastase <200 ug/g might not have EPI, and 2% (98% subtracted from 100%) of people with elastase <100 ug/g might not have EPI.

Here’s another way of thinking about it, using a weather forecast analogy. Think about how easy it is to predict rain when a major storm is coming. That’s like trying to detect severe EPI, it’s a lot easier and forecasters are pretty good about spotting major storms.

But in contrast, what about correctly predicting light rain? In Seattle, that feels close to impossible – it rains a lot, very lightly. It’s hard to predict, so we often carry a light rain jacket just in case!

And for mild EPI, that’s what the sensitivity of 63% means: less than two thirds of the time can it correctly spot mild EPI by looking for <200 ug/g levels, and only half the time by looking for <100 ug/g. The signal isn’t as strong so it’s easier to miss.

The specificity of 93% means that the forecast is pretty good at identifying not-rainy-days, even with a cut off of elastase >200 ug/g. But, occasionally (around 7/100 times), it’s wrong.

Table comparing the sensitivity for severe and mild EPI alongside specificity, plus comparing to weather forecast ability for rain in major storms.

Why might clinicians be incorrectly using the value of these numbers for the fecal elastase test?

I hypothesize that in many cases, for the elastase levels now considered to indicate mild/moderate EPI (elastase 100-200 ug/g), clinicians might be accidentally swapping the sensitivity (63%) and specificity (93%) numbers in their mind.

What these numbers tell us is that 63% of the time, we’ll catch mild EPI through elastase testing. This means 37/100 people with actual mild EPI might be missed!

In contrast, the specificity of 93% tells us about accidental false positives, and that 7/100 people without EPI might accidentally get flagged as having possible EPI.

Yet, the clinical practice in the real-world seems to swap these numbers, acting as if the accuracy goes the other way, suspecting that elastase 100-200 doesn’t indicate EPI (e.g. thinking 37/100 false positives, which is incorrect, the false positive rate is 7/100).

There’s plenty of peer-reviewed and published evidence that people with elastase 100-200 have a clear symptom burden. There’s even a more recent paper suggesting that those with symptoms and elastase of 200-500 benefit from enzymes!

Personally, as a person with EPI, I am frustrated when I see/hear cases of people whose clinicians refuse testing, or don’t prescribe PERT when elastase is <=200 ug/g, because they don’t believe elastase 100-200 ug/g is an accurate indicator of EPI. This data shows that’s incorrect. Regardless of which paper you use and which numbers you cite for sensitivity and specificity, they all end up with way more common rates of false negatives (missing people with EPI) than false positives.

And, remember that many people with FE 200-500 benefit from enzymes, too. At a cutoff of 200 ug/g, the number of people we are likely to miss (sensitivity) at the mild/moderate level is much higher than the number of false positives who don’t actually have EPI. That puts the risk/benefit calculation – to me – such that it warrants using this test, putting people on enzymes, and evaluating symptom resolution over time following PERT dosing guidelines. If people’s symptom burden does not improve, titrating PERT and re-testing elastase makes sense (and that is what the clinical guidelines say to do), but the cost of missing ~37 people out of 100 with EPI is too high!

Let’s also talk about elastase re-testing and what to make of changed numbers.

I often also observe people with EPI who have their elastase re-tested multiple times. Here are some examples and what they might mean.

  • A) Someone who tests initially with a fecal elastase of 14, later retests as 16, then 42 ug/g.
  • B) Someone who tests initially at 200 and later 168.
  • C) Someone who tests initially at 72 and later 142.
  • D) Someone who tests initially as 112 and later 537.

Remember the key to interpreting elastase is that <=200 ug/g is generally accepted as indicating EPI. Also it’s key to remember that the pancreas is still producing some enzymes, thus elastase production will vary slightly. But in scenarios A, B, and C – those changes are not meaningful. In scenario A, someone still has clear indicators of severe (elastase <100) EPI. Slight fluctuations don’t change that. Same for scenario B, 200 and 168 are both still in mild/moderate EPI (elastase <=200). Even scenario C isn’t very meaningful, even though there is an “increase”, this is still clearly EPI.

In most cases, the fluctuations in test results are likely a combination of both natural fluctuations in pancreas production and/or test reliability. If someone was eating a super low fat diet, taking enzymes effectively, that may influence how the pancreas is producing its natural enzymes – we don’t actually know what causes the pancreas to fluctuate the natural enzyme levels.

The only case that is meaningful in these examples is scenario D, where someone initially had a result of 112 and later clearly above the EPI threshold (e.g. 537). There are a few cases in the literature where people with celiac seem to have temporary EPI and later their elastase production returns to normal. This hasn’t been documented in other conditions, which doesn’t mean that it’s not possible, but we don’t know how common it is. It’s possible the first sample of 112 was due to a watery sample (e.g. during diarrhea) or other testing inaccuracy, too. If a third test result was >500, I’d assume it was a temporary fluctuation or test issue, and that it’s not a case of EPI. (Yay for that person!). If it were me (and I am not a doctor), I’d have them try out a period without enzymes to ensure that symptoms continued to be managed effectively. If the third test was anywhere around 200 or below, I’d suspect something going on contributing to fluctuations in pancreatic production and not be surprised if enzymes were continued to be needed, unless the cause could be resolved.

But what about scenario C where someone “went from severe to mild/moderate EPI”?!

A lot of people ask that. There’s no evidence in the hundreds (seriously, hundreds) of papers about EPI that indicate clearly that enzymes should be dosed based on elastase level, or that there’s different needs based on these different categories. The “categories” of EPI originally came from direct measurements of enzyme secretion via invasive tests, combined with quantitative measurements of bicarbonate and fat in stools. Now that fecal elastase is well established as a non-invasive diagnostic method, severities are usually estimated based on the sensitivity of these cutoffs for detecting EPI, and that’s it. The elastase level doesn’t actually indicate the severity of the experience through symptoms, and so enzymes should be dosed and adjusted based on the individual’s symptoms and their diet.

In summary:

  • Elastase <=200 ug/g is very reliable, indicates EPI, and warrants starting PERT.
  • There is one small study suggesting even people with elastase 200-500 might benefit from PERT, if they have symptoms, but this needs to be studied more widely.
  • It’s possible clinicians are conflating the sensitivity and specificity, thus misunderstanding how accurately elastase tests can detect cases of mild/moderate EPI (when elastase is 100-200 ug/g).

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Let me know if anyone has questions about elastase testing, sensitivity, and specificity that I haven’t answered here! Remember I’m not a doctor, and you should certainly talk with your doctor if you have questions about your specific levels. But make sure your doctor understands the research, and feel free to recommend this post to them if they aren’t already familiar with it: https://bit.ly/elastase-sensitivity-specificity

Personalized Story Prompts for Kids Books and Early Reader Books

by Dana Lewis

For the holidays this year, I decided to try my hand at creating another set of custom, illustrated stories for my nieces and nephews (and bonus nieces and nephews). I have a few that are very advanced readers and/or too old for this, but I ended up with a list of 8 kids in my life from not-yet-reading to beginning reading to early 2nd grade reading level. I wanted to write stories that would appeal to each kid, include them as the main character, be appropriate for their reading (or read-to) level, and also include some of their interests.

Their interests were varied which made it quite a challenge! Here’s the list I worked from:

  • 2nd grade reading level, Minecraft
  • early 2nd grade reading level: soccer, stunt biking, parkour, ninja, Minecraft
  • beginning reading level: soccer, stunt biking, ninja, Spiderman
  • beginning reading level: Peppa Pig, moko jumbies
  • (read to younger child): Minnie Mouse, Peppa Pig, Bluey, and tea parties
  • (read to younger child): Bluey, Olaf, Elsa, & Anna
  • (read to younger child): cars/vehicles

I enlisted ChatGPT, an LLM, and ended up creating stories for each kid, matching their grade levels and interests, then illustrating them.

But illustrating them was actually a challenge (still), trying to create images with similar characters that would be on every page of the story and similar enough throughout that they were the “same” character.

Illustration challenges and how I got successful prompts:

My first pass on images wasn’t very good. I could get basic details to repeat, but often had images that looked like this – slightly different style and character throughout:

8 different illustrations in slightly different styles and almost different characters of a girl with blonde, shoulder length hair and a purple dress in an enchanted forest

Different styles throughout and that makes it look like a different character, even though it’s the same character in the whole story. This was a book to read to a <3 year old, though, and I thought she wouldn’t mind the different styles and left it as is. I also battled with adding, for personal use, the characters that most interested her: Peppa Pig and Minnie Mouse.

Interestingly, if I described with a prompt to illustrate a scene including a character “inspired by, but distinct from, Peppa Pig”…it essentially drew Peppa Pig or a character from it. No problems.

But if you gave the same prompt “inspired by, but distinct from, Minnie Mouse”? No go. No image at all: ChatGPT would block it for copyright reasons and wouldn’t draw any of the image. I riffed a bunch of times and finally was able to prompt a good enough mouse with round ears and a red dress with white polka dots. I had to ultimately illustrate the mouse character alone with the human character, because if I tried to get a Peppa-inspired character and then separately a mouse character, it wanted to draw the mouse with a pig-style face in the correct dress! I could never work around that effectively for the time I had available (and all the other books I was trying to illustrate!) so I stopped with what I had.

This was true for other characters, too, with copyright issues. It won’t draw anything from or like Bluey – or Frozen, when prompted. But I could get it to draw “an ethereal but warm, tall female adult with icy blonde hair, blue eyes, in an icy blue dress”, which you can see in the fourth image on the top row here:

Another series of illustrations with slightly different characters but closer in style throughout. there's one image showing a Frozen-inspired female character that I got by not prompting with Frozen.

I also managed to get slightly closer matching characters throughout this, but still quite a bit of variability. Again, for a young being-read-to-child, it was good enough for my purposes. (I never could get it to draw a Bluey-like character, even when I stopped referencing Bluey by name and described the shape and character, so I gave up on that.)

I tried a variety of prompts and series of prompts for each book. Sometimes, I would give it the story and prompt it with each page’s text, asking for an illustration and to keep it in the same style and the same character as the previous image. That didn’t work well, even when I told it in every prompt to use the same style and character plus the actual image prompt. I then tried to create a “custom” GPT, with the GPT’s instructions to use the same style throughout. That started to give me slightly better results, but I still had to remind it constantly to use the same style.

I also played around with taking an image that I liked, starting a new chat, and asking it to describe that image. Then I’d use that prompt to create a new prompt, describing the character in the same way. That started to get me slightly better results, especially when I did so using the custom GPT I had designed (you can try using this GPT here). I started to get better, more consistent characters:

A series of images of a young cartoon-drawn boy with wavy blonde hair riding a bike through an enchanted forest.

 

A series of drawings of a cartoon-like character with spiky blonde hair, blue eyes, and various outfits including a ninja costume

Those two had some variability, but a lot improved beyond the first several books. They are for the beginning and second-grade reading levels, too, so they are older kids with more attention to detail so it was worth the extra effort to try to get theirs to be more consistent.

The last one with the ninja and ninja outfits is another one that ran into copyright issues. I tried to have it illustrate a character inspired by, but distinct from, Spiderman – nope, no illustration at all. I asked it to illustrate the first picture in the soccer park with a spider strand looping in the corner of the image, like Spiderman had swung by but was out of sight and not picture – NOPE. You can’t even get an image that has Spiderman in the prompt at all, even if Spiderman isn’t in the picture! (I gave up and moved on without illustrating spiderwebs, even though Spiderman is described in the story).

My other favorite and pretty consistent one was two more of the early reader ones:

A series of images showing a young cartoon boy with wavy brown hair at a car fair

The hard part from that book was actually trying to do the cars consistently, rather than the human character. The human character was fairly consistent (although in different outfits, despite clear outfit prompts – argh) throughout, because I had learned from the previous images and prompt processes and used the Custom GPT, but the cars varied more. But, for a younger reader, hopefully that doesn’t matter.

The other, more-consistent character one for an early reader had some variations in style but did a better job matching the character throughout even when the style changed.

Another example with a mostly consistent young cartoon drawn girl with whispy blonde pigtails and big blue eyes, plus moko jumbies and peppa pig

How I wrote each story:

I also found some processes for building better stories. Again, see the above list of very, varied interests for each kid. Some prompts were straight forward (Minecraft) and other were about really different characters or activities (moko jumbies and Peppa Pig? Minnie Mouse and Peppa Pig? soccer ninja and Minecraft?).

