Risk prediction to inform surveillance of chronic kidney disease in the US Healthcare Safety Net: a cohort study

Xie, Yuxiang; Maziarz, Marlena; Tuot, Delphine S.; Chertow, Glenn M.; Himmelfarb, Jonathan; Hall, Yoshio N.

doi:10.1186/s12882-016-0272-0

BMC Nephrology

Table 3 Comparative performance of the base predictive model* for end-stage renal disease by comorbid subgroup among 28,779 patients with moderate or severe chronic kidney disease from the healthcare safety net

From: Risk prediction to inform surveillance of chronic kidney disease in the US Healthcare Safety Net: a cohort study

	Measure	All	Hypertension	Diabetes mellitus	Chronic viral diseases	Severe CKD
Year 1	AUC	0.97 (0.01)	0.97 (0.01)	0.97 (0.02)	0.89 (0.03)	0.87 (0.02)
	PE	0.01 (0.00)	0.01 (0.00)	0.02 (0.00)	0.02 (0.00)	0.09 (0.02)
	PCF (0.1)	0.91 (0.03)	0.95 (0.04)	0.88 (0.05)	0.71 (0.06)	0.44 (0.04)
	PCF (0.2)	0.97 (0.02)	0.95 (0.03)	0.95 (0.04)	0.82 (0.05)	0.71 (0.04)
	PNF (0.8)	0.05 (0.02)	0.04 (0.03)	0.07 (0.03)	0.18 (0.07)	0.26 (0.05)
	PNF (0.9)	0.09 (0.05)	0.06 (0.05)	0.13 (0.06)	0.42 (0.12)	0.46 (0.07)
Year 3	AUC	0.94 (0.01)	0.94 (0.01)	0.94 (0.01)	0.91 (0.02)	0.87 (0.02)
	PE	0.02 (0.00)	0.02 (0.00)	0.04 (0.01)	0.04 (0.00)	0.14 (0.04)
	PCF (0.1)	0.83 (0.02)	0.82 (0.03)	0.68 (0.03)	0.71 (0.04)	0.34 (0.02)
	PCF (0.2)	0.91 (0.02)	0.92 (0.03)	0.89 (0.03)	0.83 (0.04)	0.57 (0.03)
	PNF (0.8)	0.08 (0.02)	0.09 (0.02)	0.14 (0.03)	0.17 (0.05)	0.39 (0.04)
	PNF (0.9)	0.17 (0.04)	0.17 (0.06)	0.23 (0.06)	0.26 (0.08)	0.47 (0.05)
Year 5	AUC	0.92 (0.01)	0.94 (0.01)	0.92 (0.01)	0.92 (0.02)	0.83 (0.02)
	PE	0.04 (0.00)	0.04 (0.01)	0.07 (0.01)	0.06 (0.01)	0.20 (0.06)
	PCF (0.1)	0.74 (0.02)	0.73 (0.03)	0.57 (0.03)	0.64 (0.04)	0.27 (0.02)
	PCF (0.2)	0.86 (0.02)	0.90 (0.02)	0.84 (0.02)	0.85 (0.04)	0.48 (0.03)
	PNF (0.8)	0.13 (0.02)	0.13 (0.02)	0.16 (0.03)	0.17 (0.04)	0.45 (0.04)
	PNF (0.9)	0.24 (0.04)	0.20 (0.05)	0.29 (0.05)	0.26 (0.08)	0.57 (0.04)
Year 7	AUC	0.90 (0.01)	0.90 (0.01)	0.88 (0.01)	0.88 (0.02)	0.80 (0.02)
	PE	0.09 (0.01)	0.10 (0.02)	0.15 (0.03)	0.12 (0.02)	0.27 (0.08)
	PCF (0.1)	0.64 (0.02)	0.64 (0.02)	0.47 (0.03)	0.53 (0.04)	0.23 (0.02)
	PCF (0.2)	0.81 (0.02)	0.83 (0.02)	0.75 (0.03)	0.75 (0.04)	0.42 (0.03)
	PNF (0.8)	0.19 (0.02)	0.18 (0.03)	0.27 (0.03)	0.24 (0.05)	0.47 (0.04)
	PNF (0.9)	0.31 (0.04)	0.28 (0.05)	0.38 (0.05)	0.39 (0.07)	0.60 (0.04)

Estimates (standard errors) of the measures of predictive performance of proportional hazards regression model adjusted for age, sex, race-ethnicity, eGFR, dipstick proteinuria and an interaction between eGFR and dipstick proteinuria. The model was fit to each of the ten imputed training sets and evaluated on each of the corresponding validation sets. The ten multiply imputed training sets were based on two-thirds of the dataset (randomly selected, stratified on eGFR), the ten multiply imputed validation sets were based on the remaining one-third of the study data for each subgroup (the imputations were performed separately on the training and validation sets)
Abbreviations: AUC area under the ROC curve (measure of discrimination); PE prediction error (measure of calibration); PCF(q) proportion of cases followed if proportion q of the population at highest risk is followed; PNF(p) proportion of the population at highest risk that needs to be followed to capture the proportion p of the cases

Back to article page

ISSN: 1471-2369

Contact us

Submission enquiries: bmcnephrology@biomedcentral.com
General enquiries: ORSupport@springernature.com