Evaluation of predictive models in daily practice for the identification of patients with Lynch syndrome

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The optimal strategy for identifying patients with Lynch syndrome among patients with newly diagnosed colorectal cancer (CRC) is still debated. Several predictive models (e.g., MMRpredict, PREMM1,2 and MMRpro) combining personal and familial data have recently been developed to quantify the risk that a given patient with CRC carries a Lynch syndrome-causing mutation. Their clinical applicability to patients with CRC from the general population requires evaluation. We studied a consecutive series of 214 patients with newly diagnosed CRC characterized for tumor microsatellite instability (MSI), somaticBRAFmutation,MLH1promoter methylation and mismatch repair (MMR) gene germline mutation status. The performances of the models for identifying MMR mutation carriers (8/214, 3.7%) were evaluated and compared to the revised Bethesda guidelines and a molecular strategy based on MSI testing in all patients followed by the exclusion of MSI-positive sporadic cases from mutational testing by screening forBRAFmutation andMLH1promoter methylation. The sensitivities of the three models, at the lowest thresholds proposed, were identical (75%), with similar numbers of probands eligible for further MSI testing (almost half the patients). In our dataset, the prediction models gave no better discrimination than the revised Bethesda guidelines. Both approaches failed to identify two of the eight mutation carriers (the same two patients, aged 67 and 81 years, both with no family history). Thus, like the revised Bethesda guidelines, predictive models did not identify all patients with Lynch syndrome in our series of consecutive CRC. Our results support systematic screening for MMR deficiency in all new CRC cases.

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