What I ended up doing for each:

  1. In a new ChatGPT window (not the custom GPT for illustrating): Describe the reading level; the name of the character(s); and the interests. Ask it to brainstorm story ideas based on these interests.
  2. It usually gave 3 story ideas in a few sentences each, including a title. Sometimes, I would pick one and move on. Other times, I would take one of the ideas and tweak it a bit and ask for more ideas based on that. Or, I’d have it try again generally, asking for 3 more ideas.
  3. Once I had an idea that I liked, I would ask it to outline the story, based on the chosen story idea and the grade level we were targeting. Sometimes I would tweak the title and other times I would take the title as-is.
  4. Once it had the outline, I could have it then write the entire story (especially for the younger, beginner reader or read-to levels that are so short), but for the “chapter” books of early 2nd and 2nd grade reading level, I had it give me a chapter at a time, based on the outline. As each chapter was generated, I edited and tweaked it and took the text to where I would build the book. Sometimes, I would re-write the whole chapter myself, then give it back the chapter text and ask it to write the next one. If you didn’t give it back, it wouldn’t know what the chapter ended up as, so this is an important step to do when you’re making more than minor sentence construction changes.
  5. Because I know my audience(s) well, I tweaked it heavily as I went, incorporating their interests. For example, in the second images I showed above, there’s a dancing dog. It’s their actual dog, with the dog named in the story along with them as characters. Or in the chapter book for the character with the bike, it described running up a big mountain on a quest and being tired. I tossed in an Aunt-Dana reference including reminding the character about run-walking as a way to keep moving forward without stopping and cover the distance that needs to be covered. I also tweaked the stories to include character traits (like kindness) that each child has, and/or behaviors that their family prioritizes.

I described the images processes first, then the story writing, in this blog post, but I actually did the opposite for each book. I would write (brainstorm, outline, write, edit, write) the entire book, then I would go start a new chat window (eventually solely using my custom GPT) and ask for illustrations. Sometimes, I would give it the page of the story’s text and ask it to illustrate it. That’s helpful when you don’t know what to illustrate, and it did fairly well for some of the images (especially the Minecraft-inspired ones!). Ultimately, though, I would often get an image, ask what the prompt was for the image, tweak the prompt, and give it back to better match the story or what I wanted to illustrate. Once I was regularly asking for the image prompts, I had realized that giving the character details repeatedly for every image helped with consistency. Then I would use the ad-nauseam details myself for a longer prompt, which resulted in better images throughout, so I spent more energy deciding myself what to illustrate to best match the story.

All in all, I made 7 custom books (and 8 copies, one of the Minecraft books I copied and converted to a different named character for a friend’s child!). Between writing and editing, and illustrating, I probably spent an average of one hour per book! That’s a lot of time, but it did get more efficient as I went, and in some cases the hour included completely starting over and re-working the images in the book for consistency compared to the version I had before. The next books I create will probably take less time, both because I figured out the above processes but also because hopefully DALL*E and other illustration tools will get better about being able to illustrate the same character consistently across multiple prompts to illustrate a story.

How other people can use this to create stories – and why:

I have been so excited about this project. I love, love, love to read and I love reading with my nieces and nephews (and bonus kids in my life) and finding books that match their interest and help spark or maintain their love of reading. That’s why I did this project, and I have been bursting for WEEKS waiting to be able to give everyone their books! I wanted it to be a surprise for their parents, too, which meant that I couldn’t tell 2/3 of my closest circles about my cool project.

One of my friends without young kids that I finally told about my project loved the idea: she works as staff at an elementary school, supporting some students who are working on their reading skills who are nonverbal. She thought it would be cool to make a book for one student in particular, and described some of her interests: violins, drums, raspberries, and unicorns. I was in the car when she told me this, and I was able to follow the same process as above in the mobile ChatGPT app and list the interests, ask for a brainstorm of story ideas for a beginning reading level style book that had some repetitive text using the interests to aid in reading. It created a story about a unicorn who gathers other animals in the forest to play in an orchestra (with drums and violins) and eat raspberries. I had it illustrate the story, and it did so (with slightly different unicorns throughout). I only had to have it re-draw one image, because it put text in one of the last images that didn’t need to be there.

Illsutrations from a quick story about a unicorn, drums, violin, and an orchestra, plus raspberries

It was quick and easy, and my friend and her student LOVED it, and the other teachers and staff at the school are now working on personalized books for a lot of other students to help them with reading skills!

It really is an efficient and relatively easy way to generate personalized content; it can do so at different reading levels (especially when a teacher or someone who knows the student can tweak it to better match the reading level or sounds and words they are working on next); and you can generate pretty good matching illustrations too.

The hardest part is consistent characters; but when you don’t need consistency throughout a whole book, the time it takes drops to ~5 or so minutes to write, tweak, and illustrate an entire story.

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Illustrations require a paid ChatGPT account, but if you have one and want to try out the custom GPT I built for (slightly more consistent) illustrations of stories, you can check it out here.

Custom stories: prompting and effective illustrating with ChatGPT, a blog post by Dana M. Lewis from DIYPS.org

Systematic Review of PERT Research and Guidelines for Exocrine Pancreatic Insufficiency (EPI or PEI)

by Dana Lewis

New Systematic Review And Evaluation of Pancreatic Enzyme Replacement Therapy (PERT) Dosing Guidelines and Research for Exocrine Pancreatic Insufficiency (EPI or PEI)

I wrote a new paper evaluating the research behind pancreatic enzyme replacement therapy (aka, PERT) dosing for people with exocrine pancreatic insufficiency (known as EPI or PEI). I decided to do this research and write this paper because in my previous papers on EPI, I saw a lot of inconsistencies in when PERT was studied, how it was studied, and how that research was then used to develop guidelines.

(Big thanks to Julia Blanchette, Jordan Rieke, Claudia Lewis (no relation), Khaleal Almusaylim , and Anuhya Kanchibhatla for collaborating on this research and co-authoring the paper with me!)

You can find an author copy of the paper here, or see it on the journal website here. As a reminder, all my research papers have author copies and you can find them at DIYPS.org/research! I also have several other EPI-related articles.

A note on methods – this is a systematic review, meaning I used keywords to search multiple electronic databases to find articles about exocrine pancreatic insufficiency. I screened articles to make sure they were about EPI in humans and focused on English-language articles. We then reviewed the title and abstract of 2,530 remaining articles (!) that mentioned EPI, and excluded those that were not focused on EPI or a co-condition and unlikely to include guidelines or specific dose information related to EPI. That left 820 articles, which we then screened again looking for the full text and reviewing them for relevancy. I ended up reading 257 papers that we used for the basis of the research described below!

We found 7 key findings from this body of research:

  1. PERT Titration Protocols Aren’t Very Specific (or useful as typically written)“Most PERT dosing guidelines do not articulate a specific, defined dose range. Instead, PERT is commonly dosed with a general starting dose, such as 50,000 units of lipase per meal and 25,000 units of lipase per snack. If needed, guidelines then recommend increasing (i.e., titrating) the dosage by a factor of two to three (commonly described as increasing by 2x – 3x), and if symptoms persist, adding a proton pump inhibitor (PPI) before exploring other potential diagnoses. As a result, providers are prompted to focus primarily on the starting dose, rather than the full range of recommended doses.”

    I ended up crafting a table (Table 2) for the paper that shows how this dosing process can result in much bigger doses – such as 150,000 units of lipase per meal – to contrast  how prescriptions are often given at very low doses in comparison and often are not sufficient.

    This is a similar version of the table that I had developed for a previous blog post talking about the ranges of PERT dosing:
    Examples of PERT starting doses of 25,000, 40,000, and 50,000 (plus half that for snacks) and what the dose would be if increased according to guidelines to 2x and 3x, plus the sum of the total daily dose needed at those levels.
    Most guidelines, and the underlying studies, do not do a good job describing what doses people actually took in the studies. This may influence then providers’ understanding of how much PERT is needed.

  1. People are not taking enough PERTLike I found in my own previous research, there have been numerous studies showing that people are not getting prescribed enough PERT. This is both based on people reporting ongoing symptoms and reduced quality of life, but also studies that show a huge gap between the doses recommended to start with in guidelines and the fact that >90% of the time, providers don’t prescribe anywhere near this dose (and therefore are not prescribing enough PERT).
  2. Comparing different PERT studies is challengingWhen PERT studies are done, they are typically for safety and efficacy at a specific dose. Very few studies record what dosing people take when they are allowed to take the amount that they need to effectively reduce symptoms.

    As a result, we don’t know how much PERT people need (on average) in order to reduce symptoms.

  3. PERT Dosing Studies and Guidelines Only Focus on Fat (and we need to talk about protein)If you’ve read my previous blog posts about ratios and PERT dosing, you’ll notice I talk about protein dosing. For some people with EPI, protein dosing makes a huge difference in symptom outcomes.

    However, PERT is described based on units of lipase (for fat digestion) and primarily studied for fat, which means that doctors often prescribe it and only talk about changing PERT doses for different sized meals based on fat.

    This is a huge area of need for future studies to determine what role protein malabsorption plays for people with EPI. I suspect, based on personal experience and talking to others in the EPI community about when they have symptoms, this influences a lot of PERT dosing efficacy in real life.

  4. PERT Dosing Guidelines Are Very Different Around The World – But Should They Be?There are dozens of PERT dosing guidelines by condition, and in different parts of the world. They don’t always agree!

    My hypothesis is that this is not because of a true varying need geographically for PERT dosing (meaning your PERT dosing needs aren’t likely different if you live in South America or Europe), but because of the selection of studies used to determine the guidelines. And because most studies have only looked at basic, minimal doses for safety/efficacy, they haven’t studied how much people need to eliminate symptoms. There’s also no data on what people eat in these studies, so the ‘regional’ differences perceived may be a result of different composition of foods, but we have no evidence for this because the studies are poorly described and/or the studies don’t actually record this.

  5. PERT Dosing Guidelines Are Different By Co-Condition The majority of the studies on EPI and PERT dosing are in chronic pancreatitis (CP). As I’ve written previously, this is likely a small fraction of the number of people with EPI. But because this body of research on CP and EPI is so big, it has a very loud voice in determining what the guidelines say about PERT dosing. (Cystic fibrosis (CF) is the second-most studied and also plays the second-biggest role in influencing guidelines).

    If you want to dig in to the differences between conditions, note that the guidelines are influenced by the volume of studies, and so many conditions (such as diabetes) have very few guidelines and very few studies, so most of the ‘guidance’ on dosing is extrapolated from CF and/or chronic pancreatitis. It’s therefore very possible that people with EPI need more dosing or different dosing than is studied in those co-conditions – but we don’t know more because it hasn’t been studied!

    (I have a lot of details in the paper about what has been studied, and you can look at Table 4 for a summary of some of the less-studied conditions or check out the appendix for a narrative description of all of the co-conditions and their bodies of research.)

  6. PERT Dosing Is Determined By Clinicians And They’re Not Following The GuidelinesMost doctors and clinicians are not following PERT guidelines. This means that many people are prescribed a too-low dose of PERT according to the guidelines. This could be because providers are unaware of the guidelines; or don’t agree with the guidelines; or have not seen evidence showing clear effects of PERT on symptom resolution (in part because this hasn’t been studied!).

    More work needs to be done to understand why patients with EPI are under-prescribed and under-dosed when prescribed, and understanding barriers for clinicians may be a key factor to study moving forward.

So, what next?

Here’s what I want to see studied next for EPI, based on the findings in this paper:

  1. All PERT studies should clearly document the titration protocol in a way that can be understood and reproduced.
  2. PERT studies should record what dose people take throughout or at the end of the trial.
  3. PERT should be studied for symptom resolution. (PS – take the anonymous EPI symptom survey if you haven’t already!) This should be done outside of conditions such as chronic pancreatitis, because there is pain associated with CP that is confounding the results of EPI symptoms. And, CP is a tiny fraction of EPI and should not therefore be used to determine whether PERT is effective at resolving EPI-related symptoms.
  4. We need more awareness of the prevalence of EPI and for clinicians to screen for EPI. When elastase results are low (e.g. less than or equal to 200-ish), providers should initiate a trial of PERT and aid people in increasing their doses to the point that symptoms resolve. We need to study the barriers/factors determining why providers are not screening for EPI and why they are not prescribing PERT.
  5. We need more tools to help doctors and patients increase PERT dosing to achieve symptom resolution.
  6. We need studies on the effect of protein in the diet of people with EPI and PERT dosing to improve protein digestion.

If clinicians are reading this, here is your call to action:

  • Screen for EPI using a fecal elastase test. This includes anyone presenting with GI symptoms, not just in people that you suspect have chronic pancreatitis. You’re probably missing a not-insignificant number of people coming to you with EPI. For example, a previous systematic review shows EPI is likely much more common in people with diabetes than celiac or gastroparesis!
  • If fecal elastase results are around or below 200, prescribe PERT. Yes, even if they’re close to 200 – PERT can help for those with EPI who have symptoms!

