domingo, 4 de junio de 2017

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

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



 2017 May 23. doi: 10.1002/cam4.1088. [Epub ahead of print]

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

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.

KEYWORDS:

Colorectal cancer; Lynch syndrome; immune checkpoint inhibitor; microsatellite instability; mismatch repair deficiency; predictive model; universal tumor screening

PMID:
 
28544821
 
DOI:
 
10.1002/cam4.1088
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