Alex Dmitrienko

Innovative Approaches for Designing and Analyzing Adaptive Dose-Ranging Trials

Inadequate selection of the dose to bring forward in confirmatory trials has been identified as one of the key drivers of the decreasing success rates observed in drug development programs across the pharmaceutical industry. In recognition of this problem, the Pharmaceutical Research and Manufacturers of America (PhRMA), formed a working group to evaluate and develop alternative approaches to dose finding, including adaptive dose-ranging designs. This paper summarizes the work of the group, including the results and conclusions of a comprehensive simulation study, and puts forward recommendations on how to improve dose ranging in clinical development, including, but not limited to, the use of adaptive dose-ranging methods.

General multistage gatekeeping procedures

A general multistage (stepwise) procedure is proposed for dealing with arbitrary gatekeeping problems including parallel and serial gatekeeping. The procedure is very simple to implement since it does not require the application of the closed testing principle and the consequent need to test all nonempty intersections of hypotheses. It is based on the idea of carrying forward the Type I error rate for any rejected hypotheses to test hypotheses in the next ordered family. This requires the use of a so-called separable multiple test procedure (MTP) in the earlier family. The Bonferroni MTP is separable, but other standard MTPs such as Holm, Hochberg, Fallback and Dunnett are not. Their truncated versions are proposed which are separable and more powerful than the Bonferroni MTP. The proposed procedure is illustrated by a clinical trial example.

Efficacy and safety of LY315920Na/S-5920, a selective inhibitor of 14-kDa group IIA secretory phospholipase A2, in patients with suspected sepsis and organ failure.

ObjectiveConcentrations of group IIA secretory phospholipase A2, an inflammatory response mediator, are increased in the plasma of patients with sepsis and septic shock, and the extent of elevation is correlated with mortality. LY315920Na/S-5920 is a selective inhibitor of group IIA secretory phospholipase A2 that has been shown to inhibit serum group IIA secretory phospholipase A2 enzyme activity in patients with severe sepsis. The primary objectives of this study were to determine whether there was a dose-response relationship between two doses of LY315920Na/S-5920 compared with placebo in the reduction of 28-day all-cause mortality in patients with severe sepsis and to determine whether LY315920Na/S-5920 had an acceptable safety profile. DesignMulticenter, double-blind, placebo-controlled trial of two doses of LY315920Na/S-5920 in a parallel design. PatientsA total of 586 patients with severe sepsis at 72 institutions in the United States. InterventionsPatients enrolled within 72 hrs from onset of first sepsis-induced organ failure were randomized (1:1:1) to low-dose LY315920Na/S-5920 (target plasma concentration of 200 ng/mL, n = 196), high-dose LY315920Na/S-5920 (800 ng/mL, n = 194), or placebo (n = 196). Study medication was administered as a constant-rate intravenous infusion for 168 hrs. Measurements and Main ResultsThe study was stopped prematurely because it was unlikely that a statistically significant difference in mortality between LY315920Na/S-5920 and placebo would be found. There was no effect of LY315920Na/S-5920 on the primary end point of 28-day all-cause mortality across the entire study population. The 28-day all-cause mortality was distributed as follows: placebo group, 33.2% (65/196 patients); low-dose LY315920Na/S-5920, 37.2% (73/196); and high-dose LY315920Na/S-5920, 36.1% (70/194);p = .525. However, in a prospectively planned analysis, there was a favorable overall dose-response effect on 28-day all-cause mortality in patients administered LY315920Na/S-5920 within 18 hrs of onset of the first sepsis-induced organ failure. Among these patients, 28-day all-cause mortality was distributed as follows: placebo group, 43.5% (20/46 patients); low-dose LY315920Na/S-5920, 31.4% (16/51); and high-dose LY315920Na/S-5920, 20.8% (10/48);p = .018. ConclusionsAdministration of LY315920Na/S-5920 had an acceptable safety profile in patients with severe sepsis. There was no overall survival benefit associated with the use of LY315920Na/S-5920 in this study. However, prospectively planned secondary analyses suggested that treatment with LY315920Na/S-5920 was associated with an improvement in survival in patients treated within 18 hrs of the first sepsis-induced organ failure.

Multiple Co-primary Endpoints: Medical and Statistical Solutions: A Report from the Multiple Endpoints Expert Team of the Pharmaceutical Research and Manufacturers of America

There are quite a few disorders for which regulatory agencies have required a treatment to demonstrate a statistically significant effect on multiple endpoints, each at the one-sided 2.5% level, before accepting the treatments efficacy for the disorders. Depending on the correlation among the endpoints, this requirement could lead to a substantial reduction in the studys power to conclude the efficacy of a treatment. To investigate the prevalence of this requirement and propose possible solutions, a multiple-disciplinary Multiple Endpoints Expert Team sponsored by Pharmaceutical Research and Manufacturers of America was formed in November 2003. The team recognized early that many researchers were not fully aware of the implications of requiring multiple co-primary endpoints. The team proposes possible solutions from both the medical and the statistical perspectives. The optimal solution is to reduce the number of multiple co-primary endpoints. If after careful considerations, multiple co-primary endpoints remain a scientific requirement, the team proposes statistical solutions and encourages that regulatory agencies be receptive to approaches that adopt modest upward adjustments of the nominal significance levels for testing individual endpoints. Finally, the team hopes that this report will draw more attention to the problem of multiple co-primary endpoints and stimulate further research.

