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1.成都市第三人民医院药学部,成都 610031
2.成都医学院药学院,成都 610500
3.四川省肿瘤临床医学研究中心/四川省肿瘤医院研究所/四川省癌症防治中心/电子科技大学附属肿瘤医院药学部,成都 610041
4.电子科技大学医学院,成都 610054
5.成都市第二人民医院药学部,成都 610021
主管药师,硕士研究生。研究方向:临床药学。电话:028-61318607。E-mail:549279916@qq.com
主任药师,博士生导师,博士。研究方向:循证药物评价方法与决策转化。电话:028-85420338。E-mail:jiangqian_3805.student@sina.com
纸质出版日期:2024-02-15,
收稿日期:2023-06-28,
修回日期:2023-12-12,
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秦小莉,高秀容,何琴等.全球肿瘤相关性血栓栓塞症风险评估工具的循证研究 Δ[J].中国药房,2024,35(03):333-338.
QIN Xiaoli,GAO Xiurong,HE Qin,et al.Evidence-based evaluation of the global cancer-associated thromboembolism risk assessment tools[J].ZHONGGUO YAOFANG,2024,35(03):333-338.
秦小莉,高秀容,何琴等.全球肿瘤相关性血栓栓塞症风险评估工具的循证研究 Δ[J].中国药房,2024,35(03):333-338. DOI: 10.6039/j.issn.1001-0408.2024.03.12.
QIN Xiaoli,GAO Xiurong,HE Qin,et al.Evidence-based evaluation of the global cancer-associated thromboembolism risk assessment tools[J].ZHONGGUO YAOFANG,2024,35(03):333-338. DOI: 10.6039/j.issn.1001-0408.2024.03.12.
目的
2
基于循证方法对全球肿瘤相关性血栓栓塞症风险评估工具进行评价,以期为构建我国特异性评估工具提供方法学参考与循证依据。
方法
2
全面检索中国知网、万方数据库、维普网、中国生物医学文献数据库、PubMed及Embase 6个数据库和NCCN、ASCO及ESMO等学会网站,检索截止时间为2022年6月30日,并于2023年1月补充检索。对纳入的风险评估工具,定性描述分析其基本特性与方法学质量,重点对比各评估工具评价维度、工具性能、风险分层能力等关键要素。
结果
2
研究共纳入14个风险评估工具,其研究样本量为208~18 956例,受试者平均年龄分布在53.1~74.0岁;适用人群涵盖门诊肿瘤患者、淋巴瘤患者及多发性骨髓瘤患者等。工具中身体质量指数、静脉血栓栓塞症既往史和肿瘤部位是常见的预测因子。所有工具均进行了方法学验证,其中9个以权重评分的方式呈现。同时进行了特异性、敏感性、阴性预测值、阳性预测值和曲线下面积或
C
统计量分析的工具仅7个。
结论
2
现有工具构建偏倚风险较高,工具验证结果异质性较大,整体方法学质量有待提高,风险分层能力也有待考究,在我国临床实践中仍存在一定局限性。
OBJECTIVE
2
To evaluate the global cancer-associated thromboembolism risk assessment tools based on evidence-based methods, and to provide methodological reference and evidence-based basis for constructing a specific tool in China.
METHODS
2
A comprehensive search was conducted on 6 databases, including CNKI, Wanfang data, VIP, CBM, PubMed, and Embase, as well as on the websites of NCCN, ASCO, ESMO and so on with a deadline of June 30, 2022. Furthermore, a supplementary search was conducted in January 2023. The essential characteristics and methodological quality of included risk assessment tools were described and analyzed qualitatively, focusing on comparing each assessment tool’s key elements, such as evaluation dimensions, tool performance, risk stratification ability.
RESULTS
2
Totally 14 risk assessment tools were included in the study, with a sample size of 208- 18 956 cases and an average age distribution of 53.1-74.0 years. The applicable population included outpatient cancer patients, lymphoma patients, and multiple myeloma patients, etc. The common predictive factors were body mass index, venous thromboembolism history, and tumor site. All tools had undergone methodological validation, with 9 presented in a weighted scoring format. Only seven tools were used simultaneously for specificity, sensitivity, negative predictive value (NPV), positive predictive value (PPV) and area under the curve (AUC) or
C
statistical analysis.
CONCLUSIONS
2
The risk of bias in constructing existing tools is high, and the heterogeneity of tool validation results is significant. The overall methodological quality must be improved, and its risk stratification ability must also be investigated. There are still certain limitations in clinical practice in China.
肿瘤相关性血栓栓塞症风险评估工具循证研究
risk assessment toolsevidence-based research
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