## statistically significant ≠ clinically relevant [General Sta­tis­tics]

Hi Siva Krishna,

I guess 100% was not contained in the 90% CI, right?
If yes, you have a statistically significant difference which is clinically not relevant.1 We abandoned testing for a statistically significant difference (see ElMaestro’s post) 33 (‼) years ago with Schuirmann’s TOST.2 To quote Wasserstein et al.3

Don’t Say “Statistically Significant”

For which power did you plan the study? It might well be that
• the T/R-ratio was closer to 100% than assumed and/or
• the CV was lower than assumed and/or
• the dropout-rate was lower than anticipated.
Any of those (and their combinations) will lead to higher power and increases the chance of a statistically significant treatment effect.
See also the second part of this post. If you are in the lower right quadrants, you have high power and a statistically significant treatment effect is likely.

1. $$\small{\Delta}$$ = clinically relevant difference. Commonly 0.20 (20%). For NTIDs (EMA and other jurisdicions) $$\small{\Delta}$$ 0.10, for Cmax (Russian Federation, EEU, GCC) $$\small{\Delta}$$ 0.25. For HVD(P)s, where CVwR >30%, $$\small{\Delta}$$ >0.30 (scaled to the variability of the reference). The acceptance range for bioequivalence $$\small{\left \{\theta_1,\theta_2\right \}}$$ is calculated by $$\small{\theta_1=1-\Delta}$$, $$\small{\theta_2=(1-\Delta)^{-1}}$$. If the 90% CI lies entirely within $$\small{\left \{\theta_1,\theta_2\right \}}$$, the observed difference of the treatment effect is considered clinically not relevant – irrespective how wide the CI is or where the point estimate lies. A formulation with a PE of 100% (CI 80.00–125.00%) is as BE as another with a PE of 85% (CI 80.00–90.31%). In the former case you were extremely lucky and in the second you have a statistically significant difference (100% not contained in the CI).
2. 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.
3. Wasserstein RL, Schirm AL, Lazar NA. Moving to a World Beyond “p < 0.05”. Am Stat. 2019; 73(sup1): 1–19. doi:10.1080/00031305.2019.1583913. Open access.

Dif-tor heh smusma 🖖
Helmut Schütz

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