ObjectiveThis study focused on developing an effective nomogram for improving prognostication for patients with primary nasopharyngeal carcinoma (NPC) restaged according to the eighth edition of the AJCC/UICC TNM staging system.MethodsBased on data of 5,903 patients with non-metastatic NPC (primary cohort), we used Cox regression analysis to identify survival risk factors and created a nomogram. We used the nomogram to predict overall survival (OS), distant metastasis-free survival (DMFS) and disease-free survival (DFS) in the primary and independent validation (3,437 patients) cohorts. Moreover, we compared the prognostic accuracy between the 8th TNM system and the nomogram.ResultsThe nomogram included gender, age, T stage, N stage, Epstein–Barr virus DNA, hemoglobin, C-reactive protein, lactate dehydrogenase, and radiotherapy with/without induction or concurrent chemotherapy. In the prediction of OS, DMFS and DFS, the nomogram had significantly higher concordance index (C-index) and area under ROC curve (AUC) than the TNM system alone. Calibration curves demonstrated satisfactory agreements between nomogram-predicted and observed survival. The stratification in different groups permitted remarkable differentiation among Kaplan–Meier curves for OS, DMFS, and DFS.ConclusionThe nomogram led to a more precise prognostic prediction for NPC patients in comparison with the 8th TNM system. Therefore, it could facilitate individualized and personalized patients’ counseling and care.
Objectives We aimed to understand the clinical characteristics and better predict the prognosis of patients with mucosal melanoma of the head and neck (MMHN) using a nomogram. Methods Three hundred patients with nometastatic MMHN were included. Multivariable Cox regression was performed to analyze independent prognostic factors for overall survival (OS), disease-free survival (DFS), distant metastasis-free survival (DMFS), and locoregional relapse-free survival (LRRFS), and these factors were used to develop a nomogram. Concordance indexes (C-indexes), calibration plots, and receiver operating characteristic (ROC) analysis were performed to test the predictive performance of the nomogram in both the primary (n = 300) and validation cohorts (n = 182). Results The primary tumor site, T stage and N stage were independent risk factors for survival and were included in the nomogram to predict the 3- and 5-year OS, DFS, DMFS, and LRRFS in the primary cohort. The C-indexes (both > 0.700), well-fit calibration plots, and area under the ROC curve (both > 0.700) indicated the high diagnostic accuracy of the nomogram, in both the primary and validation cohorts. The patients were divided into three groups (high-risk, intermediate-risk, and low-risk groups) according to their nomogram scores. The survival curves of OS, DFS, DMFS, and LRRFS were well separated by the risk groups in both cohorts (all P < 0.001). Conclusions The nomogram can stratify MMHN patients into clinically meaningful taxonomies to provide individualized treatment.
PurposeWe aimed to develop a prognostic immunohistochemistry (IHC) signature for patients with head and neck mucosal melanoma (MMHN).MethodsIn total, 190 patients with nonmetastatic MMHN with complete clinical and pathological data before treatment were included in our retrospective study.ResultsWe extracted five IHC markers associated with overall survival (OS) and then constructed a signature in the training set (n=116) with the least absolute shrinkage and selection operator (LASSO) regression model. The validation set (n=74) was further built to confirm the prognostic significance of this classifier. We then divided patients into high- and low-risk groups according to the IHC score. In the training set, the 5-year OS rate was 22.0% (95% confidence interval [CI]: 11.2%- 43.2%) for the high-risk group and 54.1% (95% CI: 41.8%-69.9%) for the low-risk group (P<0.001), and in the validation set, the 5-year OS rate was 38.1% (95% CI: 17.9%-81.1%) for the high-risk group and 43.1% (95% CI: 30.0%-61.9%) for the low-risk group (P=0.26). Multivariable analysis revealed that IHC score, T stage, and primary tumor site were independent variables for predicting OS (all P<0.05). We developed a nomogram incorporating clinicopathological risk factors (primary site and T stage) and the IHC score to predict 3-, 5-, and 10-year OS.ConclusionsA nomogram was generated and confirmed to be of clinical value. Our IHC classifier integrating five IHC markers could help clinicians make decisions and determine optimal treatments for patients with MMHN.
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