國家衛生研究院 NHRI:Item 3990099045/12466
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    题名: Development of risk prediction equations for incident chronic kidney disease
    作者: Nelson, RG;Grams, ME;Ballew, SH;Sang, YY;Azizi, F;Chadban, SJ;Chaker, L;Dunning, SC;Fox, C;Hirakawa, Y;Iseki, K;Ix, J;Jafar, TH;Kottgen, A;Naimark, DMJ;Ohkubo, T;Prescott, GJ;Rebholz, CM;Sabanayagam, C;Sairenchi, T;Schottker, B;Shibagaki, Y;Tonelli, M;Zhang, LX;Gansevoort, RT;Matsushita, K;Woodward, M;Coresh, J;Shalev, V;Chalmers, J;Arima, H;Perkovic, V;Woodward, M;Coresh, J;Matsushita, K;Grams, M;Sang, YY;Polkinghorne, K;Atkins, R;Chadban, S;Zhang, LX;Liu, LS;Zhao, MH;Wang, F;Wang, JW;Tonelli, M;Sacks, FM;Curhan, GC;Shlipak, M;Sarnak, MJ;Katz, R;Hiramoto, J;Iso, H;Muraki, I;Yamagishi, K;Umesawa, M;Brenner, H;Schottker, B;Saum, KU;Rothenbacher, D;Fox, CS;Hwang, SJ;Chang, AR;Green, J;Singh, G;Kirchner, HL;Black, C;Marks, A;Prescott, GJ;Clark, L;Fluck, N;Cirillo, M;Hallan, S;Ovrehus, M;Langlo, KA;Romundstad, S;Irie, F;Sairenchi, T;Correa, A;Rebholz, CM;Young, BA;Boulware, LE;Mwasongwe, S;Watanabe, T;Yamagata, K;Iseki, K;Asahi, K;Chodick, G;Shalev, V;Shlipak, M;Sarnak, M;Katz, R;Peralta, C;Bottinger, E;Nadkarni, GN;Ellis, SB;Nadukuru, R;Kenealy, T;Elley, CR;Collins, JF, .;et al.
    贡献者: Institute of Population Health Sciences
    摘要: IMPORTANCE Early identification of individuals at elevated risk of developing chronic kidney disease (CKD) could improve clinical care through enhanced surveillance and better management of underlying health conditions. OBJECTIVE To develop assessment tools to identify individuals at increased risk of CKD, defined by reduced estimated glomerular filtration rate (eGFR). DESIGN, SETTING, AND PARTICIPANTS Individual-level data analysis of 34 multinational cohorts from the CKD Prognosis Consortium including 5 222 711 individuals from 28 countries. Data were collected from April 1970 through January 2017. A 2-stage analysis was performed, with each study first analyzed individually and summarized overall using a weighted average. Because clinical variables were often differentially available by diabetes status, models were developed separately for participants with diabetes and without diabetes. Discrimination and calibration were also tested in 9 external cohorts (n = 2 253 540). EXPOSURES Demographic and clinical factors. MAIN OUTCOMES AND MEASURES Incident eGFR of less than 60 mL/min/1.73 m(2). RESULTS Among 4 441 084 participants without diabetes (mean age, 54 years, 38% women), 660 856 incident cases (14.9%) of reduced eGFR occurred during a mean follow-up of 4.2 years. Of 781 627 participants with diabetes (mean age, 62 years, 13% women), 313 646 incident cases (40%) occurred during a mean follow-up of 3.9 years. Equations for the 5-year risk of reduced eGFR included age, sex, race/ethnicity, eGFR, history of cardiovascular disease, ever smoker, hypertension, body mass index, and albuminuria concentration. For participants with diabetes, the models also included diabetes medications, hemoglobin A(1c), and the interaction between the 2. The risk equations had a median C statistic for the 5-year predicted probability of 0.845 (interquartile range [IQR], 0.789-0.890) in the cohorts without diabetes and 0.801 (IQR, 0.750-0.819) in the cohorts with diabetes. Calibration analysis showed that 9 of 13 study populations (69%) had a slope of observed to predicted risk between 0.80 and 1.25. Discrimination was similar in 18 study populations in 9 external validation cohorts; calibration showed that 16 of 18 (89%) had a slope of observed to predicted risk between 0.80 and 1.25. CONCLUSIONS AND RELEVANCE Equations for predicting risk of incident chronic kidney disease developed from more than 5 million individuals from 34 multinational cohorts demonstrated high discrimination and variable calibration in diverse populations. Further study is needed to determine whether use of these equations to identify individuals at risk of developing chronic kidney disease will improve clinical care and patient outcomes.
    日期: 2019-12
    關聯: JAMA-Journal of the American Medical Association. 2019 Dec;322(21):2104-2114.
    Link to: http://dx.doi.org/10.1001/jama.2019.17379
    JIF/Ranking 2023: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=NHRI&SrcApp=NHRI_IR&KeyISSN=0098-7484&DestApp=IC2JCR
    Cited Times(WOS): https://www.webofscience.com/wos/woscc/full-record/WOS:000505207400031
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