Each year, researchers identify thousands of potential new “tools” for predicting patients' medical futures. There is heightened interest for discovering, validating, and incorporating into clinical practice predictors that improve treatment choices and outcomes thereof.1,2 Thousands of articles report on potential predictors. A search of PubMed clinical queries under prognosis (specific strategy) yields 165 746 articles for cancer, 72 354 for cardiovascular disease, and even 3749 for rheumatoid arthritis. These run the gamut, including genetic tests, biomarkers, and an increasing variety of imaging modes, lengthening the list of candidate predictors.3 However, very few of these proposed predictors eventually change practice. Why? What makes a good predictor?
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