Statistical inference for decision curve analysis, with applications to cataract diagnosis
| Autor: | Jialiang Li, Tien Yin Wong, Sumaiya Z. Sande, Ralph B. D'Agostino, Ching-Yu Cheng |
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| Rok vydání: | 2019 |
| Předmět: |
Statistics and Probability
Epidemiology Computer science Interval estimation Inference Machine learning computer.software_genre 01 natural sciences Cataract Decision Support Techniques 010104 statistics & probability 03 medical and health sciences 0302 clinical medicine Statistical inference Humans 030212 general & internal medicine Sensitivity (control systems) 0101 mathematics Probability Relative value Models Statistical Receiver operating characteristic business.industry Complement (complexity) ROC Curve Artificial intelligence business computer Predictive modelling |
| Zdroj: | Statistics in medicineReferences. 39(22) |
| ISSN: | 1097-0258 |
| Popis: | Statistical learning methods are widely used in medical literature for the purpose of diagnosis or prediction. Conventional accuracy assessment via sensitivity, specificity, and ROC curves does not fully account for clinical utility of a specific model. Decision curve analysis (DCA) becomes a novel complement as it incorporates a clinical judgment of the relative value of benefits (treating a true positive case) and harms (treating a false positive case) associated with prediction models. The preference of a patient or a policy-maker is formulated statistically as the underlying threshold probability, above which the patient would choose to be treated. Net benefit is then calculated for possible threshold probability, which places benefits and harms on the same scale. We consider the inference problems for DCA in this paper. Interval estimation procedure and inference methodology are provided after we derive the relevant asymptotic properties. Our formulation can accommodate the classification problems with multiple categories. We carry out numerical studies to assess the performance of the proposed methods. An eye disease dataset is analyzed to illustrate our proposals. |
| Databáze: | OpenAIRE |
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