Abstract
Background
Secondary hyperparathyroidism (SHPT) is associated with adverse outcomes in patients receiving maintenance dialysis. Parathyroidectomy is a treatment for SHPT; whether parathyroidectomy utilization varies geographically in the US is unknown.
Methods
A retrospective cohort analysis was undertaken to identify all patients aged 18 years or older who were receiving in-center hemodialysis between 2007 and 2009, were covered by Medicare Parts A and B, and had been receiving hemodialysis for at least 1 year. Parathyroidectomy was identified from inpatient claims using relevant International Classification of Diseases, Ninth Revision, Clinical Modification procedure codes. Patient characteristics and End-Stage Renal Disease Network (a proxy for geography) were ascertained. Adjusted odds ratios for parathyroidectomy were estimated from a logistic model.
Results
A total of 286,569 patients satisfied inclusion criteria, of whom 4435 (1.5%) underwent PTX. After adjustment for a variety of patient characteristics, there was a 2-fold difference in adjusted odds of parathyroidectomy between the most- and least-frequently performing regions. Adjusted odds ratios were more than 20% higher than average in four networks, and more than 20% lower in four networks.
Conclusions
Parathyroidectomy use varies substantially by geography in the US; the factors responsible should be further investigated.
Keywords: End-stage renal disease, Dialysis, Mineral metabolism, Parathyroidectomy, Secondary hyperparathyroidism
Background
Secondary hyperparathyroidism (SHPT) is associated with adverse outcomes in patients receiving maintenance dialysis [1, 2]. Anecdotally, physicians appear to have widely variable criteria regarding which patients they choose to refer for parathyroidectomy, at least in the US. Perhaps reflecting uncertainty over its role, rates of parathyroidectomy have changed substantially over time in recent decades [3]. While guidelines recommend parathyroidectomy in patients with severe SHPT [4], how it might be used most optimally is uncertain. Parathyroidectomy has been shown to be associated with improved outcomes in some studies [5, 6]; however, it has also been shown to be associated with mortality, protracted hypocalcemia, and over-suppression of parathyroid hormone (PTH) [7], and its results with regard to mineral metabolic control are often suboptimal [8]. Thus, understanding the differences between hemodialysis patients who do and do not undergo parathyroidectomy may be important. However, the effect of geographic variation, which is associated with a variety of outcomes and care differences in the dialysis population [9, 10] has not been examined in the context of parathyroidectomy. We therefore conducted a retrospective cohort study to examine whether parathyroidectomy use varies geographically in the United States.
Methods
Using the United States Renal Data System end-stage renal disease database, we identified patients aged 18 years or older who were receiving in-center hemodialysis between 2007 and 2009, were covered by Medicare Part A (inpatient, outpatient, skilled nursing facility, hospice, or home health agency) and Part B (physician/supplier) as primary payer, and had been receiving hemodialysis for at least 1 year. Parathyroidectomy was identified from inpatient claims using International Classification of Diseases, Ninth Revision, Clinical Modification procedure codes 06.81 (complete parathyroidectomy), 06.89 (partial parathyroidectomy and parathyroidectomy not otherwise specified), and 06.95 (parathyroid tissue reimplantation).
Patient characteristics, derived from the end-stage renal disease database Medical Evidence Report and Medicare claims, were assessed on the parathyroidectomy date and on January 1 for non-parathyroidectomy patients. Characteristics included age, sex, race, body mass index, cause of renal disease, dialysis duration, and common comorbid conditions, as have been used previously [11]. Our proxy for geography was US End-Stage Renal Disease Network (n = 18, Table 1), geographically based regions designed to facilitate care and monitor quality on a regional level. Adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for parathyroidectomy were estimated from a logistic model adjusting for the factors described above. The adjusted ORs for the renal networks were calculated using the whole nation as the reference. All statistical analyses were conducted using SAS software, Version 9.2, SAS Institute Inc., Cary, NC, USA.
Table 1.
