Cancer-specific administrative dataebased comorbidity indices provided valid alternative to Charlson and National Cancer Institute Indices Diana Sarfati a, * , Jason Gurney a , James Stanley a , Clare Salmond b , Peter Crampton c , Elizabeth Dennett d , Jonathan Koea e , Neil Pearce f,g a Department of Public Health, School of Medicine and Health Sciences, University of Otago, PO Box 7343, Wellington South, Wellington 6022, New Zealand b Retired c Faculty of Health Sciences, University of Otago, PO Box 56, Dunedin 9054, New Zealand d Department of Surgery and Anaesthesia, School of Medicine and Health Sciences, University of Otago, PO Box 7343, Wellington South, Wellington 6022, New Zealand e Department of Surgery, North Shore Hospital, Waitemata District Health Board, Private Bag 93-503 Takapuna, Auckland 0740, New Zealand f Centre for Public Health Research, Massey University, PO Box 756, Wellington 6022, New Zealand g Department of Medical Statistics, London School of Hygiene and Tropical Medicine, Keppell Street, Bloomsbury, London WC1E7HT, UK Accepted 29 November 2013; Published online 25 February 2014 Abstract Objective: We aimed to develop and validate administrative dataebased comorbidity indices for a range of cancer types that included all relevant concomitant conditions. Study Design and Settings: Patients diagnosed with colorectal, breast, gynecological, upper gastrointestinal, or urological cancers identified from the National Cancer Registry between July 1, 2006 and June 30, 2008 for the development cohort (n 5 14,096) and July 1, 2008 to December 31, 2009 for the validation cohort (n 5 11,014) were identified. A total of 50 conditions were identified using hospital discharge data before cancer diagnosis. Five site-specific indices and a combined site index were developed, with conditions weighted ac- cording to their log hazard ratios from age- and stage-adjusted Cox regression models with noncancer death as the outcome. We compared the performance of these indices (the C3 indices) with the Charlson and National Cancer Institute (NCI) comorbidity indices. Results: The correlation between the Charlson and C3 index scores ranged between 0.61 and 0.78. The C3 index outperformed the Charlson and NCI indices for all sites combined, colorectal, and upper gastrointestinal cancer, performing similarly for urological, breast, and gynecological cancers. Conclusion: The C3 indices provide a valid alternative to measuring comorbidity in cancer populations, in some cases providing a modest improvement over other indices. Ó 2014 Elsevier Inc. All rights reserved. Keywords: Comorbidity; Multimorbidity; Cancer; Measurement; Validity; Indices 1. Introduction Patients diagnosed with cancer frequently have other chronic medical conditions. These concomitant conditions, or comorbidity, can affect how or when a patient is diag- nosed with cancer, the treatment options available or offered, and a patients’ ultimate prognosis [1e13]. At an individual level, a clinician can assess the presence and impact of comorbidity in a patient diagnosed with cancer. However, at the population level, assessing comorbidity is much more difficult. The severity of a patient’s comorbidity depends on the number, pattern, and severity of conditions present, and the likely impact may vary depending on the specific cancer diagnosed [4,11,14e17]. Despite these dif- ficulties, measuring comorbidity at the population level is important, as it provides researchers, policy makers, and health service planners with the necessary tools to allow them to stratify patients into groups according to risk in the same way they do for demographic and disease factors such as age and tumor stage [16,18]. There have been many attempts to measure comorbidity in cancer patient populations [4]. The most commonly cited approach is that of Charlson et al. [19]. These investigators identified all comorbid conditions from the medical records Funding sources: This work was funded by a grant from the Health Research Council of New Zealand (HRC 10/404). Conflicts of interest: None. * Corresponding author. Tel.: þ64-27-480-5660; fax: þ64 4 389 5319. E-mail address: diana.sarfati@otago.ac.nz (D. Sarfati). 0895-4356/$ - see front matter Ó 2014 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.jclinepi.2013.11.012 Journal of Clinical Epidemiology 67 (2014) 586e595