    This study was published after our systematic review, so I wasn’t able to cite it in the paper, but includes evidence that PERT also can help reduce symptoms when elastase is 200-500. Don’t get too hung up on the elastase result, it’s not very precise but that doesn’t mean you shouldn’t prescribe a trial of PERT. 
  • Prescribe PERT at a minimum of 40,000-50,000 units PER MEAL and tell patients specifically to increase dosing as needed, such as when they’re eating larger meals. Many people need much larger doses (evidence here). Give guidance on how to adjust based on meals. If you want tools, consider things like PERT Pilot or other calculators to aid in matching dosing to food intake. This matches the recent AGA Clinical Practice Update on the Epidemiology, Evaluation, and Management of Exocrine Pancreatic Insufficiency (EPI) by Whitcomb et al which emphasizes that “PERT treats the meal, not the pancreas” meaning that PERT should match food intake.The level of elastase does NOT determine the dosing need, and the size of your prescriptions shouldn’t be influenced by the elastase result.

    All EPI needs PERT, and PERT needs should be driven by the individual’s symptoms and the dose it takes to reduce or eliminate their symptoms.

—

Here’s how to cite this paper:

Lewis DM, Rieke, JG, Almusaylim, K, Kanchibhatla, A, Blanchette, JE, Lewis, C. Exocrine Pancreatic Insufficiency Dosing Guidelines For Pancreatic Enzyme Replacement Therapy Vary Widely Across Disease Types. Digestive Diseases and Sciences. 2023. https://doi.org/10.1007/s10620-023-08184-w

Accepted, Rejected, and Conflict of Interest in Gastroenterology (And Why This Is A Symptom Of A Bigger Problem)

by Dana Lewis

Recently, someone published a new clinical practice update on exocrine pancreatic insufficiency (known as EPI or PEI) in the journal called Gastroenterology, from the American Gastroenterology Association (AGA). Those of you who’ve read any of my blog posts in the last year know how much I’ve been working to raise awareness of EPI, which is very under-researched and under-treated clinically despite the prevalence rates in the general population and key sub-populations such as PWD. So when there was a new clinical practice update and another publication on EPI in general, I was jazzed and set out to read it immediately. Then frowned. Because, like so many articles about EPI, it’s not *quite* right about many things and it perpetuates a lot of the existing problems in the literature. So I did what I could, which was to check out the journal requirements for writing a letter to the editor (LTE) in response to this article and drafting and submitting a LTE article about it. To my delight, on October 17, 2023, I got an email indicating that my LTE was accepted.

You can find my LTE as a pre-print here.

See below why this pre-print version is important, and why you should read it, plus what it reminds us about what journal articles can or cannot tell us in healthcare.

Here’s an image of my acceptance email. I’ll call out a key part of the email:

A print of the acceptance email I received on October 17, 2023, indicating my letter would be sent to authors of the original articles for a chance to choose to respond (or not). Then my LTE would be published.

Letters to the Editor are sent to the authors of the original articles discussed in the letter so that they might have a chance to respond. Letters are not sent to the original article authors until the window of submission for letters responding to that article is closed (the last day of the issue month in which the article is published). Should the authors choose to respond to your letter, their response will appear alongside your letter in the journal.

Given the timeline described, I knew I wouldn’t hear more from the journal until the end of November. The article went online ahead of print in September, meaning likely officially published in October, so the letters wouldn’t be sent to authors until the end of October.

And then I did indeed hear back from the journal. On December 4, 2023, I got the following email:

A print of the email I received saying the LTE was now rejected
TLDR: just kidding, the committee – members of which published the article you’re responding to – and the editors have decided not to publish your article. 

I was surprised – and confused. The committee members, or at least 3 of them, wrote the article. They should have a chance to decide whether or not to write a response letter, which is standard. But telling the editors not to publish my LTE? That seems odd and in contrast to the initial acceptance email. What was going on?

I decided to write back and ask. “Hi (name redacted), this is very surprising. Could you please provide more detail on the decision making process for rescinding the already accepted LTE?”

The response?

Another email explaining that possible commercial affiliations influenced their choice to reject the article after accpeting it originally
“In terms of this decision, possible commercial affiliations, as well as other judgments of priority and relevance among other submissions, dampened enthusiasm for this particular manuscript. Ultimately, it was not judged to be competitive for acceptance in the journal. “

Huh? I don’t have any commercial affiliations. So I asked again, “Can you clarify what commercial affiliations were perceived? I have none (nor any financial conflict of interest; nor any funding related to my time spent on the article) and I wonder if there was a misunderstanding when reviewing this letter to the editor.”

The response was “There were concerns with the affiliation with OpenAPS; with the use of the term “guidelines,” which are distinct from this Clinical Practice Update; and with the overall focus being more fit for a cystic fibrosis or research audience rather than a GI audience.”

A final email saying the concern with my affiliation of OpenAPS, which is not a commercial organization nor related to the field of gastroenterology and EPI

Aha, I thought, there WAS a misunderstanding. (And the latter makes no sense in the context of my LTE – the point of it is that most research and clinical literature is a too-narrow focus, cystic fibrosis as one example – the very point is that a broad gastroenterology audience should pay attention to EPI).

I wrote back and explained how I, as a patient/independent researcher, struggle to submit articles to manuscript systems without a Ringgold-verified organization. (You can also listen to me describe the problem in a podcast, here, and I also talked about it in a peer-reviewed journal article about citizen science and health-related journal publishing here). So I use OpenAPS as an “affiliation” even though OpenAPS isn’t an organization. Let alone a commercial organization. I have no financial conflict of interest related to OpenAPS, and zero financial conflict of interest or commercial or any type of funding in gastroenterology at all, related to EPI or not. I actually go to such extremes to describe even perceived conflicts of interest, even non-financial ones, as you can see this in my disclosure statement publicly available from the New England Journal of Medicine here on our CREATE trial article (scroll to Supplemental Information and click on Disclosure Forms) where I articulate that I have no financial conflicts of interest but acknowledge openly that I created the algorithm used in the study. Yet, there’s no commercial or financial conflict of interest.

A screenshot from the publicly available disclosure form on NEJM's site, where I am so careful to indicate possible conflicts of interest that are not commercial or financial, such as the fact that I developed the algorithm that was used in that study. Again, that's a diabetes study and a diabetes example, the paper we are discussing here is on exocrine pancreatic insufficiency (EPI) and gastroenterology, which is unrelated. I have no COI in gastroenterology.

I sent this information back to the journal, explaining this, and asking if the editors would reconsider the situation, given that the authors (committee members?) have misconstrued my affiliation, and given that the LTE was originally accepted.

Sadly, there was no change. They are still declining to publish this article. And there is no change in my level of disappointment.

Interestingly, here is the article in which my LTE is in reply to, and the conflict of interest statement by the authors (committee members?) who possibly raised a flag about supposed concern about my (this is not true) commercial affiliation:

The conflict of interest statement for authors from the article "AGA Clinical Practice Update on the Epidemiology, Evaluation, and Management of Exocrine Pancreatic Insufficiency 2023"

The authors disclose the following: David C. Whitcomb: consultant for AbbVie, Nestlé, Regeneron; cofounder, consultant, board member, chief scientific officer, and equity holder for Ariel Precision Medicine. Anna M. Buchner: consultant for Olympus Corporation of America. Chris E. Forsmark: grant support from AbbVie; consultant for Nestlé; chair, National Pancreas Foundation Board of Directors.

As a side note, one of the companies with consulting and/or grant funding to two of the three authors is the biggest manufacturer of pancreatic enzyme replacement therapy (PERT), which is the treatment for EPI. I don’t think this conflict of interest makes these clinicians ineligible to write their article; nor do I think commercial interests should preclude anyone from publishing – but in my case, it is irrelevant, because I have none. But, it does seem weird given the stated COI for my (actually not a) COI then to be a reason to reject a LTE, of all things.

Here’s the point, though.

It’s not really about the fact that I had an accepted article rejected (although that is weird, to say the least…).

The point is that the presence of information in medical and research journals does not mean that they are correct. (See this post describing the incorrect facts presented about prevalence of EPI, for example.)

And similarly, the lack of presence of material in medical and research journals does not mean that something is not true or is not fact! 

There is a lot of gatekeeping in scientific and medical research. You can see it illustrated here in this accepted-rejected dance because of supposed COI (when there are zero commercial ties, let alone COI) and alluded to in terms of the priority of what gets published.

I see this often.

There is good research that goes unpublished because editors decide not to prioritize it (aka do not allow it to get published). There are many such factors in play affecting what gets published.

There are also systemic barriers.

  • Many journals require fees (called article processing charges or “APC”s) if your article is accepted for publication. If you don’t have funding, that means you can’t publish there unless you want to pay $2500 (or more) out of pocket. Some journals even have submission fees of hundreds of dollars, just to submit! (At least APCs are usually only levied if your article is accepted, but you won’t submit to these journals if you know you can’t pay the APC). That means the few journals in your field that don’t require APCs or fees are harder to get published in, because many more articles are submitted (thus, influencing the “prioritization” problem at the editor level) to the “free” journals.
  • Journals often require, as previously described, your organization to be part of a verified list (maintained by a third party org) in order for your article to be moved through the queue once submitted. Instead of n/a, I started listing “OpenAPS” as my affiliation and proactively writing to admin teams to let them know that my affiliation won’t be Ringgold-verified, explaining that it’s not an org/I’m not at any institution, and then my article can (usually) get moved through the queue ok. But as I wrote in this peer-reviewed article with a lot of other details about barriers to publishing citizen science and other patient-driven work, it’s one of many barriers involved in the publication process. It’s a little hard, every journal and submission system is a little different, and it’s a lot harder for us than it is for people who have staff/support to help them get articles published in journals.

I’ve seen grant funders say no to funding researchers who haven’t published yet; but editors also won’t prioritize them to publish on a topic in a field where they haven’t been funded yet or aren’t well known. Or they aren’t at a prestigious organization. Or they don’t have the “right” credentials. (Ahem, ahem, ahem). It can be a vicious cycle for even traditional (aka day job) researchers and clinicians. Now imagine that for people who are not inside those systems of academia or medical organizations.

Yet, think about where much of knowledge is captured, created, translated, studied – it’s not solely in these organizations.

Thus, the mismatch. What’s in journals isn’t always right, and the process of peer review can’t catch everything. It’s not a perfect system. But what I want you to take away, if you didn’t already have this context, is an understanding that what’s NOT in a journal is not because the information is not fact or does not exist. It may have not been studied yet; or it may have been blocked from publication by the systemic forces in play.

As I said at the end of my LTE:

“It is also critical to update the knowledge base of EPI beyond the sub-populations of cystic fibrosis and chronic pancreatitis that are currently over-represented in the EPI-related literature. Building upon this updated research base will enable future guidelines, including those like the AGA Clinical Practice Update on EPI, to be clearer, more evidence-based, and truly patient-centric ensuring that every individual living with exocrine pancreatic insufficiency receives optimal care. “

PS – want to read my LTE that was accepted then rejected, meaning it won’t be present in the journal? Here it is on a preprint server with a DOI, which means it’s still easily citable! Here’s an example citation:

Lewis, D. Navigating Ambiguities in Exocrine Pancreatic Insufficiency. OSF Preprints. 2023. DOI: 10.31219/osf.io/xcnf6

New Survey For Everyone (Including You – Yes, You!) To Help Us Learn More About Exocrine Pancreatic Insufficiency

by Dana Lewis

If you’ve ever wanted to help with some of my research, this is for you. Yes, you! I am asking people in the general public to take a survey (https://bit.ly/GI-Symptom-Survey-All) and share their experiences.

Why?

Many people have stomach or digestion problems occasionally. For some people, these symptoms happen more often. In some cases, the symptoms are related to exocrine pancreatic insufficiency (known as EPI or PEI). But to date, there have been few studies looking at the frequency of symptoms – or the level of their self-rated severity – in people with EPI or what symptoms may distinguish EPI from other GI-related conditions.

That’s where this survey comes in! We want to compare the experiences of people with EPI to people without EPI (like you!).

Will you help by taking this survey?

Your anonymous participation in this survey will help us understand the unique experiences individuals have with GI symptoms, including those with conditions like exocrine pancreatic insufficiency (EPI). In particular, data contributed by people without EPI will help us understand how the EPI experience is different (or not).

A note on privacy:

  • The survey is completely anonymous; no identifying information will be collected.
  • You can stop the survey at any point.

Who designed this survey:

Dana Lewis, an independent researcher, developed the survey and will manage the survey data. This survey design and the choice to run this survey is not influenced by funding from or affiliations with any organizations.

