Predicting early death among elderly dialysis patients: Development and validation of a risk score to assist shared decision making for dialysis initiation

Mae Thamer, James S. Kaufman, Yi Zhang, Qian Zhang, Dennis J. Cotter, Heejung Bang

Research output: Contribution to journalArticle

57 Citations (Scopus)

Abstract

Background A shared decision-making tool could help elderly patients with advanced chronic kidney disease decide about initiating dialysis therapy. Because mortality may be high in the first few months after initiating dialysis therapy, incorporating early mortality predictors in such a tool would be important for an informed decision. Our objective is to derive and validate a predictive risk score for early mortality after initiating dialysis therapy. Study Design Retrospective observational cohort, with development and validation cohorts. Setting & Participants US Renal Data System and claims data from the Centers for Medicare & Medicaid Services for 69,441 (aged ≥67 years) patients with end-stage renal disease with a previous 2-year Medicare history who initiated dialysis therapy from January 1, 2009, to December 31, 2010. Candidate Predictors Demographics, predialysis care, laboratory data, functional limitations, and medical history. Outcomes All-cause mortality in the first 3 and 6 months. Analytical Approach Predicted mortality by logistic regression. Results The simple risk score (total score, 0-9) included age (0-3 points), low albumin level, assistance with daily living, nursing home residence, cancer, heart failure, and hospitalization (1 point each), and showed area under the receiver operating characteristic curve (AUROC) = 0.69 in the validation sample. A comprehensive risk score with additional predictors was also developed (with AUROC = 0.72, high concordance between predicted vs observed risk). Mortality probabilities were estimated from these models, with the median score of 3 indicating 12% risk in 3 months and 20% in 6 months, and the highest scores (≥8) indicating 39% risk in 3 months and 55% in 6 months. Limitations Patients who did not choose dialysis therapy and did not have a 2-year Medicare history were excluded. Conclusions Routinely available information can be used by patients with chronic kidney disease, families, and their nephrologists to estimate the risk of early mortality after dialysis therapy initiation, which may facilitate informed decision making regarding treatment options.

Original languageEnglish (US)
Pages (from-to)1024-1032
Number of pages9
JournalAmerican Journal of Kidney Diseases
Volume66
Issue number6
DOIs
StatePublished - Dec 1 2015

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Dialysis
Decision Making
Mortality
Medicare
Chronic Renal Insufficiency
ROC Curve
Therapeutics
History
Medicaid
Nursing Homes
Information Systems
Chronic Kidney Failure
Albumins
Hospitalization
Heart Failure
Retrospective Studies
Logistic Models
Demography
Kidney
Neoplasms

Keywords

  • Choosing Wisely
  • chronic kidney failure
  • conservative care
  • dialysis initiation
  • End-stage renal disease (ESRD)
  • mortality
  • predictive model
  • quality of life
  • risk score
  • shared decision-making
  • treatment decisions

ASJC Scopus subject areas

  • Nephrology

Cite this

Predicting early death among elderly dialysis patients : Development and validation of a risk score to assist shared decision making for dialysis initiation. / Thamer, Mae; Kaufman, James S.; Zhang, Yi; Zhang, Qian; Cotter, Dennis J.; Bang, Heejung.

In: American Journal of Kidney Diseases, Vol. 66, No. 6, 01.12.2015, p. 1024-1032.

Research output: Contribution to journalArticle

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title = "Predicting early death among elderly dialysis patients: Development and validation of a risk score to assist shared decision making for dialysis initiation",
abstract = "Background A shared decision-making tool could help elderly patients with advanced chronic kidney disease decide about initiating dialysis therapy. Because mortality may be high in the first few months after initiating dialysis therapy, incorporating early mortality predictors in such a tool would be important for an informed decision. Our objective is to derive and validate a predictive risk score for early mortality after initiating dialysis therapy. Study Design Retrospective observational cohort, with development and validation cohorts. Setting & Participants US Renal Data System and claims data from the Centers for Medicare & Medicaid Services for 69,441 (aged ≥67 years) patients with end-stage renal disease with a previous 2-year Medicare history who initiated dialysis therapy from January 1, 2009, to December 31, 2010. Candidate Predictors Demographics, predialysis care, laboratory data, functional limitations, and medical history. Outcomes All-cause mortality in the first 3 and 6 months. Analytical Approach Predicted mortality by logistic regression. Results The simple risk score (total score, 0-9) included age (0-3 points), low albumin level, assistance with daily living, nursing home residence, cancer, heart failure, and hospitalization (1 point each), and showed area under the receiver operating characteristic curve (AUROC) = 0.69 in the validation sample. A comprehensive risk score with additional predictors was also developed (with AUROC = 0.72, high concordance between predicted vs observed risk). Mortality probabilities were estimated from these models, with the median score of 3 indicating 12{\%} risk in 3 months and 20{\%} in 6 months, and the highest scores (≥8) indicating 39{\%} risk in 3 months and 55{\%} in 6 months. Limitations Patients who did not choose dialysis therapy and did not have a 2-year Medicare history were excluded. Conclusions Routinely available information can be used by patients with chronic kidney disease, families, and their nephrologists to estimate the risk of early mortality after dialysis therapy initiation, which may facilitate informed decision making regarding treatment options.",
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T2 - Development and validation of a risk score to assist shared decision making for dialysis initiation

