Abstract

7605 Background: Overall survival (OS) can be partitioned into progression-free survival (PFS) and PPS. PPS helps to understand trial results, especially when PFS and OS data on trial treatment effects are discordant. At ASCO 2011, we reported that the magnitude of difference in the PFS estimates using different DP date methods was large enough to alter trial conclusions. Here, we investigate the impact of the DP date method on 1) PPS estimates, and 2) predictive utility of DP metrics on subsequent OS (SOS). Methods: Individual patient (pt) data from 14 trials were pooled. DP date was determined using: reported progression date (RPD) (method 1, M1), one day after last progression-free (PF) scan (M2), and midpoint between last PF scan and RPD (M3). PPS was estimated using the method of Kaplan-Meier for the 3 DP date methods. A flexible landmark analysis at 2, 4, and 6 months (mos) using Cox proportional hazards model was used to assess the impact of DP status (progression versus no-progression) on SOS (using M1, M2, or M3). Results: Among NSCLC (SCLC), 87% (91%) of pts reported DP. As expected, the PPS estimates were the lowest for RPD, highest for M2, and in-between for M3 (a direct consequence of the DP date method); with no difference by arm for the randomized trials. Regardless of the DP date method, patients who were progression-free had improved SOS (NSCLC: Hazard ratio, HR<=0.33; p < 0.0001; SCLC: HR<=0.48; p < 0.002) at each landmark time point, with comparable concordance index (SCLC: 0.57-0.65; NSCLC: 0.63-0.67), i.e., ability to discriminate patients with different SOS outcomes. Conclusions: While the DP date methods do not impact the predictive utility of the DP metrics, they significantly impact PPS estimates. The translation of a significant treatment effect on PFS to an effect on OS is influenced by PPS (longer PPS dilutes effect on OS). Standards for declaring DP date are thus critical to trial design and for trial go/no-go decisions. [Table: see text]

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