Comorbidity index in central cancer registries: The value of hospital discharge data

Daphne Y. Lichtensztajn, Brenda M. Giddings, Cyllene R. Morris, Arti Parikh-Patel, Kenneth W Kizer

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

Background: The presence of comorbid medical conditions can significantly affect a cancer patient’s treatment options, quality of life, and survival. However, these important data are often lacking from population-based cancer registries. Leveraging routine linkage to hospital discharge data, a comorbidity score was calculated for patients in the California Cancer Registry (CCR) database. Methods: California cancer cases diagnosed between 1991 and 2013 were linked to statewide hospital discharge data. A Deyo and Romano adapted Charlson Comorbidity Index was calculated for each case, and the association of comorbidity score with overall survival was assessed with Kaplan-Meier curves and Cox proportional hazards models. Using a subset of Medicare-enrolled CCR cases, the index was validated against a comorbidity score derived using Surveillance, Epidemiology, and End Results (SEER)-Medicare linked data. Results: A comorbidity score was calculated for 71% of CCR cases. The majority (60.2%) had no relevant comorbidities. Increasing comorbidity score was associated with poorer overall survival. In a multivariable model, high comorbidity conferred twice the risk of death compared to no comorbidity (hazard ratio 2.33, 95% CI: 2.32-2.34). In the subset of patients with a SEERMedicare-derived score, the sensitivity of the hospital discharge-based index for detecting any comorbidity was 76.5. The association between overall mortality and comorbidity score was stronger for the hospital discharge-based score than for the SEER-Medicare-derived index, and the predictive ability of the hospital discharge-based score, as measured by Harrell’s C index, was also slightly better for the hospital discharge-based score (C index 0.62 versus 0.59, P<0.001). Conclusions: Despite some limitations, using hospital discharge data to construct a comorbidity index for cancer registries is a feasible and valid method to enhance registry data, which can provide important clinically relevant information for population-based cancer outcomes research.

Original languageEnglish (US)
Pages (from-to)601-609
Number of pages9
JournalClinical Epidemiology
Volume9
DOIs
StatePublished - Nov 20 2017
Externally publishedYes

Fingerprint

Registries
Comorbidity
Neoplasms
Medicare
Survival
Epidemiology
Proportional Hazards Models
Population
Quality of Life
Outcome Assessment (Health Care)
Databases
Mortality

Keywords

  • Administrative health care data
  • Cancer registry
  • Data linkages
  • Hospital discharge data
  • Population-based
  • Survival
  • Validation

ASJC Scopus subject areas

  • Epidemiology

Cite this

Comorbidity index in central cancer registries : The value of hospital discharge data. / Lichtensztajn, Daphne Y.; Giddings, Brenda M.; Morris, Cyllene R.; Parikh-Patel, Arti; Kizer, Kenneth W.

In: Clinical Epidemiology, Vol. 9, 20.11.2017, p. 601-609.

Research output: Contribution to journalArticle

Lichtensztajn, Daphne Y. ; Giddings, Brenda M. ; Morris, Cyllene R. ; Parikh-Patel, Arti ; Kizer, Kenneth W. / Comorbidity index in central cancer registries : The value of hospital discharge data. In: Clinical Epidemiology. 2017 ; Vol. 9. pp. 601-609.
@article{fd18ad3c08464f2f857d81eeacc59b23,
title = "Comorbidity index in central cancer registries: The value of hospital discharge data",
abstract = "Background: The presence of comorbid medical conditions can significantly affect a cancer patient’s treatment options, quality of life, and survival. However, these important data are often lacking from population-based cancer registries. Leveraging routine linkage to hospital discharge data, a comorbidity score was calculated for patients in the California Cancer Registry (CCR) database. Methods: California cancer cases diagnosed between 1991 and 2013 were linked to statewide hospital discharge data. A Deyo and Romano adapted Charlson Comorbidity Index was calculated for each case, and the association of comorbidity score with overall survival was assessed with Kaplan-Meier curves and Cox proportional hazards models. Using a subset of Medicare-enrolled CCR cases, the index was validated against a comorbidity score derived using Surveillance, Epidemiology, and End Results (SEER)-Medicare linked data. Results: A comorbidity score was calculated for 71{\%} of CCR cases. The majority (60.2{\%}) had no relevant comorbidities. Increasing comorbidity score was associated with poorer overall survival. In a multivariable model, high comorbidity conferred twice the risk of death compared to no comorbidity (hazard ratio 2.33, 95{\%} CI: 2.32-2.34). In the subset of patients with a SEERMedicare-derived score, the sensitivity of the hospital discharge-based index for detecting any comorbidity was 76.5. The association between overall mortality and comorbidity score was stronger for the hospital discharge-based score than for the SEER-Medicare-derived index, and the predictive ability of the hospital discharge-based score, as measured by Harrell’s C index, was also slightly better for the hospital discharge-based score (C index 0.62 versus 0.59, P<0.001). Conclusions: Despite some limitations, using hospital discharge data to construct a comorbidity index for cancer registries is a feasible and valid method to enhance registry data, which can provide important clinically relevant information for population-based cancer outcomes research.",
keywords = "Administrative health care data, Cancer registry, Data linkages, Hospital discharge data, Population-based, Survival, Validation",
author = "Lichtensztajn, {Daphne Y.} and Giddings, {Brenda M.} and Morris, {Cyllene R.} and Arti Parikh-Patel and Kizer, {Kenneth W}",
year = "2017",
month = "11",
day = "20",
doi = "10.2147/CLEP.S146395",
language = "English (US)",
volume = "9",
pages = "601--609",
journal = "Clinical Epidemiology",
issn = "1179-1349",
publisher = "Dove Medical Press Ltd.",

