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Molecularly targeted, genomic‐driven, and immunotherapy‐based clinical trials continue to be advanced for the treatment of relapse or refractory cancer patients, where the growth modulation index (GMI) is often considered a primary endpoint of treatment efficacy. However, there little literature is available that considers the trial design with GMI as the primary endpoint. In this article, we derived a sample size formula for the score test under a log‐linear model of the GMI. Study designs using the derived sample size formula are illustrated under a bivariate exponential model, the Weibull frailty model, and the generalized treatment effect size. The proposed designs provide sound statistical methods for a single‐arm phase II trial with GMI as the primary endpoint. [ABSTRACT FROM AUTHOR]

Background The growth modulation index (GMI) is the ratio of time to progression with the nth line (TTPn) of therapy to the TTPn−1 with the n-1th line. GMI >1.33 is considered as a sign of activity in phase II trials. Patients and Methods This retrospective analysis evaluated the concordance between the GMI and the efficacy outcomes in 279 patients with advanced soft tissue sarcoma (ASTS) treated with trabectedin 1.5 mg/m² (24-h infusion every 3 weeks) in four phase II trials. Results One hundred and forty-two (51%) patients received one prior line and 137 ≥2 lines. The median TTPn was 2.8 months (range 0.2–26.8), whereas the median TTPn−1 was 4.0 months (0.3–79.5). The median GMI was 0.6 (0.0–14.4). Overall, 177 patients (63%) had a GMI <1; 21 (8%) a GMI equal to 1–1.33 and 81 (29%) a GMI >1.33, which correlated with the median overall survival in those patients (9.1, 13.9 and 23.8 months, respectively, P = 0.0005). A high concordance rate between the GMI and response rate (P < 0.0001) and progression-free survival (PFS, P < 0.0001) was observed. Good performance status (PS) was the only factor associated with GMI >1.33 (PS = 0; P < 0.04). Conclusions A high GMI was associated with favorable efficacy outcomes in patients treated with trabectedin. Further research is needed to assess GMI as an indicator in this setting. [ABSTRACT FROM PUBLISHER]

Abstract: For cytostatic cancer therapies, alternatives to traditional phase II endpoints are needed. Von Hoff (1998) proposed an intrapatient progression-free survival (PFS) ratio, the growth modulation index (GMI). Current practice in estimation of the GMI success rate is conservative and omits a measure of uncertainty. We investigated nonparametric and parametric methods to estimate the GMI success rate, including an approach using midranks for paired survival outcomes (Hudgens and Satten (2002)). Estimators were applied to a phase II GMI dataset (Bonetti et al. (2001)). From simulation studies, it was determined that a rank-based estimator had the most favorable statistical properties. Its point estimate bias was consistently within 1.5%; its bias and precision were robust over a range of effect and censoring scenarios. Using a proof of concept criterion of {P(GMI≥1)≥ θ}, a simulation investigation found that a θ of 50%, for sample sizes between 20 and 30 patients, had type I error of ≤20% and a power to detect Von Hoff''s 1.33 effect of ≥80%. When the amount of censoring was ≥20%, the midrank estimator had a minimum of 14% greater power over the simple percentage estimator for the GMI success rate. Future investigations reporting the GMI should consider adopting the midrank methodology. [Copyright &y& Elsevier]