30‐day mortality following palliative radiotherapy. Issue 4 (27th June 2020)

• Record Type: Journal Article
• Authors: Kain, Mollie; Bennett, Hayley; Yi, Ma; Robinson, Bridget; James, Melissa
• Is Part Of: Journal of medical imaging and radiation oncology. Volume 64:Issue 4(2020:Aug.)
• Page Start: 570
• Page End: 579
• Publication Date: 2020-06-27
• Subjects: 30‐day mortality -- palliative radiotherapy -- TEACHH; Radiology, Medical -- Periodicals; Radiology, Medical -- Australasia -- Periodicals; 616.0757
• DOI: 10.1111/1754-9485.13073
• Languages: English
• ISSNs: 1754-9477

Abstract

Abstract: Introduction: Patients dying a short time after receiving palliative radiation are unlikely to have received benefit and may experience harm. To monitor the potential for avoidable harm, 30‐day mortality following palliative radiation has been recommended for use as a quality indicator and the Royal College of Radiologist have recommended a rate of lower than 20%. At the Canterbury Regional Cancer and Haematology Service in Christchurch, New Zealand (CRCHS), we investigated 30‐day mortality and evaluated the prognostic value of the TEACHH model in our population. Methods: Palliative treatments from two, two‐year periods (2012/2013 and 2016/2017) were retrospectively reviewed. We analysed 30‐day mortality and several influencing variables. Patients were divided into three groups using the TEACHH model (type of cancer, performance status, age, prior palliative chemotherapy, prior hospitalizations and hepatic metastases). Results: There were 1744 patients; 30‐day mortality was 10% and was higher in patients with lung cancer (17% vs. 8% in non–lung cancer patients, P < 0.0001), patients having less than five fractions (13% vs. 9%, P : 0.0199) and patients in TEACHH group B/C (21% in C, 11% in B and 2% in group A, P < 0.0001). The majority of treatments (84%) used five fractions or less. Conclusions: The mortality rate is within the suggested quality indicator, and the decreasing mortality with increasing fractionation demonstrates suitable selection of patients for longer treatment regimens. The TEACHH model can be used to increase precision in estimating prognosis, identifying patients who should not receive treatment and conversely identifying those for whom a prolonged fractionation schedule may be appropriate.