How to deal with multiple treatment or dose groups in randomized clinical trials?

Abstract

Multiplicity adjustment in general is currently a controversial topic. This review focuses on the proof of efficacy in randomized clinical trials. The ICH guidelines mandate control of the familywise error rate. Confidence intervals are clinically more appropriate than P-values or yes/no decisions. Therefore, simultaneous confidence intervals are proposed for several designs and aims in clinical trials. The computation of simultaneous confidence intervals for the difference or the ratio is demonstrated by means of real data examples using the R-packages multcomp and mratios. A special problem is the evaluation of dose-finding trials with and without the assumption that the effects increase with increasing doses. Simultaneous intervals are presented not only for one-way layouts and normal distributed endpoints, but also for higher way layouts, generalized linear models, and mixed models. Under importance ordering, the conditional testing of all hypotheses at level alpha will be shown using the intersection-union test principle. Other multiplicity issues (i.e. multiple endpoints, multiple analyses, and subgroup analyses) are discussed.

Statistical analysis of no observed effect concentrations or levels in eco-toxicological assays with overdispersed count endpoints

“…Corresponding R-code is included in the Appendix III for the examples and can be easily adapted to other data situations. (1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L), .Label = c("Control", "D188", "D375", "D750", "Positive" ), class = "factor"), animal = c (1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,22,23,24), MN = c(4, 2, 4, 2, 2, 3, 5, 7, 2, 0, 5, 6, 1, 4, 2, 2, 4, 1, 1, 0, 26, 28, 22, 37, 29)), .Names = c("group", "animal", "MN"), row.names = c(NA, 25L), class = "data.frame") ## ----datDapnhia, echo=FALSE, result='asis', warning=FALSE------------------------------------daphnia <structure(list('Concentration ' = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1.56, 1.56, 1.56, 1.56, 1.56, 1.56, 1.56, 1.56, 1.56, 1.56, 3.12, 3.12, 3.12, 3.12, 3.12, 3.12, 3.12, 3.12, 3.12, 3.12, 6.25, 6.25, 6.25, 6.25, 6.25, 6.25, 6.25, 6.25, 6.25, 6. 25, 12.5, 12.5, 12.5, 12.5, 12.5, 12.5, 12.5, 12.5, 12.5, 12.5, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25), Adults = c (1,2,3,4,5,6,7,8,9,10,1,2,3,4,5,…”

“…an agreed effect size which is not considered toxicologically relevant. However, also the assumption of NOAEC via N OAEC = D M ED − 1 is problematic because of the direct control of the false positive error rate, and also because the definition of the minimum effective dose (MED) is blurred: significant or relevant decision, assuming a concentration-response monotonicity into account or not, using hypothesis tests or nonlinear models, modeling concentration qualitatively [9] or quantitatively [29,3].…”

How to deal with multiple treatment or dose groups in randomized clinical trials? Another approach

“…In a recent article in the Journal, Hothorn raised the issue of multiple testing in clinical trial data analysis [1]. He took a couple of examples where statistical analysis led to a high probability of false‐positive conclusion if the inflated α‐risk due to multiple testing had not been corrected.…”

Evaluating the Performance of Simultaneous Stepwise Confidence Intervals for the Difference between two Poisson Rates

“…However, confidence intervals can offer important additional information in many studies. For example, if there is no consensus on the value of a clinically relevant threshold, which is the case for many therapeutic areas (Hothorn, 2007), findings from non-inferiority studies involving the threshold are more informative when reported in terms of confidence intervals. Technical guidelines for the registration of pharmaceuticals for human use affirm that confidence intervals are as important as the use of statistical tests for estimating the relationship of dose and response and assert that confidence intervals should be provided when reporting estimates of treatment effects (ICH E9 Expert Working Group, 1999).…”