Bioequivalence and Bioavailability Forum • CI and alfa

Yura
★

Belarus,
2016-11-23 09:50
(3093 d 09:28 ago)

Posting: # 16808
Views: 5,929

CI and alfa [RSABE / ABEL]

Dear All,
We spend in replicate design TRR / RTR / RRT three repeated measurements. Question: how to take the level of alpha and confidence interval for the point estimate calculation between measurements (T-R1, T-R2, R1-R2)? I assumed an alpha of 0.017 and CI 96.6. :confused:

Thanks for your comments in advance

Above - for Cmax. AUCt - without reference drug - Alpha 0.025 and CI 95,0?

Edit: Merged with a later post. You can edit your OP within 24 hours (see here). [Helmut]

ElMaestro
★★★

Denmark,
2016-11-24 22:35
(3091 d 20:42 ago)

@ Yura
Posting: # 16810
Views: 4,798

CI and alfa

Post reply

Hello Yura,

❝ We spend in replicate design TRR / RTR / RRT three repeated measurements. Question: how to take the level of alpha and confidence interval for the point estimate calculation between measurements (T-R1, T-R2, R1-R2)? I assumed an alpha of 0.017 and CI 96.6. :confused:

Something sounds a bit odd here. TRR/RTR/RRT with two different Ref's is not a replicate design; alpha adjustment is in that situation usually not what you want to do. But I would be entirely wrong, depending on the question you are actually asking in your trial. What is the purpose of the R1-R2 CI?

Let's get some more info. :-)

—
Pass or fail!
ElMaestro

Yura ★ Belarus, 2016-11-25 08:51 (3091 d 10:26 ago) @ ElMaestro Posting: # 16811 Views: 4,902	CI and alfa Post reply
	Hello, ElMaestro Design - partial replicate. Each volunteer experience once the tablet T and twice R. Receive individual BE. For the difference T - R (1) and T - R (2) is carried out and the point estimate is based CI. If extend beyond BE, using the R (1) - R (2) - to expand CI, but only for Cmax. Thanks

Helmut
★★★

Vienna, Austria,
2016-11-25 14:00
(3091 d 05:17 ago)

@ Yura
Posting: # 16813
Views: 5,022

iteratively adjusted α

Post reply

Hi Yura,

since Belarus as a member of the EAEU (which in its GL closely followed the EMA’s rules for reference-scaling by Average Bioquivalence with Expanding Limits – ABEL), according “to the book” no adjustment of α is required (i.e., 90% CI of T vs. R).
However, when you suspect multiplicity issues – which might lead to an inflation of the Type I Error – you are right (Labes and Schütz¹, Muñoz et al.², Wonnemann et al.³)! Adjusting α in such a way that the consumer risk is preserved at 0.05 is provided in the open-source

package PowerTOST, function scABEL.ad().
No adjustment of α is required for PK metrics assessed by (conventional unscaled) ABE (like AUC). Adjustment for PK metrics intended for reference-scaling (like C_max) depends on the CV_wR and – to a minor degree – on the sample size. I would not recommend Bonferroni’s correction (i.e., α 0.025) because generally it is unnecessarily conservative and negatively impacts power. BTW, in rare cases (extremely high sample sizes) you would have to go below 0.025…

Labes D, Schütz H. Inflation of Type I Error in the Evaluation of Scaled Average Bioequivalence, and a Method for its Control. Pharm Res. 2016;33(11):2805–14. doi:10.1007/s11095-016-2006-1. full-text view-only.
Muñoz J, Alcaide D, Ocaña J. Consumer's risk in the EMA and FDA regulatory approaches for bioequivalence in highly variable drugs. Stat Med. 2016;35(12):1933–43. doi:10.1002/sim.6834.
Wonnemann M, Frömke C, Koch A. Inflation of the Type I Error: Investigations on Regulatory Recommendations for Bioequivalence of Highly Variable Drugs. Pharm Res. 2015;32(1):135–43. doi:10.1007/s11095-014-1450-z.

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Helmut Schütz

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Yura ★ Belarus, 2016-11-25 20:28 (3090 d 22:49 ago) @ Helmut Posting: # 16814 Views: 4,753	iteratively adjusted α Post reply
	thank you, Dear Helmut