Systemic anticancer therapy in the last 30 days of life: Retrospective audit from an Australian Regional Cancer Centre. (April 2019)

• Record Type: Journal Article
• Authors: Gilbar, Peter J; McPherson, Ian; Aisthorpe, Genevieve G; Kondalsamy-Chennakes, Srinivas
• Is Part Of: Journal of oncology pharmacy practice. Volume 25:Number 3(2019)
• Page Start: 599
• Page End: 606
• Publication Date: 2019-04
• Subjects: Benchmark -- cancer patients -- chemotherapy -- death -- end of life; Cancer -- Chemotherapy -- Periodicals; Clinical pharmacology -- Periodicals; 616.994061
• DOI: 10.1177/1078155217752077
• Languages: English
• ISSNs: 1078-1552

Abstract

Background: Cessation of chemotherapy at an appropriate time is an important component of good quality palliative care. Published studies looking at administration of chemotherapy at the end of life vary widely. Objective: To retrospectively determine the rate of death occurring within 14 and 30 days of chemotherapy and use this to benchmark against other cancer centres as a quality of care measure. Method: All adult patients who received systemic anticancer therapy for solid tumours and haematological malignancies at an Australian Regional Cancer Centre between 2011 and 2015 were included. Results: Over a five-year period, 1215 patients received systemic anticancer therapy. Of these, 23 (1.89%) died within 14 days following systemic anticancer therapy and 68 (5.60%) within 30 days. All patients who died had been treated with palliative intent. Mean time to death was 17.7 days. The majority were female (61.8%) and the mean age was 62.3 years. The most common cause of death was disease progression (80.9%). Nearly half died at the Regional Cancer Centre, including 30.9% who lived in rural or remote localities. Conclusion: The rate of death observed in this study is at the lower end of the range seen in published studies for both the last 14 and 30 days post-systemic anticancer therapy. It is important to routinely collect data to enable benchmarking against other institutions, determine factors potentially associated with higher risks of mortality at the end of life and improve clinical decision making.