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Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Development and Validation of a Time-Dependent Nomogram for Predicting Hematological Toxicity Risk During Linezolid
Wenqiang Zhou1, Hui Zhu2, Zhongquan Liu2
1Department of Infectious Diseases, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
Background:
Linezolid is essential for drug-resistant tuberculosis (DR-TB) treatment but causes frequent hematological toxicity. We developed a time-dependent nomogram to predict this risk.
Methods:
A prospective cohort of 201 patients with DR-TB receiving linezolid (600 mg/day) was enrolled. Blood trough concentration (Cmin) and clinical variables were measured. Multivariable Cox regression identified predictors, with a nomogram constructed to estimate toxicity probability at 1, 3, and 6 months. Model performance was assessed via calibration curves, C-index, and time-dependent area under the curve (AUC).
Results:
Ninety-six patients (47.8%) developed hematological adverse events (anemia: 26.4%, leukopenia: 14.4%, thrombocytopenia: 7.0%). Five predictors were significant: Cmin > 2.08 mg/L [Hazard Ratio (HR) = 2.87, p < 0.001]; lower baseline white blood cells (HR = 0.84, p = 0.003), hemoglobin (HR = 0.99, p = 0.033), and creatinine clearance rate (HR = 0.99, p = 0.001); and initial treatment (HR = 0.56 vs. retreatment, p = 0.011). The nomogram showed good discrimination (C-index = 0.73) and calibration. Time-dependent AUCs were 0.74 (1-month), 0.79 (3-month), and 0.80 (6-month). Internal validation via bootstrapping (1000×) confirmed robustness.
Conclusions:
This nomogram, integrating Cmin with baseline clinical factors, enables early identification of patients with DR-TB at high risk for hematotoxicity and could guide pre-emptive interventions. However, external validation is required to confirm its generalizability before widespread clinical implementation.
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