End-stage renal disease networks and associate US states
| Network number | States and territories |
|---|---|
| 1 | Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, Vermont |
| 2 | New York |
| 3 | New Jersey, Puerto Rico, Virgin Islands |
| 4 | Delaware, Pennsylvania |
| 5 | District of Columbia, Maryland, Virginia, West Virginia |
| 6 | Georgia, North Carolina, South Carolina |
| 7 | Florida |
| 8 | Alabama, Mississippi, Tennessee |
| 9 | Indiana, Kentucky, Ohio |
| 10 | Illinois |
| 11 | Michigan, Minnesota, North Dakota, South Dakota, Wisconsin |
| 12 | Iowa, Kansas, Missouri, Nebraska |
| 13 | Arkansas, Louisiana, Oklahoma |
| 14 | Texas |
| 15 | Arizona, Colorado, Nevada, New Mexico, Utah, Wyoming |
| 16 | Alaska, Idaho, Montana, Oregon, Washington |
| 17 | American Samoa, Guam, Mariana Islands, Hawaii, Northern California |
| 18 | Southern California |
Results
We identified 286,569 patients who satisfied our inclusion criteria, of whom 4435 (1.5%) underwent parathyroidectomy (Table 2). Parathyroidectomy frequency was 2.3 fold greater, in unadjusted terms, for the least-frequently performing region (0.97% of patients, Network 18) compared with the most-frequently performing region (2.20% of patients, Network 6).
Table 2.
Characteristics of patients who did and did not undergo parathyroidectomy
| PTX | Non-PTX | |||
|---|---|---|---|---|
| n | % | n | % | |
| Total | 4435 | 100 | 282,134 | 100 |
| Age at PTX, years | ||||
| 19–44 | 1764 | 39.8 | 38,830 | 13.8 |
| 45–64 | 2154 | 48.6 | 110,788 | 39.3 |
| 65–74 | 410 | 9.2 | 69,550 | 24.7 |
| ≥ 75 | 107 | 2.4 | 62,966 | 22.3 |
| Race | ||||
| White | 1685 | 38.0 | 156,638 | 55.5 |
| Black | 2551 | 57.5 | 108,246 | 38.4 |
| Other | 199 | 4.5 | 17,250 | 6.1 |
| Sex | ||||
| Male | 2298 | 51.8 | 155,257 | 55.0 |
| Female | 2137 | 48.2 | 126,877 | 45.0 |
| ESRD primary cause | ||||
| Diabetes | 1013 | 22.8 | 128,202 | 45.4 |
| Hypertension | 1462 | 33.0 | 81,231 | 28.8 |
| Glomerulonephritis | 934 | 21.1 | 27,250 | 9.7 |
| Other/unknown/missing | 1026 | 23.1 | 45,451 | 16.1 |
| BMI, kg/m2 | ||||
| < 18 | 151 | 3.4 | 8074 | 2.9 |
| 18– < 25 | 1217 | 27.4 | 88,838 | 31.5 |
| 25– < 30 | 1026 | 23.1 | 78,938 | 28.0 |
| 30– < 35 | 772 | 17.4 | 49,310 | 17.5 |
| 35– < 40 | 517 | 11.7 | 25,987 | 9.2 |
| ≥ 40 | 536 | 12.1 | 23,383 | 8.3 |
| Missing | 216 | 4.9 | 7604 | 2.7 |
| Dialysis duration, years | ||||
| 1– < 3 | 538 | 12.1 | 151,778 | 53.8 |
| 3– < 5 | 970 | 21.9 | 58,341 | 20.7 |
| > 5 | 2927 | 66.0 | 72,015 | 25.5 |
| Comorbidities | ||||
| Diabetes | 1954 | 44.1 | 185,029 | 65.6 |
| ASHD | 1542 | 34.8 | 131,678 | 46.7 |
| CHF | 1973 | 44.5 | 144,792 | 51.3 |
| CVA/TIA | 522 | 11.8 | 57,532 | 20.4 |
| PVD | 1389 | 31.3 | 112,972 | 40.0 |
| Dysrhythmia | 1057 | 23.8 | 77,320 | 27.4 |
| Other cardiac disease | 1623 | 36.6 | 91,955 | 32.6 |
| Network | ||||
| 1 | 151 | 3.4 | 9407 | 3.3 |
| 2 | 192 | 4.3 | 16,808 | 6.0 |
| 3 | 156 | 3.5 | 11,887 | 4.2 |
| 4 | 118 | 2.7 | 11,689 | 4.1 |
| 5 | 260 | 5.9 | 17,080 | 6.1 |
