PLoS ONE (Jan 2015)

Importance of simultaneous evaluation of multiple risk factors for hemodialysis patients' mortality and development of a novel index: dialysis outcomes and practice patterns study.

  • Eiichiro Kanda,
  • Brian A Bieber,
  • Ronald L Pisoni,
  • Bruce M Robinson,
  • Douglas S Fuller

DOI
https://doi.org/10.1371/journal.pone.0128652
Journal volume & issue
Vol. 10, no. 6
p. e0128652

Abstract

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For hemodialysis (HD) patients, many risk factors for death are associated with each other intricately. However, they are often considered separately in clinical settings. We evaluated the maintenance HD patients' risk of death within one year from multiple risk factors simultaneously considering their interrelationships using a novel index (survival index, SI) for HD patients in the United States developed using data from the Dialysis Outcomes and Practice Patterns Study (DOPPS).We analyzed data from 3899 and 3765 patients to develop and validate SI, respectively. To predict death within one year, candidate models were developed using logistic regression models. The final model was determined by comparing the accuracy among the models for the prediction of deaths.The model included age; body mass index; serum creatinine, albumin, total cholesterol and phosphorus levels; history of cardiovascular diseases; and arteriovenous fistula use. SI showed a higher accuracy in predicting death (c-statistic, 0.739) than geriatric nutritional risk index (0.647) and serum albumin level (0.637). The probability of death predicted on the basis of SI matched the observed number of deaths. Cox proportional hazard models for time-dependent SI showed that patients with low SI had a higher risk of death than patients with high SI [reference, Group 4 (26.1≤SI)]; Group 1 (SI<12.7), adjusted hazard ratio, 7.97 (95% CI, 5.02, 12.65); Group 2 (12.7≤SI<19.0), 3.18 (95% CI, 1.96, 5.16); Group 3 (19.0≤SI<26.1), 2.20 (95% CI, 1.33, 3.66).Results of this study suggest that the simultaneous evaluation of multiple risk factors can more accurately assess patients' prognosis and identify patients at an increased risk of death than single factors.