Article(id=1321425864131199936, tenantId=1146029695717560320, journalId=1235980733773295621, issueId=1321425812331549069, articleNumber=null, orderNo=null, doi=10.20251/j.cnki.1003-3734.2026.15.003, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=null, receivedDateStr=null, revisedDate=null, revisedDateStr=null, acceptedDate=1757692800000, acceptedDateStr=2025-09-13, onlineDate=1792982076914, onlineDateStr=2026-10-26, pubDate=1786723200000, pubDateStr=2026-08-15, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1792982076914, onlineIssueDateStr=2026-10-26, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1792982076914, creator=13701087609, updateTime=1792982076914, updator=13701087609, issue=Issue{id=1321425812331549069, tenantId=1146029695717560320, journalId=1235980733773295621, year='2026', volume='35', issue='15', pageStart='1569', pageEnd='1680', issueExtLink='null', onlineDate='null', pubDate='1786723200000', pubDateStr='2026-08-15', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1792982064564, creator='13701087609', updateTime=1792982904202, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1321429334083097400, tenantId=1146029695717560320, journalId=1235980733773295621, issueId=1321425812331549069, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1321429334087291705, tenantId=1146029695717560320, journalId=1235980733773295621, issueId=1321425812331549069, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=1584, endPage=1591, ext={EN=ArticleExt(id=1321425865938944962, articleId=1321425864131199936, tenantId=1146029695717560320, journalId=1235980733773295621, language=EN, title=Risk assessment of clinical research quality for innovative anti-tumor drugs based on triangular fuzzy analytic hierarchy process, columnId=null, journalTitle=Chinese Journal of New Drugs, columnName=null, runingTitle=null, highlight=null, articleAbstract=
Objective: To establish a scientific risk assessment system, identify and quantify key risk factors affecting the quality of clinical research on innovative anti-tumor drugs, and provide a decision-making basis for quality management and risk control.
Methods: This study adopted the triangular fuzzy analytic hierarchy process (TFAHP) to construct a risk assessment indicator system consisting of 8 primary indicators and 26 secondary indicators. Expert scoring was used to determine the weight of each indicator, followed by consistency testing and comprehensive ranking analysis.
Results: Among the primary indicators, the highest weights were assigned to clinical research ward construction and management risk (0.139 4), information and data risk (0.130 2), and safety event management (0.125 3), highlighting research environment, data management, and subject safety as key focus areas. At the secondary level, data security risk and system security risk under the category of information and data risk (both 0.065 1) ranked highest, followed by litigation risk and policy risk under legal and policy risk (both 0.059 3), together constituting the high-risk tier. The top ten indicators in overall ranking also included safety data collection, quality control, biospecimen collection and processing, and adverse events/serious adverse events (AE/SAE) documentation, reflecting expert emphasis on data integrity, legal compliance, research quality assurance, and subject safety.
Conclusion: TFAHP effectively identifies and quantifies multidimensional risk factors in clinical research of innovative anti-tumor drugs. This study defines high, medium, and low-risk levels and proposes corresponding preventive strategies, providing theoretical and practical guidance for improving research quality and reducing clinical trial risks.
, authors=Bang-yu ZHANG
1, 2, Yi-dan JIANG
1, Ling ZHANG
1, authorsList=Bang-yu ZHANG, Yi-dan JIANG, Ling ZHANG, authorCompany=null, correspAuthors=Ling ZHANG, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1321425866236740547, articleId=1321425864131199936, tenantId=1146029695717560320, journalId=1235980733773295621, language=CN, title=基于三角模糊层次分析法的创新性抗肿瘤药物临床研究质量风险评估研究, columnId=1236331162679955859, journalTitle=中国新药杂志, columnName=新药述评与论坛, runingTitle=null, highlight=null, articleAbstract=
目的： 构建科学的风险评估体系，识别并量化影响创新性抗肿瘤药物临床研究质量的关键风险因素，为质量管理与风险控制提供决策依据。
方法： 本研究采用三角模糊层次分析法（triangular fuzzy analytic hierarchy process, TFAHP），构建包括8项一级指标和26项二级指标的风险评估指标体系，通过专家打分确定各指标权重，并进行一致性检验和综合排序分析。
结果： 一级指标中，临床研究病房建设与管理风险（0.139 4）、信息数据风险（0.130 2）及安全性事件管理（0.125 3）权重较高，显示研究环境与数据管理、受试者安全为首要关注领域。二级指标中，信息数据风险下的数据安全风险和系统安全风险（均为0.065 1）居前2位，法律政策风险下的诉讼风险和政策风险（均为0.059 3）紧随其后，这4项构成高风险等级。综合排序前10位的指标还包括安全性数据的搜集、质量控制、生物样本采集与处理、不良事件/严重不良事件的记录等，反映出专家对数据完整性、法律合规、研究质量保障及受试者安全的高度重视。
结论： TFAHP法可有效识别和量化创新性抗肿瘤药物临床研究中的多维度风险因素。本研究明确了高、中、低风险等级及相应防控建议，为提升研究质量、降低临床试验风险提供了理论依据与实践指导。
, authors=张邦禹
1, 2, 蒋一丹
1, 张玲
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1Clinical Research Management Office, Shanghai Pulmonary Hospital Affiliated to Tongji University, Shanghai 200433, China
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1同济大学附属上海市肺科医院临床研究管理处，上海 200433
2同济大学附属上海市肺科医院药剂科，上海 200433, bio={"content":"
张邦禹，男，博士，主管药师，主要从事社会管理药学与临床药学。联系电话：（021）65115006，E-mail: zby416_pharma@163.com。
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张邦禹，男，博士，主管药师，主要从事社会管理药学与临床药学。联系电话：（021）65115006，E-mail: zby416_pharma@163.com。
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