title: Epidemiological characteristics and methodological quality of meta-analyses on diabetes mellitus treatment: a systematic review.
abstract: OBJECTIVE
  Well-conducted meta-analyses (MAs) are considered as one of the best sources of clinical evidence for treatment decision. MA with methodological flaws may introduce bias and mislead evidence users. The aim of this study is to investigate the characteristics and methodological quality of MAs on diabetes mellitus (DM) treatments.
  
  
  METHODS
  Systematic review.
  
  
  METHODS
  Cochrane Database of Systematic Review and Database of Abstract of Reviews of Effects were searched for relevant MAs. Assessing methodological quality of systematic reviews (AMSTAR) tool was used to evaluate the methodological quality of included MAs. Logistic regression analysis was used to identify association between characteristics of MA and AMSTAR results.
  
  
  RESULTS
  A total of 252 MAs including 4999 primary studies and 13,577,025 patients were included. Over half of the MAs (65.1%) only included type 2 DM patients and 160 MAs (63.5%) focused on pharmacological treatments. About 89.7% MAs performed comprehensive literature search and 89.3% provided characteristics of included studies. Included MAs generally had poor performance on the remaining AMSTAR items, especially in assessing publication bias (39.3%), providing lists of studies (19.0%) and declaring source of support comprehensively (7.5%). Only 62.7% MAs mentioned about harm of interventions. MAs with corresponding author from Asia performed less well in providing MA protocol than those from Europe.
  
  
  CONCLUSIONS
  Methodological quality of MA on DM treatments was unsatisfactory. There is considerable room for improvement, especially in assessing publication bias, providing lists of studies and declaring source of support comprehensively. Also, there is an urgent need for MA authors to report treatment harm comprehensively.
authors.affiliation: Jockey Club School of Public Health and Primary Care Hong Kong Branch of the Chinese Cochrane Centre.
authors.forename: Xin Yin
authors.initials: XY
authors.lastname: Wu
authors.affiliation: Jockey Club School of Public Health and Primary Care.
authors.forename: Victor C K
authors.initials: VC
authors.lastname: Lam
authors.affiliation: Jockey Club School of Public Health and Primary Care.
authors.forename: Yue Feng
authors.initials: YF
authors.lastname: Yu
authors.affiliation: Jockey Club School of Public Health and Primary Care.
authors.forename: Robin S T
authors.initials: RS
authors.lastname: Ho
authors.affiliation: Jockey Club School of Public Health and Primary Care.
authors.forename: Ye
authors.initials: Y
authors.lastname: Feng
authors.affiliation: Jockey Club School of Public Health and Primary Care.
authors.forename: Charlene H L
authors.initials: CH
authors.lastname: Wong
authors.affiliation: Jockey Club School of Public Health and Primary Care.
authors.forename: Benjamin H K
authors.initials: BH
authors.lastname: Yip
authors.affiliation: Jockey Club School of Public Health and Primary Care Stanley Ho Big Data Decision Analytics Research CentreThe Chinese University of Hong Kong, Shatin, Hong Kong.
authors.forename: Kelvin K F
authors.initials: KK
authors.lastname: Tsoi
authors.affiliation: Jockey Club School of Public Health and Primary Care.
authors.forename: Samuel Y S
authors.initials: SY
authors.lastname: Wong
authors.affiliation: Jockey Club School of Public Health and Primary Care Hong Kong Branch of the Chinese Cochrane Centre vchung@cuhk.edu.hk.
authors.forename: Vincent C H
authors.initials: VC
authors.lastname: Chung
mesh_terms: D003920:Diabetes Mellitus / Q000188:drug therapy* / Q000453:epidemiology; D006801:Humans; D015201:Meta-Analysis as Topic; D012107:Research Design / Q000592:standards*