Development of a Nomogram Model for Treatment of Nonmetastatic Nasopharyngeal Carcinoma.

Importance: Because of tumor heterogeneity, overall survival (OS) differs significantly among individuals with nasopharyngeal carcinoma (NPC), even among those with the same clinical stage. Relying solely on TNM staging to guide treatment remains imperfect. Objectives: To establish a comprehensive nomogram to estimate individualized OS and to explore stratified treatment regimens for risk subgroups in nonmetastatic NPC. Design, Setting, and Participants: This cohort study included 8093 patients diagnosed with NPC at a single center in China from April 2009 to December 2015. The sample was split into a training cohort (5398 participants [66.7%]) and validation cohort (2695 [33.3%]). Data were analyzed in May 2020. Exposures: Age, T stage, N stage, Epstein-Barr virus (EBV) DNA level, serum lactate dehydrogenase (LDH) levels, and albumin (ALB) levels. Main Outcomes and Measures: The primary end point was OS. The nomogram for estimating OS was generated based on multivariate Cox proportional hazards regression. The performance of the nomogram was quantified using Harrell concordance index (C index), the area under the curve (AUC) of the receiver operating characteristic curve, and a calibration curve. OS rates were established using the Kaplan-Meier method, and intersubgroup differences were examined by the log-rank test. Results: Among the 8093 participants, 5688 (70.3%) were men, and the median age at diagnosis was 45 years (range, 7-85 years). Six variables (age, T stage, N stage, EBV DNA levels, LDH levels, and ALB levels) were identified through multivariate Cox regression and incorporated into a nomogram to estimate OS. The resulting nomogram showed excellent discriminative ability and significantly outperformed the eighth edition of the American Joint Committee on Cancer/Union for International Cancer Control TNM staging system for estimating OS (C index, 0.716 [95% CI, 0.698-0.734] vs 0.643 [95% CI, 0.624-0.661]; P < .001; AUC, 0.717 [95% CI, 0.698-0.737] vs 0.643 [95% CI, 0.623-0.662]; P < .001), and the calibration curves showed satisfactory agreement between the actual and nomogram-estimated OS rates. The validation cohort confirmed the results. Patients were stratified into 4 risk groups based on the 25th, 50th, and 75th percentile score values estimated from the nomogram. The 4 nomogram-defined risk groups demonstrated significantly different intergroup OS (3-year OS rates: risk group 1, 1328 of 1345 [98.7%]; risk group 2, 1289 of 1341 [96.1%]; risk group 3, 1222 of 1321 [92.5%]; risk group 4, 1173 of 1391 [84.3%]; P < .001). These risk groups were associated with the efficacy of different treatment regimens. For example, for risk group 4, induction chemotherapy with concurrent chemoradiotherapy was associated with a significantly better OS than concurrent chemoradiotherapy (log-rank P = .008) and intensity-modulated radiotherapy alone (log-rank P < .001). Conclusions and Relevance: In this study, the proposed nomogram model enabled individualized prognostication of OS and could help to guide risk-adapted treatment for patients with nonmetastatic NPC.

Development and validation of a prognostic nomogram for the pre-treatment prediction of early metachronous metastasis in endemic nasopharyngeal carcinoma: a big-data intelligence platform-based analysis.

BACKGROUND: Early failure of cancer treatment generally indicates a poor prognosis. Here, we aim to develop and validate a pre-treatment nomogram to predict early metachronous metastasis (EMM) in nasopharyngeal carcinoma (NPC). METHODS: From 2009 to 2015, a total of 9461 patients with NPC (training cohort: n = 7096; validation cohort: n = 2365) were identified from an institutional big-data research platform. EMM was defined as time to metastasis within 2 years after treatment. Early metachronous distant metastasis-free survival (EM-DMFS) was the primary endpoint. A nomogram was established with the significant prognostic factors for EM-DMFS determined by multivariate Cox regression analyses in the training cohort. The Harrell Concordance Index (C-index), area under the receiver operator characteristic curve (AUC), and calibration curves were applied to evaluate this model. RESULTS: EMM account for 73.5% of the total metachronous metastasis rate and is associated with poor long-term survival in NPC. The final nomogram, which included six clinical variables, achieved satisfactory discriminative performance and significantly outperformed the traditional tumor-node-metastasis (TNM) classification for predicting EM-DMFS: C-index: 0.721 versus 0.638, p < 0.001; AUC: 0.730 versus 0.644, p < 0.001. The calibration curves showed excellent agreement between the predicted and actual EM-DMFS. The nomogram can stratify patients into three risk groups with distinct EM-DMFS (2-year DMFS: 96.8% versus 90.1% versus 80.3%, p < 0.001). A validation cohort supported the results. The three identified risk groups are correlated with the efficacy of different treatment regimens. CONCLUSION: Our established nomogram can reliably predict EMM in patients with NPC and might aid in formulating risk-adapted treatment decisions and personalized patient follow-up strategies.