Deep shit [RSABE / ABEL]

posted by Helmut Homepage – Vienna, Austria, 2020-01-31 13:00 (445 d 13:29 ago) – Posting: # 21119
Views: 14,399

Hi Mikalai,

» You seem to strengthen my doubts.


» » If you fail ABE (first assessment with a nominal α 0.05), you assess it for ABEL (second assessment with a nominal α 0.05). […] Two tests, each performed at level 0.05. Inflated Type I Error. Full stop.

» It has no practical sense for me. As I know trials frequently recalculated with some modifications, usually slight ones. I saw that the FDA did this, for example. I do not see that alpha levels were reduced in those recalculations.

Not limited to the FDA. We (CROs, applicants) could never, ever recalculate a study because that would be judged by assessors as cherry-picking. :cherry picking:
Of course, regulators play not in another league but in another sport, which can be expressed as

[image] Quod licet Iovi, non licet bovi

The problem with a recalculation is – since the entire α was already spent in the original analysis – the TIE → ∞. Now what? If a passing study fails now, no problem; the risk is only a theoretical one since the product will not be marketed based on this study. Question: What is the TIE if the recalculated study passes as well?

» If we employ this approach (no recalculations or lower alpha level) …

Once you started with an α which controls the TIE in the original analysis, any lower α in the recalculation cannot work. OK, you could submit all studies with a 92% CI (α 0.04) and – if a recalculation is requested – perform it with a 98% CI (α 0.01). Power drops through the floor, good luck.

» … we may paralyze the whole industry …

Agree, also with your examples.

» Actually, we can ask people from the forum how many sponsors or CROs they know whose trials have never been recalculated?

Good idea. Only very few of mine. ;-)

» It seems that we have to multiple the ABE column by 2 to get full the sample size but not the ABEL column; otherwise, it has no much sense for me.

Duno what you mean. Are you considering the sample size of a 2×2×2 crossover? The sample size of the 2-period 4-sequence full replicate is ~½ though the number of treatments / biosamples (driving the study cost) are essentially the same.
CV (%) ABE.2x2x2 ABE.2x2x4 n.ABEL n.ABEL.Bonf n.ABEL.adj n.Molins
    20        20        10     18          24         18       22
    30        40        20     34          44         42       42
    40        66        34     30          38         32       36
    50        98        50     28          34         28       32

» I also wonder if the dropout rate has been considered in the calculations.

No. That’s specific to the drug and I never “compensate for potential dropouts in order to maintain power” unless I expect a dropout rate of >15%. Waste of money because the impact of dropouts on power is generally small. Try the functions pa.ABE() and pa.scABE() of PowerTOST.

» Looking at your table and slides post, it is appears that in the region CV between 30 - 40% the sample size for ABEL and ABE trials may be very close to each other.

The plots in the slide are all for ABEL. A comparison of ABE and the EMA’s (unadjusted) ABEL:


At 30% sample sizes are 40 and 34, at 40% 68 and 30.

» If it is true, the ABEL trials (CV between 30-40) should not be allowed by ethic and regulatory bodies because of unnecessary risks for subjects. It invalidates the RABE/ABEL approach in this region.

Hhm, not sure what you mean.

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Helmut Schütz

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