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Article Abstract

Purpose: Older cancer survivors (≥ 65 years at diagnosis) are at high-risk for multimorbidity (2 + comorbid conditions). However, few studies have utilized a generalizable sample of older cancer survivors to understand how individual comorbid conditions, as opposed to total comorbidity burden, are associated with health-related quality of life (HRQOL). We examined associations between HRQOL outcomes (pain, fatigue, physical function), individual comorbidities (cardiovascular disease [CVD], lung disease, diabetes, arthritis) and total comorbidity (cancer-only, cancer + 1 condition, cancer + 2 or more conditions).

Methods: Utilizing a population-based sample of 2019 older cancer survivors, we tested associations between comorbid conditions and the HRQOL outcomes using generalized linear models. HRQOL domains were assessed using Patient-Reported Outcome Measurement Information System (PROMIS) measures. Comorbidity was assessed via self-report.

Results: Cancer survivors with lung disease reported significantly worse physical functioning (β = - 4.96, p < 0.001), survivors with arthritis reported significantly higher pain (β = 4.37, p < 0.001), and survivors with CVD reported significantly higher fatigue (β = 3.45, p < 0.001) compared to survivors without each condition. Having cancer + 1 condition was not as strongly associated with all outcomes as when individual conditions were tested (e.g. pain: β = 3.09, p < 0.001). Having 2+ comorbidities had a stronger association with all outcomes (e.g. physical function: β = - 7.51, p < 0.001) than examining conditions individually.

Conclusions: Knowing the specific comorbid condition profile of an older cancer survivor provides insight into specific HRQOL outcomes that may be impaired in cancer survivorship, but understanding total comorbidity burden, regardless of the specific conditions, sheds light on survivors at-risk for multiple impairments in HRQOL. This information, taken together, can inform risk-stratified survivorship care.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7808400PMC
http://dx.doi.org/10.1007/s11136-020-02713-0DOI Listing

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