Traditional multiplicity adjustment methods in clinical trials.

This tutorial discusses important statistical problems arising in clinical trials with multiple clinical objectives based on different clinical variables, evaluation of several doses or regiments of a new treatment, analysis of multiple patient subgroups, etc. Simultaneous assessment of several objectives in a single trial gives rise to multiplicity. If unaddressed, problems of multiplicity can undermine integrity of statistical inferences. The tutorial reviews key concepts in multiple hypothesis testing and introduces main classes of methods for addressing multiplicity in a clinical trial setting. General guidelines for the development of relevant and efficient multiple testing procedures are presented on the basis of application-specific clinical and statistical information. Case studies with common multiplicity problems are used to motivate and illustrate the statistical methods presented in the tutorial, and software implementation of the multiplicity adjustment methods is discussed.

Key multiplicity issues in clinical drug development

Much progress has been made over the past decade with the development of novel methods for addressing increasingly more complex multiplicity problems arising in confirmatory Phase III clinical trials. This includes traditional problems with a single source of multiplicity, for example, analysis of multiple endpoints or dose-placebo contrasts. In addition, more advanced problems with several sources of multiplicity have attracted attention in clinical drug development. These problems include two or more families of objectives such as multiple endpoints evaluated at multiple dose levels or in multiple patient populations. This paper provides a review of concepts that play a central role in defining and solving multiplicity problems (error rate definitions) and introduces main classes of multiple testing procedures widely used in clinical trials (nonparametric, semiparametric, and parametric procedures). The paper also presents recent advances in multiplicity research, including gatekeeping procedures for clinical trials with multiple sets of objectives. The concepts and methods introduced in the paper are illustrated using several case studies on the basis of real clinical trials. Software implementation of commonly used multiple testing and gatekeeping procedures is discussed.

Chain Procedures: A Class of Flexible Closed Testing Procedures With Clinical Trial Applications

We define a class of multiple testing procedures for testing a family of hypotheses based on a prespecified or data-driven testing sequence. These procedures, termed chain procedures, are characterized by independent sets of parameters which govern the initial allocation of the overall α level among the null hypotheses of interest and the process for iteratively reallocating available (or unspent) α among the remaining eligible null hypotheses. As a result, chain procedures are more flexible than popular stepwise procedures such as the Holm or fallback procedures. While presenting the broad class of chain procedures, this article focuses on the development of parametric chain procedures for problems with a known joint distribution of the hypothesis test statistics. Chain procedures are closed testing procedures and thus control the familywise error rate in the strong sense. Further, we discuss optimal selection of parameters of chain procedures based on clinically relevant application-specific criteria. Finally, we illustrate application of the chain testing method using a clinical trial example aimed at the development of a tailored therapy.

Mixtures of multiple testing procedures for gatekeeping applications in clinical trials.

This paper proposes a general framework for constructing gatekeeping procedures for clinical trials with hierarchical objectives. Such problems frequently exhibit complex structures including multiple families of hypotheses and logical restrictions. The proposed framework is based on combining multiple procedures across families. It enables the construction of powerful and flexible gatekeeping procedures that account for general logical restrictions among the hypotheses of interest. A clinical trial in patients with schizophrenia is used to illustrate the approach for parallel gatekeeping, whereas another clinical trial in patients with hypertension is used to illustrate the approach for gatekeeping with general logical restrictions.

Strategies for Identifying Predictive Biomarkers and Subgroups with Enhanced Treatment Effect in Clinical Trials Using SIDES

Several approaches to identification of predictive biomarkers and subgroups of patients with enhanced treatment effect have been proposed in the literature. The SIDES method introduced in Lipkovich et al. (2011) adopts a recursive partitioning algorithm for screening treatment-by-biomarker interactions. This article introduces an improved biomarker discovery/subgroup search method (SIDEScreen). The SIDEScreen method relies on a two-stage procedure that first selects a small number of biomarkers with the highest predictive ability based on an appropriate variable importance score and then identifies subgroups with enhanced treatment effect based on the selected biomarkers. The two-stage approach helps increase the signal-to-noise ratio by screening out noninformative biomarkers. We evaluate operating characteristics of the standard SIDES method and two SIDEScreen procedures based on fixed and adaptive screens. Our main finding is that the adaptive SIDEScreen method is a more flexible biomarker discovery tool than SIDES and it better handles multiplicity in complex subgroup search problems. The methods presented in the article are illustrated using a clinical trial example.

Design and Analysis Considerations in Clinical Trials With a Sensitive Subpopulation

This article deals with clinical trials with a sensitive subpopulation of patients, that is, a subgroup that is more likely to benefit from the treatment than the overall population. Given a sensitive subgroup defined by a prespecified classifier, for example, a clinical marker or pharmacogenomic marker, the trial’s outcome is declared positive if the treatment effect is established in the overall population or in the subgroup. We provide a summary of key considerations in clinical trials with a sensitive subgroup, including multiplicity and enrichment adjustments as well as optimality considerations in the analysis strategy. The methodology proposed in this article is illustrated using a neuroscience clinical trial and its operating characteristics are assessed via a simulation study.