Tumor response and progression‐free survival as potential surrogate endpoints for overall survival in extensive stage small‐cell lung cancer

Abstract

BACKGROUND:The authors investigated the putative surrogate endpoints of best response, complete response (CR), confirmed response, and progression-free survival (PFS) for associations with overall survival (OS), and as possible surrogate endpoints for OS. METHODS: Individual patient data from 870 untreated extensive stage small-cell lung cancer patients participating in 6 single-arm (274 patients) and 3 randomized trials (596 patients) were pooled. Patient-level associations between putative surrogate endpoints and OS were assessed by Cox models using landmark analyses. Trial-level surrogacy of putative surrogate endpoints were assessed by the association of treatment effects on OS and individual putative surrogate endpoints. Trial-level surrogacy measures included: R 2 from weighted least squares regression model, Spearman correlation coefficient, and R 2 from bivariate survival model (Copula R 2 ). RESULTS: Median OS and PFS were 9.6 (95% confidence interval [CI], 9.1-10.0) and 5.5 (95% CI, 5.2-5.9) months, respectively; best response, CR, and confirmed response rates were 44%, 22%, and 34%, respectively. Patient-level associations showed that PFS status at 4 months was a strong predictor of subsequent survival (hazard ratio [HR], 0.42; 95% CI, 0.35-0.51; concordance index 0.63; P < .01), with 6-month PFS being the strongest (HR, 0.41; 95% CI, 0.35-0.49; concordance index, 0.66, P < .01). At the trial level, PFS showed the highest level of surrogacy for OS (weighted least squares R 2 ¼ 0.79; Copula R 2 ¼ 0.80), explaining 79% of the variance in OS. Tumor response endpoints showed lower surrogacy levels (weighted least squares R 2 0.48). CONCLUSIONS: PFS was strongly associated with OS at both the patient and trial levels. PFS also shows promise as a potential surrogate for OS, but further validation is needed using data from a larger number of randomized phase 3 trials.

Clinical predictors of survival in young patients with small cell lung cancer: Results from the California Cancer Registry

“…In clinical trials of new agents in extensive stage SCLC, the typical median age at study entry is in the low sixties [2]. SCLC patients younger than 50 years of age are considered uncommon.…”

“…Although high response rates occur following platinum-based chemotherapy, tumor recurrence is universal and virtually all patients succumb to the disease [1]. Efforts to optimize treatment for these patients include the identification of baseline prognostic variables that may help inform therapeutic decision-making at the time of initial diagnosis [2].…”

Surrogate endpoints for overall survival in advanced non-small-cell lung cancer patients with mutations of the epidermal growth factor receptor gene

“…Biostatisticians have also proposed measures for validating surrogate endpoints (20,21). Tumor response and PFS are potential surrogate endpoints for OS in extensive-stage small-cell lung cancer (22), although their validity in advanced NSCLC is controversial (23). Broglio and Berry (2) recently focused on PPS, which they defined as survival post-progression (OS minus PFS), in a hypothetical clinical trial situation; their study hypothesized that treatment affected PFS, but not PPS.…”

Estimation of expectedness: Predictive accuracy of standard therapy outcomes in randomized phase 3 studies in epithelial ovarian cancer

“…These challenges may be more problematic in malignancies with a longer survival and many available treatment options, such as EOC, low‐grade lymphomas, or breast cancer, compared with those with limited treatment options and short survival times such as metastatic pancreatic or lung cancer. In contrast, among diseases in which the median survival after disease progression has been classically shorter (ie, <12 months), such as advanced colorectal cancer and non‐small lung cancer, a stronger correlation between PFS and OS has been demonstrated 49, 50, 51. This may mean that OS is easier to predict in these diseases.…”