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单一原发性晚期胆囊癌治疗模式的比较。

Comparison of treatment models for single primary advanced gallbladder cancer.

机构信息

Department of Hepatobiliary Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.

Department of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.

出版信息

Front Immunol. 2024 Nov 13;15:1500091. doi: 10.3389/fimmu.2024.1500091. eCollection 2024.

DOI:10.3389/fimmu.2024.1500091
PMID:39606221
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11599203/
Abstract

PURPOSE

Treatment for advanced gallbladder cancer (GBC) remains controversial, with various recommendations regarding the choice and combination of surgery and adjuvant therapy. The present article is targeting for the exploration of optimal treatment models for advanced GBC.

METHODS

AJCC (American Joint Committee on Cancer, 8th edition) stage III and stage IV GBC, were defined as advanced GBC. Patients with advanced GBC were identified using the Surveillance, Epidemiology, and End Results (SEER) database and departmental cohort. Because of the most representative, only gallbladder adenocarcinoma (GBAC) patients were selected. Based on their surgical status (No, Non-radical and Radical surgery), chemotherapy status (Chemotherapy, No chemotherapy), and radiotherapy status (Radiotherapy, No radiotherapy), treatment models were categorized. For the purposes of evaluating the treatment outcomes of various treatment models and determining the risk element for cancer-specific survival (CSS), Cox regression analysis was applied. Kaplan-Meier curves were used before and after adjusting for covariates, with log-rank tests used to analyze discrepancies between curves. Immunotherapy was analyzed using clinical data from departmental cohort. Finally, to compensate for the limitations of the database, a review examines the progress in treatment models for advanced GBC.

RESULTS

5,154 patients aged over 18 years with solitary primary advanced GBC were identified from the SEER database. In advanced GBC patients, the treatment model has emerged as a significant prognostic factor. "Radical surgery + Chemotherapy + Radiotherapy" models maximally improved the CSS of advanced GBC before and after adjusting for covariates, while "No surgery + No chemotherapy + No radiotherapy" model had the lowest CSS. The present conclusions were supported even after subgroup analysis by AJCC stage. The efficacy of immunotherapy was demonstrated in the departmental cohort analysis. Additionally, this article provides a comprehensive overview of recent advancements in various emerging treatment strategies.

CONCLUSION

Even when optimal treatment model cannot be pursued, providing comprehensive combinations of treatments to advanced GBC patients whenever possible is always beneficial for their survival.

摘要

目的

晚期胆囊癌(GBC)的治疗仍存在争议,对于手术和辅助治疗的选择和联合存在多种建议。本文旨在探索晚期 GBC 的最佳治疗模式。

方法

采用美国癌症联合委员会(AJCC)第 8 版分期标准,将 AJCC Ⅲ期和Ⅳ期 GBC 定义为晚期 GBC。通过监测、流行病学和最终结果(SEER)数据库和科室队列识别晚期 GBC 患者。由于最具代表性,仅选择胆囊腺癌(GBAC)患者。根据手术情况(无手术、非根治性手术和根治性手术)、化疗情况(化疗、无化疗)和放疗情况(放疗、无放疗)对治疗模式进行分类。为了评估各种治疗模式的治疗效果,并确定癌症特异性生存(CSS)的风险因素,采用 Cox 回归分析。使用Kaplan-Meier 曲线进行分析,并在调整协变量后进行对数秩检验,以分析曲线之间的差异。使用科室队列的临床数据对免疫治疗进行分析。最后,为了弥补数据库的局限性,对晚期 GBC 治疗模式的进展进行了综述。

结果

从 SEER 数据库中筛选出 5154 例年龄>18 岁的单发晚期 GBC 患者。在晚期 GBC 患者中,治疗模式已成为显著的预后因素。“根治性手术+化疗+放疗”模式在调整协变量前后最大程度地提高了晚期 GBC 的 CSS,而“无手术+无化疗+无放疗”模式的 CSS 最低。即使在 AJCC 分期的亚组分析中,也支持本研究的结论。在科室队列分析中,也证明了免疫治疗的疗效。此外,本文还全面概述了各种新兴治疗策略的最新进展。

结论

即使无法采用最佳治疗模式,尽可能为晚期 GBC 患者提供全面的综合治疗组合,对其生存也总是有益的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb69/11599203/c6da5b17c59e/fimmu-15-1500091-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb69/11599203/059e05d02239/fimmu-15-1500091-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb69/11599203/86a1a48f231e/fimmu-15-1500091-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb69/11599203/98acda33b368/fimmu-15-1500091-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb69/11599203/23d0867e99b0/fimmu-15-1500091-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb69/11599203/adcafd7afb70/fimmu-15-1500091-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb69/11599203/2a9936ae5170/fimmu-15-1500091-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb69/11599203/c6da5b17c59e/fimmu-15-1500091-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb69/11599203/059e05d02239/fimmu-15-1500091-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb69/11599203/86a1a48f231e/fimmu-15-1500091-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb69/11599203/98acda33b368/fimmu-15-1500091-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb69/11599203/23d0867e99b0/fimmu-15-1500091-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb69/11599203/adcafd7afb70/fimmu-15-1500091-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb69/11599203/2a9936ae5170/fimmu-15-1500091-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb69/11599203/c6da5b17c59e/fimmu-15-1500091-g007.jpg

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