PCNSL

PCNSL predicts individualized 1-, 3-, and 5-year overall survival (OS) and cancer-specific survival (CSS) probabilities for patients with primary central nervous system lymphoma (PCNSL) using nomograms derived from statistical models.

Key Features:

• Data source: Development used the Surveillance, Epidemiology, and End Results (SEER) database (1975–2016) with external validation on a cohort of 163 patients from Beijing Tiantan Hospital (2004–2018).
• Statistical models: Uses Cox regression and Fine and Grey's model with the backward method to identify independent risk factors for OS and CSS.
• Risk factors: Identified independent predictors include age at diagnosis, tumor site, pathological subtype, surgery, chemotherapy, coexisting malignancies, HIV infection (for CSS), and gender, marital status, and radiation (for OS).
• Nomogram development: Constructs nomograms to estimate 1-, 3-, and 5-year survival probabilities for both OS and CSS based on identified predictors.
• Validation and performance: Reports internal and external validation with C-indexes of 0.728 (95% CI: 0.703–0.753) for OS and 0.726 (95% CI: 0.696–0.756) for CSS, demonstrating performance in an Asian population cohort.

Scientific Applications:

• Individualized prognosis: Provides patient-specific survival probability estimates for PCNSL to quantify prognosis.
• Clinical decision support: Supports evaluation of individualized risk to inform treatment planning and patient counseling for PCNSL.
• Comparative prognostic modeling: Serves as an alternative prognostic model to previously published OS nomograms and for external validation in different populations.

Methodology:

Computational methods explicitly include Cox regression and Fine and Grey's model with backward variable selection to identify independent risk factors, construction of nomograms for 1-, 3-, and 5-year OS and CSS, and internal and external validation with C-index calculation.