PII-032

F. Mercier, L. Claret; Pharsight, Wintzenheim, France

BACKGROUND: Tumor growth inhibition (TGI) metrics estimated with longitudinal tumor size (TS) models have been shown to be predictive of overall survival (OS) in a variety of tumor types.
METHODS: TS data from 2,490 patients with first line or refractory RCC who received temsirolimus, interferon, sunitinib, sorafenib or axitinib in 10 Phase II or Phase III studies were used. TGI metrics (Early tumor shrinkage (ETS) at week 8, 10, 12, time to growth (TTG)) as well as baseline prognostic factors were tested in a multivariate log-normal model of OS. Model performances were evaluated by posterior predictive check of the OS and hazard ratio distributions.
RESULTS: TTG was the best TGI metric to predict OS, but Week 8 ETS, an earlier measure, had satisfactory performance, and was employed due to its ease of clinical utility. The parameter estimates of the model with Week 8 ETS are presented in Table 1. This model was then used in simulation mode to define a clinically relevant ETS target for future Phase II studies with investigational treatments.
CONCLUSION: A TGI-based OS model is proposed for patients with RCC. The model demonstrates good performance when fitted to data from 10 different Phase II and Phase III clinical trials. Simulations with this model help with identification of relevant ETS targets in clinical trial design.
Survival model parameter estimates
ParameterEstimate (SE)p-value
(Intercept)8.07 (0.270)<0.001
TS ratio at week 8-1.99 (0.135)<0.001
Baseline hemoglobin (g/L)0.133 (0.111)<0.001
Baseline ECOG=1-0.400 (0. 048)<0.001
Log(# baseline metastases)-0.209 (0.032)<0.001
Baseline cor. calcium (mg/dL)-0.104 (0.019)<0.001
Time from diagnosis (Days)8.0E-5 (1.7E-5)<0.001
Baseline LDH (U/L)-3.7E-4 (9.2E-5)<0.001
Log(sigma)-0.107 (0.020)<0.001