A Simple-To-Use Nomogram for Predicting Early Death in Metastatic Renal Cell Carcinoma: A Population-Based Study

Abstract

BackgroundMetastatic renal cell carcinoma (mRCC) is usually considered to have a poor prognosis, which has a high risk of early death (≤3 months). Our aim was to developed a predictive nomogram for early death of mRCC.MethodsThe SEER database was accessed to obtain the related information of 6,005 mRCC patients between 2010 and 2015. They were randomly divided into primary cohort and validation cohort in radio of 7:3. The optimal cut-off point regarding age at diagnosis and tumor size were identified by the X-tile analysis. Univariate and multivariate logistic regression models were applied to determine significant independent risk factors contributed to early death. A practical nomogram was constructed and then verified by using calibration plots, receiver operating characteristics (ROCs) curve, and decision curve analysis (DCA).ResultsThere were 6,005 patients with mRCC included in the predictive model, where 1,816 patients went through early death (death within ≤3 months of diagnosis), and among them 1,687 patients died of mRCC. Based on 11 significant risk factors, including age, grade, N-stage, histologic type, metastatic sites (bone, lung, liver and brain) and treatments (surgery, radiation, and chemotherapy), a practical nomogram was developed. The model's excellent effectiveness, discrimination and clinical practicality were proved by the AUC value, calibration plots and DCA, respectively.ConclusionsThe nomogram may play a major part in distinguishing the early death of mRCC patients, which can assist clinicians in individualized medicine.

Construction and validation of nomograms combined with novel machine learning algorithms to predict early death of patients with metastatic colorectal cancer

“…The screening process is shown in Figure 1. According to previous studies, early death was defined as death of patients within 3 months of diagnosis (13)(14)(15). All the included patients with mCRC were divided into a training cohort (accounting for 70%) and a validation cohort (accounting for 30%).…”

Development and validation of a prognostic nomogram for bone metastasis from lung cancer: A large population-based study

“…In accordance with the International Classification of Diseases for Oncology, 3rd Edition, lung cancer was classified as adenocarcinoma, squamous cell carcinoma (SCC), small cell lung cancer (SCLC), large cell lung cancer (LCLC), and nonsmall cell lung cancer or not otherwise specified lung cancer (NSCLC/NOS). The variables were extracted from the SEER plan, including age, gender, race, marital status, histological type, tumor grade, primary site, laterality, tumor size, TNM stage, distant metastasis, surgery (Code 12,13,15,(19)(20)(21)(22)(23)(24)(25)30,33,45,46,55,56,65,66,80,90), radiotherapy and chemotherapy. The following inclusion criteria were applied (1): diagnosed from 2011 to 2015 (2); lung cancer is the only malignant tumor (3); primary diagnosed lung cancer patients with BM.…”

“…Nomograms, as a visual statistical tool, can integrate multiple variables to predict the individual prognosis (15). Compared to conventional staging systems, nomograms facilitate clinical decision-making with increased accuracy and more intuitive prognostic assessment (16,17).…”

Prediction model of all-cause death based on balance ability among middle-aged and older Chinese adults of overweight and obesity

“…Multiple body indicators (including balance) can predict death and improve the performance of prediction models ( 10 ). Previous studies showed age and diabetes were indicators for death ( 11 , 12 ). The Short Physical Performance Battery (SPPB) ( 13 ) is one of the most effective tools for assessing this, but how balance ability indicates all-cause death in middle-aged and old Chinese adults with overweight and obesity has not been studied.…”