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Treatment effect has declined over time in MDD trials, and there has been a high failure rate for these trials during the entire period, but the reasons for these findings remain elusive. Baseline disease severity seems to be a more important factor in study outcome than study duration, dosing regimen, sample size, time when studies were conducted, and regions where data were generated. Close attention is needed to a variety of factors in the design and conduct of these studies, including patient population, diagnostic considerations, patient assessment, and clinical practice differences. These considerations become increasingly important as globalization of clinical trials continues to increase.

Purpose: To describe the Food and Drug Administration (FDA) review and approval of erlotinib (Tarceva, OSI Pharmaceuticals, Melville, NY) for treatment of patients with locally advanced or metastatic non^small cell lung cancer (NSCLC) after failure of at least one prior chemotherapy regimen. Experimental Design: The FDA reviewed raw data in electronic format from a randomized controlled clinical trial comparing erlotinib with placebo in patients with locally advanced or metastatic NSCLC after failure of at least one prior chemotherapy regimen. Results: Patients were randomized in a 2:1 ratio (erlotinib, n = 488 and placebo, n = 243). Erlotinib was superior to placebo for survival, progression-free survival, and tumor response rate. Exploratory analyses indicate that epidermal growth factor receptor status may be an important predictor of the erlotinib survival effect. Rash (75% versus 17%) and diarrhea (54% versus 18%) in the erlotnib and placebo group respectively were the most common adverse events. Severe rash occurred in 9% and severe diarrhea in 6% of erlotinib-treated patients and each resulted in study discontinuation in 1% of patients. Dose reductions were required for 10% of patients with rash and 4% of patients with diarrhea. Conclusions: On November18, 2004, the FDA granted erlotinib regular approval for treatment of patients with locally advanced or metastatic NSCLC after failure of at least one prior chemotherapy regimen. The applicant has committed to conduct post-marketing clinical trials to assess further the effect of epidermal growth factor receptor expression, measured with immunohistochemical staining, on erlotinib treatment effect.Lung cancer is the leading cause of cancer death in both men and women in the United States (1). Initial therapy for advanced non -small lung cancer (NSCLC) is systemic chemotherapy with a two-drug combination regimen that often includes a platinum. Docetaxel and pemetrexed are approved by the Food and Drug Administration (FDA) for use as the second-line chemotherapy. Recently, the epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor gefitinib was granted FDA-accelerated approval under subpart H for treatment of advanced NSCLC after failure of both platinum-based and docetaxel chemotherapy, based on a response rate of f10% in single-arm clinical trials. Erlotinib (T arceva, OSI Pharmaceuticals, Melville, NY) inhibits EGFR tyrosine kinase autophosphorylation by inhibition of the intracellular domain. Studies in cell lines and enzyme assays have both shown that erlotinib inhibits EGFR at concentrations significantly lower than those needed to inhibit c-src and v-abl. Whereas erlotinib was more selective for EGFR tyrosine kinase than it was for several other tyrosine kinases tested, several other tyrosine kinases in the same family as EGFR were not tested. Although erlotinib seems rather selective for EGFR, insufficient data exist to make a definitive decision regarding selectivity (2 -4). Chemistry and ToxicologyErlotinib hydrochloride is a quin...

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Antidepressant maintenance trials have a high rate of success, indicating a benefit of continuing drug treatment after initial response to an antidepressant. This benefit appears to result mainly from a decreased rate of recurrent depression rather than from an effect of drug withdrawal in the placebo groups.

A high and increasing placebo response and a declining treatment effect are of great concern in schizophrenia trials conducted in North America. In this era of global clinical trials, close attention is needed to the design and conduct of these trials.

Due to the increasing prevalence of nonalcoholic steatohepatitis (NASH) and its associated health burden, there is a high need to develop therapeutic strategies for patients with this disease. Unfortunately, its long and asymptomatic natural history, the uncertainties about disease progression, the fact that most patients are undiagnosed, and the requirement for sequential liver biopsies create substantial challenges for clinical development. Adaptive design methods are increasingly used in clinical research as they provide the flexibility and efficiency for identifying potential signals of clinical benefit of the test treatment under investigation and make prompt preplanned adaptations without undermining the validity or integrity of the trial. Given the high unmet medical need and the lack of validated surrogate endpoints in NASH, the use of adaptive design methods appears reasonable. Furthermore, due to the limited number of patients willing to have multiple liver biopsies and the need for long‐term exposure to assess an impact in outcomes, a continuous seamless adaptive design may reduce the overall sample size while allowing patients to continue after each one of the phases. Here, we review strategic frameworks that include potential surrogate endpoints as well as statistical and logistical approaches that could be considered for applying adaptive designs to clinical trials in NASH with the goal of facilitating drug development for this growing medical need. (Hepatology Communications 2017;1:577–585)

Background Clinical trials in rare diseases are difficult to conduct due to the limited number of patients available with each disorder. We developed a Phase 2 trial which is a small n sequential multiple assignment randomized trial (snSMART) design to test several treatments for a rare disease for which no standard therapy exists. Purpose This paper illustrate the design, sample size estimation and operating characteristics of an snSMART. Methods We investigate the performance of a class of weighted Z statistics via computer simulations. Results We demonstrate the increase in power over traditional single stage designs, and indicate how the power changes as a function of the weight given to each stage. Conclusion The snSMART design is promising in a rare diseases setting where several alternative treatments are under consideration and small sample sizes are necessary.