Institute for Cancer Outcomes and Survivorship, University of Alabama at Birmingham, Birmingham, AL.
Division of Hematology/Oncology, University of Alabama at Birmingham, Birmingham, AL.
JCO Clin Cancer Inform. 2022 Sep;6:e2200065. doi: 10.1200/CCI.22.00065.
Identifying older patients with GI malignancies who are at increased risk of mortality remains challenging. The goal of our study was to examine geriatric assessment (GA) predictors of 1-year mortality and explore the use of a survival tree analysis in a prospective cohort of older adults (≥ 60 years) with newly diagnosed GI malignancies.
Survival tree analysis was performed to understand variable interactions and identify predictors of overall survival, computed from time of GA to death or last follow-up. Cox regression was used to estimate associations of 1-year mortality, first using a base model (age, race, cancer stage, cancer risk group, and planned chemotherapy), then using all significant predictors from the univariable analyses, and finally only those identified in survival tree analysis.
A total of 478 participants met eligibility, with a mean age of 70 years. The survival tree analysis identified nutrition, cancer stage, physical and emotional health, age, and functional status as predictors of mortality. Older patients without malnutrition or depression had the best 1-year survival, whereas those with malnutrition, stage IV disease, and functional limitations had the worst 1-year survival. Our base model demonstrated good discrimination (area under curve [AUC] 0.76) but was improved with the addition of GA variables (AUC 0.82) or from survival tree analysis (AUC 0.82).
Measures of function, nutrition, and mental health are important predictors of mortality in older adults with GI cancers. Using GA as part of clinical management can aid in the prediction of survival and help inform treatment decision making.
识别胃肠道恶性肿瘤老年患者的死亡风险仍然具有挑战性。我们的研究目的是检验老年评估（GA）预测因素与 1 年死亡率的关系，并探索生存树分析在新诊断为胃肠道恶性肿瘤的老年患者（≥60 岁）前瞻性队列中的应用。
采用生存树分析来理解变量间的相互作用，并确定总生存期的预测因素，总生存期的计算从 GA 时间到死亡或最后一次随访。Cox 回归用于估计 1 年死亡率的相关性，首先使用基本模型（年龄、种族、癌症分期、癌症风险组和计划化疗），然后使用单变量分析中的所有显著预测因素，最后仅使用生存树分析中确定的预测因素。
共有 478 名符合条件的患者，平均年龄为 70 岁。生存树分析确定了营养状况、癌症分期、身体和心理健康、年龄和功能状态是死亡的预测因素。没有营养不良或抑郁的老年患者 1 年生存率最好，而营养不良、IV 期疾病和功能受限的患者 1 年生存率最差。我们的基本模型显示出良好的区分度（曲线下面积 [AUC] 0.76），但通过添加 GA 变量（AUC 0.82）或从生存树分析（AUC 0.82）进行改进。
功能、营养和心理健康状况是胃肠道癌症老年患者死亡的重要预测因素。将 GA 作为临床管理的一部分可以帮助预测生存率，并有助于制定治疗决策。
