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CLINICAL TRIAL
JOURNAL ARTICLE
Optimization of a multigene biochip for detection of relapsed and early relapsed colorectal cancer.
Journal of Surgical Research 2017 December
BACKGROUND: With the recent development of molecular markers, strategies for identifying patients with colorectal cancer (CRC) having a high risk of postoperative early relapse (within 1 y) and relapse have been improved. We previously constructed a multigene biochip with 19 candidate genes. The objective of the present study was to optimize a multigene biochip for detecting the risk of postoperative early relapse and relapse in patients with CRC.
METHODS: We included 357 patients with stage I-III CRC who underwent curative resection at a single institution between June 2010 and May 2015. During each follow-up, a postoperative surveillance strategy including the National Comprehensive Cancer Network recommendations and a multigene biochip was used. A statistical algorithm was developed to select candidate biomarkers for an optimal combination.
RESULTS: After a 30.9-mo median follow-up, 67 patients (18.8%) had postoperative relapse, of whom 25 (7.0%) relapsed within 1 y after operation and accounted for 37.3% of all relapsed patients. Of the 19 circulating biomarkers, ELAVL4, PTTG1, BIRC5, PDE6D, CHRNB1, MMP13, and PSG2, which presented significant predictive validity, were selected for combination. The expression of the seven-biomarker biochip resulted in area under the receiver operating characteristic curve values of 0.854 (95% confidence interval: 0.756-0.952) for early relapse and 0.884 (95% confidence interval: 0.830-0.939) for relapse. Moreover, the sensitivity, specificity, and predictive accuracy levels were 84.0%, 83.1%, and 83.2% for early relapse and 76.1%, 91.0%, and 88.2% for relapse (P = 0.415, 0.006, and 0.054, respectively). The median lead times before the detection of postoperative early relapse and relapse were 3.8 and 10.4 mo, respectively.
CONCLUSIONS: From 19 circulating biomarkers, we optimized seven contemporary circulating biomarkers. The prediction model used for the early and accurate identification of Taiwanese patients with CRC having a high risk of postoperative early relapse and relapse seems to be feasible and comparable.
METHODS: We included 357 patients with stage I-III CRC who underwent curative resection at a single institution between June 2010 and May 2015. During each follow-up, a postoperative surveillance strategy including the National Comprehensive Cancer Network recommendations and a multigene biochip was used. A statistical algorithm was developed to select candidate biomarkers for an optimal combination.
RESULTS: After a 30.9-mo median follow-up, 67 patients (18.8%) had postoperative relapse, of whom 25 (7.0%) relapsed within 1 y after operation and accounted for 37.3% of all relapsed patients. Of the 19 circulating biomarkers, ELAVL4, PTTG1, BIRC5, PDE6D, CHRNB1, MMP13, and PSG2, which presented significant predictive validity, were selected for combination. The expression of the seven-biomarker biochip resulted in area under the receiver operating characteristic curve values of 0.854 (95% confidence interval: 0.756-0.952) for early relapse and 0.884 (95% confidence interval: 0.830-0.939) for relapse. Moreover, the sensitivity, specificity, and predictive accuracy levels were 84.0%, 83.1%, and 83.2% for early relapse and 76.1%, 91.0%, and 88.2% for relapse (P = 0.415, 0.006, and 0.054, respectively). The median lead times before the detection of postoperative early relapse and relapse were 3.8 and 10.4 mo, respectively.
CONCLUSIONS: From 19 circulating biomarkers, we optimized seven contemporary circulating biomarkers. The prediction model used for the early and accurate identification of Taiwanese patients with CRC having a high risk of postoperative early relapse and relapse seems to be feasible and comparable.
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