Suppr超能文献

加利福尼亚州的肺神经内分泌肿瘤患者的生存结果因社会人口因素而异。

Survival outcomes for lung neuroendocrine tumors in California differ by sociodemographic factors.

机构信息

Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, California, USA.

Division of Hematology/Oncology, Department of Medicine, University of California, San Francisco, California, USA.

出版信息

Endocr Relat Cancer. 2023 Dec 8;31(1). doi: 10.1530/ERC-23-0068. Print 2024 Jan 1.

Abstract

Lung neuroendocrine tumors (NETs) have few known predictors of survival. We investigated associations of sociodemographic, clinicopathologic, and treatment factors with overall survival (OS) and lung cancer-specific survival (LCSS) for incident lung NET cases (typical or atypical histology) in the California Cancer Registry (CCR) from 1992 to 2019. OS was estimated with the Kaplan-Meier method and compared by sociodemographic and disease factors univariately with the log-rank test. We used sequential Cox proportional hazards regression for multivariable OS analysis. LCSS was estimated using Fine-Gray competing risks regression. There were 6038 lung NET diagnoses (5569 typical, 469 atypical carcinoid); most were women (70%) and non-Hispanic White (73%). In our multivariable model, sociodemographic factors were independently associated with OS, with better survival for women (hazard ratio (HR) 0.62, 95% confidence interval (CI) 0.57-0.68, P < 0.001), married (HR 0.76, 95% CI 0.70-0.84, P < 0.001), and residents of high socioeconomic status (SES) neighborhoods (HRQ5vsQ1 0.73, 95% CI 0.62-0.85, P < 0.001). Compared to cases with private insurance, OS was worse for cases with Medicare (HR 1.24, 95% CI 1.10-1.40, P < 0.001) or Medicaid/other public insurance (HR 1.45, 95% CI 1.24-1.68, P < 0.001). In our univariate model, non-Hispanic Black Californians had worse OS than other racial/ethnic groups, but differences attenuated after adjusting for stage at diagnosis. In our LCSS models, we found similar associations between sex and marital status on survival, but no differences in outcomes by SES or insurance. By race/ethnicity, American Indian cases had worse LCSS. In summary, beyond disease-related and treatment variables, sociodemographic factors were independently associated with survival in lung NETs.

摘要

肺神经内分泌肿瘤 (NETs) 的生存预测因素知之甚少。我们研究了社会人口统计学、临床病理学和治疗因素与加利福尼亚癌症登记处 (CCR) 1992 年至 2019 年期间发生的肺 NET 病例(典型或非典型组织学)的总生存期 (OS) 和肺癌特异性生存期 (LCSS) 的关联。使用 Kaplan-Meier 方法估计 OS,并使用对数秩检验对社会人口统计学和疾病因素进行单变量比较。我们使用序贯 Cox 比例风险回归进行多变量 OS 分析。使用 Fine-Gray 竞争风险回归估计 LCSS。有 6038 例肺 NET 诊断(5569 例典型,469 例非典型类癌);大多数为女性(70%)和非西班牙裔白人(73%)。在我们的多变量模型中,社会人口统计学因素与 OS 独立相关,女性的生存率更高(风险比 (HR) 0.62,95%置信区间 (CI) 0.57-0.68,P<0.001)、已婚(HR 0.76,95% CI 0.70-0.84,P<0.001)和居住在高社会经济地位 (SES) 社区的人群(HRQ5vsQ1 0.73,95% CI 0.62-0.85,P<0.001)。与私人保险相比,医疗保险(HR 1.24,95% CI 1.10-1.40,P<0.001)或医疗补助/其他公共保险(HR 1.45,95% CI 1.24-1.68,P<0.001)的病例 OS 更差。在我们的单变量模型中,非西班牙裔黑人加利福尼亚人比其他种族/族裔群体的 OS 更差,但在调整诊断时的阶段后,差异减弱。在我们的 LCSS 模型中,我们发现性别和婚姻状况对生存的影响相似,但 SES 或保险对结果没有差异。按种族/族裔划分,美国印第安人病例的 LCSS 更差。总之,除了与疾病相关和治疗相关的变量外,社会人口统计学因素与肺 NET 患者的生存独立相关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b8d/10762535/44fbe6f06b81/ERC-23-0068fig1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验