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- W2891682414 abstract "e21114 Background: Extending survival in advanced non-small cell lung cancer (NSCLC) is of great importance. Finding survival predictors and assessing the potential for improving patient outcomes through their modification can assist these efforts. Here we tested tumor burden changes at disease progression as survival predictors in NSCLC. Methods: Data were taken from 2 clinical trials in advanced NSCLC patients under 1st line CarboTaxol (projectdatasphere.org). Magnitude and rate of changes in tumor size (sum of longest diameters; SLD) close to progression, and other patient parameters, were evaluated as predictors of post-progression survival (PPS) using univariate/multivariate Cox proportional hazards models. The latter were built by stepwise regression, p = 0.2 being the entrance criterion. Results: In both trials (n = 381 patients with progressive disease (PD) on target lesions), the SLD rise from nadir to progression (dSLD) was significantly correlated with PPS (Table). Patients with lower-than-median dSLD showed longer survival, with a 4.9 and 9.6 month gain in PPS over large-dSLD patients. The impact of dSLD persisted in a multivariate model that included also baseline performance status, gender, appearance of new lesions, and time to progression as significant factors; the additive contribution of dSLD to the multivariate model (Table) was verified by model comparison. Conclusions: Tumor burden increase near first progression was found to be a unique survival predictor for advanced NSCLC. Continuous control of SLD features in NSCLC patients may thus assist in predicting outcomes and suggesting appropriate therapy. We have used these features to develop a new predictive tool that alerts to imminent progression and suggests a treatment switch to limit tumor growth and extend survival. Clinical Study -Identifier Target lesion PD patients (% of all PD patients) Median PPS (months) Median dSLD (cm) Median PPS (months) dSLD Hazard ratio [95% CI], p value > median dSLD < median dSLD Univariate model Multivariate model CA031 -NCT00540514 159 (44%) 7.8 2 4.8 9.7 1.46 [1.22, 1.74], 4.37x10-5 1.26 [1.04, 1.53], 0.01 IPASS -NCT00322452 222 (49%) 12.4 1.5 9.4 19 1.21 [1.12, 1.32], 5.45x10-6 1.18 [1.08, 1.29], 0.0004" @default.
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- W2891682414 date "2018-05-20" @default.
- W2891682414 modified "2023-09-26" @default.
- W2891682414 title "Increase in tumor burden at disease progression as a predictor of survival in advanced NSCLC patients." @default.
- W2891682414 doi "https://doi.org/10.1200/jco.2018.36.15_suppl.e21114" @default.
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