The effect of age on specialized palliative care use in the last year of life for patients who die of cancer: A nationwide study from Norway

Abstract

IntroductionSpecialized palliative care (SPC) is beneficial towards end of life because of its holistic approach to improve quality of life and comfort of patients and their families. Few studies have described how patient age, sex, comorbidities, and socioeconomic status (SES) are associated with SPC use in nonselective populations who die of cancer. This study aimed to evaluate the use of SPC in the year preceding death by all Norwegian individuals with a recent cancer diagnosis who died of cancer. Materials and MethodsFrom nationwide registries, we identified patients with a recent (<5 years) cancer diagnosis who died during 2010–2014. Using binary logistic regression models, we estimated the probability of receiving hospital-based SPC during the last year of life according to individual (age, sex, comorbidity), cancer (stage, type, and months since diagnosis), and SES (e.g., living alone, household income, and education) characteristics. ResultsThe analytical sample contained 45,521 patients with a median age at death of 75 years; 46% were women. The probability of receiving hospital-based SPC in the total cohort was 0.43 (95% confidence interval [CI] 0.42–0.43). Use of SPC was higher if patients were younger, female, had limited comorbidity, metastatic disease, had one the following cancer types: colorectal, pancreatic, bladder, kidney, or gastric, were diagnosed more than six months before death, and had higher SES. Adjusted model results suggested that the probability of using SPC in the last year of life for patients aged 80–89 years was 0.31 (95% CI 0.30–0.32), compared to a probability of 0.63 (95% CI 0.61–0.65) for patients aged 50–59 years. For patients ≥90 years, the probability was 0.16 (95% CI 0.15–0.18). DiscussionLess hospital-based SPC use among older patients, males, and those with lower SES indicates possible under-treatment in these groups. Future studies should be designed to determine the underlying reasons for these observed differences.