What happens to the data collected in this survey:

The aggregated data will be analyzed for patterns and shared through blog posts and academic publications. No individual data will be shared. This will help fill some of the documented gaps in the EPI-related medical knowledge and may influence the design of targeted research studies in the future.

Have Questions?
Feel free to reach out to Dana+GISymptomSurvey@OpenAPS.org.

How else can you help?
Remember, ANYONE can take this survey. So, feel free to share the link with your family and friends – they can take it, too!

Here’s a link to the survey that you can share (after taking it yourself, of course!): https://bit.ly/GI-Symptom-Survey-All

You (yes you!) can help us learn about exocrine pancreatic insufficiency by taking the survey linked on this page.

MacrosOnTheRun: an iOS app for tracking activity fuel consumption

by Dana Lewis

Last year, I built a spreadsheet template (and shared it here) to use while training and running ultramarathons to track my fuel consumption. It was helpful for me, as a person with exocrine pancreatic insufficiency, to see and decide based on macronutrient counts for each snack how many enzyme pills I needed to take each time I fueled, which is every 30 minutes.

This year, I got tired of messing with the spreadsheet while running. I don’t mind the data entry, but because of the iterative calculations updating with the hourly and overall totals of carbs, sodium, calories per hour etc, the Google Sheet would get bogged down over time, especially when I was running for 16 hours (like during my 100k in March). That would cause the Google Sheets app to crash and reload, or kick me out of the sheet and require me to click back in, wait for it to catch up, before entering my fuel item. It only took a couple of seconds, but it was annoying to have that delay while I was running.

I thought about not logging my fueling while running, especially because I had switched to a slightly more expensive but also larger over-the-counter (OTC) enzyme pill that basically covers every single snack I take with one single pill. That requires less mid-run decision making about how many to take, so it’s less important during the run to see each snack’s composition: I simply swallow a pill each time I do fuel.

Yet, after 1-2 runs of 2-3 hours where I didn’t log my intake, I still found myself missing the data from the run. Although the primary use case of in-run decision making wasn’t there for enzyme dosing, the secondary use case of making sure I was consuming enough sodium per hour and calories per hour relative to my goals was still there. I still wanted to offload that hourly tracking so I didn’t have to remember how much I had had in the last hour. Plus, the post-run data summary was nice, because it helped me evaluate my fueling overall in the grand scheme of my daily nutritional intake, which is particularly helpful for me in making sure I’m consuming enough protein to match my ultra-running activities.

And, I had figured out last year how to develop iOS apps (check out PERT Pilot if you have EPI, and Carb Pilot if you’re someone who’d like to simply use AI to generate estimates of how many carbs or macronutrients are in what you’re eating) with the help of an LLM. So I decided to try to build a custom, just for me app to mimic my spreadsheet in order to easily track my fueling on the run.

Tada! I made MacrosOnTheRun.Macros on the run logo showing "on the run" below the word Macros, stylized to look like 'on the run' is a drop down menu, reminiscent of the fuel list drop down in the app

It’s pretty simple: I open the app, hit ‘start run’, and then click the drop down and tap the fuel item (or electrolyte) that I’m consuming. I hit “add fuel”, and the items drops into the list on the screen and is added to the hourly and overall estimates shown above the drop down.

Screenshot of MacrosOnTheRun showing a pre-populated fuel list to select from and on the right, a screenshot at the end of a 9 hour run with fuel totals and individual fuel items entered
An example during a long run where after the run I open the app to export my in-run data. This is after the run, so you’ll see it’s been 97 minutes since the last fuel when I took that screenshot, and thus the sodium per hour and calories per hour calculation shows 0 given that it’s been >60 minutes since the last fuel. Below that is the total run stats, including enzymes and electrolytes counts. Given that I fuel like clockwork every 30 minutes, you can infer this was a 9 hour run since I took 18 enzymes!

When I’m done with the run, I tap the “stop and export” button at the bottom, which opens the iOS share sheet and enables me to email the CSV file to myself, so I can copy/paste the data back into the same spreadsheet template I was using before. It’s useful because I have all my runs stored as individual tabs in the sheet, and the template (same one I was using last year) autopopulates the pivot table with hourly summaries so I can see across each hour whether I was meeting my sodium and fueling goals. (Check out the 27 hour summary table in my 100 mile recap if you’re curious to see an example!)

Right now, I haven’t bothered to add a feature to edit in-app what the fuel list is – mine is programmed in via the code of the app itself, since I’m the only one using it – and I haven’t published it to the iOS App Store because I didn’t think anyone else would want to use it.

But, if I’m wrong, and this is something you’d like to use – let me know by commenting here or emailing me (Dana+MacrosOnTheRun@OpenAPS.org) and letting me know. If there’s interest, I can modify the app to allow in-app fuel list entry and modifications of the fuel list and then share it via TestFlight or in the App Store for other people to download and use.

Running a Multi-Day Ultramarathon (Aiming for 200 Miles)

by Dana Lewis

I used to make a lot of statements about things I thought I couldn’t do. I thought I couldn’t run overnight, so I couldn’t attempt to run 100 miles. I could never run 200 mile races the way other people did. Etc. Yet last year I found myself training for and attempting 100 miles (I chose to stop at 82, but successfully ran overnight and for 25 hours) and this year I found myself working through the excessive mental logistics and puzzle of determining that I could train for and attempt to run 200 miles, or as many miles as I could across 3-4 days.

Like my 100 mile attempt, I found some useful blog recaps and race reports of people’s official races they did for 200-ish mile races. However, like the 100 attempts, I found myself wanting more information for the mental training and logistical preparation people put into it. While my 200 mile training and prep anchored heavily on what I did before, this post describes more detail on how my training, prep, and ‘race’ experience for a multi-day or 200 mile ultra attempt.

DIY-ing a 200

For context, I have a previous post describing the myriad reasons of why I often choose to run DIY ultras, meaning I’m not signing up for an official race. Most of those reasons hold true for why I chose to DIY my 200. Like my 100 (82) miles, I mapped a route that was based on my home paved trail that takes me out and around the trails I’m familiar with. It has its downsides, but also the upsides: really good trail bathrooms and I feel safe running them. Plus, it’s easy and convenient for my husband to crew me. Since I expected this adventure to take 3-4 days (more on that below), that’s a heavy ask of my husband’s time and energy, so sticking with the easy routes that work for him is optimal, too. So while I also sought to run 200 miles just like any other 200-mile ultra runner, my course happens to have minimal elevation. Not all 200 mile ultramarathon races have a ton of elevation – some like the Cowboy 200 are pretty flat – so my experience is closer to that than the experience of those running mountain based ultras with 30,000 feet (or more) of elevation gain. And I’m ok with that!

Sleep

One of the puzzles I had to figure out to decide I could even attempt a 200 miler is sleep. With a 100 mile race, most people don’t sleep at all (nor did I) and we just run through the night. With 200 miles, that’s impossible, because it takes 3, 4, 5 days to finish and biologically you need sleep. Plus, I need more sleep than the average person. I’m a champion sleeper; I typically sleep much longer than everyone else; and I know I couldn’t function with an hour here or there like many people do at traditional races. So I actually designed my 200 mile ultra with this in mind: how could I cover 200 miles AND get sleep? Because I’m running to/from home, I have access to my kitchen, shower, and bed, so I decided that I would set up my run to run each day and come home and eat dinner, shower, and sleep each night for a short night in my bed.

I then decided that instead of winging it and running until I dropped before eating, showering, and sleeping, I would aim for running 50 miles each day. Then I’d come in, eat, shower, and sleep and get up the next morning and go again. 4 days, 3 nights, 50 miles each day: that would have me finishing around 87-90ish hours total (with the clock running from my initial start), including ~25 hours or more of total downtime between the eating/showering/sleeping/getting ready. That breakdown of 3.67 days is well within the typical finish times of many 200 mile ultras (yes, comparing to those with elevation gain), so it felt like it was both a stretch for me but also doable and in a sensible way that works for me and my needs. I mapped it all out in my spreadsheet, with the number of laps and my routes and pacing to finish 50 miles per day; the two times per day I would need my husband to come out and crew me at ‘aid station stops’ in between laps, and what time I would finish each night. I then factored in time to eat and shower and get ready for bed, sleep, and time to get up in the morning. Given the fact that I expected to run slower each day, the sleep windows go from 8 hours down to less than 6 hours by night 3. That being said, if I managed to sleep 5 hours per night and 15 hours total, that’s probably almost twice as much as most people get during traditional races!

Like sleep, I was also very cognizant of the fact that a 200 probably comes down to mental fortitude and will power to keep going; meticulous fueling; and excellent foot care. Plus reasonable training, of course.

Meticulous fueling

I have previously written about building and using a spreadsheet to track my fuel intake during ultras. This method works really well for me because after each training run I can see how much I consumed and any trends. I started to spot that as I got tired, I would tend to choose certain snacks that happened to be slightly lower calorie. Not by much, but the snack selections went from those that are 150-180 calories to 120-140 calories, in part because I perceived them to be both ‘smaller’ (less volume) and ‘easier to swallow’ when I was tired. Doubled up in the same hour, this meant that I started to have hours of 240 calories instead of more than 250. That doesn’t sound like much, but I need every calorie I can get.

I mapped out my estimated energy expenditure based on the 50 miles per day, and even consuming 250 calories per hour, I would end up with several thousand calories of deficit each day! I spent a lot of time testing food that I think I can eat for dinner on the 3 nights to ensure that I get a good 1000 calories or more in before going to bed, to help address and reduce the growing energy deficit. But I also ended up optimizing my race fuel, too. Because I ran so many long runs in training where I fueled every 30 minutes, and because I had been mapping out my snack list for each lap for 50 miles a day for 4 days, I’ve been aware for months that I would probably get food fatigue if I didn’t expand my fuel list. I worked really hard to test a bunch of new snacks and add them to the rotation. That really helped even in training, across all 12 laps (3 laps a day to get 50 miles, times 4 days), I carefully made sure I wouldn’t have too many repeats and get sick of one food or one group of things I planned to eat. I also recently realized that some of the smaller items (e.g. 120 calorie servings) could be increased. I’m already portioning out servings from a big bag into small baggies; in some cases adding one more pretzel or one more piece of candy (or more) would drive up the calories by 10-20 per serving. Those small tweaks I made to 5 of my ~18 possible snacks means that I added about 200 calories on top of what was already represented in those snacks. If I happen to choose those 5 snacks as part of my list for any one lap, that means I have a bonus 200 calories I’ve convinced myself to consume without it being a big deal, because it’s simply one more pretzel or one more piece of candy in the snack that I’m already use to consuming. (Again, because I’m DIYing my race and have specific needs relative to running with celiac, diabetes, and exocrine pancreatic insufficiency, for me, pre-planning my fuel and having it laid out in advance for every run, or in the race every single lap, is what works for me personally.)

Here’s a view of how I laid out my fuel. I had worked on a list of what I wanted for each lap, checking against repeats across the same day and making sure I wasn’t too heavily relying on any one snack throughout all the days. I then bagged up all snacks individually, then followed my list to lay them out by each lap and day accordingly. I also have a bag per day each for enzymes and electrolytes, which you’ll see on the left. Previously, I’ve done one bag per lap, but to reduce the number of things I’m pulling in and out of my vest each time, I decided I could do one big bag each per day (and that did end up working out well).

Two pictures side by side, with papers on the floor showing left to right laps 1-3 on the top and along the left side days 1-4, to create a grid to lay out my snacks. On the left picture, I have my enzymes, electrolytes per day and then a pile of snacks grouped for each lap. On the right, all the snacks and enzymes and electrolytes have been put into gallon bags, one for each lap.

Contingency planning

Like I did for my 100, I was (clearly) planning for as many possibilities as I could. I knew that during the run – and each evening after the run – I would have limited excess mental capacity for new ideas and brainstorming solutions when problems come up. The more I prepared for things that I knew were likely to happen – fatigue, sore body, blisters, chafing, dropping things, getting tired of eating, etc – the more likely that they would be small things and not big things that can contribute to ending a race attempt. This includes learning from my past 100 attempt and how I dealt with the rain. First of all, I planned to move my race if it looks like we’ll get 6 months of rain in a single 24 hour period! But also, I scheduled my race so that if I do have a few hours of really hard rain, I could choose to take a break and come in and eat/shower/change/rest and go back out later, or extend and finish a lap on the last day or the day after that. I was not running a race that would yank me from the course, but I did have a hard limit after day 5 based on a pre-planned doctor’s appointment that would be a hassle to reschedule, so I needed to finish by the night after day 5. But this gave me the flexibility to take breaks (that I wasn’t really planning to take but was prepared to if I needed to due to weather conditions).

