Federico Rea1, Giovanni Corrao2, Monica Ludergnani3, Luigi Cajazzo4, Luca Merlino5. 1. National Centre for Healthcare Research and Pharmacoepidemiology, University of Milano-Bicocca, Milan, Italy; Laboratory of Healthcare Research and Pharmacoepidemiology, Unit of Biostatistics, Epidemiology and Public Health, Department of Statistics and Quantitative Methods, University of Milano-Bicocca, Milan, Italy. Electronic address: f.rea@campus.unimib.it. 2. National Centre for Healthcare Research and Pharmacoepidemiology, University of Milano-Bicocca, Milan, Italy; Laboratory of Healthcare Research and Pharmacoepidemiology, Unit of Biostatistics, Epidemiology and Public Health, Department of Statistics and Quantitative Methods, University of Milano-Bicocca, Milan, Italy. 3. Lombardia Informatica S.p.a, Milan, Italy. 4. Regional Welfare Service, Lombardy Region, Milan, Italy. 5. Epidemiologic Observatory, Regional Welfare Service, Lombardy Region, Milan, Italy.
Abstract
OBJECTIVES: The aim of this study was to develop a new population-based risk stratification tool (Chronic Related Score [CReSc]) for predicting 5-year mortality and other outcomes. STUDY DESIGN AND SETTING: The score included 31 conditions selected from a list of 65 candidates whose weights were assigned according to the Cox model coefficients. The model was built from a sample of 5.4 million National Health Service (NHS) beneficiaries from the Italian Lombardy Region and applied to the remaining 2.7 million NHS beneficiaries. Predictive performance was assessed by discrimination and calibration. CReSc ability in predicting secondary endpoints (i.e., hospital admissions and health care costs) was investigated. Finally, the relationship between CReSc and income was considered. RESULTS: Among individuals aged 50-85 years, CReSc performance showed (1) an area under the receiver operating characteristic curve of 0.730, (2) an improved reclassification from 44% to 52% with respect to other scores, and (3) a remarkable calibration. A trend toward increasing rates of all the considered endpoints as CReSc increases was observed. Compared with individuals on low-intermediate income, NHS beneficiaries on high income showed better CReSc profile. CONCLUSION: We developed a risk stratification tool able to predict mortality, costs, and hospital admissions. The application of CReSc may generate clinically and operationally important effects.
OBJECTIVES: The aim of this study was to develop a new population-based risk stratification tool (Chronic Related Score [CReSc]) for predicting 5-year mortality and other outcomes. STUDY DESIGN AND SETTING: The score included 31 conditions selected from a list of 65 candidates whose weights were assigned according to the Cox model coefficients. The model was built from a sample of 5.4 million National Health Service (NHS) beneficiaries from the Italian Lombardy Region and applied to the remaining 2.7 million NHS beneficiaries. Predictive performance was assessed by discrimination and calibration. CReSc ability in predicting secondary endpoints (i.e., hospital admissions and health care costs) was investigated. Finally, the relationship between CReSc and income was considered. RESULTS: Among individuals aged 50-85 years, CReSc performance showed (1) an area under the receiver operating characteristic curve of 0.730, (2) an improved reclassification from 44% to 52% with respect to other scores, and (3) a remarkable calibration. A trend toward increasing rates of all the considered endpoints as CReSc increases was observed. Compared with individuals on low-intermediate income, NHS beneficiaries on high income showed better CReSc profile. CONCLUSION: We developed a risk stratification tool able to predict mortality, costs, and hospital admissions. The application of CReSc may generate clinically and operationally important effects.
Authors: Giuseppe Mancia; Federico Rea; Monica Ludergnani; Giovanni Apolone; Giovanni Corrao Journal: N Engl J Med Date: 2020-05-01 Impact factor: 91.245