PO.CL09.03 · 临床研究
接受晚期/转移性（a/m）胃癌、胃食管交界处癌或食管腺癌（GC/GEJC/EAC）一线（1L）治疗（tx）患者（pts）按种族划分的真实世界（RW）结局
Real-world (RW) outcomes by race in patients (pts) receiving first-line (1L) treatment (tx) for advanced/metastatic (a/m) gastric, gastroesophageal junction, or esophageal adenocarcinoma (GC/GEJC/EAC)
作者与单位 Authors & Affiliations
摘要 Abstract
中文摘要
既往研究显示GC/GEJC/EAC在治疗可及性和死亡率方面存在种族差异，但种族对1L治疗结局的影响尚不明确。我们评估了在美国接受GC/GEJC/EAC 1L治疗患者按种族划分的治疗模式和结局。这项回顾性观察性研究使用了Flatiron Health研究数据库。纳入2021年5月1日至2024年11月30日期间开始1L治疗的HER2阴性/未知GC/GEJC/EAC成人患者。随访终点为2025年5月31日，以允许≥6个月的随访。Flatiron将自我报告的种族分类为白人、黑人/非裔美国人（黑人）、亚洲人或其他（多种类别/未列出）。通过Kaplan-Meier方法估算RW总生存期（OS）、至下次治疗/死亡时间（TTNTD）和至治疗中断时间（TTD），并在各种族类别之间进行比较。在2128例符合条件的患者中，61%为白人，8%为黑人，3%为亚洲人，8%为其他，20%为种族未知。大多数在社区肿瘤诊疗机构接受治疗（77%-79%）。各种族组的中位年龄相似（69岁）；25%（白人）、76%（黑人）和77%（亚洲人）的患者患有GC。黑人与白人患者的中位OS（12.0 vs 13.0个月）和TTNTD（7.6 vs 6.7个月）相似；黑人与白人患者的中位TTD在数值上更长（4.3 vs 2.3个月）。然而，在调整关键基线混杂因素后，黑人与白人患者之间临床结局的差异无统计学意义（风险比[95%置信区间]：OS，0.97 [0.78-1.20]；TTNTD，0.93 [0.77-1.13]；TTD，0.92 [0.76-1.10]）（表）。这些发现凸显了公平的1L治疗可及性在最小化HER2阴性/未知a/m GC/GEJC/EAC患者种族差异方面的潜在影响。需要更大规模的研究来评估疾病预后和其他变量的影响，但本研究凸显了RW数据在推进健康公平和指导未来临床干预方面的价值。
表. 按种族划分的临床结局 a 中位数（HR vs 白人；95% CI），月 白人（n = 1290） 黑人/非裔美国人（n = 174） 亚洲人（n = 68） 其他（n = 170） rwOS 13.0（参照） 12.0（0.97；0.78-1.20） 16.6（0.88；0.60-1.27） 13.0（0.90；0.72-1.12） rwTTNTD 6.7（参照） 7.6（0.93；0.77-1.13） 8.6（0.87；0.63-1.20） 7.4（0.95；0.78-1.16） rwTTD 2.3（参照） 4.3（0.92；0.76-1.10） 5.0（0.79；0.59-1.07） 4.5（0.81；0.67-0.98） HR，风险比；mo，月；rwOS，真实世界总生存期；rwTTD，真实世界至治疗中断时间；rwTTNTD，真实世界至下次治疗或死亡时间。a 分析排除了种族未知的患者。
查看英文原文 English abstract
Prior studies show racial disparities in tx access and mortality in GC/GEJC/EAC, yet the effect of race on 1L tx outcomes is unclear. We evaluated tx patterns and outcomes by race in pts who received 1L tx for GC/GEJC/EAC in the US. This retrospective, observational study used the Flatiron Health Research Database. Adults starting 1L tx between May 1, 2021, and Nov 30, 2024 for HER2-negative/unknown GC/GEJC/EAC were included. End of follow-up was May 31, 2025 to allow for ≥6 months of follow-up. Flatiron categorized self-reported race as White, Black/African American (Black), Asian, or other (multiple categories/not listed). RW overall survival (OS), time to next tx/death (TTNTD), and time to tx discontinuation (TTD) were estimated via the Kaplan-Meier method and compared between race categories. Of 2128 eligible pts, 61% were White, 8% Black, 3% Asian, 8% other, and 20% unknown race. Most were treated in community-based oncology practices (77%-79%). Median age was similar across racial groups (69 years); 25% (White), 76% (Black), and 77% (Asian) of pts had GC. Median OS (12.0 vs 13.0 months) and TTNTD (7.6 vs 6.7 months) were similar in Black vs White pts; median TTD was numerically longer in Black vs White pts (4.3 vs 2.3 months). However, the differences in clinical outcomes between Black and White pts were not statistically significant (hazard ratio [95% confidence interval]: OS, 0.97 [0.78-1.20]; TTNTD, 0.93 [0.77-1.13]; TTD, 0.92 [0.76-1.10]) after adjusting for key baseline confounders (Table). These findings underscore the potential impact of equitable 1L tx access in minimizing racial disparities in pts with HER2-negative/unknown a/m GC/GEJC/EAC. Larger studies are needed to assess the influence of disease prognosis and other variables, but this study highlights the value of RW data in advancing health equity and guiding future clinical interventions.
Table. Clinical outcomes by race a Median (HR vs White; 95% CI), mo White (n = 1290) Black/African American (n = 174) Asian (n = 68) Other (n = 170) rwOS 13.0 (Referent) 12.0 (0.97; 0.78-1.20) 16.6 (0.88; 0.60-1.27) 13.0 (0.90; 0.72-1.12) rwTTNTD 6.7 (Referent) 7.6 (0.93; 0.77-1.13) 8.6 (0.87; 0.63-1.20) 7.4 (0.95; 0.78-1.16) rwTTD 2.3 (Referent) 4.3 (0.92; 0.76-1.10) 5.0 (0.79; 0.59-1.07) 4.5 (0.81; 0.67-0.98) HR, hazard ratio; mo, months; rwOS, real-world overall survival; rwTTD, real-world time to treatment discontinuation; rwTTNTD, real-world time to next treatment or death. a Analysis excluded pts with unknown race.
利益披露 Disclosure
J. Gu,
Gilead Sciences Employment, Stock.
R. Gupta,
Gilead Sciences Employment.
D. O. Koralek,
Gilead Sciences Employment, Stock.
A. Taylor,
Gilead Sciences Employment, Stock.
J. A. Ajani,
Amgen ), Other, Consulting fees; Honoraria for lectures, Speakers Bureaus, manuscript writing, or educational events; and Participation on a Data Safety Monitoring Board or Advisory Board.
Bristol-Myers Squibb ), Other, Consulting fees; Honoraria for lectures, Speakers Bureaus, manuscript writing, or educational events; and Participation on a Data Safety Monitoring Board or Advisory Board.
Genentech, MedImmune ).
Lilly/ImClone ), Other, Consulting fees; Honoraria for lectures, Speakers Bureaus, manuscript writing, or educational events.
BeiGene Other, Honoraria for lectures, Speakers Bureaus, manuscript writing, or educational events; Participation on a Data Safety Monitoring Board or Advisory Board.
Merck ), Other, Consulting fees; Honoraria for lectures, Speakers Bureaus, manuscript writing, or educational events; and Participation on a Data Safety Monitoring Board or Advisory Board.
Roche/Genentech ), Other, Consulting fees.
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Daiichi Sankyo Other, Consulting fees; Honoraria for lectures, Speakers Bureaus, manuscript writing, or educational events.
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