Training for a 200 mile ultramarathon

Like training plans for marathons and 100 milers, the training plans I’ve read about for 200 mile ultramarathons intimidate me. So much mileage! So much time for a slow run/walker like me. I did try to look at sample 200 mile ultra plans and get a sense for what they’re trying to achieve – e.g. when do they peak their mileage before the race, how many back to back runs of what general length in terms of time etc – and then loosely keep that in mind.

But basically, I trained for this 200 mile ultra just like I trained for my marathon, 50k, 100k, and 82 miler. I like to end up doing long runs (which for me are run/walks of 30 seconds run, 60 seconds walk, just like I do shorter runs) of up to around 50k distance. This time, I did two total training runs that were each around 29 miles, just based on the length of the trail I had to run. I could have run longer, but mentally had the confidence that another ~45 minutes per run wasn’t going to change my ability to attempt 50 miles a day for 4 days. If I didn’t have 3 years of this training style under my personal belt, I might feel different about it. That’s longer than many people run, but I find the experience of 7-8 hours of time on my feet fueling, run/walking, and problem solving (including building up my willpower to spend that much time moving) to be what works for me.

The main difference for my 200 is probably also that it’s my 3rd year of ultrarunning. I was able to increase my long runs a little bit more of a time, when historically I used to add 2 miles a time to a long run. I jumped up 4 miles at a time – again, run/walking so very easy on my legs – when building up my long runs, so I was able to end up with 2 different 29 mile runs, two weeks apart, even though I really kicked off training specifically for this 8 weeks prior (10 weeks including taper) to the run. In between I also did a weekend of back to back to back runs (meaning 3 days in a row) where I ran 16 miles, another 16 miles, and 13 miles to practice getting up and running on tired legs. In past cycles I had done a lot more back to back (2-day) with a long and a medium run, but this time I did less of the 2-day and did the one big 3-day since I was targeting a 4-day experience. In future, if I were to do this again, given how well my body held up with all this training, I might have done more back to back, but I took things very cautiously and wanted to not overtrain and cause injury from ramping up too quickly.

As part of that (trying not to over do it), instead of doing several little runs throughout the week I focused on more medium-long runs with my vest and fueling, so I would do something like a long run (starting at 10 miles building up to 29 miles), a medium-long run (8 miles up to 13 miles or 16 miles) and another medium-ish run (usually 8 miles). Three runs a week, and that was it. Earlier in the 8 weeks, I was still doing a lot of hiking off the season, so I had plenty of other time-on-feet experiences. Later in the season I sometimes squeezed in a 4th short run of the week if we wouldn’t be hiking, and ran without my vest and tried to do some ‘speed work’ (aka run a little faster than my easy long run pace). Nothing fancy. Again, this is based on my slow running style (that’s actually a fixed interval of short run and short walk, usually 30 seconds run and 60 seconds walk), my schedule, my personality, and more. If you read this, don’t think my mileage or training style is the answer. But I did want to share what I did and that it generally worked for me.

I did struggle with wondering if I was training “enough”. But I never train “enough” compared to others’ marathon, 50k, 100k, 100 mile plans, either. I’m a low mileage-ish trainer overall, even though I do throw in a few longer runs than most people do. My peak training for marathon, 50k, and 100k is usually around low 50s (miles per week). Surprisingly, this 200 cycle did get me to some mid 60 mile weeks! One thing that also helped me mentally was adding in a rolling 7 day calculation of the miles, not just looking at miles per calendar week. That helped when I shifted some runs around due to scheduling, because I could see that I was still keeping a reasonable 55-low60s mileage over 7 days even though the calendar week total dropped to low 40s because of the way the runs happened to land in the calendar weeks.

Generally, though, looking back at how my training was more than I had accomplished for previous races; I feel better than ever (good fueling really helps!); I didn’t have any accidents or overtraining injuries or niggles; I decided a few weeks before peak that I was training enough and it was the right amount for me.

Another factor that was slightly different was how much hiking I had done this year. I ran my 100k in March then took some time off, promising my husband that we would hike “more” this year. That also coincided with me not really bouncing back from my 100k recovery period: I didn’t feel like doing much running, so we kept planning hiking adventures. Eventually I realized (because I was diagnosed with Graves’ disease last year, I’m having my thyroid and antibody and other related blood work done every 3 months while we work on getting everything into range) that this coincided with my TSH going too high for my body’s happiness; and my disinterest in long runs was actually a symptom (for me) of slightly too-high TSH. I changed my thyroid medication and within two weeks felt HUGELY more interested in long running, which is what coincided with reinvigorating my interest in a fall ultra, training, and ultimately deciding to go for the 200. But in the meantime, we kept hiking a lot – to the tune of over 225 miles hiked and over 53,000 feet of elevation gain! I never tracked elevation gain for hiking before (last year, not sure I retrospectively tracked it all but it was closer to 100 miles – so definitely likely 2x increase), but I can imagine this is definitely >2x above what I’ve done on my previous biggest hiking year, just given the sheer number of hikes that we went out on. So overall, the strengthening of my muscles from hiking helped, as did the time on feet. Before I kicked off my 8 week cycle, we were easily spending 3-4 hours a hike and usually at least two hikes a weekend, so I had a lot of time on feet almost every hike equivalent to 12 or more miles of running at that point. That really helped when I reintroduced long runs and aided my ability to jump my long run in distance by 4 miles at a time instead of more gently progressing it by 2 miles a week as I had done in the past.

How my 200 mile attempt actually went

Spoiler alert: I DNF (did not finish) 200 miles. Instead, I stopped – happily – at 100 miles. But it wasn’t for a lack of training.

Day 1 – 51 miles – All as planned

I set out on lap 1 on Day 1 as planned and on time, starting in the dark with a waist lamp at 6am. It was dark and just faintly cool, but warm enough (51F) that I didn’t bother with long sleeves because I knew I would warm up. (Instead, for all days, I was happy in shorts and a short sleeve shirt when the temps would range from 49F to 76F and back down again.) I only had to run for about an hour in the dark and the sky gradually brightened. It ended up being a cloudy, overcast and nice weather day so it didn’t get super bright first thing, but because it wasn’t wet and cold, it wasn’t annoying at all. I tried to start and stay at an easy pace, and was running slow enough (about ~30s/mile slower than my training paces) that I didn’t have to alter my planned intervals to slow me down any more. All was fairly well and as planned in the first lap. I stopped to use the bathroom at mile 3.5 and as planned at my 8 mile turnaround point, and also stopped to stuff a little more wool in a spot in my shoe a mile later. That added 2 minutes of time, but I didn’t let it bother me and still managed to finish lap 1 at about a 15:08 min/mi average pace, which was definitely faster than I had predicted. I used the bathroom again at the turnaround while my husband re-filled my hydration pack, then I stuffed the next round of snacks in my vest and took off. The bathroom and re-fueling “aid station” stop only took 5 minutes. Not bad! And on I went.

A background-less shot of me in my ultrarunning gear. I'm wearing a grey moisture-wicking visor; sunglasses; a purple ultrarunning vest packed with snacks in front and the blue tube of my hydration pack looped in front; a bright flourescent pink short sleeve shirt; grey shorts with pockets bulging on the side with my phone (left pocket) and skittles and headphones and keys (right pocket), and in this lap I was wearing bright pink shoes. Lap 2 was also pretty reasonable, although I was surprised by how often I wanted a bathroom. My period had started that morning (fun timing), and while I didn’t have a lot of flow, the signals my abdomen was giving my brain was telling me that I needed to go to the bathroom more often than I would have otherwise. That started to stress me out slightly, because I found myself wishing for a bathroom in the longest stretch without trail bathrooms and in a very populated area, the duration of which was about 5.5 miles long. I tried to drink less but was also aware of trying not to under hydrate or imbalance my electrolytes. I always get a little dehydrated during my period; and I was running a multi-day ultra where I needed a lot of hydration and more sodium than usual; this situation didn’t add up well! But I made it without any embarrassing moments on the trail. The second aid station again only took 5 minutes. (It really makes a world of difference to not have to dry off my feet, Desitin them up, and re-do socks and shoes every single aid station like I did last year!) I could have moved faster, but I was trying to not let small minutes of time frazzle me, and I was succeeding with being efficient but not rushed and continuing on my way. I had slowed down some during lap 2, however – dropping from a 15:08 to 15:20ish min/mi pace. Not much, but noticeable.

At sunset, with light blue sky fading to yellow at the horizon behind the row of tall, skinny bush like trees with gaps and a hot air balloon a hundred or so feet off the ground seen between the trees.Lap 3 I did feel more tired. I talked my husband into bringing me my headlamp toward the end of the last lap, instead of me having to carry it for 4+ hours before the sun went down. (Originally, I thought I would need it 2-3 hours into this last lap, but because I was moving so well it was now looking like 4 hours, and it would be a 2-3 mile e-bike ride for him to bring me the lamp when I wanted it. That was a mental win to not have to run with the lamp when I wasn’t using it!) I was still run/walking the same duration of intervals, but slowed down to about 16:01 pace for this lap. Overall, I would be at 15:40 average for the whole day, but the fatigue and my tired feet started to kick in on the third lap between miles 34-51. Plus, I stopped to take a LOT more pictures, because there was a hot air balloon growing in the distance as it was flying right toward me – and then by me next to the trail! It ended up landing next to the soccer fields a mile behind me after it passed me in this picture. I actually made it home right as the sun set and didn’t have to wear my lamp at all that evening.

Day 1 recovery was better and worse than I expected. I sat down and used my foot massager on my still-socked feet, which felt very good. I took a shower after I peeled my socks off and took a look at my feet for the first time. I had one blister that I didn’t know was growing at all pop about an hour before I finished, but it was under some of my pre-taped area. I decided to leave the tape and see how it looked and felt in the morning. I had 2-3 other tiny, not a big deal blisters that I would tape in the morning but didn’t need any attention that night.

I had planned to eat a reasonably sized dinner – preferably around 1000 calories – each night, to help me address my calorie deficit. And I had a big deficit: I had burned 5,447 calories and consumed 3,051 calories in my 13 hours and 13 minutes of running. But I could only eat ¼ of the pizza I planned for dinner, and that took a lot of work to force myself to eat. So I gave up, and went to bed with a 3,846 calorie deficit, which was bigger than I wanted.

And going to bed hurt. I was stiff, which I could deal with, but my feet that didn’t hurt much while running started SCREAMING at me. All over. They hurt so bad. Not blisters, just intense aches. Ouch! I started to doubt my ability to run the next day, but this is where my pre-planning kicked in (aided by my husband who had agreed to the rules we had decided upon): no matter what, I would get up in the morning, get dressed, and go out and start my first lap. If I decided to quit, I could, but I could not quit at night in bed or in the morning in the bed or in the house. I had to get up and go. So I went to sleep, less optimistic about my ability to finish 50 miles again on day 2, but willing to see what would happen.

Day 2: 34 instead of 50 miles, and walking my first ever lap

I actually woke up before my alarm went off on day 2. Because I had finished so efficiently the day before, I was able to again get a good night’s sleep, even with the early alarm and waking up again at 4:30am with plans to be going by 6am. The extra time was helpful, because I didn’t feel rushed as I got ready to go. I spent some extra time taping my new blisters. Because they hadn’t popped, I put small torn pieces of Kleenex against them and used cut strips of kinesio tape to protect the area. (Read “Fixing Your Feet” for other great ultra-related foot care tips; I learned about Kleenex from that book.) I also use lambs’ wool for areas that rub or might be getting hot spots, so I put wool back in my usual places (between big and second toes, and on the side of the foot) plus another toe that was rubbing but not blistered and could use some cushion. I also this year have been trying Tom’s blister powder in my socks, which seems to help since my feet are extra sweat prone, and I had pre-powdered a stack of socks so I could simply slip them on and get going once I had done the Kleenex/tape and wool setup. The one blister that had popped under my tape wasn’t hurting when I pressed on it, so I left it alone and just added loose wool for a little padding.

A pretty view of the trail with bright blue sky after the sun rose with green bushes (and the river out of sight) to the left, with the trail parallel to a high concrete wall of a road with cheery red and yellow leaved trees leaning over the trail.And off I went. I managed to run/walk from the start, and faster than I had projected on my spreadsheets originally and definitely faster than I thought was possible the night before or even before I started that morning. Sure, I was slower than the day before, but 15:40 min/mi pace was nothing to sneeze at, and I was feeling good. I was really surprised that my legs, hips and body did not hurt at all! My multi-day or back-to-back training seemed to pay off here. All was well for most of the first lap (17 miles again), but then the last 2 or so miles, my pace started dipping unexpectedly so I was doing 16+ min/mi without changing my easy effort. I was disappointed, and tired, when I came into my aid station turnaround. I again didn’t need foot care and spent less than 5 minutes here, but I told Scott as I left that I was going to walk for a while, because my feet had been hurting and they were getting worse. Not blisters: but the balls of my feet were feeling excruciating.

