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RECRUITING
NCT06241729

Prospective Observational Study of Diffuse Large-cell B Lymphoma

Sponsor: Grand Hôpital de Charleroi

View on ClinicalTrials.gov

Summary

Diffuse large B-cell lymphoma (DLBCL) represents the most common type of non-Hodgkin lymphoma and is currently a curable malignant disease for many patients with immuno-chemotherapy frontline treatment. However, around 30-40 % of patients, are unresponsive or will experience early relapse. The prognosis of primary refractory patient is poor and the management and treatment are a significant challenge due to the disease heterogeneity and the complex genetic framework. The reasons for refractoriness are various and include genetic abnormalities, alterations in tumor and tumor microenvironment. Patient related factors such as comorbidities can also influence treatment outcome. Recently the progress in Machine learning (ML) showed its usefulness in the procedures used to analyze large and complex datasets. In medicine, machine learning is used to create some predictive tools based on data-driven analytic approach and integration of various risk factors and parameters. Machine learning, as a subdomain of artificial intelligence (AI), has the capability to autonomously uncover patterns within datasets. It offers algorithms that can learn from examples to perform a task automatically.The investigators tested in a previous study five machine learning algorithms to establish a model for predicting the risk of primary refractory DLBCL using parameters obtained from a monocentric dataset. The investigators observed that NB Categorical classifier was the best alternative for building a model in order to predict primary refractory disease in DLBCL patients and the second was XGBoost.The investigators plan to extend this previous study by further exploring the two best-performing models (NBC Classifier and XGBoost), progressively incorporating a larger number of patients in a prospective way.

Official title: Supervised Machine Learning for the Prediction of Primary Refractory Status in Patients With Diffuse Large Cell B Lymphoma in a Monocentric Cohort at the Grand Hôpital de Charleroi

Key Details

Gender

All

Age Range

18 Years - Any

Study Type

OBSERVATIONAL

Enrollment

50

Start Date

2023-01-03

Completion Date

2026-12-31

Last Updated

2025-07-31

Healthy Volunteers

No

Interventions

OTHER

Algorithms to predict the probability of a primary refractory state

Follow-up of a cohort of patients with diffuse large-cell B lymphoma from 2024 using algorithms to predict the probability of a primary refractory state

Locations (1)

Grand Hôpital de Charleroi

Charleroi, Hainaut, Belgium