Literature DB >> 30863898

An overview on the methodological and reporting quality of dose-response meta-analysis on cancer prevention.

Chang Xu1, Yu Liu2, Chao Zhang3, Joey S W Kwong4, Jian-Guo Zhou5, Long Ge6, Jing-Yu Huang7, Tong-Zu Liu8.   

Abstract

BACKGROUND: Dose-response meta-analysis (DRMA) has been widely used in exploring cancer risk factors. Understanding the quality of published DRMAs on cancer risk factors may be beneficial for informed prevention for cancer.
METHODS: We searched eligible DRMAs from 1st January 2011 to 31st-July-2017. The modified AMSTAR 1.0 (15 items) and PRISMA checklist (26 items) were used to evaluate the methodological and reporting quality of included DRMAs. We compared the adherence rate of these items by journal type, publication years, region, and funding information, in prior.
RESULTS: We included 260 DRMAs. Colorectal, breast, prostate, and lung were the four most commonly investigated cancers. For methodological quality, 6 out of 15 items were adhered by less than 30% of the DRMAs, 2 by less than 60%, only 7 of which by 80% or more. For reporting quality, 3 out of 26 items were adhered by less than 30% of the DRMAs, 1 by less than 80% (> 30%), and 20 of which by 80% or more. Those published in general journal, published more recently, and received any financial support have better methodological (Rate differences, RDs = 10-36%; P < 0.05) and reporting adherence (RDs = 12-36%; P < 0.05). DRMAs by Asian author tend to be less qualified than by European and American.
CONCLUSIONS: The methodological quality of DRMAs on cancer risk factors is worrisome that the findings of them may be deflective; more efforts are needed to improve the validity of it.

Entities:  

Keywords:  Cancer prevention; Dose–response meta-analysis; Methodological quality; Reporting quality

Mesh:

Year:  2019        PMID: 30863898     DOI: 10.1007/s00432-019-02869-4

Source DB:  PubMed          Journal:  J Cancer Res Clin Oncol        ISSN: 0171-5216            Impact factor:   4.553


  23 in total

1.  Flexible meta-regression functions for modeling aggregate dose-response data, with an application to alcohol and mortality.

Authors:  Vincenzo Bagnardi; Antonella Zambon; Piero Quatto; Giovanni Corrao
Journal:  Am J Epidemiol       Date:  2004-06-01       Impact factor: 4.897

2.  Meta-analysis for linear and nonlinear dose-response relations: examples, an evaluation of approximations, and software.

Authors:  Nicola Orsini; Ruifeng Li; Alicja Wolk; Polyna Khudyakov; Donna Spiegelman
Journal:  Am J Epidemiol       Date:  2011-12-01       Impact factor: 4.897

3.  Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement.

Authors:  David Moher; Alessandro Liberati; Jennifer Tetzlaff; Douglas G Altman
Journal:  Int J Surg       Date:  2010-02-18       Impact factor: 6.071

4.  Tobacco use among youth and adults in Mainland China: the China Seven Cities Study.

Authors:  C Anderson Johnson; Paula H Palmer; Chih-Ping Chou; Zengchang Pang; Dunjin Zhou; Lijun Dong; Haiqing Xiang; Peijun Yang; Hongjie Xu; Jian Wang; Xiaolu Fu; Qian Guo; Ping Sun; Huiyan Ma; Peggy E Gallaher; Bin Xie; Liming Lee; Tianren Fang; Jennifer B Unger
Journal:  Public Health       Date:  2006-09-26       Impact factor: 2.427

5.  Global cancer statistics, 2012.

Authors:  Lindsey A Torre; Freddie Bray; Rebecca L Siegel; Jacques Ferlay; Joannie Lortet-Tieulent; Ahmedin Jemal
Journal:  CA Cancer J Clin       Date:  2015-02-04       Impact factor: 508.702

Review 6.  Global Cancer Incidence and Mortality Rates and Trends--An Update.

Authors:  Lindsey A Torre; Rebecca L Siegel; Elizabeth M Ward; Ahmedin Jemal
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2015-12-14       Impact factor: 4.254

7.  Cancer incidence and mortality worldwide: sources, methods and major patterns in GLOBOCAN 2012.

Authors:  Jacques Ferlay; Isabelle Soerjomataram; Rajesh Dikshit; Sultan Eser; Colin Mathers; Marise Rebelo; Donald Maxwell Parkin; David Forman; Freddie Bray
Journal:  Int J Cancer       Date:  2014-10-09       Impact factor: 7.396

8.  Development of AMSTAR: a measurement tool to assess the methodological quality of systematic reviews.

Authors:  Beverley J Shea; Jeremy M Grimshaw; George A Wells; Maarten Boers; Neil Andersson; Candyce Hamel; Ashley C Porter; Peter Tugwell; David Moher; Lex M Bouter
Journal:  BMC Med Res Methodol       Date:  2007-02-15       Impact factor: 4.615

9.  Limitations of A Measurement Tool to Assess Systematic Reviews (AMSTAR) and suggestions for improvement.

Authors:  Brittany U Burda; Haley K Holmer; Susan L Norris
Journal:  Syst Rev       Date:  2016-04-12

10.  Epidemiology and Reporting Characteristics of Systematic Reviews of Biomedical Research: A Cross-Sectional Study.

Authors:  Matthew J Page; Larissa Shamseer; Douglas G Altman; Jennifer Tetzlaff; Margaret Sampson; Andrea C Tricco; Ferrán Catalá-López; Lun Li; Emma K Reid; Rafael Sarkis-Onofre; David Moher
Journal:  PLoS Med       Date:  2016-05-24       Impact factor: 11.069

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  2 in total

1.  Predictors of Higher Quality of Systematic Reviews Addressing Nutrition and Cancer Prevention.

Authors:  Dawid Storman; Magdalena Koperny; Joanna Zając; Maciej Polak; Paulina Weglarz; Justyna Bochenek-Cibor; Mateusz J Swierz; Wojciech Staskiewicz; Magdalena Gorecka; Anna Skuza; Adam A Wach; Klaudia Kaluzinska; Małgorzata M Bała
Journal:  Int J Environ Res Public Health       Date:  2022-01-03       Impact factor: 3.390

2.  The association between body mass index and the risk of different urinary cancers: Protocol for an overview of systematic reviews.

Authors:  Wenli Zhao; Jiyuan Shi; Yamin Chen; Ziwei Song; Liangliang Si; Xin Jiang; Yu Gu
Journal:  Medicine (Baltimore)       Date:  2020-07-24       Impact factor: 1.817

  2 in total

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