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. 2018 Jul;17(3):361-370.
doi: 10.1007/s10689-017-0039-1.

Evaluation of current prediction models for Lynch syndrome: updating the PREMM5 model to identify PMS2 mutation carriers

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Evaluation of current prediction models for Lynch syndrome: updating the PREMM5 model to identify PMS2 mutation carriers

A Goverde et al. Fam Cancer. 2018 Jul.

Abstract

Until recently, no prediction models for Lynch syndrome (LS) had been validated for PMS2 mutation carriers. We aimed to evaluate MMRpredict and PREMM5 in a clinical cohort and for PMS2 mutation carriers specifically. In a retrospective, clinic-based cohort we calculated predictions for LS according to MMRpredict and PREMM5. The area under the operator receiving characteristic curve (AUC) was compared between MMRpredict and PREMM5 for LS patients in general and for different LS genes specifically. Of 734 index patients, 83 (11%) were diagnosed with LS; 23 MLH1, 17 MSH2, 31 MSH6 and 12 PMS2 mutation carriers. Both prediction models performed well for MLH1 and MSH2 (AUC 0.80 and 0.83 for PREMM5 and 0.79 for MMRpredict) and fair for MSH6 mutation carriers (0.69 for PREMM5 and 0.66 for MMRpredict). MMRpredict performed fair for PMS2 mutation carriers (AUC 0.72), while PREMM5 failed to discriminate PMS2 mutation carriers from non-mutation carriers (AUC 0.51). The only statistically significant difference between PMS2 mutation carriers and non-mutation carriers was proximal location of colorectal cancer (77 vs. 28%, p < 0.001). Adding location of colorectal cancer to PREMM5 considerably improved the models performance for PMS2 mutation carriers (AUC 0.77) and overall (AUC 0.81 vs. 0.72). We validated these results in an external cohort of 376 colorectal cancer patients, including 158 LS patients. MMRpredict and PREMM5 cannot adequately identify PMS2 mutation carriers. Adding location of colorectal cancer to PREMM5 may improve the performance of this model, which should be validated in larger cohorts.

Keywords: Colorectal cancer; Hereditary cancer; Lynch syndrome; Prediction models.

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Conflict of interest statement

None of the authors declare a conflict of interest.

Figures

Fig. 1
Fig. 1
Performance of PREMM5 and MMRpredict in a clinical setting for all mutation carriers and for individual MMR mutations
Fig. 2
Fig. 2
Performance of PREMM5 and the extended PREMM5 model in a clinical setting for all mutation carriers and for individual MMR mutations

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