A Phase II Study of PX-866 in Patients With Recurrent or Metastatic Castration-resistant Prostate Cancer: Canadian Cancer Trials Group Study IND205.

BACKGROUND: In PTEN-loss models, the phosphatidylinositol 3-kinase (PI3K)/AKT and androgen receptor signaling pathways cross-regulate by reciprocal feedback whereby inhibition of one activates the other, creating a rationale for co-targeting. We studied the irreversible, pan-isoform inhibitor of Class I PI-3K PX-866 singly (part A) and with abiraterone acetate (AA) in patients on AA with rising prostate-specific antigen (PSA) (part B). PATIENTS AND METHODS: The primary endpoint was lack of progression at 12 weeks. Exploratory endpoints included changes in circulating tumor cells (CTC), pharmacodynamic studies on platelets (part A), and archival tumor exploration of PTEN as predictor of response (part B). RESULTS: A total of 43 and 25 patients accrued to parts A and B, respectively. In part A, 14 (33%) patients were progression-free at 12 weeks, with 2 partial objective responses and 1 confirmed PSA response. Favorable CTC conversion (< 5 CTC/7.5 mL) occurred in 6 (24%) of 25 evaluable patients. In part B, 11 of 25 patients had measurable disease. Six (24%) patients were progression-free at 12 weeks. No objective or PSA responses were observed. For all 68 patients, the most common toxicities were diarrhea (53 patients), nausea (36), anorexia (24), fatigue (22), and vomiting (20). Among 17 patients for whom PTEN testing was possible, 3 had PTEN homozygous deletion and 14 had no change. No correlation between PTEN status and response was seen. CONCLUSIONS: PX-866 had modest single agent activity. Adding AA to PX-866 showed no evidence of resistance reversal. Strategies to combine PI3K inhibition with androgen receptor-targeted therapies could consider initiation earlier, combination with other agents, and/or recruiting a selected population.

Some design issues of strata-matched non-randomized studies with survival outcomes.

Non-randomized studies for the evaluation of a medical intervention are useful for quantitative hypothesis generation before the initiation of a randomized trial and also when randomized clinical trials are difficult to conduct. A strata-matched non-randomized design is often utilized where subjects treated by a test intervention are matched to a fixed number of subjects treated by a standard intervention within covariate based strata. In this paper, we consider the issue of sample size calculation for this design. Based on the asymptotic formula for the power of a stratified log-rank test, we derive a formula to calculate the minimum number of subjects in the test intervention group that is required to detect a given relative risk between the test and standard interventions. When this minimum number of subjects in the test intervention group is available, an equation is also derived to find the multiple that determines the number of subjects in the standard intervention group within each stratum. The methodology developed is applied to two illustrative examples in gastric cancer and sarcoma.