医学
急诊分诊台
梅德林
老年肿瘤学
癌症
预测值
老年学
内科学
急诊医学
政治学
法学
作者
Marije E. Hamaker,J.M. Jonker,Sophia E. de Rooij,Alinda G. Vos,Carolien H. Smorenburg,Barbara C. Van Munster
出处
期刊:Lancet Oncology
[Elsevier]
日期:2012-10-01
卷期号:13 (10): e437-e444
被引量:576
标识
DOI:10.1016/s1470-2045(12)70259-0
摘要
Summary
Comprehensive geriatric assessment (CGA) is done to detect vulnerability in elderly patients with cancer so that treatment can be adjusted accordingly; however, this process is time-consuming and pre-screening is often used to identify fit patients who are able to receive standard treatment versus those in whom a full CGA should be done. We aimed to assess which of the frailty screening methods available show the best sensitivity and specificity for predicting the presence of impairments on CGA in elderly patients with cancer. We did a systematic search of Medline and Embase, and a hand-search of conference abstracts, for studies on the association between frailty screening outcome and results of CGA in elderly patients with cancer. Our search identified 4440 reports, of which 22 publications from 14 studies, were included in this Review. Seven different frailty screening methods were assessed. The median sensitivity and specificity of each screening method for predicting frailty on CGA were as follows: Vulnerable Elders Survey-13 (VES-13), 68% and 78%; Geriatric 8 (G8), 87% and 61%; Triage Risk Screening Tool (TRST 1+; patient considered frail if one or more impairments present), 92% and 47%, Groningen Frailty Index (GFI) 57% and 86%, Fried frailty criteria 31% and 91%, Barber 59% and 79%, and abbreviated CGA (aCGA) 51% and 97%. However, even in case of the highest sensitivity, the negative predictive value was only roughly 60%. G8 and TRST 1+ had the highest sensitivity for frailty, but both had poor specificity and negative predictive value. These findings suggest that, for now, it might be beneficial for all elderly patients with cancer to receive a complete geriatric assessment, since available frailty screening methods have insufficient discriminative power to select patients for further assessment.
科研通智能强力驱动
Strongly Powered by AbleSci AI