Alex ☆ Austria, 20231222 11:08 (72 d 16:40 ago) Posting: # 23800 Views: 1,023 

Hi all, I am wondering whether the following publication made it to your attention: Wynne et al. (2022): A randomized, adaptive design, doubleblind, 3arm, parallel study assessing the pharmacokinetics and safety of AVT02, a highconcentration (100 mg/mL) Adalimumab biosimilar, in healthy adult subjects (ALVOPAD FIRST). I would love to get your opinion on it. I was the opinion that only simulationbased methods (Fuglsang 2014  Sequential Bioequivalence Approaches for Parallel Designs) are currently available/acceptable for parallel group designs due to the complexity of contructing repeated confidence intervals allowing for unequal variances between groups (a requirement for parallel designs according to FDA guidelines). However, in the publication repeated confidence intervals were constructed using the Fisher combination test assuming equal variances (3 parallel treatment arms were analysed using ANOVA). What do you think about it? I also have another question (likely a stupid one but it is in my head since some time). As there seems to be no solution currently avaiable for adaptive parallel group designs that analytically controls the typeIerror using the confidence interval inclusion approach and allows for unequal variances, wouldn't it be acceptable to use a hypothesis test like in (Maurer 2016  Controlling the type I error rate in twostage sequential adaptive designs when testing for average bioequivalence) only? In that case, we cannot construct confidence intervals consistent with the hypothesis test but the decision for BE=Y/N can be answered, right? I know that FDA guidelines state that it needs to be done by the confidence interval but is this less preferable than using Potvin's algorithm (not strictly controlling typeIerror)? Thanks in advance, any opinion is highly recommended! Alex 
Helmut ★★★ Vienna, Austria, 20231222 13:01 (72 d 14:47 ago) @ Alex Posting: # 23801 Views: 891 

Hi Alex, ❝ I am wondering whether the following publication made it to your attention: … No. ❝ I was the opinion that only simulationbased methods (Fuglsang 2014) are currently available/acceptable for parallel group designs due to the complexity of contructing repeated confidence intervals allowing for unequal variances between groups (a requirement for parallel designs according to FDA guidelines). Right. I had serious problems convincing European regulators even with extensive simulations (unequal variances and/or group sizes due to dropouts). Note that the FDA is fine with simulationbased methods (5^{th} GBHI workshop*). ❝ However, in the publication repeated confidence intervals were constructed using the Fisher combination test assuming equal variances (3 parallel treatment arms were analysed using ANOVA). What do you think about it? Equal variances are a rather strong assumption, right? Very – very! – unlikely in practice. The ttest is sensitive (i.e., liberal) to unequal variances and – to a minor extent – to unequal group sizes. Not by any chance the Welchtest is the default in R and SAS. Was in the paper an ANOVA (with all arms) used? A pooled variance is just crap. Follow the “TwoataTime” approach, i.e., two analyses with pairwise comparisons. That’s recommended in the latest guidelines (FDA, EMA, ICH M13A). ❝ As there seems to be no solution currently avaiable for adaptive parallel group designs that analytically controls the typeIerror using the confidence interval inclusion approach and allows for unequal variances, … Right. ❝ … wouldn't it be acceptable to use a hypothesis test like in (Maurer 2016) only? Unlikely, though that’s a Radio Yerewan question. ❝ In that case, we cannot construct confidence intervals consistent with the hypothesis test but the decision for BE=Y/N can be answered, right? When we had a poster about this stuff (doi:10.1186/1745621516S2P218), Franz said “it’s doable in principle”. Well roared, lion. It’s on the todolist of Benjamin Lang (main author of the inverse normal method in the package Power2Stage ). Difficult… ❝ I know that FDA guidelines state that it needs to be done by the confidence interval but is this less preferable than using Potvin's algorithm (not strictly controlling typeIerror)? I don’t think that any agency will accept a study without a CI. BTW, the EMA ❤️ a stageterm in the final analysis. Calls for an ANOVA, right? That’s like deciding between Skylla (ANOVA ignoring unequal variances to make regulators happy) and Charybdis (Welchtest given regulators headaches). Michael Tomashevskiy suggested some code a while ago but it’s not implemented in the function power.tsd.p() yet.
— Diftor heh smusma 🖖🏼 Довге життя Україна! _{} Helmut Schütz The quality of responses received is directly proportional to the quality of the question asked. 🚮 Science Quotes 
Alex ☆ Austria, 20240108 17:22 (55 d 10:26 ago) @ Helmut Posting: # 23822 Views: 638 

Hi Helmut, thanks for confirming my understanding. Yes, as far as I understood, the paper uses ANOVA, which caused confusion at my side and was the reason for my post. I thought that I may have missed something. But I totally agree with you, the “TwoataTime” approach with unequal variances would have been the better choice (but again leading to the problem of contructing RCIs for the inverse normal combination test and the need to use Potvin's algorithms). Hope to see you again in person soon. Alex 
Helmut ★★★ Vienna, Austria, 20240109 10:48 (54 d 17:00 ago) @ Alex Posting: # 23825 Views: 598 

