Nonparametric adaptive enrichment designs using categorical surrogate data.

Adaptive survival trials are particularly important for enrichment designs in oncology and other life-threatening diseases. Current statistical methodology for adaptive survival trials provide type I error rate control only under restrictions. For instance, if we use stage-wise P values based on increments of the log-rank test, then the information used for the interim decisions need to be restricted to the primary survival endpoint. However, it is often desirable to base interim decisions also on correlated short-term endpoints like tumor response. Alternative statistical approaches based on a patient-wise splitting of the data require unnatural restrictions on the follow-up times and do not permit to efficiently account for an early rejection of the primary null hypothesis. We therefore suggest new approaches that enable us to use discrete surrogate endpoints (like tumor response status) and also to incorporate interim rejection boundaries. The new approaches are based on weighted Kaplan-Meier estimates and thereby have additional advantages. They permit us to account for nonproportional hazards and are robust against informative censoring based on the surrogate endpoint. We will show that nonproportionality is an intrinsic and relevant issue in enrichment designs. Moreover, informative censoring based on the surrogate endpoint is likely because of withdrawals and treatment switches after insufficient treatment response. It is shown and illustrated how nonparametric tests based on weighted Kaplan-Meier estimates can be used in closed combination tests for adaptive enrichment designs, such that type I error rate control is achieved and justified asymptotically.

Left ventricular geometry predicts cardiovascular outcomes associated with anemia correction in CKD.

Partial correction of anemia in patients with chronic kidney disease (CKD) reduces left ventricular hypertrophy (LVH), which is a risk factor for cardiovascular (CV) morbidity, but complete correction of anemia does not improve CV outcomes. Whether LV geometry associates with CV events in patients who are treated to different hemoglobin (Hb) targets is unknown. One of the larger trials to study the effects of complete correction of anemia in stages 3 to 4 CKD was the Cardiovascular Risk Reduction by Early Anemia Treatment with Epoetin Beta (CREATE) trial. Here, we analyzed echocardiographic data from CREATE to determine the prevalence, dynamics, and prognostic implications of abnormal LV geometry in patients who were treated to different Hb targets. The prevalence of LVH at baseline was 47%, with eccentric LVH more frequent than concentric. During the study, LVH prevalence and mean left ventricular mass index did not change significantly, but LV geometry fluctuated considerably within 2 yr in both groups. CV event-free survival was significantly worse in the presence of concentric LVH and eccentric LVH compared with the absence of LVH (P = 0.0009 and P < or = 0.0001, respectively). Treatment to the higher Hb target associated with reduced event-free survival in the subgroup with eccentric LVH at baseline (P = 0.034). In conclusion, LVH is common and associates with poor outcomes among patients with stages 3 to 4 CKD, although both progression and regression of abnormal LV geometry occur. Complete anemia correction may aggravate the adverse prognosis of eccentric LVH.

Clinical pharmacokinetic/pharmacodynamic and physiologically based pharmacokinetic modeling in new drug development: the capecitabine experience.

Preclinical studies, along with Phase I, II, and III clinical trials demonstrate the pharmacokinetics, pharmacodynamics, safety and efficacy of a new drug under well controlled circumstances in relatively homogeneous populations. However, these types of studies generally do not answer important questions about variability in specific factors that predict pharmacokinetic and pharmacodynamic (PKPD) activity, in turn affecting safety and efficacy. Semi-physiological and clinical PKPD modeling and simulation offer the possibility of utilizing data obtained in the laboratory and the clinic to make accurate characterizations and predictions of PKPD activity in the target population, based on variability in predictive factors. Capecitabine is an orally administered pro-drug of 5-fluorouracil (5-FU), designed to exploit tissue-specific differences in metabolic enzyme activities in order to enhance efficacy and safety. It undergoes extensive metabolism in multiple physiologic compartments, and presents particular challenges for predicting pharmacokinetic and pharmacodynamic activity in humans. Clinical and physiologically based pharmacokinetic (PBPK) and pharmacodynamic models were developed to characterize the activity of capecitabine and its metabolites, and the clinical consequences under varying physiological conditions such as creatinine clearance or activity of key metabolic enzymes. The results of the modeling investigations were consistent with capecitabine's rational design as a triple pro-drug of 5-FU. This paper reviews and discusses the PKPD and PBPK modeling approaches used in capecitabine development to provide a more thorough understanding of what the key predictors of its PBPK activity are, and how variability in these predictors may affect its PKPD, and ultimately, clinical outcomes.