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Cancer Res ; 83(7): 1147-1157, 2023 04 04.
Article in English | MEDLINE | ID: mdl-36779863

ABSTRACT

Comorbidities can have major implications for cancer care, as they might impact the timing of cancer diagnosis, compromise optimal care, affect treatment outcomes, and increase healthcare costs. Thus, it is important to comprehensively evaluate cancer comorbidities and examine trends over time. Here, we performed a systematic literature review on the prevalence and types of comorbidities for the five most common forms of cancer. Observational studies from Organisation for Economic Co-operation and Development countries published between 1990 and 2020 in English or Dutch that used routinely collected data from a representative population were included. The search yielded 3,070 articles, of which, 161 were eligible for data analyses. Multilevel analyses were performed to evaluate determinants of variation in comorbidity prevalence and trends over time. The weighted average comorbidity prevalence was 33.4%, and comorbidities were the most common in lung cancer (46.7%) and colorectal cancer (40.0%), followed by prostate cancer (28.5%), melanoma cancer (28.3%), and breast cancer (22.4%). The most common types of comorbidities were hypertension (29.7%), pulmonary diseases (15.9%), and diabetes (13.5%). After adjusting for gender, type of comorbidity index, age, data source (patient records vs. claims), and country, a significant increase in comorbidities of 0.54% per year was observed. Overall, a large and increasing proportion of the oncologic population is dealing with comorbidities, which could be used to inform and adapt treatment options to improve health outcomes and reduce healthcare costs. SIGNIFICANCE: Comorbidities are frequent and increasing in patients with cancer, emphasizing the importance of exploring optimal ways for uniform comorbidity registration and incorporating comorbidity management into cancer care.


Subject(s)
Lung Neoplasms , Male , Humans , Multilevel Analysis , Prevalence , Comorbidity , Lung Neoplasms/epidemiology , Regression Analysis
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