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Quantitative methodology using CT for predicting survival in patients with metastatic colorectal carcinoma: a pilot study
Authors:Ronald H. Gottlieb  Cheryl Raczyk  Timothy Hanna  Ahmad Fora  Wei Tan  Rahul Nayyar  Marwan Fakih
Affiliation:Roswell Park Cancer Institute, Buffalo, NY 14263
Abstract:ObjectiveTo develop a methodology which quantifies multiple changing lesion features resulting in an optimized computed tomography (CT) response score (CRS) for prediction of overall survival (OS) in response to treatment for metastatic colorectal carcinoma (MCRC).Subjects and MethodsThis Health Insurance Portability and Accountability Act-compliant, institutional review board-approved retrospective study evaluated multiple changing imaging findings and their correlation with OS with a new methodology comparing the baseline and first post-treatment CT scans in 38 MCRC patients on last-line chemotherapy (cetuximab and irinotecan). Tumor size/enhancement changes and interval development of new lesions were quantified with either Likert-type scales (all parameters) or Response Evaluation Criteria in Solid Tumors (RECIST) (size change only). The most predictive parameters for OS were used to generate the CRS with an overall range of ?3 (complete disappearance) to +2 (definite tumor increase). The Cox Hazard Ratio was used to assess prediction of survival. Reader agreement was evaluated by the kappa statistic.ResultsTumor size was the best predictor of OS using the Likert-type scale or RECIST. The CRS was not improved combining size change with other parameters. Use of the Likert-type scale resulted in predicting OS with a Cox hazard ratio of 1.697 (P=.0004) and good agreement (kappa=0.73, 95% CI=0.41–1.10) between observers with no significant difference using RECIST.ConclusionThe methodology produces a CRS for MCRC predicting OS resulting from therapy which expands standard RECIST guidelines to allow critical evaluation of multiple additional imaging parameters. Size change alone was found to be the best parameter of those considered in terms of maximizing agreement and prediction of OS.
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