| Title: |
Development of Risk Prediction Equations for Incident Chronic Kidney Disease |
| Authors: |
Nelson, RG; Grams, ME; Ballew, SH; Sang, Y; Azizi, F; Chadban, SJ; Chaker, L; Dunning, SC; Fox, C; Hirakawa, Y; Iseki, K; Ix, J; Jafar, TH; Köttgen, A; Naimark, DMJ; Ohkubo, T; Prescott, GJ; Rebholz, CM; Sabanayagam, C; Sairenchi, T; Schöttker, B; Shibagaki, Y; Tonelli, M; Zhang, L; Gansevoort, RT; Matsushita, K; Woodward, M; Coresh, J; Shalev, V; Woodward, Mark; Chalmers, John; Arnlov, Johan |
| Source: |
urn:ISSN:0098-7484 ; urn:ISSN:1538-3598 ; JAMA Journal of the American Medical Association, 322, 21, 2104-2114 |
| Publisher Information: |
American Medical Association (AMA) |
| Publication Year: |
2019 |
| Collection: |
UNSW Sydney (The University of New South Wales): UNSWorks |
| Subject Terms: |
4206 Public Health; 42 Health Sciences; Kidney Disease; Diabetes; Prevention; Clinical Research; Minority Health; Health Disparities; Health Disparities and Racial or Ethnic Minority Health Research; Renal and urogenital; 3 Good Health and Well Being; Aged; Female; Glomerular Filtration Rate; Humans; Male; Middle Aged; Models; Theoretical; Renal Insufficiency; Chronic; Risk Assessment; Risk Factors; CKD Prognosis Consortium; anzsrc-for: 4206 Public Health; anzsrc-for: 42 Health Sciences; anzsrc-for: 11 Medical and Health Sciences; anzsrc-for: 32 Biomedical and clinical sciences |
| Description: |
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 m 2 . 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 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 ... |
| Document Type: |
article in journal/newspaper |
| File Description: |
application/pdf |
| Language: |
unknown |
| Relation: |
https://hdl.handle.net/1959.4/unsworks_67132; https://doi.org/10.1001/jama.2019.17379 |
| DOI: |
10.1001/jama.2019.17379 |
| Availability: |
https://hdl.handle.net/1959.4/unsworks_67132; https://unsworks.unsw.edu.au/bitstreams/192db5ce-ca65-4cef-8c57-ff5a6a393805/download; https://doi.org/10.1001/jama.2019.17379 |
| Rights: |
open access ; https://purl.org/coar/access_right/c_abf2 ; CC-BY-NC-ND ; https://creativecommons.org/licenses/by-nc-nd/4.0/ ; free_to_read |
| Accession Number: |
edsbas.10FEFADD |
| Database: |
BASE |