A close up of a yellow shelled snail against the paved trail that I saw while walking the world's slowest 17-mile lap on day 2.I headed out, and within a few minutes he had re-packed up and biked up to ride alongside me for a few minutes and chat. I told him I was probably going to need to walk this entire lap. We agreed this was fine and to be expected, and was in fact built into my schedule that I would slow down. I’ve never walked a full lap in an ultra before, so this would be novel to me. But then my feet got louder and louder and I told him I didn’t think I could even walk the full lap. We decided that I should take some Tylenol, because I wasn’t limping and this wouldn’t mask any pain that would be important cues for my body that I would be overriding, but simply muting the “ow this is a lot” screams that the bones in the balls of my feet were feeling. He biked home, grabbed some, and came back out. I took the Tylenol and sent him home again, walking on. Luckily, the Tylenol did kick in and it went from almost unbearable to manageable super-discomfort, so I continued walking. And walking. And walking. It took FOREVER, it felt like, having gone from 15-16 min/mi pace with 30 seconds of running, 60 seconds of walking, to doing 19-20 minute miles of pure walking. It was boring. I had podcasts, music, audiobooks galore, and I was still bored and uncomfortable and not loving this experience. I also was thinking about it on the way back about how I did not want to do a 3rd lap that day (to get me to my planned 50 miles) walking again.

Scott biked out early to meet me and bring me extra ice, because it was getting hot and I was an hour slower than the day before and risking running out of water that lap if he didn’t. After he refilled my hydration pack and brought it back to me while I walked on, I told him I wanted to be done for the day. He pointed out that when I finished this lap, I would be at 34 miles for the day, and combined with the day before (51), that put me at 85 miles, which would be a new distance PR for me since last year I had stopped at 82. That was true, and that would be a nice place to stop for the day. He reminded me of our ‘rules’ that I could go out the next day and do another lap to get me to 100, and decide during that lap what else I wanted to do. I was pretty sure I didn’t want to do more, but agreed I would decide the next day. So I walked home, completing lap 2 and 34 miles for the day, bringing me to 85 miles overall across 2 days.

Day 2 recovery went a little better, in part because I didn’t do 51 miles (only 34) and I had walked rather than ran the second lap, and also stopped earlier in the day (4pm instead of 7pm). I had more time to shower and bring myself to finally eat an entire 1000 calories before going to bed, again with my feet screaming at me. I had more blisters this time, mostly again on my right foot, but the balls of my feet and the bones of my feet ached in a way they never had before. This time, though, instead of setting my alarm to get up and go by 6am, I decided to sleep for longer, and go out a little later to start my first lap. This was a deviation from my plan, but another deviation I felt was the right one: I needed the sleep to help my body recover to be able to even attempt another lap.

Day 3: Only 16 miles, but hitting 100 for the first time ever

Instead of 6am, I set out on Day 3 around 8:30am. I would have taken even longer to go, but the forecast was for a warm day (we ended up hitting 81F) and I wanted to be done with the lap before the worst of the heat. I thought there was a 10% chance I’d keep going after this lap, but it was a pretty small chance. However, I set out for the planned 16 mile lap and was pleasantly surprised that I was run/walking at about a 15:40 pace! Again, better than I had projected (although yes, I had deviated from my mileage plan the day before), and it felt like a good affirmation that stopping the day before instead of slogging out another walking lap was the right thing to do.

After a first few miles, I toyed with the idea of continuing on. But I knew with the heat I probably wouldn’t stand more than one more lap, which would get me to 116. Even if I went out again the fourth day, and did 1-2 laps, that would MAYBE get me to 150, but I doubted I could do that without starting to cause some serious damage. And it honestly wasn’t feeling fun. I had enjoyed the first day, running in the dark, the fog, the daylight, and the twilight, seeing changing fall leaves and running through piles of them. The second day was also fun for the first lap, but the second lap walking was probably what a lot of ultra marathoners call the “death march” and just not fun. I didn’t want to keep going if it wasn’t fun, and I didn’t want to run myself into the ground (meaning to be so worn down that it would take weeks to months to recover) or into injury, especially when the specific milestones didn’t really mean anything. Sure, I wanted to be a 200 mile ultramarathoner, something that only a few thousand people have ever done – but I didn’t want to do it at the expense of my well-being. I spent a lot of time thinking about it, especially miles 4-8, and was thinking about the fact that the day before I had started, I had gone to a doctor’s appointment and had an official diagnosis confirming my fifth autoimmune disease, then proceeded to run (was running) 100 miles. Despite all the fun challenges of running with autoimmune conditions, I’m in really good health and fitness. My training this year went so well and I really enjoyed it. Most of this ultra had gone so well physically, and my legs and body weren’t hurting at all: the weakness was my feet. I didn’t think I could have trained any differently to address that, nor do I think I could change it moving forward. It’s honestly just hard to run that many hours or that many miles, as most ultramarathoners know, and your feet take a beating. Given that I was running on pavement for all of those hours, it can be even harder – or a different kind of hard – than kicking roots and rocks on a dirt trail. I figured I would metaphorically kick myself if I tried for 116 or 134 and injured myself in a way that would take 6-8 weeks to recover, whereas I felt pretty confident that if I stopped after this lap (at 100), I would have a relatively short and easy recovery, no major issues, and bounce back better than I ever have, despite it being my longest ever ultramarathon. Yes, I was doing it as a multi-day with sleep in between, but both in time on feet and in mileage, it was still the most I’d ever done in 2 or 3 days.

And, I was tired of eating. I was fueling SO well. Per my plans, I set out to do >500 mg of sodium per hour and >250 calories per hour. I had been nailing it every lap and every day! Day 1 I averaged 809 mg of sodium per hour and 290 calories per hour. Day 2 was even increased from that, averaging 934 mg of sodium per hour and 303 calories per hour! Given the decreased caloric burn of day 2 because I walked the second lap, my caloric deficit for day 2 was a mere ~882 calories (given that I also managed to eat a full dinner that night), even though I skipped the last hour as I finished the walking lap. Day 3 I was also fueling above my goals, but I was tired of it. Sooooo tired of it. Remember, I have to take a pill every time I eat, because I have exocrine pancreatic insufficiency (EPI or PEI). I was eating every 30 minutes as I ran or walked, so that meant swallowing at least one pill every 30 minutes. I had swallowed 57 pills on Day 1 and 48 pills on Day 2, between my enzymes and electrolyte pills. SO MANY PILLS. The idea of continuing to eat constantly every 30 minutes for another lap of ~5 or more hours was also not appealing. I knew if I didn’t eat, I couldn’t continue.

A chart with an hourly break down of sodium, calories, and carbs consumed per hour, plus totals of caloric consumption, burn, and calculated deficit across ~27 hours of move time to accomplish 100 miles run.

And so, I decided to stop after one more lap on day 3, even though I was holding up a respectable 15:41 min/mi pace throughout. I hit 100 miles and finished the lap at home, happy with my decision.

Two pictures of me leaning over after my run holding a sign (one reading 50 miles, one reading 100 miles) for each of my cats to sniff.(You can see from these two pictures that I smelled VERY interesting, sweaty and salty and exhausted at the end of day 1 and day 3, when I hit 50 miles and 100 miles, respectively. We have two twin kittens (now 3 years old) and one came out to sniff me first on the first day, and the other came out as I came home on the third day!)

Because I had only run one final lap (16 miles) on day 3, and had so many bonus hours in the rest of the day afterward when I was done and home, I was able to eat more and end up with only a 803 calorie deficit for the day. So overall, day 1 had the biggest deficit and probably influenced my fatigue and perception of pain on day 2, but because I had shortened day 2 and then day 3, my very high calorie intake every hour did a pretty good job matching my calorie expenditure, which is probably why I felt very little muscle fatigue in my body and had no significant sore areas other than the bottoms of my feet. I ended up averaging 821 mg/hr of sodium and 279 calories per hour (taking into account the fact that I skipped two final snacks at the end of day 2 when I was walking it out; ignoring that completely skipped hour would mean the average caloric intake on hours I ate anything at all was closer to 290 calories/hr!)

In total, I ended up consuming 124 pills in approximately 27 hours of move time across my 100 miles. (This doesn’t include enzyme pills for my breakfast or dinners each of those days, either – just the electrolyte and enzyme pills consumed while running!)

AFTERMATH

Recovery after day 3 was pretty similar to day 2, with me being able to eat more and limit my calorie deficit. I’ve had long ~30 mile training runs where I wasn’t very hungry afterward, but it surprised me that even two days after my ultra, I still haven’t really regained my appetite. I would have figured my almost 4000 calorie deficit from day 1 would drive a lot of hunger, so this surprised me.

So too has my physical state: 48 hours following the completion of my 100 miles, I am in *fantastic* shape compared to other multi-day back to back series of runs I’ve done, ultramarathons or not. The few blisters I got, mainly on my right foot, have already flattened themselves up and mostly vanished. I think I get more blisters on my right foot because of breaking my toe last year: my right foot now splays wider in my shoe, so it tends to get more blisters and cause more trouble than my left foot. I got only one blister on my left foot, which is still fluid filled but not painful and starting to visibly deflate now that I’m not rubbing it onto a shoe constantly any more. And my legs don’t feel like I ran at all, let alone running 51+34+16 miles!

I am tired, though. I don’t have brain fog, probably because of my excellent fueling, but I am fatigued in terms of overall energy and lack of motivation to get a lot done yesterday and today (other than writing this blog post!). So that’s probably pretty on par with my effort expended and matches what I expected, but it’s nice to be able to move around without hurting (other than my feet).

My feet in terms of general aches and ows are what came out the worst from my run. Day 2, what hurt was the bottom of the balls of my feet. Starting each night though, I was getting aches all over in all of the bones of my feet. After day 3, that night the foot aches were particularly strong, and I took some Tylenol to help with that. Yesterday evening and today though, the ache has settled down to very minor and only occasionally noticeable. The tendon from the top of my left foot up my ankle is sore and gets cranky when I wear my sneakers (although it didn’t bother me at all while running any of the days), so after tying and re-tying my shoelaces 18 times yesterday to try to find the perfect fit for my left foot, today I went on my recovery walk in flip flops and was much happier.

What I’m taking away from this 200 mile attempt that was only 100 miles:

I feel a little disappointed that I didn’t get anywhere near 200 miles, but obviously, I was not willing to hurt long enough or hard enough to get there. My husband called it a stretch goal. Rationally, I am very happy with my choices to stop at 100 and end up in the fantastic physical shape that I am in, and I recognize that I made a very rational choice and tradeoff between ending in good shape (and health) and the mainly ego-driven benefits of possibly achieving 200 miles (for me).

Would I do anything different? I can’t think of anything. If I somehow had an alternate do-over, I can’t think of anything I would think to change. I’d like to reduce my risk of blisters but I’m already doing all I can there, and dealing with changes in my right foot shape post-broken toe that I have no control over. And I’m not sure how to train more/better for reducing the bottom ball of foot pain that I got: I already trained multiple days, back to back, long hours of feet on pavement. It’s possible that having my doctor’s appointment the day before I started influenced my mental calculation of my future risk/benefit tradeoff of continuing more miles, and so not having had that then may have changed my calculations to do another lap or two, or go out on the 4th day (which I did not). But, I don’t have a do over, and I’ll never know, and I’m not too upset about that because I was able to control what I could control and am again pretty happy with the outcomes. 100 or 150 miles felt about the same to me, psychologically, in terms of satisfaction.

What I would tell other people about attempting multiple day ultramarathons or 200 mile ultramarathons:

Training back to back days is one option, as is long spurts of time on feet walking/hiking/running. I don’t think “just running” has to be the only way to train for these things. I’m also a big proponent of short intervals: If you hear people recommend taking walk breaks, it doesn’t have to be 1 minute every 10 minutes or every mile. It can be as short as every 30 seconds of running, take a walk break! There’s no wrong way to do it, whatever makes your body and brain happy. I get bored running longer (and don’t like it); other people get bored running the short intervals that I do – so find what works for you and what you’re actually willing to do.

Having plans for how you’ll rest X hours and go out and try to make it another lap or to the next aid station works really well, especially if you have crew/pacers/support (for me, my husband) who will stick to those rules and help you get back out there to try the next lap/section. Speaking of sleep/rest, laying down for a while helps as much as sleeping, so even if you can’t sleep, committing to the rest of X hours is also good for resting your feet and everything. I found that the hour laying down before I fell asleep helped my body process the noise of the “ouch” from my feet and it was a lot easier to sleep after that. Plan that you’ll have some down/up time before and after your sleep/rest time, and figure that into your time plans accordingly.

