Prediction of Overall Survival Status of Diffuse Large B-Cell Lymphoma Using a Prognostic Classification Model

Prediction of Overall Survival Status of Diffuse Large B-Cell Lymphoma Using a Prognostic Classification Model | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 29 August 2025 V1 Latest version Share on Prediction of Overall Survival Status of Diffuse Large B-Cell Lymphoma Using a Prognostic Classification Model Author : Ananya Ganapathy 0009-0000-3570-1753 [email protected] Authors Info & Affiliations https://doi.org/10.22541/au.175649113.36750850/v1 297 views 113 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Diffuse large B-cell lymphoma (DLBCL) is an aggressive form of non-Hodgkin lymphoma accounting for approximately one-third of cases and marked by significant variation in patient survival outcomes. This study aims to improve prognostic prediction in DLBCL by integrating machine learning to both identify previously unreported gene mutations associated with poor survival outcomes and enhance existing models' interpretability and accuracy. By analyzing targeted genomic and clinical data from 396 DLBCL samples, we identified key gene mutations, such as those in CRLF2, MOB3B and P2RY8 which were strongly associated with progression and overall survival status. Our model incorporates these mutations to provide a more accurate prediction of patient outcomes, achieving high performance, including an AUC of 0.81 and an accuracy of 85%. This model provides an interpretable approach to DLBCL prognosis, aiding clinical decisions by identifying high-risk patients and informing treatment intensity. Future work will focus on further validation in larger, independent cohorts to solidify these findings. Supplementary Material File (ananya_dlbcl_paper.pdf) Download 1.80 MB Information & Authors Information Version history V1 Version 1 29 August 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords diffuse large b-cell lymphoma dlbcl lymphoma non-hodgkin lymphoma overall survival status prediction Authors Affiliations Ananya Ganapathy 0009-0000-3570-1753 [email protected] The International School Bangalore(TISB) View all articles by this author Metrics & Citations Metrics Article Usage 297 views 113 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Ananya Ganapathy. Prediction of Overall Survival Status of Diffuse Large B-Cell Lymphoma Using a Prognostic Classification Model. Authorea . 29 August 2025. DOI: https://doi.org/10.22541/au.175649113.36750850/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . 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