}

TY - JOUR

T1 - Comorbidity index in central cancer registries

T2 - The value of hospital discharge data

AU - Lichtensztajn, Daphne Y.

AU - Giddings, Brenda M.

AU - Morris, Cyllene R.

AU - Parikh-Patel, Arti

AU - Kizer, Kenneth W

PY - 2017/11/20

Y1 - 2017/11/20

N2 - Background: The presence of comorbid medical conditions can significantly affect a cancer patient’s treatment options, quality of life, and survival. However, these important data are often lacking from population-based cancer registries. Leveraging routine linkage to hospital discharge data, a comorbidity score was calculated for patients in the California Cancer Registry (CCR) database. Methods: California cancer cases diagnosed between 1991 and 2013 were linked to statewide hospital discharge data. A Deyo and Romano adapted Charlson Comorbidity Index was calculated for each case, and the association of comorbidity score with overall survival was assessed with Kaplan-Meier curves and Cox proportional hazards models. Using a subset of Medicare-enrolled CCR cases, the index was validated against a comorbidity score derived using Surveillance, Epidemiology, and End Results (SEER)-Medicare linked data. Results: A comorbidity score was calculated for 71% of CCR cases. The majority (60.2%) had no relevant comorbidities. Increasing comorbidity score was associated with poorer overall survival. In a multivariable model, high comorbidity conferred twice the risk of death compared to no comorbidity (hazard ratio 2.33, 95% CI: 2.32-2.34). In the subset of patients with a SEERMedicare-derived score, the sensitivity of the hospital discharge-based index for detecting any comorbidity was 76.5. The association between overall mortality and comorbidity score was stronger for the hospital discharge-based score than for the SEER-Medicare-derived index, and the predictive ability of the hospital discharge-based score, as measured by Harrell’s C index, was also slightly better for the hospital discharge-based score (C index 0.62 versus 0.59, P<0.001). Conclusions: Despite some limitations, using hospital discharge data to construct a comorbidity index for cancer registries is a feasible and valid method to enhance registry data, which can provide important clinically relevant information for population-based cancer outcomes research.

AB - Background: The presence of comorbid medical conditions can significantly affect a cancer patient’s treatment options, quality of life, and survival. However, these important data are often lacking from population-based cancer registries. Leveraging routine linkage to hospital discharge data, a comorbidity score was calculated for patients in the California Cancer Registry (CCR) database. Methods: California cancer cases diagnosed between 1991 and 2013 were linked to statewide hospital discharge data. A Deyo and Romano adapted Charlson Comorbidity Index was calculated for each case, and the association of comorbidity score with overall survival was assessed with Kaplan-Meier curves and Cox proportional hazards models. Using a subset of Medicare-enrolled CCR cases, the index was validated against a comorbidity score derived using Surveillance, Epidemiology, and End Results (SEER)-Medicare linked data. Results: A comorbidity score was calculated for 71% of CCR cases. The majority (60.2%) had no relevant comorbidities. Increasing comorbidity score was associated with poorer overall survival. In a multivariable model, high comorbidity conferred twice the risk of death compared to no comorbidity (hazard ratio 2.33, 95% CI: 2.32-2.34). In the subset of patients with a SEERMedicare-derived score, the sensitivity of the hospital discharge-based index for detecting any comorbidity was 76.5. The association between overall mortality and comorbidity score was stronger for the hospital discharge-based score than for the SEER-Medicare-derived index, and the predictive ability of the hospital discharge-based score, as measured by Harrell’s C index, was also slightly better for the hospital discharge-based score (C index 0.62 versus 0.59, P<0.001). Conclusions: Despite some limitations, using hospital discharge data to construct a comorbidity index for cancer registries is a feasible and valid method to enhance registry data, which can provide important clinically relevant information for population-based cancer outcomes research.

KW - Administrative health care data

KW - Cancer registry

KW - Data linkages

KW - Hospital discharge data

KW - Population-based

KW - Survival

KW - Validation

UR - http://www.scopus.com/inward/record.url?scp=85036475045&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85036475045&partnerID=8YFLogxK

U2 - 10.2147/CLEP.S146395

DO - 10.2147/CLEP.S146395

M3 - Article

AN - SCOPUS:85036475045

VL - 9

SP - 601

EP - 609

JO - Clinical Epidemiology

JF - Clinical Epidemiology

SN - 1179-1349

ER -