Is there a rationale for rationing chronic dialysis? A hospital based cohort study of factors affecting survival and morbidity

Abstract

Objectives: To determine factors influencing survival and need for hospitalisation in patients needing dialysis, and to define the potential basis for rationing access to renal replacement therapy.

Design: Hospital based cohort study of all patients starting dialysis over a 4 year recruitment period (follow up 15-63 months). Groups were defined on the basis of age, comorbidity, functional status, and whether dialysis initiation was planned or unplanned.

Setting: Renal unit in a district general hospital, which acts as the main renal referral centre for four other such hospitals and serves a population of about 1.15 million people.

Subjects: 292 patients, mean age 61.3 years (18-92 years, SD 15.8), of whom 193 (66%) were male, and 59 (20%) were patients with diabetes. Dialysis initiation was planned in 163 (56%) patients and unplanned in 129 (44%).

Main outcome measures: Overall survival, 1 year survival, and hospitalisation rate.

Results: Factors affecting survival in the Cox's proportional hazard model were Karnofsky performance score at presentation (hazard ratio 0.979, 95% confidence interval 0.972 to 0. 986), comorbidity severity score (1.240, 1.131 to 1.340), age (1.036, 1.018 to 1.054), and myeloma (2.15, 1.140 to 4.042). The Karnofsky performance score used 3 months before presentation was significant (0.970, 0.956 to 0.981), as was unplanned presentation in this model (1.796, 1.233 to 2.617). Using these factors, a high risk group of 26 patients was defined, with 19.2% 1 year survival. Denying dialysis to this group would save 3.2% of the total cost of the chronic programme but would sacrifice five long term survivors. Less rigorous definition of the high risk group would save more money but lose more long term survivors.

Conclusions: Severity of comorbid conditions and functional capacity are more important than age in predicting survival and morbidity of patients on dialysis. Late referral for dialysis affects survival adversely. Denial of dialysis to patients in an extremely high risk group, defined by a new stratification based on logistic regression, would be of debatable benefit.

Figure 1

Study population comprising 292 patients from groups 1, 2, and 3

Figure 2

Kaplan-Meier survival curves. Each step represents one death, and each triangle denotes survivor at latest follow up. Numbers on top of lines are patients remaining in analysis at each time point. (a) Effect of age on survival. (b) Effect of comorbidity (using comorbidity severity score: mild-moderate comorbidity, 1-4; severe comorbidity, 5-8. (c) Survival in three groups defined by Karnofsky performance scale. (d) Difference in survival between planned and unplanned presentations for dialysis

Figure 3

(a) Difference in survival between patients with and without diabetes. (b) Survival in patients with malignancies

Figure 4

Risk stratification. Risk groups based on (a) logistic regression and (b) scheme by Wright, and Khan et al^{15 16}