| 6 | 667 | 15.0 | 29,663 | 10.5 |
| 7 | 253 | 5.7 | 16,076 | 5.7 |
| 8 | 364 | 8.2 | 17,060 | 6.1 |
| 9 | 293 | 6.6 | 21,152 | 7.5 |
| 10 | 154 | 3.5 | 11,977 | 4.3 |
| 11 | 252 | 5.7 | 18,814 | 6.7 |
| 12 | 199 | 4.5 | 11,188 | 4.0 |
| 13 | 254 | 5.7 | 12,073 | 4.3 |
| 14 | 487 | 11.0 | 27,892 | 9.9 |
| 15 | 182 | 4.1 | 12,016 | 4.3 |
| 16 | 139 | 3.1 | 7254 | 2.6 |
| 17 | 136 | 3.1 | 11,860 | 4.2 |
| 18 | 178 | 4.0 | 18,238 | 6.5 |
ASHD atherosclerotic heart disease, BMI body mass index, CHF congestive heart failure, CVA/TIA cerebrovascular accident/transient ischemic attack, ESRD end-stage renal disease, PTX parathyroidectomy, PVD peripheral vascular disease
Network was associated with substantial variability in likelihood of parathyroidectomy (Fig. 1). Even after adjustment for all characteristics in Table 2, adjusted ORs for parathyroidectomy varied from 0.67 (95% CIs 0.58–0.78) to 1.37 (1.17–1.60) between the least- and most-frequently performing regions. Adjusted ORs were more than 20% higher than the national level in four networks and more than 20% lower in four networks.
Fig. 1.
Odds ratios for factors associated with parathyroidectomy. ASHD, atherosclerotic heart disease; CHF, congestive heart failure; CVA, cerebrovascular accident; ESRD, end-stage renal disease; PVD, peripheral vascular disease
In addition, younger age (adjusted OR 1.95, 95% CI 1.83–2.08, vs. age 45–64 years), female sex (1.23, 1.16–1.30), black race (1.29, 1.21–1.37 vs. white), dialysis duration > 5 years (3.70, 3.27–4.05 vs. 1- < 3 years), and atherosclerotic heart disease (1.15, 1.07–1.23) were associated with parathyroidectomy (P < 0.001). Diabetes (0.82, 0.76–0.89) and history of stroke (0.82, 0.74–0.89) were inversely associated with parathyroidectomy.
Results for the multivariable model for factors associated with parathyroidectomy are shown in Table 3.
Table 3.
Multivariable model for factors associated with parathyroidectomy
| Factors | HR (95% CI) | P |
|---|---|---|
| Age at PTX, years | ||
| 19–44 | 1.95 (1.83–2.08) | <0.001 |
| 45–64 | 1 (Referent) | |
| 65–74 | 0.37 (0.34–0.42) | < 0.001 |
| ≥ 75 | 0.11 (0.09–0.13) | < 0.001 |
| Race | ||
| White | 1 (Referent) | |
| Black | 1.29 (1.21–1.37) | < 0.001 |
| Other | 0.89 (0.77–1.03) | 0.11 |
| Sex | ||
| Male | 0.82 (0.77–0.87) | < 0.001 |
| Female | 1 (Referent) | |
| ESRD primary cause | ||
| Diabetes | 0.58 (0.53–0.64) | < 0.001 |
| Hypertension | 1 (Referent) | |
| Glomerulonephritis | 1.11 (1.02–1.21) | 0.011 |
| Other/unknown/missing | 1.04 (0.96–1.13) | 0.30 |
| BMI, kg/m2 | ||
| < 18 | 0.96 (0.82–1.13) | 0.62 |
| 18– < 25 | 1 (Referent) | |
| 25– < 30 | 1.10 (1.02–1.20) | 0.016 |
| 30– < 35 | 1.32 (1.21–1.44) | < 0.001 |
| 35– < 40 | 1.48 (1.34–1.64) | < 0.001 |
| ≥ 40 | 1.53 (1.38–1.69) | < 0.001 |
| Missing | 1.08 (0.94–1.24) | 0.29 |
| Dialysis duration, years | ||
| 1– < 3 | 1 (Referent) | |
| 3– < 5 | 2.23 (2.02–2.47) | < 0.001 |
| ≥ 5 | 3.70 (3.37–4.05) | < 0.001 |
| Comorbid conditions | ||
| Diabetes | 0.82 (0.76–0.89) | < 0.001 |
