ArticleJournal of personalized medicine2013
A method for biomarker directed survival prediction in advanced non-small-cell lung cancer patients treated with Carboplatin-based therapy.
Article in Journal of personalized medicine, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Abstract
unlabelledPlatinum-based chemotherapy is a primary treatment of choice for advanced non-small-cell lung cancer (NSCLC). Analytical methods to specifically evaluate biomarkers predictive of therapeutic efficacy have not been developed. Two randomized phase III trials of carboplatin-based chemotherapy in advanced NSCLC were used for learning and validating the predictive value of ERCC1 in situ protein levels, as measured by accurate quantitative analysis (AQUA). A novel Bayesian method was applied to identify the outcome-based threshold in the learning trial only. Overall survival (OS) was assessed by Kaplan-Meier analysis with log rank testing to determine statistical significance in the validating trial. For patients treated with gemcitabine and carboplatin, the median OS was 9.5 months (95% CI 6.7 to 11.8) for the high ERCC1 group compared to 15.6 months (95% CI 11.6 to 24.8) for the low ERCC1 group in the validation trial (log rank p-value = 0.007). The hazard ratio for low ERCC1 was 0.598 (95% CI, 0.394 to 0.908; p = 0.016) relative to high ERCC1 adjusted for age, sex, and histology.
conclusionsPatients with advanced NSCLC could be stratified into high and low ERCC1 expression groups. Patients with low levels benefited from platinum-based chemotherapy, whereas those with high levels did not.
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