How to identify patients with cancer at risk of falling: a review of the evidence.
Affiliation
Department of Education & Research, Our Lady's Hospice and Care Services, Dublin, Ireland. cstone@olh.ieIssue Date
2011-02MeSH
Accidental FallsAdolescent
Adult
Aged
Aged, 80 and over
Humans
Middle Aged
Neoplasms
Risk Assessment
Young Adult
Metadata
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How to identify patients with cancer at risk of falling: a review of the evidence. 2011, 14 (2):221-30 J Palliat MedJournal
Journal of palliative medicineDOI
10.1089/jpm.2010.0326PubMed ID
21214370Abstract
Clinical experience and a limited number of studies suggest that a cancer diagnosis confers a high risk of accidental falls. The negative sequelae of falls in older persons are well documented; risk factors for falls in this population have been extensively investigated and evidence for the efficacy of interventions to reduce falls is steadily emerging. It is not known whether the risk factors for falls and effective interventions for falls risk reduction in patients with cancer are different from those in older persons.Electronic databases MEDLINE, Embase, and CINAHL were searched for studies of risk factors for falls or effective interventions for falls risk reduction in patients with cancer. Assessment of study quality was performed. Data analysis was descriptive.
Seven studies designed to identify the risk factors for falls in patients with cancer and one study to determine the predictive validity of a screening tool for falls in patients with cancer were included. All had methodological shortcomings, precluding the generation of a new synthesis from this review, but highlighting important design and statistical issues.
Further research is needed to identify patients at risk and inform the design of an interventional model to reduce falls risk. Investigators should be cognizant of the limitations of using cross-sectional study design to answer this research question, should employ validated tools to measure exposure variables, use reliable methods to ascertain the occurrence of falls and appropriate statistical models to adjust for confounding variables.
Item Type
ArticleLanguage
enISSN
1557-7740ae974a485f413a2113503eed53cd6c53
10.1089/jpm.2010.0326