Prediction of clinical outcome in CLL based on recurrent gene mutations, CLL-IPI variables, and (para)clinical data

Mehdi Parviz, Christian Brieghel, Rudi Agius, Carsten Utoft Niemann

Publikation: Bidrag til tidsskriftArtikelForskningpeer review

Abstract

A highly variable clinical course, immune dysfunction, and a complex genetic blueprint pose challenges for treatment decisions and the management of risk of infection in patients with chronic lymphocytic leukemia (CLL). In recent years, the use of machine learning (ML) technologies has made it possible to attempt to untangle such heterogeneous disease entities. In this study, using 3 classes of variables (international prognostic index for CLL [CLL-IPI] variables, baseline [para]clinical data, and data on recurrent gene mutations), we built ML predictive models to identify the individual risk of 4 clinical outcomes: death, treatment, infection, and the combined outcome of treatment or infection. Using the predictive models, we assessed to what extent the different classes of variables are predictive of the 4 different outcomes, within both a short-term 2-year outlook and a long-term 5-year outlook after CLL diagnosis. By adding the baseline (para)clinical data to CLL-IPI variables, predictive performance was improved, whereas no further improvement was observed when including the data on recurrent genetic mutations. We discovered 2 main clusters of variables predictive of treatment and infection. Further emphasizing the high mortality resulting from infection in CLL, we found a close similarity between variables predictive of infection in the short-term outlook and those predictive of death in the long-term outlook. We conclude that at the time of CLL diagnosis, routine (para)clinical data are more predictive of patient outcome than recurrent mutations. Future studies on modeling genetics and clinical outcome should always consider the inclusion of several (para)clinical data to improve performance.

OriginalsprogEngelsk
Sider (fra-til)3716-3728
Antal sider13
TidsskriftBlood advances
Vol/bind6
Udgave nummer12
Tidlig onlinedato25 apr. 2022
DOI
StatusUdgivet - 28 jun. 2022

Bibliografisk note

Copyright © 2022 American Society of Hematology.

© 2022 by The American Society of Hematology. Licensed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0), permitting only noncommercial, nonderivative use with attribution. All other rights reserved.

Fingeraftryk

Udforsk hvilke forskningsemner 'Prediction of clinical outcome in CLL based on recurrent gene mutations, CLL-IPI variables, and (para)clinical data' indeholder.

Citationsformater