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https://doi.org/10.1001/jama.2019.17379
Title: | Development of Risk Prediction Equations for Incident Chronic Kidney Disease | Authors: | Nelson, Robert G Grams, Morgan E Ballew, Shoshana H Sang, Yingying Azizi, Fereidoun Chadban, Steven J Chaker, Layal Dunning, Stephan C Fox, Caroline Hirakawa, Yoshihisa Iseki, Kunitoshi Ix, Joachim Jafar, Tazeen H Koettgen, Anna Naimark, David MJ Ohkubo, Takayoshi Prescott, Gordon J Rebholz, Casey M Sabanayagam, Charumathi Sairenchi, Toshimi Schoettker, Ben Shibagaki, Yugo Tonelli, Marcello Zhang, Luxia Gansevoort, Ron T Matsushita, Kunihiro Woodward, Mark Coresh, Josef Shalev, Varda Chalmers, John Arima, Hisatomi Perkovic, Vlado Woodward, Mark Coresh, Josef Matsushita, Kunihiro Grams, Morgan Sang, Yingying Polkinghorne, Kevan Atkins, Robert Chadban, Steven Zhang, Luxia Liu, Lisheng Zhao, Ming-Hui Wang, Fang Wang, Jinwei Tonelli, Marcello Sacks, Frank M Curhan, Gary C Shlipak, Michael Sarnak, Mark J Katz, Ronit Hiramoto, Jade Iso, Hiroyasu Muraki, Isao Yamagishi, Kazumasa Umesawa, Mitsumasa Brenner, Hermann Schoettker, Ben Saum, Kai-Uwe Rothenbacher, Dietrich Fox, Caroline S Hwang, Shih-Jen Chang, Alex R Green, Jamie Singh, Gurmukteshwar Kirchner, H Lester Black, Corri Marks, Angharad Prescott, Gordon J Clark, Laura Fluck, Nick Cirillo, Massimo Hallan, Stein Ovrehus, Marius Langlo, Knut Asbjorn Romundstad, Solfrid Irie, Fujiko Sairenchi, Toshimi Correa, Adolfo Rebholz, Casey M Young, Bessie A Boulware, L Ebony Mwasongwe, Stanford Watanabe, Tsuyoshi Yamagata, Kunihiro Iseki, Kunitoshi Asahi, Koichi Chodick, Gabriel Shalev, Varda Shlipak, Michael Sarnak, Mark Katz, Ronit Peralta, Carmen Bottinger, Erwin Nadkarni, Girish N Ellis, Stephen B Nadukuru, Rajiv Kenealy, Timothy Elley, C Raina Collins, John F Drury, Paul L Ohkubo, Takayoshi Asayama, Kei Kikuya, Masahiro Metoki, Hirohito Nakayama, Masaaki Iseki, Kunitoshi Iseki, Chiho Nelson, Robert G Looker, Helen C Knowler, William C Gansevoort, Ron T Bakker, Stephan JL Heerspink, Hiddo JL Bernardo, Rancho Jassal, Simerjot K Bergstrom, Jaclyn Ix, Joachim H Barrett-Connor, Elizabeth Kovesdy, Csaba P Sumida, Keiichi Kalantar-Zadeh, Kamyar Sedaghat, Sanaz Chaker, Layal Ikram, M Arfan Hoorn, Ewout J Dehghan, Abbas Carrero, Juan J Evans, Marie Elinder, Carl-Gustaf Wettermark, Bjorn Wong, Tien Y Sabanayagam, Charumathi Cheng, Ching-Yu Sokor, Riswana Banu Binte Mohamed Abdul Wen, Chi-Pang Tsao, Chwen-Keng Tsai, Min-Kuang Chen, Chien-Hua Hosseinpanah, Farhad Hadaegh, Farzad Azizi, Fereidoun Mirbolouk, Mohammadhassan Solbu, Marit Dahl Eriksen, Bjorn Odvar Jenssen, Trond Geir Eggen, Anne Elise Lannfelt, Lars Larsson, Anders Arnlov, Johan Bilo, Henk JG Landman, Gijs WD van Hateren, Kornelis JJ Kleefstra, Nanne Dunning, Stephan C Stempniewicz, Nikita Cuddeback, John Ciemins, Elizabeth Coresh, Josef Grams, Morgan E Ballew, Shoshana H Matsushita, Kunihiro Woodward, Mark Gansevoort, Ron T Chang, Alex R Hallan, Stein Koettgen, Anna Kovesdy, Csaba P Levey, Andrew S Shalev, Varda Zhang, Luxia Ballew, Shoshana H Chen, Jingsha Coresh, Josef Grams, Morgan E Kwak, Lucia Matsushita, Kunihiro Sang, Yingying Surapeneni, Aditya Woodward, Mark |
Keywords: | Science & Technology Life Sciences & Biomedicine Medicine, General & Internal General & Internal Medicine RENAL-DISEASE MODEL CKD |
