Patrick Albertus1, Hal Morgenstern2, Bruce Robinson3, Rajiv Saran4. 1. Kidney Epidemiology and Cost Center, School of Public Health, University of Michigan, Ann Arbor, MI; Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI. 2. Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI; Department of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI; Department of Urology, Medical School, University of Michigan, Ann Arbor, MI; Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI. Electronic address: halm@umich.edu. 3. Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI; Arbor Research Collaborative for Health, Ann Arbor, MI; Department of Internal Medicine, Medical School, University of Michigan, Ann Arbor, MI. 4. Kidney Epidemiology and Cost Center, School of Public Health, University of Michigan, Ann Arbor, MI; Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI; Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI; Department of Internal Medicine, Medical School, University of Michigan, Ann Arbor, MI.
Abstract
BACKGROUND: Although incidence rates of end-stage renal disease (ESRD) in the United States are reported routinely by the US Renal Data System (USRDS), risks (probabilities) are not reported. Short- and long-term risk estimates need to be updated and expanded to minority populations, including Native Americans, Asian/Pacific Islanders, and Hispanics. STUDY DESIGN: Risk estimation from surveillance data in large populations using life-table methods. A competing-risks framework was applied by constructing a hypothetical cohort followed from birth to death. SETTING & PARTICIPANTS: Total US population. Incidence and mortality rates of ESRD were obtained from the USRDS; all-cause mortality rates were obtained from CDC WONDER. PREDICTORS: Age, sex, race/ethnicity, and year. OUTCOMES: 10-year to lifetime risks (cumulative incidence) of ESRD. RESULTS: Among males, lifetime risks of ESRD from birth using 2013 data were 3.1% (95% CI, 3.0%-3.1%) for non-Hispanic whites, 8.0% (95% CI, 7.9%-8.2%) for non-Hispanic blacks, 3.8% (95% CI, 3.4%-4.9%) for non-Hispanic Native Americans, 5.1% (95% CI, 4.8%-5.4%) for non-Hispanic Asians/Pacific Islanders, and 6.2% (95% CI, 6.1%-6.4%) for Hispanics. Among females, lifetime risks were 2.0% (95% CI, 2.0%-2.1%) for non-Hispanic whites, 6.8% (95% CI, 6.7%-6.9%) for non-Hispanic blacks, 3.6% (95% CI, 3.3%-4.2%) for non-Hispanic Native Americans, 3.8% (95% CI, 3.6%-4.0%) for non-Hispanic Asian/Pacific Islanders, and 4.3% (95% CI, 4.2%-4.5%) for Hispanics. Lifetime risk of ESRD from birth increased from 3.5% in 2000 to 4.0% in 2013 in males and decreased from 3.0% to 2.8% in females. LIMITATIONS: Standard life-time assumption of fixed age-specific rates over time and possible ESRD misclassification. To be useful in clinical practice, this application will require additional predictors (eg, comorbid conditions and chronic kidney disease stage). CONCLUSIONS: ESRD risk in the United States varies more than 2-fold among racial/ethnic groups for both sexes.
BACKGROUND: Although incidence rates of end-stage renal disease (ESRD) in the United States are reported routinely by the US Renal Data System (USRDS), risks (probabilities) are not reported. Short- and long-term risk estimates need to be updated and expanded to minority populations, including Native Americans, Asian/Pacific Islanders, and Hispanics. STUDY DESIGN: Risk estimation from surveillance data in large populations using life-table methods. A competing-risks framework was applied by constructing a hypothetical cohort followed from birth to death. SETTING & PARTICIPANTS: Total US population. Incidence and mortality rates of ESRD were obtained from the USRDS; all-cause mortality rates were obtained from CDC WONDER. PREDICTORS: Age, sex, race/ethnicity, and year. OUTCOMES: 10-year to lifetime risks (cumulative incidence) of ESRD. RESULTS: Among males, lifetime risks of ESRD from birth using 2013 data were 3.1% (95% CI, 3.0%-3.1%) for non-Hispanic whites, 8.0% (95% CI, 7.9%-8.2%) for non-Hispanic blacks, 3.8% (95% CI, 3.4%-4.9%) for non-Hispanic Native Americans, 5.1% (95% CI, 4.8%-5.4%) for non-Hispanic Asians/Pacific Islanders, and 6.2% (95% CI, 6.1%-6.4%) for Hispanics. Among females, lifetime risks were 2.0% (95% CI, 2.0%-2.1%) for non-Hispanic whites, 6.8% (95% CI, 6.7%-6.9%) for non-Hispanic blacks, 3.6% (95% CI, 3.3%-4.2%) for non-Hispanic Native Americans, 3.8% (95% CI, 3.6%-4.0%) for non-Hispanic Asian/Pacific Islanders, and 4.3% (95% CI, 4.2%-4.5%) for Hispanics. Lifetime risk of ESRD from birth increased from 3.5% in 2000 to 4.0% in 2013 in males and decreased from 3.0% to 2.8% in females. LIMITATIONS: Standard life-time assumption of fixed age-specific rates over time and possible ESRD misclassification. To be useful in clinical practice, this application will require additional predictors (eg, comorbid conditions and chronic kidney disease stage). CONCLUSIONS:ESRD risk in the United States varies more than 2-fold among racial/ethnic groups for both sexes.
