Thompson Leah L, Amin Priya M, Shah Sanjana, Lipson Sarah M, Yoon Jenny, Lee Grace, Anabaraonye Nancy, Gregg Austin T, Jiang Sharon, Baxter Emilie, Florissi Caterina, He John, Saraf Anurag, Nipp Ryan D, Bontempi Dennis, Haugg Fridolin, Aerts Hugo J W L, Mak Raymond H
Department of Radiation Oncology, Brigham & Women's Hospital, Dana-Farber Cancer Institute, Boston, Massachusetts, USA; Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Boston, Massachusetts, USA; Harvard Medical School, Boston, Massachusetts, USA.
Department of Radiation Oncology, Brigham & Women's Hospital, Dana-Farber Cancer Institute, Boston, Massachusetts, USA; Harvard Medical School, Boston, Massachusetts, USA.
Int J Radiat Oncol Biol Phys. 2025 Jul 26. doi: 10.1016/j.ijrobp.2025.07.1431.
Comprehensive geriatric assessment can identify older adult oncology patients at high risk for adverse outcomes, but is variably feasible. Therefore, we assessed whether an abridged geriatric vulnerability model incorporating abstracted G8 score (G8), Charlson Comorbidity Index (CCI), and FaceAge (an AI-based aging measure) was associated with all-cause mortality or falls risk in patients undergoing stereotactic body radiation therapy (SBRT) for early-stage non-small cell lung cancer (NSCLC).
We reviewed the records of 708 patients aged ≥65 years with stage I-II NSCLC treated with SBRT from June 1, 2009, to March 31, 2023. We abstracted demographics, functional status (Eastern Cooperative Oncology Group [ECOG] score), oncologic history, G8, CCI, falls risk (Morse Fall Scale or Strategies to Reduce Injuries and Develop Confidence in Elders screening tool), and time-to-death. FaceAge was calculated using AI-based facial analysis of SBRT simulation photographs. We examined associations between a vulnerability model incorporating G8, CCI, and FaceAge, and all-cause mortality and falls risk, using Cox and regression models adjusted for age, sex, stage, ECOG, and significant covariates (P < .10).
Patients (median age, 76.2 years; 60.7% female; median stage IA), commonly had functional limitations (median ECOG, 1; IQR, 1-2), multimorbidity (median CCI, 7; IQR, 6-8), poor G8 scores (median, 12.5; IQR, 11.5-13.5), and elevated biological FaceAge (median 2.6 years above chronological age). In an adjusted Cox regression model, worse performance on all 3 geriatric vulnerability measures was independently associated with higher all-cause mortality (hazard ratio [HR] = 1.04, 95% confidence interval [CI], 1.02-1.06, P = .002; HR = 1.15, 95% CI, 1.08-1.22, P < .001; HR = 1.14, 95% CI, 1.06-1.22, P < .001). However, only worse G8 was associated with falls risk (HR = 1.19; 95% CI, 1.05-1.35; P = .006).
Among older adults with early-stage NSCLC, a multimodal vulnerability measure leveraging routinely collected data was associated with all-cause mortality, identifying patients who might benefit from additional services.
综合老年医学评估可识别出有不良结局高风险的老年肿瘤患者，但可行性各异。因此，我们评估了一种简化的老年脆弱性模型，该模型纳入了摘要G8评分（G8）、查尔森合并症指数（CCI）和面部年龄（一种基于人工智能的衰老测量指标），是否与接受立体定向体部放射治疗（SBRT）的早期非小细胞肺癌（NSCLC）患者的全因死亡率或跌倒风险相关。
我们回顾了2009年6月1日至2023年3月31日期间接受SBRT治疗的708例年龄≥65岁的I-II期NSCLC患者的记录。我们提取了人口统计学信息、功能状态（东部肿瘤协作组[ECOG]评分）、肿瘤病史、G8、CCI、跌倒风险（莫尔斯跌倒量表或减少老年人伤害及增强信心策略筛查工具）和死亡时间。面部年龄通过对SBRT模拟照片进行基于人工智能的面部分析来计算。我们使用Cox回归模型和针对年龄、性别、分期、ECOG及显著协变量（P < 0.10）进行调整的回归模型，研究了纳入G8、CCI和面部年龄的脆弱性模型与全因死亡率及跌倒风险之间的关联。
患者（中位年龄76.2岁；60.7%为女性；中位分期为IA期）通常存在功能受限（中位ECOG为1；四分位间距为1 - 2）、多种合并症（中位CCI为7；四分位间距为6 - 8）、G8评分较差（中位值为12.5；四分位间距为11.5 - 13.5）以及生物学面部年龄升高（中位值比实际年龄大2.6岁）。在调整后的Cox回归模型中，所有3项老年脆弱性指标表现较差均与较高的全因死亡率独立相关（风险比[HR] = 1.04，95%置信区间[CI]为1.02 - 1.06，P = 0.002；HR = 1.15，95% CI为1.08 - 1.22，P < 0.001；HR = 1.14，95% CI为1.06 - 1.22，P < 0.001）。然而，只有较差的G8与跌倒风险相关（HR = 1.19；95% CI为1.05 - 1.35；P = 0.006）。
在患有早期NSCLC的老年人中，一种利用常规收集数据的多模式脆弱性测量指标与全因死亡率相关，可识别出可能从额外服务中受益的患者。
