Suppr超能文献

抗血管生成药物单药及联合治疗卵巢癌的疗效与安全性:一项随机对照试验的荟萃分析和试验序贯分析

Efficacy and safety of anti-angiogenic drug monotherapy and combination therapy for ovarian cancer: a meta-analysis and trial sequential analysis of randomized controlled trials.

作者信息

Xie Yao, Zhou Fei

机构信息

Department of Obstetrics and Gynaecology, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.

出版信息

Front Pharmacol. 2024 May 27;15:1423891. doi: 10.3389/fphar.2024.1423891. eCollection 2024.

Abstract

BACKGROUND

As the development of novel anti-angiogenic drugs and the continuous evolution of guideline recommendations, the efficacy and safety of anti-angiogenic agents in ovarian cancer (OC) remains unclear. Consequently, a meta-analysis was carried out to assess the efficacy and safety of anti-angiogenic drug monotherapy and combination therapy for OC.

METHODS

An exhaustive literature review was performed across multiple databases, including PubMed, Embase, Web of Science, and Cochrane, encompassing all relevant randomized controlled trials (RCTs) up until 6 April 2024. The evaluation of efficacy outcomes incorporated progression-free survival (PFS), overall survival (OS), and objective response rate (ORR). Safety was assessed through the occurrence of any grade adverse events (AEs) and grade ≥3 AEs. Synthesis of the data involved the calculation of hazard ratios (HRs), relative risks (RRs), and their corresponding 95% confidence intervals (CIs) and prediction intervals (PIs). Trial sequential analysis was executed employing TSA v0.9.5.10 Beta software, STATA 12.0, and R software 4.3.1.

RESULTS

In this meta-analysis, 35 RCTs were included, encompassing 16,199 subjects in total. The overall analysis indicated that anti-angiogenic drug combination therapy significantly improved PFS (HR [95% CI] = 0.678 [0.606-0.759], 95% PI: 0.415-1.108), OS (HR [95% CI] = 0.917 [0.870-0.966], 95% PI: 0.851-0.984), and ORR (RR [95% CI] = 1.441 [1.287-1.614], 95% PI: 1.032-2.014), but also increased the incidence of grade ≥3 AEs (RR [95% CI] = 1.137 [1.099-1.177], 95% PI: 1.011-1.252). The analysis did not corroborate any benefit of anti-angiogenic monotherapy over placebo concerning PFS (HR [95% CI] = 0.956 [0.709-1.288], 95% PI: 0.345-2.645) and OS (HR [95% CI] = 1.039 [0.921-1.173], 95% PI: 0.824-1.331). However, it was observed that monotherapy with anti-angiogenic drugs did increase the incidence of any grade AEs (RR [95% CI] = 1.072 [1.036-1.109], 95% PI: 0.709-1.592).

CONCLUSION

Our study confirmed the PFS, OS, and ORR benefits of anti-angiogenic drug combination therapy for OC patients. The efficacy results of anti-angiogenic monotherapy necessitates further evaluation as more RCTs become available. Clinicians should be vigilant of AEs when administering anti-angiogenic agents in a clinical setting.

摘要

背景

随着新型抗血管生成药物的发展以及指南推荐的不断演变,抗血管生成药物在卵巢癌(OC)中的疗效和安全性仍不明确。因此,进行了一项荟萃分析,以评估抗血管生成药物单药治疗和联合治疗OC的疗效和安全性。

方法

对多个数据库进行了详尽的文献检索,包括PubMed、Embase、科学网和Cochrane,涵盖截至2024年4月6日的所有相关随机对照试验(RCT)。疗效结果评估包括无进展生存期(PFS)、总生存期(OS)和客观缓解率(ORR)。通过任何级别不良事件(AE)和≥3级AE的发生情况评估安全性。数据合成涉及计算风险比(HR)、相对风险(RR)及其相应的95%置信区间(CI)和预测区间(PI)。使用TSA v0.9.5.10 Beta软件、STATA 12.0和R软件4.3.1进行试验序贯分析。

结果

在这项荟萃分析中,纳入了35项RCT,共涉及16199名受试者。总体分析表明,抗血管生成药物联合治疗显著改善了PFS(HR [95% CI] = 0.678 [0.606 - 0.759],95% PI:0.415 - 1.108)、OS(HR [95% CI] = 0.917 [0.870 - 0.966],95% PI:0.851 - 0.984)和ORR(RR [95% CI] = 1.441 [1.287 - 1.614],95% PI:1.032 - 2.014),但也增加了≥3级AE的发生率(RR [95% CI] = 1.137 [1.099 - 1.177],95% PI:1.011 - 1.252)。分析未证实抗血管生成单药治疗在PFS(HR [95% CI] = 0.956 [0.709 - 1.288],95% PI:0.345 - 2.645)和OS(HR [95% CI] = 1.039 [0.921 - 1.173],95% PI:0.824 - 1.331)方面比安慰剂有任何益处。然而,观察到抗血管生成药物单药治疗确实增加了任何级别AE的发生率(RR [95% CI] = 1.072 [1.036 - 1.109],95% PI:0.709 - 1.592)。

结论

我们的研究证实了抗血管生成药物联合治疗对OC患者的PFS、OS和ORR有益。随着更多RCT的出现,抗血管生成单药治疗的疗效结果需要进一步评估。临床医生在临床环境中使用抗血管生成药物时应警惕AE。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d27/11163095/f50b9df0a843/fphar-15-1423891-g001.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