AU - Thamer, Mae

AU - Kaufman, James S.

AU - Zhang, Yi

AU - Zhang, Qian

AU - Cotter, Dennis J.

AU - Bang, Heejung

PY - 2015/12/1

Y1 - 2015/12/1

N2 - Background A shared decision-making tool could help elderly patients with advanced chronic kidney disease decide about initiating dialysis therapy. Because mortality may be high in the first few months after initiating dialysis therapy, incorporating early mortality predictors in such a tool would be important for an informed decision. Our objective is to derive and validate a predictive risk score for early mortality after initiating dialysis therapy. Study Design Retrospective observational cohort, with development and validation cohorts. Setting & Participants US Renal Data System and claims data from the Centers for Medicare & Medicaid Services for 69,441 (aged ≥67 years) patients with end-stage renal disease with a previous 2-year Medicare history who initiated dialysis therapy from January 1, 2009, to December 31, 2010. Candidate Predictors Demographics, predialysis care, laboratory data, functional limitations, and medical history. Outcomes All-cause mortality in the first 3 and 6 months. Analytical Approach Predicted mortality by logistic regression. Results The simple risk score (total score, 0-9) included age (0-3 points), low albumin level, assistance with daily living, nursing home residence, cancer, heart failure, and hospitalization (1 point each), and showed area under the receiver operating characteristic curve (AUROC) = 0.69 in the validation sample. A comprehensive risk score with additional predictors was also developed (with AUROC = 0.72, high concordance between predicted vs observed risk). Mortality probabilities were estimated from these models, with the median score of 3 indicating 12% risk in 3 months and 20% in 6 months, and the highest scores (≥8) indicating 39% risk in 3 months and 55% in 6 months. Limitations Patients who did not choose dialysis therapy and did not have a 2-year Medicare history were excluded. Conclusions Routinely available information can be used by patients with chronic kidney disease, families, and their nephrologists to estimate the risk of early mortality after dialysis therapy initiation, which may facilitate informed decision making regarding treatment options.

AB - Background A shared decision-making tool could help elderly patients with advanced chronic kidney disease decide about initiating dialysis therapy. Because mortality may be high in the first few months after initiating dialysis therapy, incorporating early mortality predictors in such a tool would be important for an informed decision. Our objective is to derive and validate a predictive risk score for early mortality after initiating dialysis therapy. Study Design Retrospective observational cohort, with development and validation cohorts. Setting & Participants US Renal Data System and claims data from the Centers for Medicare & Medicaid Services for 69,441 (aged ≥67 years) patients with end-stage renal disease with a previous 2-year Medicare history who initiated dialysis therapy from January 1, 2009, to December 31, 2010. Candidate Predictors Demographics, predialysis care, laboratory data, functional limitations, and medical history. Outcomes All-cause mortality in the first 3 and 6 months. Analytical Approach Predicted mortality by logistic regression. Results The simple risk score (total score, 0-9) included age (0-3 points), low albumin level, assistance with daily living, nursing home residence, cancer, heart failure, and hospitalization (1 point each), and showed area under the receiver operating characteristic curve (AUROC) = 0.69 in the validation sample. A comprehensive risk score with additional predictors was also developed (with AUROC = 0.72, high concordance between predicted vs observed risk). Mortality probabilities were estimated from these models, with the median score of 3 indicating 12% risk in 3 months and 20% in 6 months, and the highest scores (≥8) indicating 39% risk in 3 months and 55% in 6 months. Limitations Patients who did not choose dialysis therapy and did not have a 2-year Medicare history were excluded. Conclusions Routinely available information can be used by patients with chronic kidney disease, families, and their nephrologists to estimate the risk of early mortality after dialysis therapy initiation, which may facilitate informed decision making regarding treatment options.

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KW - predictive model

KW - quality of life

KW - risk score

KW - shared decision-making

KW - treatment decisions

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