DeepAI
Log In Sign Up

Development, validation and clinical usefulness of a prognostic model for relapse in relapsing-remitting multiple sclerosis

05/14/2021
by   Konstantina Chalkou, et al.
0

Prognosis on the occurrence of relapses in individuals with Relapsing-Remitting Multiple Sclerosis (RRMS), the most common subtype of Multiple Sclerosis (MS), could support individualized decisions and disease management and could be helpful for efficiently selecting patients in future randomized clinical trials. There are only three previously published prognostic models on this, all of them with important methodological shortcomings. We aim to present the development, internal validation, and evaluation of the potential clinical benefit of a prognostic model for relapses for individuals with RRMS using real world data. We followed seven steps to develop and validate the prognostic model. Finally, we evaluated the potential clinical benefit of the developed prognostic model using decision curve analysis. We selected eight baseline prognostic factors: age, sex, prior MS treatment, months since last relapse, disease duration, number of prior relapses, expanded disability status scale (EDSS), and gadolinium enhanced lesions. We also developed a web application where the personalized probabilities to relapse within two years are calculated automatically. The optimism-corrected c-statistic is 0.65 and the optimism-corrected calibration slope was 0.92. The model appears to be clinically useful between the range 15 threshold probability to relapse. The prognostic model we developed offers several advantages in comparison to previously published prognostic models on RRMS. Importantly, we assessed the potential clinical benefit to better quantify the clinical impact of the model. Our web application, once externally validated in the future, could be used by patients and doctors to calculate the individualized probability to relapse within two years and to inform the management of their disease.

READ FULL TEXT

page 14

page 15

page 20

page 21

page 26

page 27

02/04/2022

Decision curve analysis for personalized treatment choice between multiple options

Decision curve analysis can be used to determine whether a personalized ...
09/19/2018

Wearable-based Mediation State Detection in Individuals with Parkinson's Disease

One of the most prevalent complaints of individuals with mid-stage and a...
12/15/2021

Ten years of image analysis and machine learning competitions in dementia

Machine learning methods exploiting multi-parametric biomarkers, especia...