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

Autor: Hung FH; Health Data Analytics and Statistics Center, Office of Data Science, Taipei Medical University, Taipei, Taiwan., Peng HP; Biomedical Translation Research Center, Academia Sinica, Taipei, Taiwan., Hung CF; Department of Research, Koo Foundation Sun-Yat Sen Cancer Center, Taipei, Taiwan., Hsieh LL; Department of Internal Medicine, Koo Foundation Sun-Yat Sen Cancer Center, Taipei, Taiwan., Yang AS; Genomics Research Center, Academia Sinica, Taipei, Taiwan., Wang YA; Department of Internal Medicine, Koo Foundation Sun-Yat Sen Cancer Center, Taipei, Taiwan.; School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.
Jazyk: angličtina
Zdroj: International journal of cancer [Int J Cancer] 2024 Dec 15; Vol. 155 (12), pp. 2201-2210. Date of Electronic Publication: 2024 Jul 20.
DOI: 10.1002/ijc.35106
Abstrakt: Identifying 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: PREMM 5 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). PREMM 5 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 PREMM 5 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 PREMM 5 and MMRPredict. Our findings have important implications for personalized mutation risk assessment and counseling on genetic testing.
(© 2024 The Author(s). International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC.)
Databáze: MEDLINE
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