| ASHD | 1.15 (1.07–1.23) | < 0.001 |
| CHF | 1.08 (1.01–1.15) | 0.019 |
| CVA/TIA | 0.82 (0.74–0.89) | < 0.001 |
| PVD | 0.97 (0.91–1.04) | 0.42 |
| Dysrhythmia | 1.08 (1.00–1.16) | 0.058 |
| Other cardiac disease | 1.37 (1.29–1.47) | < 0.001 |
| ESRD Network | ||
| 16 | 1.37 (1.17–1.60) | < 0.001 |
| 1 | 1.35 (1.17–1.57) | < 0.001 |
| 12 | 1.24 (1.09–1.40) | 0.001 |
| 13 | 1.24 (1.08–1.37) | 0.001 |
| 6 | 1.18 (1.09–1.28) | < 0.001 |
| 8 | 1.17 (1.06–1.29) | 0.002 |
| 15 | 1.14 (0.99–1.31) | 0.067 |
| 14 | 1.13 (1.03–1.23) | 0.008 |
| 11 | 1.03 (0.92–1.16) | 0.60 |
| 7 | 1.01 (0.90–1.13) | 0.91 |
| 3 | 0.97 (0.84–1.12) | 0.69 |
| 9 | 0.92 (0.83–1.02) | 0.12 |
| 5 | 0.88 (0.79–0.99) | 0.032 |
| 10 | 0.88 (0.76–1.01) | 0.070 |
| 17 | 0.80 (0.68–0.93) | 0.005 |
| 2 | 0.78 (0.68–0.88) | < 0.001 |
| 4 | 0.69 (0.59–0.82) | < 0.001 |
| 18 | 0.67 (0.58–0.78) | < 0.001 |
| Year | ||
| 2007 | 1 (Referent) | |
| 2008 | 0.89 (0.83–0.95) | 0.001 |
| 2009 | 0.83 (0.78–0.89) | < 0.001 |
ASHD atherosclerotic heart disease, BMI body mass index, CHF congestive heart failure, CI confidence interval, CVA/TIA cerebrovascular accident/transient ischemic attack, ESRD end-stage renal disease, HR hazard ratio, PTX parathyroidectomy, PVD peripheral vascular disease
Discussion
SHPT treatment presents a complex clinical challenge. Practice guidelines provide direction [4] but suffer from lack of randomized clinical trial data, resulting in uncertainty about the benefits and risks of parathyroidectomy. Understanding use of parathyroidectomy is important, given widely varying recent data demonstrating both clinical benefits [5, 6], as well as high rates of adverse events and suboptimal mineral metabolic outcomes [7, 8]. Our large retrospective analysis demonstrated substantial geographic variation in parathyroidectomy use. This difference was not driven solely by outliers at the extremes; AORs were 20% higher or lower than unity in eight Networks. This could reflect regional differences in many potential factors, including provider-related ones such as particular treatment approaches instilled during training, access to qualified parathyroid surgeons, or local “cultures” of treatment, all of which might play substantial roles in how care is differentially rendered [12].
Certain demographic factors, specifically younger age and black race, were also associated with likelihood of parathyroidectomy; this was not unexpected given that both of these factors have been previously reported to be associated with more severe SHPT [2, 13]. Dialysis duration was also associated with parathyroidectomy, possibly because the changes that characterize severe parathyroid gland dysregulation may take many years to develop [14]; alternatively, providers may be resorting to parathyroidectomy only after prolonged attempts at other interventions prove fruitless. The inverse associations between older age and history of stroke and parathyroidectomy may reflect poor surgical candidacy in the provider’s estimation.
