The new comorbidity index for predicting survival in elderly dialysis patients: a long-term population-based study

PLoS One. 2013 Aug 6;8(8):e68748. doi: 10.1371/journal.pone.0068748. Print 2013.

Abstract

Background: The worldwide elderly (≥ 65 years old) dialysis population has grown significantly. This population is expected to have more comorbid conditions and shorter life expectancies than the general elderly population. Predicting outcomes for this population is important for decision-making. Recently, a new comorbidity index (nCI) with good predictive value for patient outcomes was developed and validated in chronic dialysis patients regardless of age. Our study examined the nCI outcome predictability in elderly dialysis patients.

Methods and findings: For this population-based cohort study, we used Taiwan's National Health Insurance Research Database of enrolled elderly patients, who began maintenance dialysis between January 1999 and December 2005. A total of 21,043 incident dialysis patients were divided into 4 groups by nCI score (intervals ≤ 3, 4-6, 7-9, ≥ 10) and followed nearly for 10 years. All-cause mortality and life expectancy were analyzed. During the follow-up period, 11272 (53.55%) patients died. Kaplan-Meier curves showed significant group difference in survival (log-rank: P<0.001). After stratification by age, life expectancy was found to be significantly longer in groups with lower nCI scores.

Conclusion: The nCI, even without the age component, is a strong predictor of mortality in elderly dialysis patients. Because patients with lower nCI scores may predict better survival, more attention should paid to adequate dialysis rather than palliative care, especially in those without obvious functional impairments.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Aged, 80 and over
  • Comorbidity*
  • Dialysis / statistics & numerical data*
  • Female
  • Follow-Up Studies
  • Humans
  • Kaplan-Meier Estimate*
  • Life Expectancy
  • Male
  • Risk Factors
  • Time Factors

Grants and funding

The study was supported by grant CMFHR10016 from the Chi-Mei Medical Center and grant NHRI-NHIRD-99182 from the National Health Research Institutes in Taiwan. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.