Conditional survival nomogram for monitoring real-time survival of young non-metastatic nasopharyngeal cancer survivors
Journal of cancer research and clinical oncology(2023)
Abstract
Background The aim of this study was to clarify the improvement of the overall survival (OS) over time in young non-metastatic nasopharyngeal carcinoma (NPC) survivors by conditional survival (CS) analysis and to construct a CS-nomogram for updating individualized real-time prognosis. Methods The study included 3409 young non-metastatic NPC patients from the Surveillance, Epidemiology, and End Results (SEER) database (2004–2019). OS was estimated using the Kaplan–Meier method. CS was calculated based on CS(y|x) = OS(y + x)/OS(x), defined as the probability that a patient would survive for another y years after surviving for x years since diagnosis. We identified predictors using the least absolute shrinkage and selection operator (LASSO) regression and developed the CS-nomogram using multivariate Cox regression and the CS formula. Results CS analysis showed a continuous increase in 10-year OS for young non-metastatic NPC from the initial 60.4% to 65.0%, 70.2%, 74.2%, 78.2%, 82.6%, 86.9%, 91.1%, 96.2% and 97.0% (surviving 1–9 years after diagnosis, respectively). After screening by LASSO regression, age, race, marital status, histological type, T- and N-status were used as predictors to construct the CS-nomogram. The model accurately estimated the real-time prognosis of survivors during follow-up with a stable time-dependent area under the curve (AUC). Conclusions CS analysis based on SEER database calibrated the real-time prognosis of young non-metastatic NPC survivors, revealing a dynamic improvement during follow-up time. We developed a novel CS-nomogram to update survival data for real-time optimization of monitoring strategies, medical resource allocation, and patient counseling. However, it was important to note that the model still needed external data validation and continuous improvement.
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Key words
Nasopharyngeal carcinoma,Conditional survival,Overall survival,Nomogram,Prognosis
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