Our study was limited by lack of patient-level data about degree of PTH control, SHPT therapies employed, or other SHPT markers such as serum calcium and phosphorus, which likely predict the parathyroidectomy decision. For example, use of cinacalcet, which has been shown to reduce rates of parathyroidectomy [15], might vary widely by region, although we have no a priori reason to posit this and it seems unlikely to account for a more than 2-fold variation in parathyroidectomy rates. Additionally, we lack information about geographic variation in renal transplant; fewer individuals in areas in which early transplant occurs more commonly might be at risk of developing severe SHPT and subsequently undergoing parathyroidectomy. Again, given the magnitude of variation between the most- and least-frequently parathyroidectomy performing regions, case mix alone is unlikely to fully account for it.
Conclusion
Even after adjustment of a variety of case-mix variables, use of parathyroidectomy varies substantially by geography in the US; the factors responsible should be further investigated. Given recent information about the potential risks associated with parathyroidectomy [7, 8], the factors responsible for shaping the decision to undertake it should also be the subject of future investigation.
Acknowledgments
The data reported here have been supplied by the United States Renal Data System. The interpretation and reporting of these data are the responsibility of the authors and in no way should be seen as an official policy or interpretation of the US Government. The authors thank Chronic Disease Research Group colleagues Delaney Berrini, BS, for manuscript preparation and figure design and Nan Booth, MSW, MPH, ELS, for manuscript editing.
Funding
This study was supported by a research contract from Amgen Inc., Thousand Oaks, California. The contract provides for the Minneapolis Medical Research Foundation authors to have final determination of manuscript content.
Availability of data and materials
Data were obtained from the United States Renal Data System (USRDS), which is publically available and free of charge from the USRDS Coordinating Center.
Authors’ contributions
Substantial contributions to conception and design, or acquisition of data, or analysis and interpretation of data: JBW, JL, PJD, AI, GAB, AJC; drafting the manuscript or revising it critically for important intellectual content: JBW, JL, PJD, AI, GAB, AJC; final approval of the version to be published: JBW, JL, PJD, AI, GAB, AJC; sufficient participation in the work to take public responsibility for appropriate portions of the content: JBW, JL, PJD, AI, GAB, AJC; agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved: JBW, JL, PJD, AI, GAB, AJC. All authors read and approved the final manuscript.
Competing interests
James B. Wetmore, Jiannong Liu, Areef Ishani, and Allan J. Collins are employed by the Chronic Disease Research Group, which receives research support from Amgen. Dr. Liu has provided consultation to Daiichi Sankyo. Dr. Dluzniewski is employed by Amgen and owns Amgen stock. Dr. Collins has provided consultation to Amgen, Relypsa, DaVita Clinical Research, NxStage, Keryx, and ZS Pharma. Geoffrey A. Block is employed by Denver Nephrologists, and has provided consultation to, and received research support from, Amgen.
Consent for publication
Not applicable.
Ethics approval and consent to participate
We applied to and received approval from the Human Subjects Research Committee of the Hennepin County Medical Center/Hennepin Healthcare System, Inc., Minneapolis, Minnesota.
Abbreviations
- CI
Confidence interval
- OR
Odds ratio
- PTH
Parathyroid hormone
- SHPT
Secondary hyperparathyroidism
Contributor Information
James B. Wetmore, Phone: (612) 873-6988, Email: James.Wetmore@hcmed.org
Jiannong Liu, Email: jliu@cdrg.org.
Paul J. Dluzniewski, Email: pdluznie@amgen.com
Areef Ishani, Email: isha0012@umn.edu.
