Rebecca Miller1, Clifford Akateh2, Noelle Thompson3, Dmitry Tumin4,5, Don Hayes6,7, Sylvester M Black2, Joseph D Tobias4,8. 1. Department of Anesthesiology and Pain Medicine, Nationwide Children's Hospital, 700 Children's Drive, Columbus, OH, 43205, USA. Rebecca.Miller@nationwidechildrens.org. 2. Department of Surgery, The Ohio State University College of Medicine, Columbus, OH, USA. 3. Center for Innovation in Pediatric Practice, Nationwide Children's Hospital, Columbus, OH, USA. 4. Department of Anesthesiology and Pain Medicine, Nationwide Children's Hospital, 700 Children's Drive, Columbus, OH, 43205, USA. 5. Department of Pediatrics, The Ohio State University College of Medicine, Columbus, OH, USA. 6. Section of Pulmonary Medicine, Nationwide Children's Hospital, Columbus, OH, USA. 7. Department of Pulmonary and Critical Care, The Ohio State University College of Medicine, Columbus, OH, USA. 8. Department of Anesthesiology and Pain Medicine, The Ohio State University College of Medicine, Columbus, OH, USA.
Abstract
BACKGROUND: Existing risk adjustment models for solid organ transplantation omit socioeconomic status (SES). With limited data available on transplant candidates' SES, linkage of transplant outcomes data to geographic SES measures has been proposed. We investigate the utility of county SES for understanding differences in pediatric kidney transplantation (KTx) outcomes. METHODS: We identified patients < 18 years of age receiving first-time KTx using United Network for Organ Sharing registry data in two eras: 2006-2010 and 2011-2015, corresponding to periods of county SES data collection. In each era, counties were ranked by 1-year rates of survival with intact graft, and by county SES score. We used Spearman correlation (ρ) to evaluate the association between county rankings on SES and transplant outcomes in each era and consistency between these measures across eras. We also evaluated the utility of county SES for improving prediction of individual KTx outcomes. RESULTS: The analysis included 2972 children and 108 counties. County SES and transplant outcomes were not correlated in either 2006-2010 (ρ = 0.06; p = 0.525) or 2011-2015 (ρ = 0.162, p = 0.093). County SES rankings were strongly correlated between eras (ρ = 0.99, p < 0.001), whereas county rankings of transplant outcomes were not correlated between eras (ρ = 0.16, p = 0.097). Including county SES quintile in individual-level models of transplant outcomes did not improve model predictive utility. CONCLUSIONS: Pediatric kidney transplant outcomes are unstable from period to period at the county level and are not correlated with county-level SES. Appropriate adjustment for SES disparities in transplant outcomes could require further collection of detailed individual SES data.
BACKGROUND: Existing risk adjustment models for solid organ transplantation omit socioeconomic status (SES). With limited data available on transplant candidates' SES, linkage of transplant outcomes data to geographic SES measures has been proposed. We investigate the utility of county SES for understanding differences in pediatric kidney transplantation (KTx) outcomes. METHODS: We identified patients < 18 years of age receiving first-time KTx using United Network for Organ Sharing registry data in two eras: 2006-2010 and 2011-2015, corresponding to periods of county SES data collection. In each era, counties were ranked by 1-year rates of survival with intact graft, and by county SES score. We used Spearman correlation (ρ) to evaluate the association between county rankings on SES and transplant outcomes in each era and consistency between these measures across eras. We also evaluated the utility of county SES for improving prediction of individual KTx outcomes. RESULTS: The analysis included 2972 children and 108 counties. County SES and transplant outcomes were not correlated in either 2006-2010 (ρ = 0.06; p = 0.525) or 2011-2015 (ρ = 0.162, p = 0.093). County SES rankings were strongly correlated between eras (ρ = 0.99, p < 0.001), whereas county rankings of transplant outcomes were not correlated between eras (ρ = 0.16, p = 0.097). Including county SES quintile in individual-level models of transplant outcomes did not improve model predictive utility. CONCLUSIONS: Pediatric kidney transplant outcomes are unstable from period to period at the county level and are not correlated with county-level SES. Appropriate adjustment for SES disparities in transplant outcomes could require further collection of detailed individual SES data.
Entities:
Keywords:
Kidney transplant; Socioeconomic status; Transplant outcomes; UNOS; United Network for Organ Sharing
Authors: A M Epstein; J Z Ayanian; J H Keogh; S J Noonan; N Armistead; P D Cleary; J S Weissman; J A David-Kasdan; D Carlson; J Fuller; D Marsh; R M Conti Journal: N Engl J Med Date: 2000-11-23 Impact factor: 91.245
Authors: Frank L Ward; Patrick O'Kelly; Fionnuala Donohue; Coilin ÓhAiseadha; Trutz Haase; Jonathan Pratschke; Declan G deFreitas; Howard Johnson; Peter J Conlon; Conall M O'Seaghdha Journal: Nephrology (Carlton) Date: 2015-06 Impact factor: 2.506
Authors: R Cutler Quillin; Gregory C Wilson; Koffi Wima; Samuel F Hohmann; Jeffrey M Sutton; Joshua J Shaw; Ian M Paquette; E Steve Woodle; Daniel E Abbott; Shimul A Shah Journal: Clin Gastroenterol Hepatol Date: 2014-06-04 Impact factor: 11.382
Authors: T P Singh; D C Naftel; L Addonizio; W Mahle; M T Foushee; S Zangwill; E D Blume; J K Kirklin; R Singh; J K Johnston; R Chinnock Journal: Am J Transplant Date: 2010-09 Impact factor: 8.086
Authors: A Hart; J M Smith; M A Skeans; S K Gustafson; D E Stewart; W S Cherikh; J L Wainright; A Kucheryavaya; M Woodbury; J J Snyder; B L Kasiske; A K Israni Journal: Am J Transplant Date: 2017-01 Impact factor: 8.086
Authors: Robert L Barrack; Erin L Ruh; Jiajing Chen; Adolph V Lombardi; Keith R Berend; Javad Parvizi; Craig J Della Valle; William G Hamilton; Ryan M Nunley Journal: Clin Orthop Relat Res Date: 2014-01 Impact factor: 4.176
Authors: Rachel E Patzer; Sandra Amaral; Haimanot Wasse; Nataliya Volkova; David Kleinbaum; William M McClellan Journal: J Am Soc Nephrol Date: 2009-04-01 Impact factor: 10.121
Authors: Dmitry Tumin; Jessica Horan; Emily A Shrider; Sakima A Smith; Joseph D Tobias; Don Hayes; Randi E Foraker Journal: Am Heart J Date: 2017-06-03 Impact factor: 4.749
Authors: Clifford Akateh; Rebecca Miller; Eliza W Beal; Dmitry Tumin; Joseph D Tobias; Don Hayes; Sylvester M Black Journal: Dig Dis Sci Date: 2019-07-22 Impact factor: 3.199