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A predictive diagnostic model for refractory diffuse large B-cell lymphoma: a single-center retrospective cohort
Yun Lin1,2, Yang Sun1, Chunyuan Li3
1Department of Ultrasound, Peking University Third Hospital, Beijing, 100191, China.
Annals of Hematology
|March 15, 2025
Summary
A new predictive model using ultrasound and clinical data can identify patients with refractory diffuse large B-cell lymphoma (DLBCL). This tool aids in early detection of high-risk DLBCL, improving patient management.
Area of Science:
- Oncology
- Medical Imaging
- Biostatistics
Background:
- Diffuse large B-cell lymphoma (DLBCL) is an aggressive non-Hodgkin lymphoma.
- Identifying patients with refractory DLBCL early is crucial for treatment planning.
- Current prediction methods may not fully integrate diverse data sources.
Purpose of the Study:
- To develop and validate a predictive model for refractory DLBCL.
- To integrate ultrasound imaging and clinical parameters for enhanced prediction.
- To identify significant risk factors associated with refractory DLBCL.
Main Methods:
- Retrospective analysis of 140 newly diagnosed DLBCL patients.
- Utilized ultrasound, PET-CT, and histopathological data.
- Constructed a nomogram predictive model using logistic regression and validated its performance.
Main Results:
- Blurred lymph node margins on ultrasound (OR=18.238) and IPI score (OR=3.131) were significant risk factors.
- The predictive nomogram achieved an AUC of 0.835, with 85.5% sensitivity and 79.5% specificity.
- The model showed high alignment between predicted and observed refractory DLBCL outcomes.
Conclusions:
- A predictive model combining ultrasound and clinical data effectively identifies high-risk DLBCL patients.
- This model can aid clinicians in stratifying patients for refractory disease.
- Further prospective validation is warranted to confirm clinical utility.