Geoffrey A. Block, Email: gablock@dnresearch.org
Allan J. Collins, Email: acollins@cdrg.org
References
- 1.Tentori F, Blayney MJ, Albert JM, Gillespie BW, Kerr PG, Bommer J, et al. Mortality risk for dialysis patients with different levels of serum calcium, phosphorus, and PTH: the Dialysis Outcomes and Practice Patterns Study (DOPPS) Am J Kidney Dis. 2008;52:519–30. doi: 10.1053/j.ajkd.2008.03.020. [DOI] [PubMed] [Google Scholar]
- 2.Kalantar-Zadeh K, Miller JE, Kovesdy CP, Mehrotra R, Lukowsky LR, Streja E, et al. Impact of race on hyperparathyroidism, mineral disarrays, administered vitamin D mimetic, and survival in hemodialysis patients. J Bone Miner Res. 2010;25:2724–34. doi: 10.1002/jbmr.177. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Kim SM, Long J, Montez-Rath ME, Leonard MB, Norton JA, Chertow GM. Rates and Outcomes of Parathyroidectomy for Secondary Hyperparathyroidism in the United States. Clin J Am Soc Nephrol. 2016;11:1260–7. doi: 10.2215/CJN.10370915. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Kidney Disease: Improving Global Outcomes (KDIGO) CKD-MBD Work Group KDIGO clinical practice guideline for the diagnosis, evaluation, prevention, and treatment of Chronic Kidney Disease-Mineral and Bone Disorder (CKD-MBD) Kidney Int Suppl. 2009;76(Suppl 113):S1–130. doi: 10.1038/ki.2009.188. [DOI] [PubMed] [Google Scholar]
- 5.Goldenstein PT, Elias RM, Pires de Freitas do Carmo L, Coelho FO, Magalhaes LP, Antunes GL, et al. Parathyroidectomy improves survival in patients with severe hyperparathyroidism: a comparative study. PLoS One. 2013;8:e68870. doi: 10.1371/journal.pone.0068870. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Komaba H, Taniguchi M, Wada A, Iseki K, Tsubakihara Y, Fukagawa M. Parathyroidectomy and survival among Japanese hemodialysis patients with secondary hyperparathyroidism. Kidney Int. 2015;88:350–9. doi: 10.1038/ki.2015.72. [DOI] [PubMed] [Google Scholar]
- 7.Ishani A, Liu J, Wetmore JB, Lowe KA, Do T, Bradbury BD, et al. Clinical outcomes after parathyroidectomy in a nationwide cohort of patients on hemodialysis. Clin J Am Soc Nephrol. 2015;10:90–7. doi: 10.2215/CJN.03520414. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Wetmore JB, Liu J, Do TP, Lowe KA, Ishani A, Bradbury BD, et al. Changes in secondary hyperparathyroidism-related biochemical parameters and medication use following parathyroidectomy. Nephrol Dial Transplant. 2016;31:103–11. doi: 10.1093/ndt/gfv291. [DOI] [PubMed] [Google Scholar]
- 9.Erickson KF, Tan KB, Winkelmayer WC, Chertow GM, Bhattacharya J. Variation in nephrologist visits to patients on hemodialysis across dialysis facilities and geographic locations. Clin J Am Soc Nephrol. 2013;8:987–94. doi: 10.2215/CJN.10171012. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Sood MM, Manns B, Dart A, Hiebert B, Kappel J, Komenda P, et al. Variation in the level of eGFR at dialysis initiation across dialysis facilities and geographic regions. Clin J Am Soc Nephrol. 2014;9:1747–56. doi: 10.2215/CJN.12321213. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Liu J, Huang Z, Gilbertson DT, Foley RN, Collins AJ. An improved comorbidity index for outcome analyses among dialysis patients. Kidney Int. 2010;77:141–51. doi: 10.1038/ki.2009.413. [DOI] [PubMed] [Google Scholar]
- 12.Wennberg J, Gittelsohn A. Variations in medical care among small areas. Sci Am. 1982;246:120–34. doi: 10.1038/scientificamerican0482-120. [DOI] [PubMed] [Google Scholar]
- 13.Wolf M, Betancourt J, Chang Y, Shah A, Teng M, Tamez H, et al. Impact of activated vitamin D and race on survival among hemodialysis patients. J Am Soc Nephrol. 2008;19:1379–88. doi: 10.1681/ASN.2007091002. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Slatopolsky E, Brown A, Dusso A. Pathogenesis of secondary hyperparathyroidism. Kidney Int Suppl. 1999;73:S14–9. doi: 10.1046/j.1523-1755.1999.07304.x. [DOI] [PubMed] [Google Scholar]
- 15.EVOLVE Trial Investigators. Chertow GM, Block GA, Correa-Rotter R, Drueke TB, Floege J, et al. Effect of cinacalcet on cardiovascular disease in patients undergoing dialysis. N Engl J Med. 2012;367:2482–94. doi: 10.1056/NEJMoa1205624. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
Data were obtained from the United States Renal Data System (USRDS), which is publically available and free of charge from the USRDS Coordinating Center.