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Abstract Objective We aimed to assess the significance of rENE and creat a predictive tool (nomogram) for estimating Overall Survival (OS) in locoregionally advanced Nasopharyngeal Carcinoma (NPC) patients with Lymph Node Metastasis (LNM) based on their clinical characteristics and Radiologic Extranodal Extension (rENE). Methods Five hundred and sixty-nine NPC patients with LNM were randomly divided into training and validation groups. Significant factors were identified using univariate and multivariate analyses in the training cohort. Then, the nomogram based on the screening results was established to predict the Overall Survival (OS). Calibration curves and the Concordance index (C-index) gauged predictive accuracy and discrimination. Receiver Operating Characteristic (ROC) analysis assessed risk stratification, and clinical utility was measured using Decision Curve Analysis (DCA). The nomogram's performance was validated for discrimination and calibration in an independent validation cohort. Results A total of 360 (63.2%) patients were present with radiologic extranodal extension at initial diagnosis. Patients with rENE had significantly lower OS than other patients. Multivariate analysis identified the five factors, including rENE, for the nomogram model. The C-index was 0.75 (0.71-0.78) in the training cohort and 0.76 (0.69-0.83) in the validation cohort. Notably, the nomogram outperformed the 8th TNM staging system, as evident from the higher AUC values (0.77 vs. 0.60 for 2 year and 0.75 vs. 0.65 for 3 year) and well-calibrated calibration curves. Decision curve analysis indicated improved Net Benefit (NB) with the nomogram for predicting OS. The log-rank test confirmed significant survival distinctions between risk groups in both training and validation cohorts. Conclusions We demonstrated the prognostic value of rENE in nasopharyngeal carcinoma and developed a nomogram based on rENE and other factors to provide individual prediction of OS for locoregionally advanced nasopharyngeal carcinoma with lymph node metastasis. Level of evidence: III.
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Objective@#To analyze current situation of HIV/AIDS case detection and factors associated with late diagnosis among the newly diagnosed cases from 2013 to 2018 in Hangzhou, so as to provide basis for improving the detection capacity of HIV. @*Methods@#The data of HIV testing and newly diagnosed HIV/AIDS cases in Hangzhou from 2013 to 2018 were collected through the China AIDS Prevention and Control Information System. The proportion of HIV antibody detection and positive cases in different regions, detection ways and high-risk groups were analyzed. The influencing factors for late diagnosis were analyzed by multivariate logistic regression model. @*Results@#The proportions of cases with HIV detected, HIV positive and late diagnosis increased from 2013 to 2018, and the annual ones were 24.99%, 6.95 per ten thousand and 30.07%, respectively. The results of the multivariate logistic regression analysis showed that people who were male ( OR=1.656, 95%CI: 1.351-2.030 ) and aged older ( OR: 1.912-5.117, 95%CI: 1.250-7.904 ) had higher risks of late diagnosis; who detected HIV through pre-test of receiving blood ( OR=4.429, 95%CI:2.217-9.225 ) , other inpatient detection ( OR=2.137, 95%CI: 1.615-2.826 ) , preoperative testing ( OR=2.137, 95%CI: 1.615-2.826 ) and testing of STD clinic attendants ( OR=1.359, 95%CI: 1.007-1.834 ) had higher risks of late diagnosis compared to those diagnosed at VCT clinics; who diagnosed at CDCs ( OR=0.714,95%CI: 0.558-0.915 ) and community health centers ( OR=0.645, 95%CI: 0.441-0.943 ) had lower risks of late diagnosis than those diagnosed in hospitals; who were infected by heterosexual contact ( OR=1.299, 95%CI: 1.130-1.493 ) had a higher risk of late diagnosis than MSM; who had history of STD ( OR=0.818, 95%CI: 0.706-0.948 ) had a lower risk of late diagnosis than who did not.@*Conclusions@# HIV testing and case detection had been expanded, but late diagnosis had not been improved in Hangzhou from 2013 to 2018. Age, sex, route and institution of diagnosis, transmission route and history of STD were influencing factors of late diagnosis.