The cheesy “know your why” and “know what you want” recommendations do help. I didn’t want 200 miles badly enough to hurt more for longer and risk months of recovery (or the inability to recover). Maybe you’d be lucky enough to achieve 200 without hurting that bad, that long, or risking injury – or maybe you’ll have to make that choice, and you might make it differently than I did. (Maybe you’re lucky enough to not have 5 autoimmune things to juggle! I hope you don’t have to!) I kind of knew going in that I was only going to hit 200 if all went perfect.

Diabetes and this 200 mile ultramarathon that was a 100 mile ultra:

I just realized that I managed to write an ENTIRE race report without talking about diabetes and glucose management…because I had zero diabetes-related thoughts or issues during these several days of my run! Sweet! (Pun fully intended.)

Remember, I have type 1 diabetes and use an open source automated insulin delivery (AID) system (in my case, still using OpenAPS after alllllll these years), and I’ve talked previously about how I fuel while ultrarunning and juggling blood glucose management. Unlike previous ultras, I had zero pump site malfunctions (phew) and my glucose stayed nicely in range throughout. I think I had one small drift above range for 2 hours due to an hour of higher carb activity right when I shifted to walking the second lap on day 2, but otherwise was nicely in range all days and all nights without any extra thought or energy expended. I didn’t have to take a single “low carb”/hypoglycemia treatment! I think there was one snack I took a few minutes early when I saw I was drifting down slightly, but that was mostly a convenience thing and I probably would not have gone low (below target) even if I had waited for my planned fuel interval. But out of 46 snacks, only one 5-10 minutes early is impressive to me.

I had no issues after each day’s run, either: OpenAPS seamlessly adjusted to the increasing insulin sensitivity (using “autosensitivity” or “autosens”) so I didn’t have to do manual profile shifts or overrides or any manual interference. I did decide each night whether I wanted to let it SMB (supermicrobolus) as usual or stick to temp basal only to reduce the risk of hypoglycemia, but I had no post-dinner or overnight lows at all.

The most “work” I had to do was deciding to wear a second CGM sensor (staggered, 5 days after my other one started) so that I had a CGM sensor session going with good quality data that I could fall back to if my other sensor started to get jumpy, because the sensor session was supposed to end the night of day 4 of my planned run. I obviously didn’t run day 4, but even so I was glad to have another sensor going (worth the cost of overlapping my sensors) in order to have the reassurance of constant data if the first one died or fell out and I could seamlessly switch to an already-warmed up sensor with good data. I didn’t need it, but I was glad to have done that in prep.

(Because I didn’t talk about diabetes a lot in this post, because it was not very relevant to my experiences here, you might want to check out my previous race recaps and posts about utlrarunning like this one where I talk in more detail about balancing fueling, insulin, and glucose management while running for zillions of hours.)

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TLDR: I ran 100 miles, and I did it my DIY way: my own course, my own (slow pace), with sleep breaks, a lot of fueling, and a lot of satisfaction of setting big goals and attempting to achieve them. I think for me, the process goals of figuring out how to even safely attempt ultramarathons are even more rewarding than the mileage milestones of ultrarunning.

Running a multi-day ultramarathon by Dana M. Lewis from DIYPS.org

New Research Shows Most People With Exocrine Pancreatic Insufficiency (EPI) Are Not Taking Enough Enzymes

by Dana Lewis

Last year when I was diagnosed with exocrine pancreatic insufficiency (known as EPI or PEI), I quickly noticed that many people in the online social media community I joined didn’t seem to have their pancreatic enzyme replacement therapy (PERT) working effectively for them.

Possibly because I have been counting carbohydrates and dosing insulin using a ratio of insulin to carbohydrates for ~20+ years (for type 1 diabetes), it came intuitively to me to try to develop ratios of the amount of enzymes compared to the amount of macronutrients I was consuming, For me, it worked really well (and you can read more about my methods for titrating enzymes and/or check out PERT Pilot if you have an iOS phone, which helps automating the dosing calculations based on logging what you eat).

However, I was surprised at how many people still seemed to share online that their PERT wasn’t working or that they still had symptoms. It made me curious: were these folks all newly diagnosed? How long does it take for most people to titrate their enzymes (e.g. arrive at an ideal dose or dosing strategy)? There seemed to be a mismatch between what I was seeing in real life in these communities versus what was in the medical literature about typical dosing of enzymes and expected outcomes for this community.

And so, I set out to do a survey to learn more. I sought permission from the administrators of the Facebook group, designed the survey, got the administrators’ feedback and incorporated it, had a few people trial the survey, and then shared it in the Facebook group and on Twitter.

I ended up closing the survey after 3 weeks and 111 responses, although I wish I had left it open to collect more data. I was so excited to analyze the data and get it published!

…but I forgot how long and silly the traditional medical literature publishing process is. I just now got this article published, almost a year later! Sigh. Anyway, this post is to share what we learned from the EPI Community survey and what I think people – both people with EPI and clinicians – should do based on this information.

(PS – the full research paper is available here and is open access and free to read anytime! Big thanks to Dr. Arsalan Shahid for collaborating with me on writing up the results and getting this published.

Below is a plain language summary that I wrote for those who don’t want to read the full paper.)

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Understanding who took the EPI Community survey

First things first, it’s helpful to understand who ended up taking the survey to help us understand the results.

111 people with EPI filled out the survey. Most (93%) were female, and most happened to be in North America. So, this survey won’t necessarily represent the entire EPI community, based on the small sample size and the demographic makeup. (That being said, I found a previous EPI study on a smaller sample size with a majority of male participants where the findings matched pretty similarly, so I don’t think gender played a large role in the results).

But I was interested to see that the ages ended up being pretty balanced: the largest group was between 55 and 64 years (27%) followed by 65-74 (23%); 45-54 (21%); 34-44 (16%); 25-34 (6%); 75+ (5%); and 18-24 (2%). Also, the duration of how long people had EPI was also fairly distributed: diagnosed within 0-6 months (27%);  1-2 years (25%); 5+ years and 3-5 years (both 18%); or 6 months – 1 year (12%). This was all coincidental, as I did not do any particular recruitment based on age groups or length of EPI.

I was also interested and a little surprised to look at the list of other conditions that people have. 68% of people mentioned at least one other condition. Remember, we had 111 participants – and 26 of them (35%) mentioned having diabetes of any type. The next most common was celiac (10 people), followed by chronic pancreatitis (8 people) and acute pancreatitis (4 people).

This is compelling additional evidence supporting my recent systematic review that shows a higher prevalence of EPI among people with diabetes, and also adds to my argument that chronic pancreatitis and cystic fibrosis are likely NOT the biggest co-conditions associated with EPI. No, this study is not necessarily a representative sample of EPI, but this is more evidence added to these arguments. People with diabetes, celiac, and other conditions presenting with GI symptoms should be screened for EPI.

Understanding the Elastase in the EPI Community

The most common diagnosis test for EPI is the fecal elastase test. Most participants in this survey (all but 15 people) had their elastase tested, although not everyone shared the number or remembered what it was. 76 people shared their elastase results, so the sub-analyses related to elastase are based on this group rather than the overall survey participant number (111).

Of those who reported their elastase, the average was 92 (with a standard deviation of 57).

Remember that the diagnostic criteria for EPI say that anything <200 is considered to be EPI, with 100-200 being “mild/moderate” and <100 being “severe”, although the categorization technically doesn’t change anything including how much enzymes are given to people. (That being said, though, it shows that the majority of people surveyed do have severe EPI, which helps counter potential pushback on this survey that people with only slightly lowered elastase don’t have EPI. Many of us with elastase in the mild/moderate category, myself included, show clear response to symptoms on PERT no matter what the elastase number says, but there seems to be some resistance in the clinical community to prescribing PERT when elastase is 100-200.)

I ended up reviewing the elastase data by age group and also by duration of EPI (meaning how long people have had EPI). A statistical test showed that as age increases, elastase levels tend to decrease. That wasn’t surprising to me as many studies that I have read also show that older adults are more likely to have lowered elastase. I also ran a statistical test that showed that people who have had EPI for longer are more likely to have reported lowered elastase levels, again matching previous studies.

If you look at Table 1 in the paper, you can see the breakdown of enzyme dosing for meals and snacks for each of the duration sub-groups. I chose 0-6 months, 6 months to 1 year, 1 to 2 years, 3-5 years, and 5+ years as the duration groups to ask people about. In the elastase column you can clearly see that elastase lowers over the duration groups, too. You can also see the varied enzyme dosing (with standard deviations) by groups, too. Interestingly, the 0-6 month group takes the highest average enzyme dose, followed by the 5+ year group, with lower amounts in the other groups. This I haven’t seen reported in the literature as I haven’t found any other studies evaluating enzyme dosing in the real world nor any breakdowns by duration of EPI, so this would be interesting to repeat in a study that better controls for variables of age and duration of EPI.

We did not observe a statistical correlation between enzymes taken for meals or snacks and elastase levels. That didn’t surprise me personally because the enzyme dosing guidelines are not different based on elastase levels (e.g. people with elastase <100 or between 100-200 are given the same dose).

What Enzymes Are People Taking, And What About the Cost of PERT?

I had hypothesized that maybe some people adjust their meals in order to reduce enzyme cost, because PERT can be expensive.

Most people (100, which is 90% of participants) do take enzymes, and 87% are taking prescription enzymes. The results of what people take prescription-wise in terms of brand is likely influenced by the order in which the prescription options entered the US market, given that most participants are in North America. 5 people reported taking OTC enzymes only (see my comments about over the counter or OTC enzymes here), and 7 people take a combination of prescription and OTC. The biggest reason people reported taking OTCs or a mix was that the enzyme prescription was not written so that they had enough to cover a full month (which means they are not getting enough prescription enzymes from their doctor, and their prescription should be increased). 7 people also indicated that lack of insurance coverage for prescription enzymes was an issue and that even OTC enzymes were expensive for them. Otherwise, for those taking prescription enzymes, 40% have insurance and said the cost was reasonable for them; 32% find the cost of prescription enzymes expensive even with insurance.

Based on my curiosity, I had asked people how often cost played a role in choosing what to eat and/or how much enzymes to take, 32% of people said ‘yes often”, 20% said sometimes, and 40% said they do not change what they eat in order to change the amount of enzymes they’re taking.

Again, this is primarily in North America where PERT can be very expensive, so the results in other geographic regions with different health plans and coverage options for PERT would likely be very different to those questions about cost and modifying food and PERT intake!

People With EPI Are Not Taking Enough Enzymes

Here’s where I was most surprised by the data:

I knew anecdotally that  many people with EPI weren’t taking enough enzymes, but this survey showed that only 1 in 5 people believe that they are always taking enough enzymes! Another 1 in 5 people said they are usually not taking enough, and the remaining 3 of 5 people think they take enough most of the time but not always.

Additionally, the data from this survey shows that the longer duration of EPI was correlated with taking less enzymes per meal. It’s possible that people were taking enough but their elastase production lowered further over time, and they did not (or were not able to due to lack of healthcare provider support for updating prescriptions) update their dosing over time, which I think would be another interesting area for future studies.

On average, individuals who reported their elastase levels were taking 64,303 (SD: ±39,980) units of lipase per meal (minimum 0; maximum 180,000). There were 14 participants who reported taking less than or equal to 30,000 units of lipase per meal; 7 participants reported taking between 30,000 and 40,000 units of lipase per meal; 6 participants who reported between 40-50,000 units of lipase per meal and 44 participants who reported taking >=50,000 units of lipase per meal. What do these numbers mean? Well, most dosing guidelines recommend a starting dose of 40-50,000 units of lipase per meal, so this means that the majority of people are taking at least the recommended starting dose (or higher), whereas about a third are taking well under even the recommended starting dose (more from me here in this blog about starting dose and the ranges people should increase to).

It probably will surprise a lot of clinicians to see that the average intake was around 64,000 units of lipase (with a large standard deviation, which means there was a lot of variance in dose sizes). It’s surprising because this is above the typical starting dose yet the majority of this population, as described above, is still experiencing symptoms and still not always taking enough enzymes to manage these symptoms

It’s also worth noting that most people said they still have not arrived at the ideal enzyme dosing: 42% said they still weren’t there yet. For those who thought they did have the ideal enzyme dosage, it took anywhere from a few weeks (16%) to a few months (20%); more than 6 months (10%), more than a year (10%) or even up to a few years (3%).

