Global, regional, and national burden of nasopharyngeal carcinoma from 1990 to 2017-Results from the Global Burden of Disease Study 2017.

BACKGROUND: The aim of this study is to estimate the incidence, mortality, and disability-adjusted life years (DALYs) of nasopharyngeal carcinoma from 1990 to 2017. METHODS: We collected detailed information on nasopharyngeal carcinoma from 1990 to 2017 based on data from Global Burden of Disease (GBD) study 2017. The global incidence, mortality, and DALYs attributable to nasopharyngeal carcinoma was reported, as well as the age-standardized rates (ASRs). RESULTS: The ASR of nasopharyngeal carcinoma incidence decreased from 1.88 (95% UI: 1.76-2.00) in 1990 to 1.35 (95% UI: 1.28-1.42) in 2017. The ASR of mortality decreased from 1.19 (95% UI: 1.13-1.25) in 1990 to 0.86 (95% UI: 0.82-0.89) in 2017, while ASR-DALYs decreased from 38.2 (95% UI: 35.9-40.2) in 1990 to 25.4 (95% UI: 24.4-26.5) in 2017. CONCLUSIONS: The ASR of incidence, mortality, and DALYs of nasopharyngeal carcinoma have decreased slightly worldwide. East Asia carried the heaviest burden of nasopharyngeal carcinoma. The majority of nasopharyngeal carcinoma burden was observed in men, especially among male aged 55 to 69 years.

Nomograms for predicting long-term overall survival and cancer-specific survival in lip squamous cell carcinoma: A population-based study.

BACKGROUND: The goal of this study was to establish and validate two nomograms for predicting the long-term overall survival (OS) and cancer-specific survival (CSS) in lip squamous cell carcinoma (LSCC). METHODS: This study selected 4175 patients who were diagnosed with LSCC between 2004 and 2015 in the SEER (Surveillance, Epidemiology, and End Results) database. The patients were allocated randomly to a training cohort and validation cohort. Variables were selected using a backward stepwise method in a Cox regression model. Based on the predictive model with the identified prognostic factors, nomograms were established to predict the 3-, 5-, and 8-year survival OS and CSS rates of LSCC patients. The accuracy of the nomograms was evaluated based on the consistency index (C-index), while their prediction accuracy was evaluated using calibration plots. Decision curve analyses (DCAs) were used to evaluate the performance of our survival model. RESULTS: The multivariate analyses demonstrated that age at diagnosis, marital status, sex, race, American Joint Committee on Cancer stage, surgery status, and radiotherapy status were risk factors for both OS and CSS. The C-index, area under the time-dependent receiver operating characteristic curve, and calibration plots demonstrated the good performance of the nomograms. DCAs of both nomograms further showed that they exhibited good 3-, 5-, and 8-year net benefits. CONCLUSIONS: We have developed and validated LSCC prognosis nomograms for OS and CSS for the first time. These nomograms can be valuable tools for clinical practice when clinicians are helping patients to understand their survival risk for the next 3, 5, and 8 years.