Trials avoid high risk patients and underestimate drug harms

It's understandable that unusual patients are seen as confounding variables in any study, especially those with small numbers of patients. Though I haven't read beyond the abstract, it also makes sense that larger studies (phase 3 or 4) should not exclude such patients, but perhaps could report results in more than one way -- including only those with the primary malady as well as those with common confounding conditions.

Introducing too many secondary conditions in any trial is an invitation for the drug to fail safety and/or efficacy due to increased demands on both. And as we all know, a huge fraction of drugs fail in phase 3 already. Raising the bar further, without great care, will serve neither patients nor business.

Abstract: "The FDA does not formally regulate representativeness, but if trials under-enroll vulnerable patients, the resulting evidence may understate harm from drugs. We study the relationship between trial participation and the risk of drug-induced adverse events for cancer medications using data from the Surveillance, Epidemiology, and End Results Program linked to Medicare claims. Initiating treatment with a cancer drug increases the risk of hospitalization due to serious adverse events (SAE) by 2 percentage points per month (a 250% increase). Heterogeneity in SAE treatment effects can be predicted by patient's comorbidities, frailty, and demographic characteristics. Patients at the 90th percentile of the risk distribution experience a 2.5 times greater increase in SAEs after treatment initiation compared to patients at the 10th percentile of the risk distribution yet are 4 times less likely to enroll in trials. The predicted SAE treatment effects for the drug's target population are 15% larger than the predicted SAE treatment effects for trial enrollees, corresponding to 1 additional induced SAE hospitalization for every 25 patients per year of treatment. We formalize conditions under which regulating representativeness of SAE risk will lead to more externally valid trials, and we discuss how our results could inform regulatory requirements."

I've personally been excluded from several depression clinical trials for having suicidal ideations, it makes me wonder just what kind of "depression" they are testing drugs on.

i would imagine to make life of the statisticians downstream easier

Tangentially related, but I was surprised to learn about the lax attitude towards placebos in trials. Classes of drugs have expected side effects, so it's common to use medications with similar effects as placebos. Last I heard, there is no requirement or expectation to document placebos used, and they are often not mentioned in publications.

This covers the trials not being fully representative, but largely neglects why that is the case.

The paper defines a population "at high risk of drug-induced serious adverse events", which presumably means they're also the most likely people to be harmed or killed by the drug trial itself.

This was a plot in an early season of ER.

Move generally, whenever you read the percentage of patients that are noted as having a particular side effect from a medicine, the real percentage is much higher.

See also: women.

This problem is actually even worse than the article identifies, because broad definitions of what a "risk" is, result in broad exclusions.

The most pernicious of these problems is that women--yes, more than half the earth's population--are considered a high risk group because researchers fear menstrual cycles will affect test results. Until 1993 policy changes, excluding women from trials was the norm. Many trials have not been re-done to include women, and the policies don't include animal trials, so many rat studies, for example, still do not include female rats--a practice which makes later human trials more dangerous for (human) female participates.

[1] Sort of one citation: https://www.aamc.org/news/why-we-know-so-little-about-women-... There's more than this--I wrote a paper about this in college, but I don't have access to jstor now, so I'm not sure I could find the citations any more.