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

AbstractUntil recently, no prediction models for Lynch syndrome (LS) had been validated forPMS2 mutation carriers. We aimed to evaluate MMRpredict and PREMM5 in a clinical cohort and forPMS2 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; 23MLH1, 17MSH2, 31MSH6 and 12PMS2 mutation carriers. Both prediction models performed well forMLH1 andMSH2 (AUC 0.80 and 0.83 for PREMM5 and 0.79 for MMRpredict) and fair forMSH6 mutation carriers (0.69 for PREMM5 and 0.66 for MMRpredict). MMRpredict performed fair forPMS2 mutation carriers (AUC 0.72), while PREMM5 failed to discriminatePMS2 mutation carriers from non-mutation carriers (AUC 0.51). The only statistically significant difference betweenPMS2 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 forPMS2 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 identifyPMS2 mutation carriers. Adding loca...
Source: Familial Cancer - Category: Cancer & Oncology Source Type: research