Evidence-based evaluation of the global cancer-associated thromboembolism risk assessment tools
- VernacularTitle:全球肿瘤相关性血栓栓塞症风险评估工具的循证研究
- Author:
Xiaoli QIN
1
,
2
;
Xiurong GAO
2
;
Qin HE
1
;
Shunlong OU
3
;
Jing LUO
4
;
Hua WEI
5
;
Qian JIANG
3
Author Information
1. Dept. of Pharmacy，the Third People’s Hospital of Chengdu，Chengdu 610031，China
2. College of Pharmacy，Chengdu Medical College，Chengdu 610500，China
3. Dept. of Pharmacy，Sichuan Clinical Research Center for Cancer/Sichuan Cancer Hospital&Institute/Sichuan Cancer Center/the Affiliated Cancer Hospital of University of Electronic Science and Technology of China，Chengdu 610041，China
4. School of Medicine，University of Electronic Science and Technology of China，Chengdu 610054，China
5. Dept. of Pharmacy，Chengdu Second People’s Hospital，Chengdu 610021，China
- Publication Type:Journal Article
- Keywords:
cancer-associated thromboembolism;
risk assessment tools;
evidence-based research
- From:
China Pharmacy
2024;35(3):333-338
- CountryChina
- Language:Chinese
-
Abstract:
OBJECTIVE 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 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 stratification ability. RESULTS 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 student@sina.com 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 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.
