An individualized nomogram for predicting progression-free survival in systemic anaplastic large cell lymphoma: a multicenter, retrospective, and internally validated study.
The study presents a nomogram that predicts progression-free survival in sALCL patients, but it requires external validation before being used in clinical practice.
Where it sits
this study against the rest of the ss-31 corpusSummary and findings
This study developed a nomogram for predicting progression-free survival (PFS) in systemic anaplastic large cell lymphoma (sALCL) patients. It involved 109 patients from 2010 to 2022, identifying predictors like serum β2-microglobulin elevation and treatment choice. The nomogram showed strong prognostic accuracy but requires further validation.
Abstract
<h4>Objectives</h4>To develop an individualized nomogram for predicting disease progression risk in systemic anaplastic large cell lymphoma (sALCL).<h4>Methods</h4>Independent predictors of progression-free survival (PFS) were identified using Cox regression in a multicenter retrospective cohort of 109 sALCL patients (2010-2022). These were incorporated into a three-factor nomogram, evaluated via bootstrapped internal validation (1000 resamples), ROC analysis, C-index, decision curve analysis (DCA), and clinical impact curve (CIC).<h4>Results</h4>A total of 29 PFS events occurred during a median follow-up of 31 months. Multivariable modelling selected serum β2-microglobulin elevation, extranodal disease, and front-line chemotherapy choice (CHOP versus CHOPE or BV+CHP) as autonomous progression drivers. Upon internal bootstrap validation, the nomogram yielded strong prognostic accuracy, achieving AUCs of 0.81, 0.85 and 0.87 for 1-, 3- and 5-year progression-free survival, alongside a corrected C-index of 0.779 (95% CI: 0.699 - 0.861). Calibration plots showed close agreement between predicted and observed outcomes, while DCA confirmed superior net clinical benefit versus conventional IPI or Ann Arbor stratification across multiple decision thresholds.<h4>Conclusion</h4>This first sALCL-specific nomogram integrates clinical and treatment variables to provide personalized PFS risk estimation. While internally validated, this exploratory, observation-based tool requires external validation and recalibration in prospective cohorts before clinical implementation.
Background
This paper addresses the need for personalized risk assessment in systemic anaplastic large cell lymphoma (sALCL). Previous studies have identified various prognostic factors, but a specific nomogram for sALCL has not been established. Developing such a tool could enhance clinical decision-making and patient management.
Methods
The study utilized a multicenter retrospective cohort design, involving 109 sALCL patients from 2010 to 2022. Independent predictors of progression-free survival were identified using Cox regression analysis. The nomogram incorporated three factors and was evaluated through bootstrapped internal validation with 1000 resamples, ROC analysis, C-index, decision curve analysis, and clinical impact curve.
Results
During the study, 29 PFS events occurred over a median follow-up of 31 months. The multivariable model identified serum β2-microglobulin elevation, extranodal disease, and front-line chemotherapy choice as independent predictors of progression. The nomogram achieved AUCs of 0.81, 0.85, and 0.87 for 1-, 3-, and 5-year PFS, respectively, with a corrected C-index of 0.779 (95% CI: 0.699 - 0.861).
Interpretation
The findings suggest that the nomogram may provide a useful tool for predicting PFS in sALCL patients, showing statistically significant prognostic accuracy. However, the clinical significance of the AUC values and the need for external validation limit the immediate applicability of the results. The study's retrospective nature and reliance on historical data may also introduce confounding factors.
Key findings
- 29 PFS events occurred during a median follow-up of 31 months.
- AUCs of 0.81, 0.85, and 0.87 for 1-, 3-, and 5-year progression-free survival.
- Corrected C-index of 0.779 (95% CI: 0.699 - 0.861).
Limitations
- Exploratory, observation-based study.
- Requires external validation and recalibration in prospective cohorts.
- Retrospective cohort design may introduce confounding factors.