Performance evaluation of predictive models for detecting MMR gene mutations associated with Lynch syndrome in cancer patients in a Chinese cohort in Taiwan

Abstract

AbstractIdentifying Lynch syndrome significantly impacts cancer risk management, treatment, and prognosis. Validation of mutation risk predictive models for mismatch repair (MMR) genes is crucial for guiding genetic counseling and testing, particularly in the understudied Asian population. We evaluated the performance of four MMR mutation risk predictive models in a Chinese cohort of 604 patients with colorectal cancer (CRC), endometrial cancer (EC), or ovarian cancer (OC) in Taiwan. All patients underwent germline genetic testing and 36 (6.0%) carried a mutation in the MMR genes (MLH1, MSH2, MSH6, and PMS2). All models demonstrated good performance, with area under the receiver operating characteristic curves comparable to Western cohorts: PREMM5 0.80 (95% confidence interval [CI], 0.73–0.88), MMRPro 0.88 (95% CI, 0.82–0.94), MMRPredict 0.82 (95% CI, 0.74–0.90), and Myriad 0.76 (95% CI, 0.67–0.84). Notably, MMRPro exhibited exceptional performance across all subgroups regardless of family history (FH+ 0.88, FH‐ 0.83), cancer type (CRC 0.84, EC 0.85, OC 1.00), or sex (male 0.83, female 0.90). PREMM5 and MMRPredict had good accuracy in the FH+ subgroup (0.85 and 0.82, respectively) and in CRC patients (0.76 and 0.82, respectively). Using the ratio of observed and predicted mutation rates, MMRPro and PREMM5 had good overall fit, while MMRPredict and Myriad overestimated mutation rates. Risk threshold settings in different models led to different positive predictive values. We suggest a lower threshold (5%) for recommending genetic testing when using MMRPro, and a higher threshold (20%) when using PREMM5 and MMRPredict. Our findings have important implications for personalized mutation risk assessment and counseling on genetic testing.