Neoadjuvant and Adjuvant Treatments Compared to Concurrent Chemoradiotherapy for Patients With Locally Advanced Cervical Cancer: A Bayesian Network Meta-Analysis

Author:

Qiao Yunfeng,Li Huijun,Peng Bing

Abstract

AimThis study aimed to identify the most effective treatment mode for locally advanced cervical cancer (LACC) by adopting a network meta-analysis (NMA).MethodsRandomized controlled trials about treatments were retrieved from PubMed, Medline and Embase. Odds ratios (OR) of overall survival (OS) and progression-free survival (PFS) were calculated by synthesizing direct and indirect evidence to rank the efficacy of nine treatments. Consistency was assessed by node-splitting method. Begg’s test was performed to evaluate publication bias. The surface under cumulative ranking curve (SUCRA) was also used in this NMA.ResultsA total of 24 eligible randomized controlled trials with 6,636 patients were included in our NMA. These trials compared a total of nine different regimens: radiotherapy (RT) alone, surgery, RT plus adjuvant chemotherapy (CT), concurrent chemoradiotherapy (CCRT), neoadjuvant CT plus CCRT, CCRT plus adjuvant CT, neoadjuvant CT, RT, CCRT plus surgery. Among those therapeutic modalities, we found that the two interventions with the highest SUCRA for OS and PFS were CCRT and CCRT plus adjuvant CT, respectively. ORs and 95% confidence interval (CI) for the two best strategies were CCRT versus CCRT plus adjuvant CT (OR, 0.84; 95% CI, 0.53–1.31) for OS, CCRT plus adjuvant CT versus CCRT (OR, 0.60; 95% CI, 0.38–0.96) for PFS.ConclusionsThis NMA supported that CCRT and CCRT plus adjuvant CT are likely to be the most optimal treatments in terms of both OS and PFS for LACC. Future studies should focus on comparing CCRT and CCRT plus adjuvant CT in the treatment of LACC.Systematic Review RegistrationPROSPERO, CRD42019147920.

Publisher

Frontiers Media SA

Subject

Cancer Research,Oncology

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3