Residual mass histology in testicular cancer: development and validation of a clinical prediction rule
Autor: | J. Dik F. Habbema, H. Jan Keizer, Yvonne Vergouwe, Ewout W. Steyerberg |
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Rok vydání: | 2001 |
Předmět: |
Male
Statistics and Probability medicine.medical_specialty Epidemiology Calibration (statistics) Clinical prediction rule Logistic regression Residual Testicular Neoplasms Predictive Value of Tests Biomarkers Tumor medicine Humans Neoplasm Metastasis Testicular cancer Bootstrapping (statistics) Models Statistical business.industry Reproducibility of Results Decision rule medicine.disease Surgery Data set Multivariate Analysis Regression Analysis Radiology business |
Zdroj: | Statistics in Medicine. 20:3847-3859 |
ISSN: | 1097-0258 0277-6715 |
DOI: | 10.1002/sim.915 |
Popis: | After chemotherapy for metastatic non-seminomatous testicular cancer, surgical resection is a generally accepted treatment to remove remnants of the initial metastases, since residual tumour may still be present (mature teratoma or viable cancer cells). In this paper, we review the development and external validation of a logistic regression model to predict the absence of residual tumour. Three sources of information were used. A quantitative review identified six relevant predictors from 19 published studies (996 resections). Second, a development data set included individual data of 544 patients from six centres. This data set was used to assess the predictive relationships of five continuous predictors, which resulted in dichotomization for two, and a log, square root, and linear transformation for three other predictors. The multiple logistic regression coefficients were reduced with a shrinkage factor (0.95) to improve calibration, based on a bootstrapping procedure. Third, a validation data set included 172 more recently treated patients. The model showed adequate calibration and good discrimination in the development and in the validation sample (areas under the ROC curve 0.83 and 0.82). This study illustrates that a careful modelling strategy may result in an adequate predictive model. Further study of model validity may stimulate application in clinical practice. |
Databáze: | OpenAIRE |
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