Strange result [Regulatives / Guidelines]
❝ […] I read some report […] and the one sided 90% CI was reported as lower = -18.33%, upper = -6.36%; T/R Ratio = 93.86, n=24. I found it strange to report CI in such a way so I was wondering if the reporting was based on some old rules.
Strange!
As the name tells, TOST are interval (significance) tests giving two p-values – one for the 1st (left) test where
H01: PE < ln(1–0.2)
H11: PE ≥ ln(1–0.2)
H02: PE > ln(1+0.2)
H12: PE ≤ ln(1+0.2).
The two one-sided hypotheses at the α = 0.05 level of
significance should be tested for AUC and Cmax by con-
structing the 90% confidence interval for the ratio
between the test and reference averages.
Coming back to your case. I’ve never seen results reported in such a way.
If we would report the CI as usual we would give (93.86 – 18.33)% = 75.53% and (93.86 – 6.36)% = 87.53% and the study failed (like nobody assumed). But then we have another problem with the reported T/R-ratio which transforms to (93.86 – 100)% = –6.14%. Then –18.33% < –6.14% < –6.36%, or what? Based on 100√0.7553 × 0.8753 we get 81.29% ≠ 93.86%.
Or are the boundaries given relative to 100%? Bizarre. However, then the study would pass since (100 – 18.33)% = 81.67% and (100 – 6.36)% = 93.64%. Note that the reported PE is outside the CI…
❝ […] (dated 1990; the synopsis only)
Was the study performed for Health Canada? In the 1989 draft 80–120% (untransformed data) were recommended and changed to 80–125% (log-transformed) in 1991.
Then the study would have passed again cause –18.33% > –20% and –6.36% < +20%. However, the problem with the PE persists cause 100(–0.1833 + (–0.0636)) / 2 = –12.35% ≠ –6.14%. I don’t get it.
- I did it myself in a few studies upon sponsor’s wish. In all cases assessors asked for the 90% CI later…
For ages I do it the other way ’round. Describe the confidence interval inclusion approach according to the guidelines and – to make newbies happy – state that it is “operationally equivalent” to TOST.
- Brown LD, Casella G, Hwang JTG. Optimal Confidence Sets, Bioequivalence, and the Limaçon of Pascal. J Amer Statist Assoc. 1995;90(431):880–9. doi:10.1080/01621459.1995.10476587. free resource.
- Schuirmann DJ. A comparison of the Two One-Sided Tests Procedure and the Power Approach for Assessing the Equivalence of Average Bioavailability. J Pharmacokin Biopharm. 1987;15(6):657–80. doi:10.1007/BF01068419.
- FDA/CDER. Guidance for Industry. Statistical Procedures for Bioequivalence Studies Using a Standard Two-Treatment Crossover Design. Jul 1992. Internet Archive.
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Helmut Schütz
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Science Quotes
Complete thread:
- History lessons - FDA BE 90% CI jag009 2019-02-25 22:03 [Regulatives / Guidelines]
- History lessons - FDA BE 90% CI nobody 2019-02-25 22:39
- History lessons - FDA BE 90% CI Helmut 2019-02-26 00:44
- History lessons - FDA BE 90% CI jag009 2019-02-26 15:19
- History lessons - FDA BE 90% CI nobody 2019-02-26 16:07
- Strange resultHelmut 2019-02-28 12:03
- Strange result nobody 2019-03-01 08:50
- Pandora's box? jag009 2019-03-01 17:40
- Confusing Helmut 2019-03-02 15:37
- Pandora's box? jag009 2019-03-01 17:40
- Strange result jag009 2019-03-01 17:44
- Transformation, acceptance range Helmut 2019-03-02 15:09
- Transformation, acceptance range nobody 2019-03-02 16:42
- Transformation, acceptance range Helmut 2019-03-02 15:09
- Strange result nobody 2019-03-01 08:50
- History lessons - FDA BE 90% CI jag009 2019-02-26 15:19
- History lessons - FDA BE 90% CI Helmut 2019-02-26 00:44
- History lessons - FDA BE 90% CI nobody 2019-02-25 22:39