ArticleCancer management and research2018
Nomogram predicts survival benefit for non- metastatic esophageal cancer patients who underwent preoperative radiotherapy.
Article in Cancer management and research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.
- Systematic review and validation of clinical models predicting survival after oesophagectomy for adenocarcinoma.The British journal of surgery · 2022Pooled it
- Survival trends and conditional survival in primary non-metastatic esophageal cancer: a SEER population-based study and external validation.Translational cancer research · 2023Article
- Prognostic models for stage I-III esophageal cancer: a comparison between existing calculators.Journal of gastrointestinal oncology · 2021Article
- Prognostic nomograms and risk-stratifying systems for predicting survival in patients with resected pT2-4aN0M0 esophageal carcinoma.Journal of thoracic disease · 2021Article
- Nomogram to predict overall survival for patients with non-metastatic cervical esophageal cancer: a SEER-based population study.Annals of translational medicine · 2020Article
- Identifying an Eight-Gene Signature to Optimize Overall Survival Prediction of Esophageal Adenocarcinoma Using Bioinformatics Analysis of ceRNA Network.OncoTargets and therapy · 2020Article
- Development and validation of a nomogram to predict the prognosis of patients with squamous cell carcinoma of the bladder.Bioscience reports · 2019Article
- Prognostic nomogram predicts overall survival in pulmonary large cell neuroendocrine carcinoma.PloS one · 2019Article
- A Prognostic Model for Patients With Gastric Signet Ring Cell Carcinoma.Technology in cancer research & treatmentArticle
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundA prognostic model to predict the individual disease-specific survival (DSS) rates of non-metastatic esophageal cancer (nMEC) patients after preoperative radiotherapy (pRT) has not been established. In the current study, we aimed to establish a survival nomogram for nMEC patients after pRT.
methodsWe identified 2,424 nMEC patients who underwent pRT from the Surveillance, Epidemiology, and End Results database. Approximately, 80% (n=1,948) of the included patients were randomly selected and designated as training data set, and the remaining patients (n=476) were defined as external validation set. Nomogram was established by the training set and validated by the validation set.
resultsAccording to the results of the multivariate analysis, a nomogram combined with age at diagnosis, sex, tumor location, yp-T stage, yp metastatic lymph node ratio stage (yp-mLNRS), and grade was developed. The C-index of the model was significantly higher than that of yp-TNM staging system (0.62, 95% CI, 0.58 to 0.66 vs 0.55, 95% CI, 0.51 to 0.60;
conclusionThe proposed nomogram resulted in more reliable DSS prediction for nMEC patients in general population, regardless of the patient's histological type. Upon validation, it will aid in individualized survival prediction and prove useful in clinical decision making in nMECs after pRT.
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