Literature DB >> 30774434

Letter to the editor regarding the publication "Association between matrix-metalloproteinase polymorphisms and prostate cancer risk: a meta-analysis and systematic review".

Rama Jayaraj1, Chellan Kumarasamy2.   

Abstract

Entities:  

Year:  2019        PMID: 30774434      PMCID: PMC6353026          DOI: 10.2147/CMAR.S195169

Source DB:  PubMed          Journal:  Cancer Manag Res        ISSN: 1179-1322            Impact factor:   3.989


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The authors of the article, “Association between matrix-metalloproteinase polymorphisms and prostate cancer risk: a meta-analysis and systematic review”, Zhou et al, have put forth a number of interesting points.1 This paper, published in the journal Cancer Management and Research attempts to link matrix metalloproteinase (MMP) polymorphisms and the propensity to developing prostate cancer. Though a similar study has previously been done on ovarian cancer by authors credited in this study, this study does tread fresh ground on the topic of prostate cancer and has potential to act as a guideline for future research. However, we would like to bring to attention a few possible improvements to the paper that may serve to benefit the study and better position it as a citable article. We believe that it is important to highlight, refer, and compare previous pioneer studies and publications in said field. Therefore, previous studies by Weng et al and Lin et al are of relevance to the study conducted by Zhou et al and are worthy of being included in the literature review.2,3 Furthermore, the inclusion of the “funnel plot”, “Orwin’s classic fail-safe N test”, “Begg and Mazumdar Rank correlation test” and the “Duval and Tweedie’s trim and fill” would present a better analysis of the possible publication bias as they are the standard tools used for assessment of bias.4–6 Finally, a minor suggestion to the authors is the inclusion of the Tau-squared value in the random effects model of statistical analysis, as it considers threshold effect, which is not considered by the usual I-squared and chi-squared values.7 We hope that the authors will consider the inclusion of these suggestions into their study as they have been presented solely to heighten the value of the paper and elevate it as a reference for future studies.
  6 in total

1.  Trim and fill: A simple funnel-plot-based method of testing and adjusting for publication bias in meta-analysis.

Authors:  S Duval; R Tweedie
Journal:  Biometrics       Date:  2000-06       Impact factor: 2.571

2.  Bias in meta-analysis detected by a simple, graphical test.

Authors:  M Egger; G Davey Smith; M Schneider; C Minder
Journal:  BMJ       Date:  1997-09-13

3.  Operating characteristics of a rank correlation test for publication bias.

Authors:  C B Begg; M Mazumdar
Journal:  Biometrics       Date:  1994-12       Impact factor: 2.571

Review 4.  Systematic Review and Meta-Analysis of Studies Evaluating Diagnostic Test Accuracy: A Practical Review for Clinical Researchers-Part II. Statistical Methods of Meta-Analysis.

Authors:  Juneyoung Lee; Kyung Won Kim; Sang Hyun Choi; Jimi Huh; Seong Ho Park
Journal:  Korean J Radiol       Date:  2015-10-26       Impact factor: 3.500

5.  Association between matrix-metalloproteinase polymorphisms and prostate cancer risk: a meta-analysis and systematic review.

Authors:  Hongxing Zhou; Xuming Zhu
Journal:  Cancer Manag Res       Date:  2018-11-02       Impact factor: 3.989

6.  Genetic Association between Matrix Metalloproteinases Gene Polymorphisms and Risk of Prostate Cancer: A Meta-Analysis.

Authors:  Hong Weng; Xian-Tao Zeng; Xing-Huan Wang; Tong-Zu Liu; Da-Lin He
Journal:  Front Physiol       Date:  2017-12-01       Impact factor: 4.566

  6 in total

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