Variation in the use of palliative radiotherapy at end of life: Examining demographic, clinical, health service, and geographic factors in a population-based study

Abstract

Palliative radiotherapy (PRT) can improve quality of life for people dying of cancer. Variation in the delivery of PRT by factors unrelated to need may indicate that not all patients who may benefit from PRT receive it. In this study, 13,494 adults who died of cancer between 2000 and 2005 in Nova Scotia, Canada, were linked to radiotherapy records. Multivariate logistic regression was used to examine the relationships among demographic, clinical, service, and geographic variables, and PRT consultation and treatment. Among the decedents, 4188 (31.0%) received PRT consultation and 3032 (22.3%) treatment. PRT declined with increased travel time and community deprivation. Females, older persons, and nursing home residents also had lower PRT rates. Variations were observed by cancer site and previous oncology care. Variations in PRT use should be discussed with referring physicians, and improved means of access to PRT considered. Benchmarks for optimal rates of PRT are needed.

Radiation therapy at the end of life in patients with incurable nonsmall cell lung cancer

“…1 It is estimated that 159,000 patients died of lung cancer alone in Original Article 2009 6 and that a considerable share of these patients' health care expenses were incurred during the last months of life. [6][7][8][9] However, it is not clear whether more aggressive EOL care improves either the duration or the quality of life. For example, Temel et al observed that, for patients with newly diagnosed metastatic NSCLC, there were statistically significant survival and quality-of-life benefits among patients who used fewer health care services.…”

“…10 After accounting for confounding variables, we observed that younger patients were more likely to receive EOL RT, which concurs with previously reported American and Canadian data. 7,8,11,12 Although the reasons for this are not entirely clear, it is possible that younger patients and/or their providers pursue more aggressive treatment despite the finding that their survival rates are similar to the rates among older patients who receive more conservative treatment. 13 Previous studies that aimed to define the factors associated with palliative RT indicated that patients with metastatic disease who have lower socioeconomic status 3,7,11 and those who live in nursing homes or rural settings are less likely to be referred for RT and, thus, to receive less treatment.…”

“…13 Previous studies that aimed to define the factors associated with palliative RT indicated that patients with metastatic disease who have lower socioeconomic status 3,7,11 and those who live in nursing homes or rural settings are less likely to be referred for RT and, thus, to receive less treatment. 7,8,11 Unfortunately, the NCCN database does not currently capture information on patients' socioeconomic status or living situation, so we were not able to assess these factors as part of our analysis.…”

“…Third, we have limited this report to patients with NSCLC. It has been demonstrated that the rates of palliative RT differ widely, depending on the primary disease site 7,8,11 ; thus, if other cancers were investigated, there could be differing rates of EOL RT. Finally, our database did not collect detailed data on the palliative versus curative intent of therapy, making it difficult to determine whether treatment was clinically appropriate.…”

Use of Opioid Analgesics Among Older Persons With Colorectal Cancer in Two Health Districts With Palliative Care Programs

“…For example, the variable location of residence (urban and rural) was included in the final model, despite demonstrating a nonsignificant relationship with opioid use in the unadjusted models because differential access to care based on geographic location has been noted in the literature for persons nearing the end of life in NS. [28][29][30] Variables were entered into the multivariate models in hierarchical blocks, beginning with the sociodemographic variables. The final model included the following independent variables: sex, age, CRC diagnosis less than six months before death, cause of death, residence in a long-term care facility, enrollment in a PCP, number of days in hospital during the six months before death, and location of death.…”