A portfolio-based approach to optimize proof of concept clinical trials

Improving proof-of-concept (PoC) studies is a primary lever for improving drug development. Since drug development is often done by institutions that work on multiple drugs simultaneously, the present work focused on optimum choices for rates of false positive (α) and false negative (β) results across a portfolio of PoC studies. Simple examples and a newly derived equation provided conceptual understanding of basic principles regarding optimum choices of α and β in PoC trials. In examples that incorporated realistic development costs and constraints, the levels of α and β that maximized the number of approved drugs and portfolio value varied by scenario. Optimum choices were sensitive to the probability the drug was effective and to the proportion of total investment cost prior to establishing PoC. Results of the present investigation agree with previous research in that it is important to assess optimum levels of α and β. However, the present work also highlighted the need to consider cost structure using realistic input parameters relevant to the question of interest.status: publishe

Indicators of Lifetime Estrogen Exposure: Effect on Breast Cancer Incidence and Interaction With Raloxifene Therapy in the Multiple Outcomes of Raloxifene Evaluation Study Participants

PURPOSE: To test the hypothesis that risk factors related to lifetime estrogen exposure predict breast cancer incidence and to test if any subgroups experience enhanced benefit from raloxifene. PATIENTS AND METHODS: Postmenopausal women with osteoporosis (N = 7,705), enrolled onto the Multiple Outcomes of Raloxifene Evaluation (MORE) trial, were randomly assigned to receive placebo, raloxifene 60 mg/d, or raloxifene 120 mg/d for 4 years. Breast cancer risk was analyzed by the following baseline characteristics indicative of estrogen exposure: previous hormone replacement therapy, prevalent vertebral fractures, family history of breast cancer, estradiol level, bone mineral density (BMD), body mass index, and age at menopause. Therapy-by-subgroup interactions were assessed using a logistic regression model. RESULTS: Overall, women with the highest one-third estradiol levels (≥ 12 pmol/L) had a 2.07-fold increased invasive breast cancer risk compared with women with lower levels. Raloxifene significantly reduced breast cancer risk in both the low- and high-estrogen subgroups for all risk factors examined (P < .05 for each comparison). The women with the highest BMD and those with a family history of breast cancer experienced a significantly greater therapy benefit with raloxifene, compared with the two thirds of patients with lower BMD or those without a family history, respectively; the subgroup-by-therapy interactions were significant (P = .005 and P = .015, respectively). CONCLUSION: The MORE trial confirms that increased lifetime estrogen exposure increases breast cancer risk. Raloxifene therapy reduces breast cancer risk in postmenopausal osteoporotic women regardless of lifetime estrogen exposure, but the reduction is greater in those with higher lifetime exposure to estrogen

Correlation between treatment effects on response rate and progression-free survival and overall survival in trials of targeted therapies in molecularly enriched populations

Background: The number of randomized trials of agents targeting oncogene-addicted tumors has surged in the past 10 years. Using a meta-analysis, we explored whether improvements in objective response rate (ORR) in comparative trials using targeted agents could serve as a potential surrogate endpoint for improvements in progression-free survival (PFS) or overall survival (OS) in populations with oncogene-addicted cancer. Patients and methods: Using commercial text mining software I2E, we searched ClinicalTrials.gov and MEDLINE databases for randomized, phase III trials based on prospectively defined criteria, including (i) use of agents targeting EGFR activating mutations, ALK rearrangements, BRAF V600E or V600K mutations, and BCR-ABL fusion protein; (ii) molecularly enriched trial population or subpopulation; (iii) control arm only randomized to chemo/ cytotoxic therapy. Correlative analyses were performed using ORR, OS, and PFS data from trials that met these criteria. Results: A total of 62 trials were identified; 15 met all of the prespecified criteria. The ORR effect size (both the difference in ORR between arms and the log odds ratio) and log PFS hazard ratio were strongly correlated: -0.78 (P = 0.0007) for the ORR difference model; -0.74 (P = 0.0017) for the log odds ratio model. ORR effect size was positively correlated with the log OS hazard ratio, but more weakly: -0.67 (P = 0.013) for the ORR difference model and -0.58 (P = 0.036) for the log odds ratio model. Analysis of the treatment effects between OS and PFS found no correlation. Conclusions: These analyses identified a strong correlation between treatment effects on ORR and PFS in randomized clinical trials investigating agents targeting oncogene-driven cancers. A weaker correlation was observed between ORR and OS. These meta-analysis results support the use of a high ORR forming the basis of an initial regulatory approval in biomarker-driven studies