Kyowa Kirin (the US iteration) did a press release about its presentations at the ASBMR conference earlier this month, which I encourage you to read.
The findings aren’t surprising to patients — they boil down to a familiar message: #XLH is a whole-body, whole-life, whole-family disorder! No kidding! (I’m being a bit snarky here, frustrated by how often the message needs to be repeated before a significant number of clinicians hear it, but it really is important to keep translating the patient experience into data and to keep repeating the message.)
One thing I found interesting though is a bit of detour from the main points about the real-world experience of living with XLH — they relied heavily on diagnostic codes to identify the study population.
The article notes, “There were several study limitations including the lack of a specific diagnosis code for XLH.” They were referring to the fact that the relevant ICD10 code (E83.39) includes both x-linked and autosomal hypophosphatemias, and they were trying to look at X-linked only.
Which raises two issues, one a problem for all rare patients, and one specific to our community.
First, the common problem. The use of diagnostic codes to identify patients assumes that they’re correct, and we all know that they’re not even close. I had “nutritional rickets” as a current diagnosis as recently as ten years ago, when I was well past childhood. Even my endocrinologist’s office uses a “rickets” diagnosis, and she has significant XLH experience! In her case, it’s just an administrative carry-over from when I first went to that clinic, before there was an expert there., and it’s never been updated.
Rare patients’ records are littered with errors like that, along with misdiagnoses. I’m currently dealing with the fall-out from an endocrinologist getting all excited about the chance to diagnose a rare condition (not my XLH, but thyroid eye disease, aka TED), which sent me into a bit of a panic, (it can cause blindness) and caused me to waste time on unnecessary medical appointments over the past two years, when it’s pretty clear now that I never had TED at all, just other symptoms of a hyperactive thyroid.
The problem is that for the rest of my life, I’ll always have that diagnostic code for TED floating around in my records. Ditto for the “nutritional rickets” code and I don’t know what-all else (the ICU doctor came up with when I had my heart attack. He put all sorts of bizarre and terminal diagnoses in my record instead of asking me if certain anomalies were due to my XLH; yes, I’m still angry). AND THERE’S NO WAY TO DELETE OR FIX THE BAD CODES. Certainly no way for the patient to do it, and I’m not sure even a clinician could remove past diagnoses, as opposed to simply adding the correct one.
It’s mostly just annoying right now, but I’m worried about what will happen when Artificial Intelligence gets its hands on these wrong codes in our records, even the spelled-out diagnoses in our medical records. It won’t have any way of knowing which ones are correct and which aren’t, so when our records are fed into an AI system, it could causes problems for patients, especially those of us with rare conditions. Rare patients are particularly at risk for accumulating a lot of misdiagnoses, so we’re likely to be adversely affected more often than the non-rare patient. I’m not sure how to avoid that completely, but patients being able to correct misdiagnoses in the records would be a start, so the AI system would have to remove those misdiagnoses from its calculations.
The second issue related to diagnostic codes is more specific to the hypophosphatemia community, I think it’s actually GOOD that we’re combining the x-linked and autosomal hypophosphatemias (at least the FGF23-mediated ones) in a single code, since we have so much in common. It might encourage more research that includes both forms of transmission. As it stands now, with researchers insisting on separating them, we’re missing a lot of potentially useful information through natural history studies and other research that excludes autosomals. As long as you can tag which patients are x-linked and which are autosomal, it should be possible to collect data from both subgroups, and still produce statistics specific to each subgroup as well as for the subgroups combined. That’s the sort of thing that computers are good at — it’s EASY, so why not collect that information and simply sort it if necessary?
This really bugs me, because I think we’re missing out on some really useful information. It started when Ultragenyx insisted that only genetically-confirmed XLHers could participate in the burosumab trials. I don’t know what went into that decision, and it’s entirely possible that it was mandated by the FDA. The decision sort of makes sense based on the then-understanding of XLH and lack of information on autosomal variants. I understand that they (Ultragenyx and FDA) needed to focus their investigation, and presumably they felt that adding a few autosomals would complicate matters, perhaps make the data less clear. Personally, I think that was a bad decision since, again, it would have been possible to filter out the tiny number of autosomals if their results were different from the x-linked subjects. Plus, over the long term, it leaves the autosomals in no-patients-land, knowing burosumab would likely help them, but unable to access it, because the treatment would be off-label, not covered by insurance, and prohibitively expensive.
The trend for clinical trials today seems to be leaning more inclusive, especially with gene and cell therapy, but sadly that wasn’t so much the case in 2015 when the clinical trial protocols were established. I’d like to see the research into hypophosphatemia catch up to this trend, and start including autosomals in the participation criteria, to the extent feasible. And then maybe we can go even bigger, for research into the shared experiences across several rare bone disorders, not just the hypophosphatemias!
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Please note that the author is a well-read patient, not a doctor, and is not offering medical or legal advice.
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