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Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
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Development and validation of a novel prognostic nomogram for advanced diffuse large B cell lymphoma
Mengdi Wan1, Wei Zhang1, He Huang2
1Department of Medical Oncology, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, University of Electronic Science and Technology of China, Chengdu, 610054, Sichuan Province, China.
Clinical and Experimental Medicine
|March 30, 2024
Summary
A new nomogram identifies key prognostic factors for advanced diffuse large B cell lymphoma (DLBCL). This tool aids in assessing survival and personalizing treatment for patients with this aggressive cancer.
Area of Science:
- Hematology
- Oncology
- Biostatistics
Background:
- Advanced diffuse large B cell lymphoma (DLBCL) presents aggressive clinical features and a poor prognosis.
- Currently, an effective prognostic tool for advanced (stage III/IV) DLBCL is lacking.
Purpose of the Study:
- To identify prognostic indicators influencing survival and response in advanced DLBCL.
- To establish the first survival prediction nomogram for advanced DLBCL patients.
Main Methods:
- A cohort of 402 advanced DLBCL patients was analyzed.
- COX multivariate analysis identified independent prognostic factors.
- A nomogram was constructed using R rms package, validated with C-index, AUC, and calibration curves.
Main Results:
- Ki-67, lactate dehydrogenase (LDH), ferritin (FER), and β2-microglobulin were identified as independent predictors.
- The nomogram demonstrated significant differences in overall survival (OS) across risk groups (81.6% for low, 44% for intermediate, 6% for high risk at 5 years).
- The nomogram achieved strong predictive performance with C-indices of 0.76 (training) and 0.74 (validation), and AUCs of 0.828 (training) and 0.803 (validation).
Conclusions:
- The developed nomogram provides a valuable tool for individualized risk assessment of overall survival in advanced DLBCL.
- This prognostic model can aid clinicians in treatment planning and patient management.
