Clinical Epidemiology (Oct 2014)

Utilizing national patient-register data to control for comorbidity in prognostic studies

  • Nilssen Y,
  • Str,
  • TE,
  • Wiik R,
  • Bakken IJ,
  • Yu XQ,
  • O’Connell DL,
  • Møller B

Journal volume & issue
Vol. 2014, no. default
pp. 395 – 404

Abstract

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Yngvar Nilssen,1 Trond-Eirik Strand,1 Robert Wiik,2 Inger Johanne Bakken,3 Xue Qin Yu,4,5 Dianne L O'Connell,4–7 Bjørn Møller1 1Department of Registration, Cancer Registry of Norway, Oslo, 2Norwegian Patient Register Department, Norwegian Directorate of Health, Trondheim, 3Norwegian Institute of Public Health, Oslo, Norway; 4Cancer Research Division, Cancer Council NSW, 5School of Public Health, University of Sydney, 6School of Public Health and Community Medicine, University of New South Wales, Sydney, 7School of Medicine and Public Health, University of Newcastle, Newcastle, NSW, Australia Objective: To construct an updated comorbidity index (Patient Register Index [PRI]) using national data collections from Norway and compare its predictive ability of 1-year mortality with the Charlson Comorbidity Index (CCI). Materials and methods: Data regarding over 1.11 million patients registered in the Norwegian Patient Register in 2010 and 2011 were used to construct the PRI. The PRI was evaluated by comparing its model fit and discrimination with the CCI. Results: Compared with the CCI, the PRI weights decreased for six, increased for four, and were unchanged for seven diseases. When the PRI was added to the model including age and sex, the age effects were reduced by up to 38% for patients older than 50 years. All measures of model fit improved for the PRI model. Conclusion: Adjustment for comorbidity is especially important for patients 50 years of age or older, and its effect on 1-year mortality is almost comparable to the age effect. The PRI is based on more recent data than the CCI, and is more representative of the general population due to its construction. Keywords: comorbidity, National Patient Register, Charlson Comorbidity Index, predictive ability, patient-register index, prognostic value