Fig. 3: Performance of the top cerebrospinal fluid (CSF) proteins for predicting diagnosis and disease activity over 2 years.
Predictive power, assessed by area under the curve (AUC), of the most significant CSF proteins in the discovery cohort in differentiating between a persons with MS (pwMS; n = 92 samples in the discovery and n = 51 samples in the replication cohort) and healthy controls (HC; n = 23 samples in the discovery and n = 20 samples in the replication cohort) and b pwMS showing evidence of disease activity after 2 years (n = 48 samples in discovery and n = 45 samples in replication cohort) and pwMS not showing evidence of disease activity after 2 years (n = 30 samples in discovery and n = 5 samples in replication cohort). A logistic regression model was used to assess the predictive power of both individual proteins (the top 5 proteins in the discovery cohort are shown) and a combination of proteins, selected with a stepwise method, trained on the discovery cohort and independently validated on the replication cohort. The significance of the AUC scores were assessed with a two-sided Mann–Whitney U test. The p-values for the AUC scores of the diagnosis models in the order (stepwise model, NfL, CD79B, CD27, TNFRSF13B, IL-12p40) were (2∗10−13, 4∗10−13, 1∗10−12, 3∗10−12, 6∗10−12, 6∗10−11) for the discovery cohort and (6∗10−7, 4∗10−7, 2∗10−5, 10∗10−7, 1∗10−7, 2∗10−8) for the replication cohort. The p-values for the AUC scores of the disease activity models in the order (stepwise model, NfL, IL-1RA, FASLG, CCL3, CD6) were (1∗10−8, 9∗10−5, 0.002, 0.003, 0.004, 0.004) for the discovery cohort and (0.19, 0.02, 0.02, 0.14, 0.03, 0.41) for the replication cohort.
