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Comorbidity Prevalence Among Cancer Patients: a Population-based Cohort Study of Four Cancers

Overview
Journal BMC Cancer
Publisher Biomed Central
Specialty Oncology
Date 2020 Jan 29
PMID 31987032
Citations 89
Authors
Affiliations
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Abstract

Background: The presence of comorbidity affects the care of cancer patients, many of whom are living with multiple comorbidities. The prevalence of cancer comorbidity, beyond summary metrics, is not well known. This study aims to estimate the prevalence of comorbid conditions among cancer patients in England, and describe the association between cancer comorbidity and socio-economic position, using population-based electronic health records.

Methods: We linked England cancer registry records of patients diagnosed with cancer of the colon, rectum, lung or Hodgkin lymphoma between 2009 and 2013, with hospital admissions records. A comorbidity was any one of fourteen specific conditions, diagnosed during hospital admission up to 6 years prior to cancer diagnosis. We calculated the crude and age-sex adjusted prevalence of each condition, the frequency of multiple comorbidity combinations, and used logistic regression and multinomial logistic regression to estimate the adjusted odds of having each condition and the probability of having each condition as a single or one of multiple comorbidities, respectively, by cancer type.

Results: Comorbidity was most prevalent in patients with lung cancer and least prevalent in Hodgkin lymphoma patients. Up to two-thirds of patients within each of the four cancer patient cohorts we studied had at least one comorbidity, and around half of the comorbid patients had multiple comorbidities. Our study highlighted common comorbid conditions among the cancer patient cohorts. In all four cohorts, the odds of having a comorbidity and the probability of multiple comorbidity were consistently highest in the most deprived cancer patients.

Conclusions: Cancer healthcare guidelines may need to consider prominent comorbid conditions, particularly to benefit the prognosis of the most deprived patients who carry the greater burden of comorbidity. Insight into patterns of cancer comorbidity may inform further research into the influence of specific comorbidities on socio-economic inequalities in receipt of cancer treatment and in short-term mortality.

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References
1.
Sarfati D, Gurney J, Lim B, Bagheri N, Simpson A, Koea J . Identifying important comorbidity among cancer populations using administrative data: Prevalence and impact on survival. Asia Pac J Clin Oncol. 2013; 12(1):e47-56. DOI: 10.1111/ajco.12130. View

2.
Exarchakou A, Rachet B, Belot A, Maringe C, Coleman M . Impact of national cancer policies on cancer survival trends and socioeconomic inequalities in England, 1996-2013: population based study. BMJ. 2018; 360:k764. PMC: 5850596. DOI: 10.1136/bmj.k764. View

3.
Hu F, Manson J, Stampfer M, Colditz G, Liu S, Solomon C . Diet, lifestyle, and the risk of type 2 diabetes mellitus in women. N Engl J Med. 2001; 345(11):790-7. DOI: 10.1056/NEJMoa010492. View

4.
Quan H, Li B, Couris C, Fushimi K, Graham P, Hider P . Updating and validating the Charlson comorbidity index and score for risk adjustment in hospital discharge abstracts using data from 6 countries. Am J Epidemiol. 2011; 173(6):676-82. DOI: 10.1093/aje/kwq433. View

5.
Devereux G . ABC of chronic obstructive pulmonary disease. Definition, epidemiology, and risk factors. BMJ. 2006; 332(7550):1142-4. PMC: 1459603. DOI: 10.1136/bmj.332.7550.1142. View