Reporting methods in studies developing prognostic models in cancer: a review
Open Access
- 30 March 2010
- journal article
- review article
- Published by Springer Nature in BMC Medicine
- Vol. 8 (1) , 20
- https://doi.org/10.1186/1741-7015-8-20
Abstract
Development of prognostic models enables identification of variables that are influential in predicting patient outcome and the use of these multiple risk factors in a systematic, reproducible way according to evidence based methods. The reliability of models depends on informed use of statistical methods, in combination with prior knowledge of disease. We reviewed published articles to assess reporting and methods used to develop new prognostic models in cancer.Keywords
This publication has 79 references indexed in Scilit:
- Reporting performance of prognostic models in cancer: a reviewBMC Medicine, 2010
- Evaluation of Logistic Regression Reporting in Current Obstetrics and Gynecology LiteratureObstetrics & Gynecology, 2008
- The cost of dichotomising continuous variablesBMJ, 2006
- Improvement of breast cancer relapse prediction in high risk intervals using artificial neural networksBreast Cancer Research and Treatment, 2005
- A model for predicting outcomes in patients with differentiated thyroid cancer and model performance in comparison with other classification systemsJournal of the American College of Surgeons, 2005
- Validation and adaptation of a nomogram for predicting the survival of patients with extremity soft tissue sarcoma using a three‐grade systemCancer, 2005
- A POSTOPERATIVE PROGNOSTIC NOMOGRAM PREDICTING RECURRENCE FOR PATIENTS WITH CONVENTIONAL CLEAR CELL RENAL CELL CARCINOMAJournal of Urology, 2005
- Empirical Evidence for Selective Reporting of Outcomes in Randomized TrialsJAMA, 2004
- Potential for Selection Bias with Tumor Tissue Retrieval in Molecular Epidemiology StudiesAnnals of Epidemiology, 2002
- Dangers of Using "Optimal" Cutpoints in the Evaluation of Prognostic FactorsJNCI Journal of the National Cancer Institute, 1994