Issue Date: | 3-Dec-2019 | Publisher: | AMER MEDICAL ASSOC | Citation: | Nelson, Robert G, Grams, Morgan E, Ballew, Shoshana H, Sang, Yingying, Azizi, Fereidoun, Chadban, Steven J, Chaker, Layal, Dunning, Stephan C, Fox, Caroline, Hirakawa, Yoshihisa, Iseki, Kunitoshi, Ix, Joachim, Jafar, Tazeen H, Koettgen, Anna, Naimark, David MJ, Ohkubo, Takayoshi, Prescott, Gordon J, Rebholz, Casey M, Sabanayagam, Charumathi, Sairenchi, Toshimi, Schoettker, Ben, Shibagaki, Yugo, Tonelli, Marcello, Zhang, Luxia, Gansevoort, Ron T, Matsushita, Kunihiro, Woodward, Mark, Coresh, Josef, Shalev, Varda, Chalmers, John, Arima, Hisatomi, Perkovic, Vlado, Woodward, Mark, Coresh, Josef, Matsushita, Kunihiro, Grams, Morgan, Sang, Yingying, Polkinghorne, Kevan, Atkins, Robert, Chadban, Steven, Zhang, Luxia, Liu, Lisheng, Zhao, Ming-Hui, Wang, Fang, Wang, Jinwei, Tonelli, Marcello, Sacks, Frank M, Curhan, Gary C, Shlipak, Michael, Sarnak, Mark J, Katz, Ronit, Hiramoto, Jade, Iso, Hiroyasu, Muraki, Isao, Yamagishi, Kazumasa, Umesawa, Mitsumasa, Brenner, Hermann, Schoettker, Ben, Saum, Kai-Uwe, Rothenbacher, Dietrich, Fox, Caroline S, Hwang, Shih-Jen, Chang, Alex R, Green, Jamie, Singh, Gurmukteshwar, Kirchner, H Lester, Black, Corri, Marks, Angharad, Prescott, Gordon J, Clark, Laura, Fluck, Nick, Cirillo, Massimo, Hallan, Stein, Ovrehus, Marius, Langlo, Knut Asbjorn, Romundstad, Solfrid, Irie, Fujiko, Sairenchi, Toshimi, Correa, Adolfo, Rebholz, Casey M, Young, Bessie A, Boulware, L Ebony, Mwasongwe, Stanford, Watanabe, Tsuyoshi, Yamagata, Kunihiro, Iseki, Kunitoshi, Asahi, Koichi, Chodick, Gabriel, Shalev, Varda, Shlipak, Michael, Sarnak, Mark, Katz, Ronit, Peralta, Carmen, Bottinger, Erwin, Nadkarni, Girish N, Ellis, Stephen B, Nadukuru, Rajiv, Kenealy, Timothy, Elley, C Raina, Collins, John F, Drury, Paul L, Ohkubo, Takayoshi, Asayama, Kei, Kikuya, Masahiro, Metoki, Hirohito, Nakayama, Masaaki, Iseki, Kunitoshi, Iseki, Chiho, Nelson, Robert G, Looker, Helen C, Knowler, William C, Gansevoort, Ron T, Bakker, Stephan JL, Heerspink, Hiddo JL, Bernardo, Rancho, Jassal, Simerjot K, Bergstrom, Jaclyn, Ix, Joachim H, Barrett-Connor, Elizabeth, Kovesdy, Csaba P, Sumida, Keiichi, Kalantar-Zadeh, Kamyar, Sedaghat, Sanaz, Chaker, Layal, Ikram, M Arfan, Hoorn, Ewout J, Dehghan, Abbas, Carrero, Juan J, Evans, Marie, Elinder, Carl-Gustaf, Wettermark, Bjorn, Wong, Tien Y, Sabanayagam, Charumathi, Cheng, Ching-Yu, Sokor, Riswana Banu Binte Mohamed Abdul, Wen, Chi-Pang, Tsao, Chwen-Keng, Tsai, Min-Kuang, Chen, Chien-Hua, Hosseinpanah, Farhad, Hadaegh, Farzad, Azizi, Fereidoun, Mirbolouk, Mohammadhassan, Solbu, Marit Dahl, Eriksen, Bjorn Odvar, Jenssen, Trond Geir, Eggen, Anne Elise, Lannfelt, Lars, Larsson, Anders, Arnlov, Johan, Bilo, Henk JG, Landman, Gijs WD, van Hateren, Kornelis JJ, Kleefstra, Nanne, Dunning, Stephan C, Stempniewicz, Nikita, Cuddeback, John, Ciemins, Elizabeth, Coresh, Josef, Grams, Morgan E, Ballew, Shoshana H, Matsushita, Kunihiro, Woodward, Mark, Gansevoort, Ron T, Chang, Alex R, Hallan, Stein, Koettgen, Anna, Kovesdy, Csaba P, Levey, Andrew S, Shalev, Varda, Zhang, Luxia, Ballew, Shoshana H, Chen, Jingsha, Coresh, Josef, Grams, Morgan E, Kwak, Lucia, Matsushita, Kunihiro, Sang, Yingying, Surapeneni, Aditya, Woodward, Mark (2019-12-03). Development of Risk Prediction Equations for Incident Chronic Kidney Disease. JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION 322 (21) : 2104-2114. ScholarBank@NUS Repository. https://doi.org/10.1001/jama.2019.17379 | Abstract: | © 2019 American Medical Association. All rights reserved. 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 5222711 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 = 2253540). Exposures: Demographic and clinical factors. Main Outcomes and Measures: Incident eGFR of less than 60 mL/min/1.73 m2. Results: Among 4441084 participants without diabetes (mean age, 54 years, 38% women), 660856 incident cases (14.9%) of reduced eGFR occurred during a mean follow-up of 4.2 years. Of 781627 participants with diabetes (mean age, 62 years, 13% women), 313646 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 A1c, 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.. | Source Title: | JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION | URI: | https://scholarbank.nus.edu.sg/handle/10635/173174 | ISSN: | 00987484 15383598 |
DOI: | 10.1001/jama.2019.17379 |
Appears in Collections: | Staff Publications Elements |
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