The methodological quality of robotic surgical meta-analyses needed to be improved: a cross-sectional study

Peijing Yan; Liang Yao; Huijuan Li; Min Zhang; Yangqin Xun; Meixuan Li; Hui Cai; Cuncun Lu; Lidong Hu; Tiankang Guo; Rong Liu; Kehu Yang

doi:10.1016/j.jclinepi.2018.12.013

The methodological quality of robotic surgical meta-analyses needed to be improved: a cross-sectional study

J Clin Epidemiol. 2019 May:109:20-29. doi: 10.1016/j.jclinepi.2018.12.013. Epub 2018 Dec 21.

Authors

Peijing Yan¹, Liang Yao², Huijuan Li³, Min Zhang⁴, Yangqin Xun³, Meixuan Li³, Hui Cai⁵, Cuncun Lu⁶, Lidong Hu⁵, Tiankang Guo⁵, Rong Liu⁷, Kehu Yang⁸

Affiliations

¹ Institute of Clinical Research and Evidence Based Medicine, Gansu Provincial Hospital, Lanzhou, Gansu 730000, P.R. China.
² Institute of Clinical Research and Evidence Based Medicine, Gansu Provincial Hospital, Lanzhou, Gansu 730000, P.R. China; Chinese Medicine Faculty of Hong Kong Baptist University, Kowloon Tong, Hong Kong, P.R. China; Evidence-Based Medicine Center, School of Basic Medical Science, Lanzhou University, Lanzhou, Gansu 730000, P.R. China.
³ Evidence-Based Medicine Center, School of Basic Medical Science, Lanzhou University, Lanzhou, Gansu 730000, P.R. China; Key Laboratory of Evidence Based Medicine and Knowledge Translation of Gansu Province, Lanzhou, Gansu 730000, P.R. China; School of public Health of Lanzhou University, Lanzhou, Gansu 730000, P.R. China.
⁴ Department of Scientific Research, Gansu Provincial Hospital, Lanzhou, Gansu 730000, P.R. China.
⁵ General Surgery Clinical Medical Center, Gansu Provincial Hospital, Lanzhou, Gansu 730000, P.R. China.
⁶ Evidence-Based Medicine Center, School of Basic Medical Science, Lanzhou University, Lanzhou, Gansu 730000, P.R. China; Key Laboratory of Evidence Based Medicine and Knowledge Translation of Gansu Province, Lanzhou, Gansu 730000, P.R. China.
⁷ Department of Hepatobiliary and Pancreatic Surgical Oncology, Chinese People's Liberation Army General Hospital, Beijing, 100853 P.R. China. Electronic address: liurong@301hospital.com.cn.
⁸ Institute of Clinical Research and Evidence Based Medicine, Gansu Provincial Hospital, Lanzhou, Gansu 730000, P.R. China; Evidence-Based Medicine Center, School of Basic Medical Science, Lanzhou University, Lanzhou, Gansu 730000, P.R. China; Key Laboratory of Evidence Based Medicine and Knowledge Translation of Gansu Province, Lanzhou, Gansu 730000, P.R. China. Electronic address: kehuyangebm2006@126.com.

PMID: 30579979
DOI: 10.1016/j.jclinepi.2018.12.013

Abstract

Objectives: The aims of the article were to assess the methodological quality of robotic surgical meta-analyses (MAs) using A MeaSurement Tool to Assess systematic Reviews (AMSTAR-2) and to explore the factors of methodological quality.

Study design and setting: Robotic surgical MAs published between 2015 and 2018 were identified through a systematical search in PubMed, EMBASE, Cochrane library, and Web of Science databases. The methodological quality of eligible MAs was evaluated by AMSTAR-2. Data extraction and the methodological quality of MAs assessment were double checked by four trained reviewers. The intraclass correlation coefficient (ICC) was used to assess the consistency of quantitative measurements, and the ICC for overall score and score of critical domains were 0.952 and 0.912, respectively. Multivariate regression analysis was used to identify potential factors affecting methodological quality.

Results: A total of 123 MAs focused on 18 surgical locations were included. The findings showed that, regarding quality, only two (1.6%) of 123 MAs were high, two (1.6%) were moderate, two (1.6%) were low, and the remainder 117 (95.1%) were critical low. Multiple linear regression analysis revealed that publishing year and journal rank independently associated with methodological quality of MAs; origin region (P > 0.05), Preferred Reporting Items for Systematic Reviews and Meta-Analyses (P = 0.421), randomized controlled trial enrollment (P = 0.304), and funding support (P = 0.958) did not influence the quality of the MAs. Registration (item 2) and funding reported for individual studies (item 10) showed the poorest adherence in the MAs.

Conclusion: Our study showed that the previously published robotic surgical MAs lack good scientific quality, especially in those published in Q2- to Q4-rated journals. Potential solutions to improve the quality of future robotic surgical MAs include preregistration and funding reported for individual studies.

Keywords: AMSTAR-2; Cross-sectional study; Meta-analyses; Methodological quality; Robotic surgical.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Cross-Sectional Studies
Humans
Meta-Analysis as Topic
Multivariate Analysis
Robotic Surgical Procedures*