A simple test-based frailty index to predict survival among cancer patients with an unplanned hospitalization: An observational cohort study

一种基于简易测试的衰弱指数预测非计划住院癌症患者的生存率:一项观察性队列研究

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Abstract

BACKGROUND: Frailty is a state of increased vulnerability to stressors, and predicts risk of adverse outcomes, such as mortality. Frailty can be defined by a frailty index (FI) using an accumulation of deficits approach. An FI comprised of 20 items derived from our previously studied test-based frailty index (TBFI) and an additional 33 survey-based elements sourced from the standard CGA was developed to evaluate if predictive validity of survival was improved. METHODS: One hundred eighty-nine cancer patients during acute hospitalization were consented between September 2018 and May 2019. Frailty scores were calculated, and patients were categorized into four groups: non-frail (0-0.2), mildly frail (0.2-0.3), moderately frail (0.3-0.4), and severely frail (>0.4). Patients were followed for 1-year to assess FI and TBFI prediction of survival. Area under the curve (AUC) statistics from ROC analyses were compared for the FI versus TBFI. RESULTS: Increasing frailty was similarly associated with increased risk of mortality (HR, 4.5 [95% CI, 2.519-8.075] and HR, 4.1 [95%CI, 1.692-9.942]) and the likelihood of death at 6 months was about 11-fold (odds ratio, 10.9 [95% CI, 3.97-33.24]) and 9.73-fold (95% CI, 2.85-38.50) higher for severely frail patients compared to non-frail patients for FI and TBFI, respectively. This association was independent of age and type of cancer. The FI and TBFI were predictive of survival for older and younger cancer patients with no significant differences between models in discriminating survival (FI AUC, 0.747 [95% CI, 0.6772-0.8157] and TBFI AUC, 0.724 [95% CI, 0.6513-0.7957]). CONCLUSIONS: The TBFI was predictive of survival, and the addition of an in-person assessment (FI) did not greatly improve predictive validity. Increasing frailty, as measured by a TBFI, resulted in a meaningfully increased risk of mortality and may be well-suited for screening of hospitalized cancer patients.

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