A Nomogram for the Prediction of Kras Mutation in Colorectal Cancer

Background: KRAS mutation status is crucial in treatment decisions regarding the use of EGFR tyrosine kinase inhibitors in colorectal cancer (CRC). However, genetic testing is not available for some patients, either because tissue is limited and/or tests are not routinely offered. Aim: We aimed to build a nomogram based on clinical factors for the prediction of KRAS mutations in CRC. Methods: Colorectal cancer patients who had their tumors genotyped for KRAS mutation at Fudan University Shanghai Cancer Center (FUSCC) were retrospectively analyzed. Variables of interest were integrated in a multivariate logistic regression model. Results: A total of 759 hospitalized patients were extracted from FUSCC database. KRAS mutation presented in 40.1% (309/759) cases. Multivariate logistic regression suggested that female (OR 1.47, 95% CI 1.06-2.04), mucinous histology (OR 2.04, 95% CI 1.28-3.25), right-sided tumor (OR 1.65, 95% CI 1.13-2.39) and high levels of preoperative CEA (OR 1.45, 95% CI 1.03-2.03), CA19-9 (OR 3.87, 95% CI 2.70-5.53) and albumin/globular protein (OR 2.02, 95% CI 1.33-3.06) were significantly correlated with KRAS mutation status. A nomogram was established and showed considerable discriminating accuracy (AUC 0.744, 95% CI 0.709-0.779) in this cohort. Patients with the highest score had 88.6% chance to bear a KRAS-mutant tumor. Subgroup analysis based on metastasis status revealed a sound applicability of the established nomogram both in metastatic (AUC 0.723, 95% CI 0.666-0.781) and nonmetastatic (AUC 0.753, 95% CI 0.707-0.798) CRC. Conclusion: Six simple and easy-to-collect characteristics defined a useful nomogram to predict KRAS status both in metastatic and nonmetastatic CRC with great predictive accuracy.