Hi Alex, ❝ Yes, as far as I understood, the paper uses ANOVA,… ❝ […] the “TwoataTime” approach with unequal variances would have been the better choice (but again leading to the problem of contructing RCIs for the inverse normal combination test and the need to use Potvin's algorithms). ❝ Hope to see you again in person soon. — Diftor heh smusma 🖖🏼 Довге життя Україна! _{} Helmut Schütz The quality of responses received is directly proportional to the quality of the question asked. 🚮 Science Quotes 
Achievwin ★ US, 20240105 12:53 (58 d 14:56 ago) @ Alex Posting: # 23819 Views: 699 

I am thinking of using two stage approach for a parallel BE study (in patients) is there an accepted procedure for sample size calculations? at stage 1 and stage 2? Any instances where FDA accepted a two stage design methodology for calculating samples size for stage 2 after reviewing stage 1 results? 
Helmut ★★★ Vienna, Austria, 20240105 13:40 (58 d 14:09 ago) @ Achievwin Posting: # 23820 Views: 694 

Hi Achievwin, ❝ I am thinking of using two stage approach for a parallel BE study (in patients) is there an accepted procedure for sample size calculations? at stage 1 and stage 2? ❝ Any instances where FDA accepted a two stage design methodology for calculating samples size for stage 2 after reviewing stage 1 results? The relevant points:
If you give me your current email address, I will send you the presentation. Practically for parallel designs simulations are mandatory because:
Power2Stage , function power.tsd.p() .Start with a reasonably narrow grid of n_{1} / CV_{1} combinations to find a – preliminary – adjusted α which controls the Type I Error. Repeat with some scenarios based on the worst case expected dropout rate (same for T and R, all under T – none under R and vice versa), different CVs (CV_{T} < CV_{R}, CV_{T} > CV_{R}). If the Type I Error is still controlled in all scenarios, fine. If not (likely), adjust more. One of mine. α_{adj} 0.0274, validated for n_{1} 124–250, homoscedastic CV 50% (our best guess), heteroscedastic (variance ratios 1:4 to 4:1). Maximum empirical Type I Error 0.04987: 32 pages report with justification, methods, all results, scripts to reproduce them. Not accepted by the EMA because “we don’t like (‼) simulations”… — Diftor heh smusma 🖖🏼 Довге життя Україна! _{} Helmut Schütz The quality of responses received is directly proportional to the quality of the question asked. 🚮 Science Quotes 
Achievwin ★ US, 20240108 17:55 (55 d 09:53 ago) @ Helmut Posting: # 23823 Views: 619 

Thank you for your nice reply. 
Helmut ★★★ Vienna, Austria, 20240109 10:31 (54 d 17:17 ago) @ Achievwin Posting: # 23824 Views: 591 

Hi Achievwin, ❝ Thank you for your nice reply. Just to be clear: Some authors (right now I’m reviewing a manuscript submitted to Stat Med…) believe (‼) that Pocock’s \(\small{\color{Blue}{\alpha_\text{adj}=0.0294}}\) (94.12% CI) is ‘universally’ valid. This is a gross misunderstanding and not even wrong. It was derived for superiority testing in a GSD (fixed sample size N) with one interim at – exactly – N/2 and known variances. The fact that it controlled the Type I Error in Potvin’s Method B (TSD in a 2×2×2 design) was a mere lucky punch. In my example I needed \(\small{\color{Red}{\alpha_\text{adj}=0.0274}}\) (94.52% CI) to control the Type I Error. — Diftor heh smusma 🖖🏼 Довге життя Україна! _{} Helmut Schütz The quality of responses received is directly proportional to the quality of the question asked. 🚮 Science Quotes 
Achievwin ★ US, 20240109 22:11 (54 d 05:37 ago) @ Helmut Posting: # 23826 Views: 557 

Hi Helmut: ❝ Just to be clear: Some authors (right now I’m reviewing a manuscript submitted to Stat Med…)" I and everyone absolutely interested to know essence of that article you are reviewing. 
Helmut ★★★ Vienna, Austria, 20240109 23:10 (54 d 04:38 ago) @ Achievwin Posting: # 23827 Views: 567 

Hi Achievwin, ❝ I and everyone absolutely interested to know essence of that article you are reviewing. — Diftor heh smusma 🖖🏼 Довге життя Україна! _{} Helmut Schütz The quality of responses received is directly proportional to the quality of the question asked. 🚮 Science Quotes 
Achievwin ★ US, 20240119 16:11 (44 d 11:38 ago) @ Helmut Posting: # 23833 Views: 434 

❝ Sorry, as long as the review process is ongoing I cannot say anything about it. understood and respect that 