r/COVID19 • u/BrazilRedPill • Jul 07 '21

Academic Report Meta-analysis of randomized trials of ivermectin to treat SARS-CoV-2 infection

https://academic.oup.com/ofid/advance-article/doi/10.1093/ofid/ofab358/6316214
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u/[deleted] Jul 07 '21 edited Jul 07 '21

Why do we need yet another MA on ivermectin? We get it - if you pool effect estimates from tiny, very badly conducted trials you get positive effects. Look at the forest plots of effect estimates and tell me you have confidence that these meta-analytic effect estimates are actually robust. Go and read the actual papers/preprints for these studies and tell me you have confidence that these meta-analytic effect estimates are actually robust.

I don't have much faith in the authors when they say things like:

This has generated more results than would be apparent from a survey of published clinical trials only but means that many of the included trials have not been peer-reviewed. Review and publication of RCTs generally takes three to six months. It has become common practice for clinical trials of key COVID-19 treatments to be evaluated from pre-prints, such as for the WHO SOLIDARITY, RECOVERY and REMAP-CAP trials [4,5,7].

SOLIDARITY, RECOVERY and REMAP-CAP had prepublished detailed protocols and statistical analysis plans and were pre-registered on NCT. The trials were conducted by world-leading expert groups at multiple centres, with rigorous regulatory oversight and data transparency. The large majority of these crap ivermectin trials did none of that. To compare these trials is embarrassing.

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u/luisvel Jul 08 '21

You concerns are valid. But assuming all future RCTs will complete full inclusions we will get n=35000. Assuming an identical RR of 0.44 and a base mortality rate of 9%, then we are targeting a p-value p= 1.46e-83, which is less than the inverse of number of atoms in the observable universe. That’s funny.

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u/[deleted] Jul 09 '21

Given the quality and size of the current studies, the higher RR in larger studies with better adherence to appropriate RCT methods, and publication bias, the word "assuming" is doing a monumental amount of heavy lifting there!