Understanding survivors' needs and outcomes: the role of routinely collected data. Issue 3 (September 2018)

• Record Type: Journal Article
• Authors: Lu, Liya; Deane, Jennifer; Sharp, Linda
• Is Part Of: Current opinion in supportive and palliative care. Volume 12:Issue 3(2018:Sep.)
• Publication Date: 2018-09
• Subjects: cancer survivors -- outcomes -- quality of life -- routinely collected data -- unmet needs; Palliative treatment -- Periodicals; Pain -- Periodicals; Palliative Care -- Periodicals; Pain Management -- Periodicals; 616.02905
• DOI: 10.1097/SPC.0000000000000352
• Languages: English
• ISSNs: 1751-4266

Abstract

Abstract : Purpose of review: The number of cancer survivors is growing due to population ageing, earlier detection and more effective therapies. Routinely collected data (RCD), generally cancer registry data, has been used to investigate survivors' needs and outcomes. We reviewed uses of RCD since 2017, identifying novel findings and research directions. Recent findings: Survival is improving internationally but continues to vary between subgroups. Longitudinal survivor surveys suggest malignancy-specific temporal patterns in unmet needs and health-related quality-of-life (HRQoL). Unmet needs are a risk factor for future depression and depression predicts poorer HRQoL in all domains. Emerging evidence suggests links between posttraumatic stress and poor HRQoL and posttraumatic growth and improved HRQoL. Evidence for a link between cancer-related financial hardship and poor HRQoL is accumulating. Surveys and linkage studies continue to show poorer work outcomes in survivors. Among survivors of childhood and young adult cancers, large linkage studies demonstrate significant risk of late effects, including hospitalization, pregnancy and labour complications, and cardiac death. Summary: RCD plays a significant role in understanding survivors' needs and outcomes. New approaches which overlay different types of data – including detailed clinical and treatment data, biomarker data and nonhealth administrative data – have the potential to generate considerable new knowledge.