I briefly dated someone with a PHD in cancer biology who worked on the marketing side for pharmaceuticals through a "consulting" company.
On multiple occasions I watched her manipulate datasets to produce visualizations favoring whatever drug was being pushed at that time.
The rationalization process was something like the treatments were basically all equally ineffective against the specific type/stage of cancer, but still the best choices at the time for people who were going to live for a brief period no matter what. So they tweak the graphs to slightly favor whoever is paying for the research, something on the order of a couple more months of life expectancy vs. the alternatives. Just enough to funnel the patients.
I'd like to raise the possibility that this is a milquetoast to reaction to something that sounds potentially criminal and cruel. I have a friend with a daughter coming out of 9 months of chemo. The thought that any of the many drugs she consumed, some of which could damaged her body in various ways, were unnecessary and given only because of fraud seems positively monstrous to me.
> this is a milquetoast to reaction to something that sounds potentially criminal
General statement: if you see someone manipulating clinical data for personal gain, write an anonymous letter to your state attorney general and top doctor. That is fraud. Brushing it off could be construed as aiding and abetting. At the very least, it is a moral failure.
I appreciate you sharing the story. There's a difference between characterizing a specific reaction as weak and calling a person weak.
There's also a natural human tendency to overlook horrors when they are abstract and "data" which is why "5000 dead" is a statistic, but that kid around the corner who died is a tragedy.
The word "milquetoast" specifically criticizes a man as weak, timid, unasertive, or childish. If that's not your intention, you're misusing the word.
It's not equivalent to saying "this is a weak reaction".
You may have preferred I reacted more severely to what I observed, but I, like everyone, must pick my battles and this particular one was and is not a priority for me. And if it were a priority, I wouldn't go about combating it at such an individual level - this is just a symptom of the profit-driven system. Just look at Purdue and the opiod crisis they've created by lying to doctors and consumers, and how rich and powerful they've become in the process. The behavior is rewarded systemically.
How is that possible though? You cant really tweak clinical results because it is auditable by authorities, and at most what is done to favor one drug over another is cherry picking during recruitment of patients (carrying the risk of narrowing your indications in the end) or excluding patients from the study (again that has to be fixed in the study design, you cant tweak it after the fact). The kind of hacking you describe would be just plainly not allowed and easy to discover upon any investigation.
There is quite a bit of leeway when you have real world data. You have to clean it. You can always find some justification. This is not neatly black/white at all. Similar in all other fields from accounting to law. I think it's a serious issue that we managed to make so many people believe way too strongly in absolutes ("science" as a magic word to end all discussions, because hey, "science" and "data" - now we have an objective reality!), when in reality the world is way more messy.
The original parent comment is describing someone hand-picking samples to obtain a predetermined conclusion. I know touching data to clean it before analysis can be a grey area, but the original parent comment -- if it is accurate -- is describing clear-cut fraud.
I refer back to what I wrote. You miss the point. There is no black/white in what is necessary and unnecessary or even nefarious "data cleaning". You just use the same fuzzy undefinable words again, but you did not make it any more a "hard fact" than any of it was before.
On multiple occasions I watched her manipulate datasets to produce visualizations favoring whatever drug was being pushed at that time.
The rationalization process was something like the treatments were basically all equally ineffective against the specific type/stage of cancer, but still the best choices at the time for people who were going to live for a brief period no matter what. So they tweak the graphs to slightly favor whoever is paying for the research, something on the order of a couple more months of life expectancy vs. the alternatives. Just enough to funnel the patients.
sigh