کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
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3990144 | 1258726 | 2012 | 7 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Optimization of Response Classification Criteria for Patients with Malignant Pleural Mesothelioma Optimization of Response Classification Criteria for Patients with Malignant Pleural Mesothelioma](/preview/png/3990144.png)
IntroductionResponse-assessment metrics play an important role in clinical trials and routine patient management. For patients with malignant pleural mesothelioma (MPM), the standard for response assessment is image-based measurements of tumor thickness made according to the modified RECIST (Response Evaluation Criteria in Solid Tumors) protocol. To classify tumor response, changes in tumor thickness are compared with the standard RECIST −30% and +20% cutoffs for partial response (PR) and progressive disease (PD), respectively, which are not specific to MPM. The purpose of this work is to optimize the correlation between tumor response and patient survival by assessing the validity of existing response criteria in MPM and proposing alternative criteria.MethodsComputed tomography measurements of tumor thickness were acquired at baseline and throughout treatment for 78 patients undergoing standard-of-care chemotherapy. Overall survival was correlated with best response and first follow-up response using Harrell's C statistic. The response criteria for PD and PR were each varied in 1% increments to obtain optimized classification criteria. The performance was cross-validated using a leave-one-out approach.ResultsMedian survival was 14.9 months. The performance of the standard RECIST criteria in correlating response with survival was C=0.778, whereas the optimized performance of C=0.855 was obtained with criteria of −64% for PR and +50% for PD. After cross-validation, this performance was slightly reduced to C=0.829.ConclusionsOptimized tumor-response classification criteria were obtained for patients with MPM. These criteria improve the correlation between image-based response and patient survival.
Journal: Journal of Thoracic Oncology - Volume 7, Issue 11, November 2012, Pages 1728–1734