Clinical prediction using complex models

Mathematical description of how things work.

https://www.uptodate.com/contents/indications-for-switching-or-stopping-disease-modifying-therapy-for-multiple-sclerosis

An example of individual prediction of response to interferon β-1a and natalizumab in moderately advanced, active multiple sclerosis. Six treatment outcomes are predicted for a 43-year-old female with relapsing-remitting multiple sclerosis, with an EDSS score of 5 (with sensory functional score of 4, and pyramidal, cerebellar and ambulatory functional scores of 3) and increase in the EDSS score within the previous year, who first presented with spinal cord symptoms at the age of 33. The patient had previously experienced 10 multiple sclerosis relapses, mostly with pyramidal symptoms, six of these of high severity and one while treated with DMTs, with the most recent relapse having occurred 51 days before the date of the prediction. She was previously treated with two DMTs, her most aggressive DMT was natalizumab and she discontinued interferon β-1a subcutaneous 51 days before the prediction. Her brain and spinal cord MRI showed abnormal findings in keeping with the diagnosis of multiple sclerosis and her CSF showed oligoclonal bands that were not present in the serum. Information about 74–93% of the variables informing the predictive models was available. The curves represent the most probable number of outcome events or area under EDSS-time curve (±95% prediction interval) over the next 4 years if recommencing natalizumab or interferon β-1a subcutaneous. The shading of the curves illustrates the robustness of the prediction (quantified as the product of the size of the training cohort and the accuracy of the prediction in the testing cohort).

The effect size, expressed as mean difference in annual percentage cortical thickness change (MD-APC), is graphically displayed in different shades of blue for each of the Desikan-Killiany atlas25 regions presenting significant differences between groups after correction for multiple comparisons.