Chronic condition clusters and functional impairment in older cancer survivors: a population-based study
- 421 Downloads
The purpose of the study is to identify chronic condition clusters at pre- and post-cancer diagnosis, evaluate predictors of developing clusters post-cancer, and examine the impact on functional impairment among older cancer survivors.
We identified 5991 survivors age 65 and older of prostate, breast, colorectal, lung, bladder, kidney, head and neck, and gynecologic cancer and non-Hodgkin lymphoma from the Surveillance, Epidemiology and End Results-Medicare Health Outcomes Survey resource. Survivors completed surveys pre- and post-cancer diagnosis on 13 chronic conditions and functional status. Among those with ≥2 conditions, exploratory factor analysis identified clusters of conditions. Differences in cluster frequency from pre- to post-cancer diagnosis were evaluated across the top five cancer types using chi-square tests. Modified Poisson regression models estimated the relative risk of developing clusters post-diagnosis. Chi-square tests evaluated associations between function and clusters.
Clusters included the following: cardiovascular disease cluster (pre 6.1 % and post 7.7 %), musculoskeletal cluster (28.2 % and 29.3 %), metabolic cluster (14.9 % and 17.6 %), and the major depressive disorder risk (MDDr) + gastrointestinal (GI) + pulmonary condition cluster (5.8 % and 8.7 %). Increases in MDDr + GI + Pulmonary cluster from pre- to post-cancer diagnosis were observed for prostate, lung, and colorectal cancer survivors. Functional impairment was more prevalent in survivors with defined clusters, especially in MDDr + GI + pulmonary, compared to survivors with ≥2 un-clustered conditions.
Distinct condition clusters of two or more chronic conditions are prevalent among older cancer survivors. Cluster prevalence increases from pre- to post-cancer diagnosis and these clusters have a significant impact on functional limitations.
Implications for Cancer Survivors
Tailored management on specific multimorbidity patterns will have implications for functional outcomes among older survivors.
KeywordsCancer survivor Comorbidity Function Geriatric
KMK was supported by grants T32HS013852 and K12HS023009 from the Agency for Healthcare Research and Quality. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Cancer Institute or AHRQ.
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflicts of interests.
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.
- 2.Thompson K, Dale W How do I best manage the care of older cancer patients with multimorbidity? J Geriatr Oncol 2015.Google Scholar
- 15.Institute of Medicine Delivering high-quality cancer care. Charting a new course for a system in crisis. Washington, DC: National Academies Press; 2013.Google Scholar
- 21.Kubinger K. On artificial results due to using factor analysis for dichotomous variables. Psychol Sci. 2003;45:106–10.Google Scholar
- 22.Fayers PM, Machin D Chapter 6: Factor analysis and structural equation modeling. In: Quality of Life: the assessment, analysis, and interpretation of patient-reported outcomes. Chichester; Hoboken, NJ: John Wiley & Sons, 2007, p. 131–160.Google Scholar
- 23.Muthen B, Muthen LK Mplus Version 7.1. 2012; 7.Google Scholar
- 25.van den Bussche H, Koller D, Kolonko T, Hansen H, Wegscheider K, Glaeske G, et al. Which chronic diseases and disease combinations are specific to multimorbidity in the elderly? Results of a claims data based cross-sectional study in Germany. BMC Public Health 2011; 11:101-2458-11-101.Google Scholar
- 30.Fried TR, Tinetti ME, Iannone L, Oâ€™Leary JR, Towle V, Van Ness PH HEalth outcome prioritization as a tool for decision making among older persons with multiple chronic conditions. Arch Intern Med 2011; 171:1856–1858.Google Scholar
- 31.Smith SM, Soubhi H, Fortin M, Hudon C, O’Dowd T. Interventions for improving outcomes in patients with multimorbidity in primary care and community settings. Cochrane Database Syst Rev. 2012;4, CD006560.Google Scholar
- 33.Watson LC, Amick HR, Gaynes BN, Brownley KA, Thaker S, Viswanathan M, et al. Practice-based interventions addressing concomitant depression and chronic medical conditions in the primary care setting: a systematic review and meta-analysis. J Prim Care Commun Health. 2013;4:294–306.CrossRefGoogle Scholar