Introduction: Large variability in the clinical outcomes has been observed among the nasopharyngeal cancer (NPC) patients with the same stage receiving similar treatment. This suggests that the current Tumour-Node-Metastasis staging systems need to be refined. The nomogram is a useful predictive tool that integrates individual variables into a statistical model to predict outcome of interest. This study was to design predictive nomograms based on the clinical and pathological features of patients with NPC.
Materials and methods: Clinical data of 270 NPC patients who underwent definitive radiation therapy (RT) alone or concurrent with chemotherapy were collected. Factors predictive of response to RT and overall survival (OS) were determined by univariate and multivariate analyses, and predictive nomograms were created. Nomograms were validated externally by assessing discrimination and calibration using an independent data set (N=122).
Results: Three variables predictive of response to RT (age, histology classification and N classification) and four predictive of OS (age, performance status, smoking status and N classification), in addition to T classification, were extracted to generate the nomograms. The nomograms were validated externally, which showed perfect correlation with each other.
Conclusion: The designed nomograms proved highly predictive of response to RT and OS in individual patients, and could facilitate individualised and personalised patients' counselling and care.
Keywords: Nasopharyngeal cancer; Nomogram; Outcomes; Prognosis; Validation.
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