Predicted survival of patients with human immunodeficiency virus-associated non-Hodgkin’s lymphoma based on clinical and imaging factors: A multicenter retrospective study

BACKGROUND: Non-Hodgkin’s lymphoma (NHL) has a poor prognosis and serious risk of mortality. Furthermore, the clinical and imaging characteristics differ between human immunodeficiency virus (HIV)-positive and HIV-negative NHL. We aimed to create a nomogram based on imaging, clinical, and laboratory indicators to predict the mortality risk of patients with HIV-positive NHL. MATERIALS AND METHODS: A total of 306 patients were enrolled. The training cohort comprised 194 patients with HIV-positive NHL treated at four Chinese medical centers between April 2012 and October 2020. A series of statistical methods were used to screen potential predictive factors for inclusion in a prognostic nomogram. The performance of the nomogram was assessed by internal validation, external validation, and clinical utility. The independent external verification cohort comprised 112 patients treated between January 2013 and November 2020. RESULTS: After investigating 39 potentially predictive factors, a nomogram containing eight factors (three imaging factors, four clinical factors, and one HIV-infection special factor) was developed. Internal and external validation revealed good discrimination (concordance index: 0.837 vs. 0.817; 95% confidence interval, 0.826–0.848 vs. 0.798–0.836) and excellent calibration. Regarding the clinical utility, our nomogram was more accurate in predicting survival than the International Prognostic Index (area under the curve, 0.9217 vs. 0.8150; sensitivity, 0.85 vs. 0.67; and specificity, 0.89 vs. 0.87). The nomogram identified low-risk, intermediate-risk, and high-risk groups with 1-year survival rates of 95%, 59%, and 2%, respectively. CONCLUSION: The nomogram model based on imaging, clinical, and laboratory indicators may be useful in predicting the treatment efficacy and long-term mortality risk of patients with HIV-positive NHL. This may provide a new scientific basis for clinical decision-making.