Clinical Research Directory
Browse clinical research sites, groups, and studies.
Prospective Observational Study of Diffuse Large-cell B Lymphoma
Sponsor: Grand Hôpital de Charleroi
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
Conditions
Interventions
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