BMJ open · 2020
Construction of the secondary care administrative records frailty (SCARF) index and validation on older women with operable invasive breast cancer in England and Wales: a cohort study.
СтатьяПоддержка исследования: вне правительства СШАВалидационное исследованиеНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Jauhari Yasmin, Gannon Melissa Ruth, Dodwell David, Horgan Kieran, Clements Karen, Medina Jibby, Tsang Carmen, Robinson Thompson, Tang Sarah Shuk-Kay, Pettengell Ruth, Cromwell David A
Аннотация
OBJECTIVES: Studies that use national datasets to evaluate the management of older women with breast cancer are often constrained by a lack of information on patient fitness. This study constructed a frailty index for use with secondary care administrative records and evaluated its ability to improve models of treatment patterns and overall survival in women with breast cancer.
DESIGN: Retrospective cohort study.
PARTICIPANTS: Women aged ≥50 years with oestrogen receptor (ER) positive early invasive breast cancer diagnosed between 2014 and 2017 in England.
METHODS: The secondary care administrative records frailty (SCARF) index was based on the cumulative deficit model of frailty, using International Statistical Classification of Diseases, Injuries and Causes of Death, 10th revision codes to define a set of deficits. The index was applied to administrative records that were linked to national cancer registry datasets. The ability of the SCARF index to improve the performance of regression models to explain observed variation in the rate of surgery and overall survival was evaluated using Harrell's c-statistic and decision curve analysis. External validation was performed on a dataset of similar women diagnosed in Wales.
RESULTS: The SCARF index captured 32 deficits that cover functional impairment, geriatric syndromes, problems with nutrition, cognition and mood, and medical comorbidities. In the English dataset (n=67 925), the prevalence of frailty in women aged 50-69, 70-79 and ≥80 years was 15%, 28% and 47%, respectively. Adding a frailty measure to regression models containing age, tumour characteristics and comorbidity improved their ability to: (1) discriminate between whether a woman was likely to have surgery and (2) predict overall survival. Similar results were obtained when the models were applied to the Welsh cohort (n=4 230).
CONCLUSION: The SCARF index provides a simple and consistent method to identify frailty in population level data and could help describe differences in breast cancer treatments and outcomes.
DESIGN: Retrospective cohort study.
PARTICIPANTS: Women aged ≥50 years with oestrogen receptor (ER) positive early invasive breast cancer diagnosed between 2014 and 2017 in England.
METHODS: The secondary care administrative records frailty (SCARF) index was based on the cumulative deficit model of frailty, using International Statistical Classification of Diseases, Injuries and Causes of Death, 10th revision codes to define a set of deficits. The index was applied to administrative records that were linked to national cancer registry datasets. The ability of the SCARF index to improve the performance of regression models to explain observed variation in the rate of surgery and overall survival was evaluated using Harrell's c-statistic and decision curve analysis. External validation was performed on a dataset of similar women diagnosed in Wales.
RESULTS: The SCARF index captured 32 deficits that cover functional impairment, geriatric syndromes, problems with nutrition, cognition and mood, and medical comorbidities. In the English dataset (n=67 925), the prevalence of frailty in women aged 50-69, 70-79 and ≥80 years was 15%, 28% and 47%, respectively. Adding a frailty measure to regression models containing age, tumour characteristics and comorbidity improved their ability to: (1) discriminate between whether a woman was likely to have surgery and (2) predict overall survival. Similar results were obtained when the models were applied to the Welsh cohort (n=4 230).
CONCLUSION: The SCARF index provides a simple and consistent method to identify frailty in population level data and could help describe differences in breast cancer treatments and outcomes.