evaluation in a clinical genetic setting Mutation prediction models in Lynch syndrome: http://jmg.bmj.com/cgi/content/abstract/jmg.2009.066589v1 Updated information and services can be found at: These include: Rapid responses http://jmg.bmj.com/cgi/eletter-submit/jmg.2009.066589v1 Abstract Background/aims: The identification of Lynch syndrome is hampered by the absence of specific diagnostic features and underutilization of genetic testing. Prediction models have therefore been developed, but

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... ey have not been validated for a clinical genetic setting. The aim of the present study was to evaluate the usefulness of currently available prediction models. Methods: We collected data of 321 index probands who were referred to the department of Clinical Genetics of the Erasmus Medical Center because of a family history of colorectal cancer. These data were used as input for five previously published models. External validity was assessed by discriminative ability (AUC: area under the receiver operating characteristic curve) and calibration. For further insight, predicted probabilities were categorized with cutoffs of 5%, 10%, 20% and 40%. Furthermore, costs of different testing strategies were related to the number of extra detected mutation carriers. Results: Of the 321 index probands, 66 harboured a germline mutation. All models discriminated well between high risk and low risk index probands (AUC: 0.82-0.84). Calibration was well for the Premm 1,2 and Edinburgh model, but poor for the other models. Cut-offs could be found for the prediction models where costs could be saved while missing only few mutations. Conclusions: The Edinburgh and Premm 1,2 model were the models with the best performance for an intermediate to high-risk setting. These models may well be of use in clinical practice to select patients for further testing of mismatch repair gene mutations. on