The average life-expectancy of end-stage renal disease patients starting maintenance dialysis in the US is about three years. Most clinical trials that tested a variety of potentially promising interventions have been unable to demonstrate a reduction in death risk of dialysis patients. The continued quest to improve outcomes has led to modifications of the conventional hemodialysis prescription to either significantly increase treatment time for each session or the frequency of therapy. The benefits on the co-primary composite of death risk or left ventricular mass increase seen in the recently concluded Frequent Hemodialysis Network (FHN) Daily Trial lends support to these modified prescriptions. However, the therapies being increasingly used in clinical practice differ from the interventions tested in the FHN trial. Nocturnal in-center hemodialysis (NICHD) provides longer treatment times but is generally delivered at a lower frequency (thrice weekly) than nocturnal home hemodialysis (5-6 times/ week) studied by FHN. Similarly, the most popular form of daily hemodialysis is performed at home with a device that is user-friendly but delivers lower solute clearances (short-daily, low-flow, home hemodialysis, SD-LF-HHD) than systems used in the FHN Daily Trial. NICHD or SD-LF-HHD patients cannot be identified in any publicly available data-source, including from the United States Renal Data System (USRDS) but this information is readily available in data from dialysis providers. In this project, we will obtain, refine, and ink data from DaVita, an organization that treats almost one-third of all US dialysis patients across 43 states, with the USRDS to examine outcomes of NICHD and SD-LF-HHD patients (n=2400, and 3500 respectively). The comparisons of these therapies with peritoneal dialysis and/or thrice-weekly conventional hemodialysis will be adequately powered for all-cause mortality, the primary outcome measure. The novel analytic strategy will use marginal structural models, a non-parametric causal model and will adjust for confounding from (1) baseline patient characteristics, (2) time-varying modality change, and (3) censoring for transplantation or drop-out. Confounding from site of care (TWICHD outcomes in facilities with/without NICHD programs) will be examined and to account for difficult-to-measure bias from patients who choose self-care home dialysis SD-LF-HHD outcomes will compared to PD, another home dialysis therapy. The high granularity of the linked data will allow us to study the association of NICHD and SD-LF-HHD with additional outcomes including cause-specific mortality, hospitalizations, solute clearances, hypertension, anemia, mineral metabolism, nutrition, dialysis tolerability, and vascular access morbidity. The DaVita-USRDS data linkage will provide access to Medicare claims data which will be used to calculate incremental societal cost-effectiveness or cost-savings with NICHD and SD-LF-HHD. Thus, this 3-year proposal will efficiently generate a wealth of time-sensitive information about two increasingly popular dialysis therapies that will be of immediate clinical and

Public Health Relevance

and inform decision making by physicians, patients, providers, and payers. The average life expectancy of patients with end-stage kidney disease starting maintenance dialysis in the United States is about three years and these patients spend 13 days in the hospital every year. Many more patients are being treated with hemodialysis therapy with either longer treatment times, or performed more frequently than thrice weekly. The overarching goal of this proposal is to determine whether these modifications to conventional hemodialysis treatments lead to improvements in life-expectancy, or reduction in hospitalizations for dialysis patients, and generate cost-savings for the healthcare system.

Agency
National Institute of Health (NIH)
Institute
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Type
Research Project (R01)
Project #
5R01DK095668-03
Application #
8713986
Study Section
Special Emphasis Panel (ZRG1-PSE-K (03))
Program Officer
Narva, Andrew
Project Start
2012-09-15
Project End
2015-07-31
Budget Start
2014-08-01
Budget End
2015-07-31
Support Year
3
Fiscal Year
2014
Total Cost
$338,675
Indirect Cost
$56,176
Name
University of Washington
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
605799469
City
Seattle
State
WA
Country
United States
Zip Code
98195
Chen, Joline L T; Mehrotra, Rajnish; Kalantar-Zadeh, Kamyar (2014) Surviving the first year of peritoneal dialysis: enduring hard times. Am J Kidney Dis 64:673-6
de Boer, Ian H; Mehrotra, Rajnish (2014) Insulin resistance in chronic kidney disease: a step closer to effective evaluation and treatment. Kidney Int 86:243-5
Mehrotra, Rajnish; Perazella, Mark A; Choi, Michael J (2014) American Society of Nephrology Quiz and Questionnaire 2013: RRT. Clin J Am Soc Nephrol 9:1497-503
Bieber, Scott D; Anderson, Arthur Eric; Mehrotra, Rajnish (2014) Diagnostic testing for peritonitis in patients undergoing peritoneal dialysis. Semin Dial 27:602-6
Bieber, Scott D; Burkart, John; Golper, Thomas A et al. (2014) Comparative outcomes between continuous ambulatory and automated peritoneal dialysis: a narrative review. Am J Kidney Dis 63:1027-37
Mehrotra, Rajnish (2013) Nutritional issues in peritoneal dialysis patients: how do they differ from that of patients undergoing hemodialysis? J Ren Nutr 23:237-40
Mehrotra, Rajnish; Glassock, Richard J; Bleyer, Anthony J (2013) American Society of Nephrology quiz and questionnaire 2012: renal replacement therapy. Clin J Am Soc Nephrol 8:1632-6
Mehrotra, Rajnish (2013) Translating an understanding of the determinants of technique failure to maximize patient time on peritoneal dialysis? Perit Dial Int 33:112-5
Mehrotra, Rajnish; Peralta, Carmen A; Chen, Shu-Cheng et al. (2013) No independent association of serum phosphorus with risk for death or progression to end-stage renal disease in a large screen for chronic kidney disease. Kidney Int 84:989-97
Hoshino, Junichi; Mehrotra, Rajnish; Rhee, Connie M et al. (2013) Using hemoglobin A1c to derive mean blood glucose in peritoneal dialysis patients. Am J Nephrol 37:413-20