Tanya M Wildes1, Ronald J Maggiore2, William P Tew3, David Smith4, Can-Lan Sun4, Harvey Cohen5, Supriya G Mohile2, Ajeet Gajra6, Heidi D Klepin7, Cynthia Owusu8, Cary P Gross9, Hyman Muss10, Andrew Chapman11, Stuart M Lichtman3, Vani Katheria4, Arti Hurria4. 1. Division of Medical Oncology, Washington University School of Medicine, 660 South Euclid Ave, Campus Box 8056, St Louis, MO, 63110, USA. twildes@dom.wustl.edu. 2. University of Rochester Medical Center, Rochester, NY, USA. 3. Memorial Sloan Kettering Cancer Center, New York, NY, USA. 4. City of Hope, Duarte, CA, USA. 5. Duke University, Raleigh, Durham, NC, USA. 6. Upstate University Hospital, Syracuse, NY, USA. 7. Wake Forest University, Wake Forest, NC, USA. 8. Case Western Reserve University School of Medicine, Cleveland, OH, USA. 9. Yale University, New Haven, CT, USA. 10. Lineberger Cancer Center, University of North Carolina, Chapel Hill, NC, USA. 11. Thomas Jefferson University, Philadelphia, PA, USA.
Abstract
BACKGROUND: Falls in older adults with cancer are common, yet factors associated with fall-risk are not well-defined and may differ from the general geriatric population. This study aims to develop and validate a model of factors associated with prior falls among older adults with cancer. METHODS: In this cross-sectional secondary analysis, two cohorts of patients aged ≥ 65 with cancer were examined to develop and validate a model of factors associated with falls in the prior 6 months. Potential independent variables, including demographic and laboratory data and a geriatric assessment (encompassing comorbidities, functional status, physical performance, medications, and psychosocial status), were identified. A multivariate model was developed in the derivation cohort using an exhaustive modeling approach. The model selected for validation offered a low Akaike Information Criteria value and included dichotomized variables for ease of clinical use. This model was then applied in the validation cohort. RESULTS: The development cohort (N = 498) had a mean age of 73 (range 65-91). Nearly one-fifth (18.2%) reported a fall in the prior 6 months. The selected model comprised nine variables involving functional status, objective physical performance, depression, medications, and renal function. The AUC of the model was 0.72 (95% confidence intervals 0.65-0.78). In the validation cohort (N = 250), the prevalence of prior falls was 23.6%. The AUC of the model in the validation cohort was 0.62 (95% confidence intervals 0.51-0.71). CONCLUSION: In this study, we developed and validated a model of factors associated with prior falls in older adults with cancer. Future study is needed to examine the utility of such a model in prospectively predicting incident falls.
BACKGROUND: Falls in older adults with cancer are common, yet factors associated with fall-risk are not well-defined and may differ from the general geriatric population. This study aims to develop and validate a model of factors associated with prior falls among older adults with cancer. METHODS: In this cross-sectional secondary analysis, two cohorts of patients aged ≥ 65 with cancer were examined to develop and validate a model of factors associated with falls in the prior 6 months. Potential independent variables, including demographic and laboratory data and a geriatric assessment (encompassing comorbidities, functional status, physical performance, medications, and psychosocial status), were identified. A multivariate model was developed in the derivation cohort using an exhaustive modeling approach. The model selected for validation offered a low Akaike Information Criteria value and included dichotomized variables for ease of clinical use. This model was then applied in the validation cohort. RESULTS: The development cohort (N = 498) had a mean age of 73 (range 65-91). Nearly one-fifth (18.2%) reported a fall in the prior 6 months. The selected model comprised nine variables involving functional status, objective physical performance, depression, medications, and renal function. The AUC of the model was 0.72 (95% confidence intervals 0.65-0.78). In the validation cohort (N = 250), the prevalence of prior falls was 23.6%. The AUC of the model in the validation cohort was 0.62 (95% confidence intervals 0.51-0.71). CONCLUSION: In this study, we developed and validated a model of factors associated with prior falls in older adults with cancer. Future study is needed to examine the utility of such a model in prospectively predicting incident falls.
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