Authors: Michelle E Tarver-Carr; Neil R Powe; Mark S Eberhardt; Thomas A LaVeist; Raynard S Kington; Josef Coresh; Frederick L Brancati Journal: J Am Soc Nephrol Date: 2002-09 Impact factor: 10.121
Authors: Marino A Bruce; Bettina M Beech; Mario Sims; Tony N Brown; Sharon B Wyatt; Herman A Taylor; David R Williams; Errol Crook Journal: J Investig Med Date: 2009-04 Impact factor: 2.895
Authors: Andy I Choi; Rudolph A Rodriguez; Peter Bacchetti; Daniel Bertenthal; German T Hernandez; Ann M O'Hare Journal: Am J Med Date: 2009-07 Impact factor: 4.965
Authors: Carl D Langefeld; Jasmin Divers; Nicholas M Pajewski; Amret T Hawfield; David M Reboussin; Diane E Bild; George A Kaysen; Paul L Kimmel; Dominic S Raj; Ana C Ricardo; Jackson T Wright; John R Sedor; Michael V Rocco; Barry I Freedman Journal: Kidney Int Date: 2014-07-16 Impact factor: 10.612
Authors: Ana C Ricardo; Wei Yang; Daohang Sha; Lawrence J Appel; Jing Chen; Marie Krousel-Wood; Anjella Manoharan; Susan Steigerwalt; Jackson Wright; Mahboob Rahman; Sylvia E Rosas; Milda Saunders; Kumar Sharma; Martha L Daviglus; James P Lash Journal: J Am Soc Nephrol Date: 2018-12-03 Impact factor: 10.121
Authors: Meera N Harhay; Ryan M McKenna; Suzanne M Boyle; Karthik Ranganna; Lissa Levin Mizrahi; Stephen Guy; Gregory E Malat; Gary Xiao; David J Reich; Michael O Harhay Journal: Clin J Am Soc Nephrol Date: 2018-06-21 Impact factor: 8.237
Authors: Nicholas A Kolaitis; Daniel R Calabrese; Patrick Ahearn; Aida Venado; Rebecca Florez; Huey-Ling Lei; Karolina Isaak; Erik Henricksen; Emily Martinez; Tiffany Chong; Rupal J Shah; Lorriana E Leard; Mary Ellen Kleinhenz; Jeffrey Golden; Teresa De Marco; John R Greenland; Jasleen Kukreja; Steven R Hays; Paul D Blanc; Jonathan P Singer Journal: Am J Health Syst Pharm Date: 2019-12-02 Impact factor: 2.637
Authors: Joi Lee; Chi Chu; David Guzman; Valy Fontil; Alexandra Velasquez; Neil R Powe; Delphine S Tuot Journal: Am J Nephrol Date: 2019-06-05 Impact factor: 3.754
Authors: Paul Muntner; Marwah Abdalla; Adolfo Correa; Michael Griswold; John E Hall; Daniel W Jones; George A Mensah; Mario Sims; Daichi Shimbo; Tanya M Spruill; Katherine L Tucker; Lawrence J Appel Journal: Hypertension Date: 2017-03-20 Impact factor: 10.190
Authors: Salman Ahmed; Cameron T Nutt; Nwamaka D Eneanya; Peter P Reese; Karthik Sivashanker; Michelle Morse; Thomas Sequist; Mallika L Mendu Journal: J Gen Intern Med Date: 2020-10-15 Impact factor: 5.128