Step 3: classification performance comparison

We plotted cross-validated Harrell’s C and 3-year Brier scores of stepwise models with increasing proportion of patients receiving biomarker testing against the models with clinical data only (demographics only/demographics and MRI) and the model with additional CSF testing for all patients. This allowed us to identify the optimal proportion of patients where the stepwise approach performed better than the model with clinical data only and equally good as the additional CSF biomarker model in terms of prognostic discrimination (Harrell’s C) and prognostic accuracy (3-year Brier scores).

As we used percentiles of the calculated prognostic probabilities with demographic and/or MRI data, the optimal proportion that is selected corresponds with certain demographic or MRI-model derived probabilities (supplemental Table 1). As a result, the optimal proportion also provided us with an algorithm that defines the threshold of demographic or MRI-model derived probabilities where additional biomarker testing would be indicated, further referred to as probability thresholds.