A New Survival Prediction Model for Patients with Synchronous Colorectal Carcinomas Based on SEER
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Summary
The nomogram for postoperative prediction of overall survival in patients’ synchronous colorectal carcinomas was developed and validated by LASSO regression combined with COX regression and decreases the variables of the model, avoids overfitting and collinearity and has clinical significance.
- Type
- preprint
- Published
- 2020-04-08
- Cited by
- 1
- References
- 30
- Access
- Open access
- OpenAlex
- https://openalex.org/W3170608010
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:236790601
Keywords
Proportional hazards model, Lasso (programming language), Regression, Regression analysis, Linear regression
References
- Prognostic significance of lymph node status in patients with metastatic colorectal carcinoma treated with lymphadenectomy
- Cancer survival: an overview of measures, uses, and interpretation.
- Regression Modeling Strategies: With Applications to Linear Models, Logistic Regression, and Survival Analysis
- Synchronous and metachronous colorectal carcinoma
- Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): Explanation and Elaboration
- Synchronous colorectal cancer: clinical, pathological and molecular implications.
- Clinicopathologic Features of Synchronous Colorectal Carcinoma: A Distinct Subset Arising From Multiple Sessile Serrated Adenomas and Associated With High Levels of Microsatellite Instability and Favorable Prognosis
- Synchronous Colorectal Carcinoma: A Risk Factor in Colorectal Cancer Surgery
- Frequency and clinical features of multiple tumors of the large bowel in the general population and in patients with hereditary colorectal carcinoma
- Stability Investigations of Multivariable Regression Models Derived from Low- and High-Dimensional Data
- Several methods to assess improvement in risk prediction models: Extension to survival analysis
- Improved estimates of cancer-specific survival rates from population-based data.
- A method of comparing the areas under receiver operating characteristic curves derived from the same cases.
- Extensions of net reclassification improvement calculations to measure usefulness of new biomarkers
- Nonparametric estimation of time‐dependent ROC curves conditional on a continuous covariate
- Estimating and comparing time‐dependent areas under receiver operating characteristic curves for censored event times with competing risks
- Time‐Dependent ROC Curves for Censored Survival Data and a Diagnostic Marker
- Clinicopathologic characteristics and outcomes of gastric cancers with the MSI‐H phenotype
- The lasso method for variable selection in the Cox model.
- A predictive model for progression of chronic kidney disease to kidney failure.
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