Hi Ryan, I need to know what input data and assumptions he used to be able to verify/replicate/interpret his math. Without this information, I cannot comment further. Thanks!
You could cast about for various relevant base-rates (“What is the chance of any given proposed conjecture in medical science being true?” “What is the chance of a given medical trial giving a positive result?”). Crisp data on these questions are hard to find, but the proportion for either is comfortably less than even. (Maybe ~5% for the first, ~20% for the second).
From something like this one can make further adjustments based on the particular circumstances, which are generally in the adverse direction:
Typical trials have more than n=6 non-consecutive case series behind them, and so this should be less likely to replicate than the typical member of this class.
(Particularly, heterodox theories of pathogenesis tend to do worse, and on cursory search I can find a alternative theories of Crohn’s which seem about as facially plausible as this).
The wild theory also imposes a penalty: even if the minimal prediction doesn’t demand the wider ‘malasezzia causes it etc.’, that the hypothesis is generated through these means is a further cost.
There’s also information I have from medical training which speaks against this (i.e. if antifungals had such dramatic effects as proposed, it probably would have risen to attention somewhat sooner).
All the second order things I noted in my first comment.
As Ryan has explained, standard significance testing puts a floor of 2.5% of a (false) positive result in any trial even if the true effect is zero. There is some chance the ground truth really is that itraconazole cures Crohn’s (given some evidence of TNFa downstream effects, background knowledge of fungal microbiota disregulation, and the very slender case series), which gives it a small boost above this, although this in itself is somewhat discounted by the limited power of the proposed study (i.e. even if Itraconazole works, the study might miss it).
Hi Gregory, Thanks for the detailed answer. I’m still not clear on how the numbers quoted above (0.005, 3%, 2.5%) were calculated, nor how they affect the probability of Samuel et al 2010 replicating successfully. It is worthwhile to break down the problem in two parts:
(I) Does Samuel et al 2010 give us any information to support the hypothesis that Crohn’s might be cured by itraconazole? If so, how much?
(II) How large does an RCT need to be to properly test this hypothesis?
Answering these two questions is essential to determine if Samuel et al 2010 should be replicated or not (obviously with proper controls this time). This is what I am trying to determine with this forum post: should we raise ~500K$ to replicate it or not? What is the expected return on giving for this experiment?
Hi Ryan, I need to know what input data and assumptions he used to be able to verify/replicate/interpret his math. Without this information, I cannot comment further. Thanks!
In hope but little expectation:
You could cast about for various relevant base-rates (“What is the chance of any given proposed conjecture in medical science being true?” “What is the chance of a given medical trial giving a positive result?”). Crisp data on these questions are hard to find, but the proportion for either is comfortably less than even. (Maybe ~5% for the first, ~20% for the second).
From something like this one can make further adjustments based on the particular circumstances, which are generally in the adverse direction:
Typical trials have more than n=6 non-consecutive case series behind them, and so this should be less likely to replicate than the typical member of this class.
(Particularly, heterodox theories of pathogenesis tend to do worse, and on cursory search I can find a alternative theories of Crohn’s which seem about as facially plausible as this).
The wild theory also imposes a penalty: even if the minimal prediction doesn’t demand the wider ‘malasezzia causes it etc.’, that the hypothesis is generated through these means is a further cost.
There’s also information I have from medical training which speaks against this (i.e. if antifungals had such dramatic effects as proposed, it probably would have risen to attention somewhat sooner).
All the second order things I noted in my first comment.
As Ryan has explained, standard significance testing puts a floor of 2.5% of a (false) positive result in any trial even if the true effect is zero. There is some chance the ground truth really is that itraconazole cures Crohn’s (given some evidence of TNFa downstream effects, background knowledge of fungal microbiota disregulation, and the very slender case series), which gives it a small boost above this, although this in itself is somewhat discounted by the limited power of the proposed study (i.e. even if Itraconazole works, the study might miss it).
Hi Gregory, Thanks for the detailed answer. I’m still not clear on how the numbers quoted above (0.005, 3%, 2.5%) were calculated, nor how they affect the probability of Samuel et al 2010 replicating successfully. It is worthwhile to break down the problem in two parts:
(I) Does Samuel et al 2010 give us any information to support the hypothesis that Crohn’s might be cured by itraconazole? If so, how much?
(II) How large does an RCT need to be to properly test this hypothesis?
Answering these two questions is essential to determine if Samuel et al 2010 should be replicated or not (obviously with proper controls this time). This is what I am trying to determine with this forum post: should we raise ~500K$ to replicate it or not? What is the expected return on giving for this experiment?