In summary:


People with EPI are not taking enough enzymes; are not arriving at an ideal dose quickly; and it is absolutely worth it for any clinician who sees someone with EPI – even someone who has been diagnosed by another clinician or had EPI for a long time – to check to see whether their prescription is meeting their needs and/or whether they need support in increasing their dose to resolve symptoms!

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Recommended Takeaways From This Study

 

Patients (aka, people living with EPI):

  • If you are still experiencing symptoms, you may need to take more enzymes. The starting doses should be around 40-50,000 and it’s common for many people to need even larger doses. Based on this study, some people take up to 180,000 units per meal!
  • Talk to your doctor if you need your script adjusted, and remember PERT pills come in different sizes so you may be able to get a higher pill size (which holds more enzymes) so you have to take fewer pills per meal.
  • If your doctor seems resistant to adjusting your prescription, I have citations in this blog post that you can share listing out the various guidelines that point to 40-50,000 units of lipase being the starting dose with guidelines to increase up to 2-3x as needed based on the individual’s symptoms – share those guidelines/citations with your clinician if needed.
  • Over time, it is possible you will need to change your enzyme dosing as your body changes.

 

Doctors who treat people living with EPI

  • Other studies show that the majority of people with EPI are undertreated, even when compared to the baseline level of starting doses. This survey shows most people need more than the ‘starting dose’, so don’t be surprised and also proactively talk with patients about increasing enzyme doses and how to do so, and be prepared to update prescriptions for PERT over time.
  • Treat people with mild/moderate EPI (fecal elastase results 100-200, and not just those <100). The symptom burden of EPI is pretty significant even in those of us with mild/moderate EPI. Yes, PERT can be expensive, but let patients make the choice to treat/manage and don’t make the choice for them by refusing to prescribe PERT for elastase <200.
  • If symptoms aren’t resolved on the initial dose given, follow the guidelines for increasing the doses 2-3x from the starting 40-50,000 dose before considering adding a PPI or investigating other causes after that. But, dropping PERT after a short trail of a dose of <40,000 is not an approved nor evidence-based approach to treating EPI. Dose according to the starting guidelines and follow up or explain to your patients how to follow up on their own in order to increase their prescription as needed. Think of PERT similarly to insulin, where dosing is also self-managed by patients at every meal.
  • Speaking of insulin and diabetes: EPI occurs in more people than you think, and people with diabetes and celiac and other conditions need to be screened for EPI. Chronic pancreatitis is not the leading cause of EPI.

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The paper described in this blog post can be accessed here for free – it’s open access!

You can cite it as:

Lewis DM, Shahid A. Survey on Pancreatic Enzyme Replacement Therapy Dosing Experiences of Adults with Exocrine Pancreatic Insufficiency. Healthcare 2023, 11,2316. https://doi.org/10.3390/healthcare11162316

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Want to read more about EPI? Check out DIYPS.org/EPI for other posts I have written about my personal experiences with EPI and PERT, plus links to my other EPI-related research papers (with more on the way!)

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You can also contribute to another research study – take this anonymous survey to share your experiences with EPI-related symptoms!

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A blue square with white text that says "New Research: Most people with EPI (PEI) are not taking enough enzymes", a blog post by Dana M. Lewis

What I’ve Learned From 5,000 Pills Of Pancreatic Enzyme Replacement Therapy (PERT) For Exocrine Pancreatic Insufficiency (EPI/PEI)

by Dana Lewis

I recently reached a weird milestone that no one likely cares about, but that I find fascinating: in the first 534 days of exocrine pancreatic insufficiency (EPI / PEI), I’ve taken more than 5,000 pills of pancreatic enzyme replacement therapy (PERT).

That’s an average of 9.41 pills per day!

PERT (enzymes) helps my body successfully digest the food that I eat, because my pancreas is no longer producing enough enzymes. Like insulin treatment for diabetes, PERT will be a lifelong necessity for me: this number of pills consumed is one that only goes up from here.

Here’s a look at what the pills per day intake has looked like over this time:

  • Min: 2 (early days)
  • Max: 72 (hello, outlier of two ultramarathons! One was 62 miles, the other was 82 miles! Other 30-40+ pill days are likely also ultra 🏃🏼‍♀️ training days, e.g. around 50k of running, which is still 8-9 hours of running and fueling every 30 minutes)
  • Median: 8

Analyzing a graph of my daily PERT enzyme pills, there are noticeable spikes, particularly around my ultramarathon training days. Two distinct spikes at 72 pills per day correspond to my 100k (62 mile) and 82-mile ultra runs.

Here is a graph showing my PERT (enzyme) pills per day totals, there are a few noticeable spikes in the 20-40ish range that are likely ultra training days. The two spikes around 72/day are my 100k (62 mile) and 82 mile ultra runs.

Why so many pills?!

Not everyone with EPI takes as many pills as I do. The number is titrated (adjusted) based on what and how often I eat. A typical meal for me requires 2-3 prescription pills of PERT.

In my case, I sometimes use over-the-counter (OTC) enzymes to ‘top off’ a prescription pill.

For hikes and runs, which I do 4-5 times each week, I eat small amounts every 30 minutes if I’m out for more than 2 hours, which is 3+ times a week. For a run of 5 hours, where I consume 10 snacks, I’d use 10 pills if I went the prescription route. In contrast, I usually use 2-4 OTC pills per snack, which combined costs an average of $0.70. That means $7 in enzyme costs for 5 hours compared to $80 if I had taken prescription PERT! Multiply times several times a week, and you can see why I choose this strategy.

Balancing Cost ($) and Convenience (Fewer Pills)

The “cost” for using OTC pills, though, is 20-40 pills ($7) instead of 10 pills ($80). On a day-to-day basis, my choice depends on convenience, how confident I am in my counts/dosing (I’m very confident for hike/run pre-portioned snacks that I’ve tested rigorously), and other factors.

Increasingly, when I’m not pursuing physical activity, I’m more likely to choose fewer pills at the financial cost of prescription PERT. I’d like to choose fewer pills for physical activity, too, which is why I’ve recently shifted to a slightly more expensive OTC pill that has more enzymes in it, in order to take 1 pill for most snacks instead of 2-4. In a typical long run of 4 hours, for example, instead of 7 snacks resulting in 28 pills, those 7 snacks would instead result in 7 pills! (There’s also a challenge with finding these particular OTC pills, as prescription pill shortage has driven more people to try OTCs and now the OTC pills I prefer are regularly out of stock, too. If you’re curious about using OTC pills with EPI, or prior to a diagnosis of EPI, you may be interested in this post where I describe in more detail using over the counter (OTC) enzyme pills for this purpose.)

Long run days are outliers in my pill count per day numbers and graphs. However, even if I skipped those and only took 8 prescription PERT per day, I’d still have consumed over 4,200 enzyme pills at this point.

EPI or PEI leads to a lot of pill-swallowing, regardless of whether you’re using over the counter enzymes or prescription enzymes.

But they work! Oh, do they work. My GI symptoms used to be most days a week and caused me to feel miserable (read about my experience getting diagnosed with EPI here). Now, I rarely have any symptoms, and when they do occur (likely mistiming a dose compared to what I was eating or taking not quite enough to match what I was eating), they are significantly less bothersome. It’s awesome, and I feel back to “normal” for me well before all of my GI symptoms started years ago! So yes, I have to swallow many pills a day for EPI but my symptoms are completely and regularly managed as a result and my quality of life is back to being what it was before.

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If you’re curious to read more about my experiences with EPI, or posts about adjusting enzymes to match what you’re eating, check out DIYPS.org/EPI for a list of other EPI related posts.

If you have EPI and have an iOS device, you also might be interested in checking out PERT Pilot, a free iOS app to track food intake and PERT dosing and outcomes.

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You can also contribute to a research study and help us learn more about EPI/pEI – take this anonymous survey to share your experiences with EPI-related symptoms!

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You’d Be Surprised: Common Causes of Exocrine Pancreatic Insufficiency

by Dana Lewis

Academic and medical literature often is like the game of “telephone”. You can find something commonly cited throughout the literature, but if you dig deep, you can watch the key points change throughout the literature going from a solid, evidence-backed statement to a weaker, more vague statement that is not factually correct but is widely propagated as “fact” as people cite and re-cite the new incorrect statements.

The most obvious one I have seen, after reading hundreds of papers on exocrine pancreatic insufficiency (known as EPI or PEI), is that “chronic pancreatitis is the most common cause of exocrine pancreatic insufficiency”. It’s stated here (“Although chronic pancreatitis is the most common cause of EPI“) and here (“The most frequent causes [of exocrine pancreatic insufficiency] are chronic pancreatitis in adults“) and here (“Besides cystic fibrosis and chronic pancreatitis, the most common etiologies of EPI“) and here (“Numerous conditions account for the etiology of EPI, with the most common being diseases of the pancreatic parenchyma including chronic pancreatitis, cystic fibrosis, and a history of extensive necrotizing acute pancreatitis“) and… you get the picture. I find this statement all over the place.

But guess what? This is not true.

First off, no one has done a study on the overall population of EPI and the breakdown of the most common co-conditions.

Secondly, I did research for my latest article on exocrine pancreatic insufficiency in Type 1 diabetes and Type 2 diabetes and was looking to contextualize the size of the populations. For example, I know overall that diabetes has a ~10% population prevalence, and this review found that there is a median prevalence of EPI of 33% in T1D and 29% in T2D. To put that in absolute numbers, this means that out of 100 people, it’s likely that 3 people have both diabetes and EPI.

How does this compare to the other “most common” causes of EPI?

First, let’s look at the prevalence of EPI in these other conditions:

  • In people with cystic fibrosis, 80-90% of people are estimated to also have EPI
  • In people with chronic pancreatitis, anywhere from 30-90% of people are estimated to also have EPI
  • In people with pancreatic cancer, anywhere from 20-60% of people are estimated to also have EPI

Now let’s look at how common these conditions are in the general population:

  • People with cystic fibrosis are estimated to be 0.04% of the general population.
    • This is 4 in every 10,000 people
  • People with chronic pancreatitis combined with all other types of pancreatitis are also estimated to be 0.04% of the general population, so another 4 out of 10,000.
  • People with pancreatic cancer are estimated to be 0.005% of the general population, or 1 in 20,000.

What happens if you add all of these up: cystic fibrosis, 0.04%, plus all types of pancreatitis, 0.04%, and pancreatic cancer, 0.005%? You get 0.085%, which is less than 1 in 1000 people.

This is quite a bit less than the 10% prevalence of diabetes (1 in 10 people!), or even the 3 in 100 people (3%) with both diabetes and EPI.

Let’s also look at the estimates for EPI prevalence in the general population:

  • General population prevalence of EPI is estimated to be 10-20%, and if we use 10%, that means that 1 in 10 people may have EPI.

Here’s a visual to illustrate the relative size of the populations of people with cystic fibrosis, chronic pancreatitis (visualized as all types of pancreatitis), and pancreatic cancer, relative to the sizes of the general population and the relative amount of people estimated to have EPI:

Gif showing the relative sizes of populations of people with cystic fibrosis, chronic pancreatitis, pancreatic cancer, and the % of those with EPI, contextualized against the prevalence of these in the general population and those with EPI. It's a small number of people because these conditions aren't common, therefore these conditions are not the most common cause of EPI!

What you should take away from this:

  • Yes, EPI is common within conditions such as cystic fibrosis, chronic pancreatitis (and other forms of pancreatitis), and pancreatic cancer
  • However, these conditions are not common: even combined, they add up to less than 1 in 1000!
  • Therefore, it is incorrect to conclude that any of these conditions, individually or even combined, are the most common causes of EPI.

You could say, as I do in this paper, that EPI is likely more common in people with diabetes than all of these conditions combined. You’ll notice that I don’t go so far as to say it’s the MOST common, because I haven’t seen studies to support such a statement, and as I started the post by pointing out, no one has done studies looking at huge populations of EPI and the breakdown of co-conditions at a population level; instead, studies tend to focus on the population of a co-condition and prevalence of EPI within, which is a very different thing than that co-condition’s EPI population as a percentage of the overall population of people with EPI. However, there are some great studies (and I have another systematic review accepted and forthcoming on this topic!) that support the overall prevalence estimates in the general population being in the ballpark of 10+%, so there might be other ‘more common’ causes of EPI that we are currently unaware of, or it may be that most cases of EPI are uncorrelated with any particular co-condition.

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(Need a citation? This logic is found in the introduction paragraph of a systematic review found here, of which the DOI is 10.1089/dia.2023.0157. You can also access a full author copy of it and my other papers here.)

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You can also contribute to a research study and help us learn more about EPI/PEI – take this anonymous survey to share your experiences with EPI-related symptoms!

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