Homelessness and risk of end-stage renal disease

Abstract

To identify homeless people with chronic kidney disease (CKD) who were at highest risk for end-stage renal disease (ESRD), we studied 982 homeless and 15,674 domiciled people with CKD receiving public health care. We developed four risk prediction models for the primary outcome of ESRD. Overall, 71 homeless and 888 domiciled people progressed to ESRD during follow-up (median: 6.6 years). Homeless people with CKD experienced significantly higher incidence rates of ESRD than poor but domiciled peers. Most homeless people who developed progressive CKD were readily identifiable well before ESRD using a prediction model with five common variables. We estimated that program following homeless people in the highest decile of ESRD risk would have captured 64-85% of those who eventually progressed to ESRD within five years. Thus, an approach targeting homeless people at high risk for ESRD appears feasible and could reduce substantial morbidity and costs incurred by this highly vulnerable group.

Figure 1

The estimated proportion of ESRD cases captured among the homeless (PCF) if a given proportion of the homeless subjects at highest predicted risk of ESRD (PNF) were to be followed. The predictions were based on model 2 (age, sex, ethnicity, eGFR, dipstick proteinuria, interaction of eGFR and dipstick proteinuria, and stratified by homeless status) and were made for one, three, and five- year time frames. To obtain the estimates, we generated 20 multiply imputed datasets. For each of those sets, we fit model 2 to all of the domiciled subjects and a randomly selected two- thirds of the homeless subjects in that dataset. We then predicted ESRD risk for the remaining third of the homeless subjects. The process was repeated for each of the 20 imputed datasets and three (mutually exclusive) splits of the homeless subjects per dataset. The black dots represent the estimated PCF for a given PNF in one of the 60 estimations. The blue line is a spline fit (with three degrees of freedom) and the 95% confidence intervals are shown in grey. The solid grey vertical line corresponds to PCF(0.1) = 0.96 (at one year), which means that an estimated 96% (n = 10/11) of all ESRD cases that were diagnosed within the one- year time frame were among the 10% of all subjects at highest risk as predicted by model 2. Similarly, the solid grey lines correspond to PCF(0.1) = 0.66 (n = 19/30) and 0.64 (n = 31/49) at three and five years, respectively. The dashed vertical grey lines correspond to PCF(0.1) = 1.00 (n = 11/11), 0.85 (n = 25/30) and 0.84 (n = 41/49) at one, three, and five years, respectively.