BackgroundThe efficacy and benefits of telmisartan in cats with chronic kidney disease (CKD) have not previously been reported.HypothesisLong‐term treatment of cats with CKD using telmisartan decreases urine protein‐to‐creatinine ratio (UP/C) similar to benazepril.AnimalsTwo‐hundred and twenty‐four client‐owned adult cats with CKD.MethodsProspective, multicenter, controlled, randomized, parallel group, blinded clinical trial with noninferiority design. Cats were allocated in a 1 : 1 ratio to either telmisartan (1 mg/kg; n = 112) or benazepril (0.5–1.0 mg/kg; n = 112) PO q24 h. The primary endpoint was prospectively defined as the change in proteinuria (benazepril:telmisartan) based on a log transformed weighted average of UP/C change from baseline (AUC 0→t/t) as a percentage compared using a confidence interval (CI) approach. Changes of UP/C from baseline were assessed on all study days and corrected for multiple comparisons.ResultsTelmisartan proved noninferior to benazepril in controlling proteinuria (CI, −0.035 to 0.268). At Day 180, UP/C compared to baseline in the telmisartan group was significantly lower (−0.05 ± 0.31; P = .016), whereas in the benazepril group the change (−0.02 ± 0.48) was not statistically significant (P = .136). Similar results were obtained at all assessment points with significant decrease in UP/C occurring with telmisartan but not benazepril.Conclusion and Clinical ImportanceBoth telmisartan and benazepril were well tolerated and safe. Telmisartan proved to be noninferior to benazepril and significantly decreased proteinuria relative to baseline at all assessment points whereas benazepril did not.

Statistical equivalence analyses are well-established parts of many studies in the biomedical sciences. Also in pharmaceutical development and manufacturing equivalence testing methods are required in order to statistically establish similarities between machines, process components, or complete processes. This article presents a choice of multivariate equivalence testing procedures for normally distributed data as generalizations of existing univariate methods. In all derived methods, variability is interpreted as nuisance parameter. The use of the proposed methods in pharmaceutical development is demonstrated with a comparative analysis of dissolution profiles.

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The score card is a first step in the assessment of adequate differentiation of tablets and can be used for the design of tablets that promote safe use of medication.

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