At present, there is no clear definition of what constitutes an abnormal geriatric assessment (GA) in geriatric oncology. Various threshold numbers of abnormal GA domains are often used, but how well these are associated with treatment plan modification (TPM) and whether specific GA domains are more important in this context remains uncertain. A retrospective review of the geriatric oncology clinic database at Princess Margaret Cancer Centre in Toronto, Canada, including new patients seen for treatment decision making from May 2015 to June 2022, was conducted. Logistic regression modelling was performed to determine the association between various predictor variables (including the GA domains and numerical thresholds) and TPM. The study cohort (n = 736) had a mean age of 80.7 years, 46.1% was female, and 78.3% had a VES-13 score indicating vulnerability (≥3). In the univariable analysis, the best-performing threshold number of abnormal domains based on area under the curve (AUC) was 4 (AUC 0.628). The best-performing multivariable model (AUC 0.704) included cognition, comorbidities, and falls risk. In comparison, the multivariable model with the sole addition of the threshold of 4 had an AUC of 0.689. Overall, an abnormal GA may be best defined as one with abnormalities in the domains of cognition, comorbidities, and falls risk. The optimal numerical threshold to predict TPM is 4.
目前，老年肿瘤学中对于老年综合评估（GA）异常尚无明确定义。尽管常采用不同异常GA领域的数量阈值，但这些阈值与治疗计划调整（TPM）的关联程度如何，以及特定GA领域在此背景下是否更为重要，仍存在不确定性。本研究对加拿大多伦多玛格丽特公主癌症中心老年肿瘤门诊数据库进行了回顾性分析，纳入2015年5月至2022年6月期间为制定治疗决策而就诊的新患者。通过逻辑回归模型分析，探讨了多种预测变量（包括GA领域及数量阈值）与TPM之间的关联。研究队列（n=736）的平均年龄为80.7岁，女性占46.1%，78.3%的患者VES-13评分显示为脆弱状态（≥3分）。单变量分析显示，基于曲线下面积（AUC）的最佳异常领域数量阈值为4（AUC 0.628）。表现最佳的多变量模型（AUC 0.704）纳入了认知功能、合并症及跌倒风险。相比之下，仅添加阈值4的多变量模型AUC为0.689。总体而言，异常GA的最佳定义可能是在认知功能、合并症及跌倒风险领域存在异常。预测TPM的最佳数量阈值为4。
Defining an Abnormal Geriatric Assessment: Which Deficits Matter Most?
肿瘤(癌症)患者之家