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Predictive model for high-frequency microsatellite instability in colorectal cancer patients over 50 years of age.

Authors :
Fujiyoshi K
Yamaguchi T
Kakuta M
Takahashi A
Arai Y
Yamada M
Yamamoto G
Ohde S
Takao M
Horiguchi SI
Natsume S
Kazama S
Nishizawa Y
Nishimura Y
Akagi Y
Sakamoto H
Akagi K
Source :
Cancer medicine [Cancer Med] 2017 Jun; Vol. 6 (6), pp. 1255-1263. Date of Electronic Publication: 2017 May 23.
Publication Year :
2017

Abstract

Microsatellite instability (MSI) is an important biomarker for screening for Lynch syndrome, and also of response to immune checkpoint inhibitors. The aim of this study is to create a predictive model to determine which elderly patients with colorectal cancer (CRC) should undergo MSI and/or immunohistochemistry testing on the basis of clinicopathological data. We analyzed a test cohort of CRC patients aged ≥50 years (n = 2219) by multivariate logistic regression analyses to identify predictors of high-frequency MSI (MSI-H). The created prediction model was validated in an external cohort (n = 992). The frequency of MSI-H was 5.5% among CRC patients aged ≥ 50 years. The following five predictors of MSI-H were identified in the test cohort: female (1 point), mucinous component (2 points), tumor size ≥ 60 mm (2 points), location in proximal colon (3 points), and BRAF mutation (6 points). The area under curve (AUC) in the receiver-operating characteristic (ROC) analysis of this prediction model was 0.832 (95% confidence interval: 0.790-0.874). The sensitivity and specificity were 74.4% and 77.7%, respectively, for a cut-off score of 4 points. The receiver-operating characteristic curve of the validation cohort also showed an AUC of 0.856 (95% CI: 0.806-0.905). This prediction model is useful to select elderly CRC patients who should undergo MSI testing, and who may benefit from treatment with 5-FU-based adjuvant chemotherapy and cancer immunotherapy.<br /> (© 2017 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.)

Details

Language :
English
ISSN :
2045-7634
Volume :
6
Issue :
6
Database :
MEDLINE
Journal :
Cancer medicine
Publication Type :
Academic Journal
Accession number :
28544821
Full Text :
https://doi.org/10.1002/cam4.1088