PT  - JOURNAL ARTICLE
AU  - OKIHIDE SUZUKI
AU  - TATSURO YAMAGUCHI
AU  - MINORU FUKUCHI
AU  - ERITO MOCHIKI
AU  - TOMIO ARAI
AU  - KIWAMU AKAGI
AU  - HIDEYUKI ISHIDA
TI  - Prediction Model for Gastric Cancer With DNA Mismatch Repair Deficiency
AID  - 10.21873/anticanres.14851
DP  - 2021 Feb 01
TA  - Anticancer Research
PG  - 975--982
VI  - 41
IP  - 2
4099  - http://ar.iiarjournals.org/content/41/2/975.short
4100  - http://ar.iiarjournals.org/content/41/2/975.full
SO  - Anticancer Res2021 Feb 01; 41
AB  - Background/Aim: DNA mismatch repair (MMR) deficiency has received increasing attention as a biomarker of anti-PD-1 treatments of solid tumors including gastric cancer (GC). However, efficient screening has not been established. Patients and Methods: A total of 513 patients were tested for the expression of MMR proteins by immunohistochemistry to identify MMR deficient GC. Development of a prediction model was attempted using the common clinicopathological features. Results: In total, 11% (57/513) of the patients showed loss of expression of either one or more MMR proteins (MMR protein deficiency; MMR-D). Multivariate analysis demonstrated that age (≥70 years), sex (female), tumor location (lower 1/3), depth invasion (low, T1/T2/T3), and absence of distant metastasis were significantly independent predictive factors of MMR-D GCs. The MMR-D GC probability estimated by the prediction model ranged from 0.4% to 62.2%, and the area under the curve of the receiver operating characteristics curve was 0.82 (95% confidence interval=0.75-0.87). Conclusion: Our prediction model can sufficiently and efficiently identify MMR-D GCs using clinical features.