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• W3091143399 abstract "The coronavirus disease 19 (COVID-19) pandemic has brought into focus realities in scientific publishing, with a perceived pressure to rapidly share and publish relevant information also resulting in instances of misinformation.[1] Rheumatologists have found themselves at the unwanted center of one of such arguments, regarding the safety and utility of hydroxychloroquine, a time-tested disease modifying anti rheumatic drug. This was particularly the case when a large global study purported the apparent increase in mortality risk for patients with COVID-19 treated with hydroxychloroquine. Later, when questions arose about the geographic coverage and numbers of patients included in the published database, as well as queries regarding the remarkable homogeneity of such data across diverse geographical regions, attempts were made to verify the study data by external sources.[23] As sensational and unbelievable the origins of this remarkable study were, so was its fall from grace when part of the author group themselves refused to stand by this study and recommended retraction of this as well as another prominent study (addressing another area of controversy in COVID-19, regarding the use of angiotensin converting enzyme inhibitors and mortality risk).[456] A surprising fallout of such public disowning of these studies and subsequent retraction were the remarkable criticism that seemed targeted at peer reviewers of these studies.[6] This raised questions in our mind as to who should bear the responsibility for research integrity – the authors themselves, the handling editors of journals, or peer reviewers. Therefore, we overviewed various types of research misconduct related to data handling, consequences of such articles containing research misconduct and propose distribution of responsibilities for such research misconduct amongst authors, editors, and reviewers. Types of Scientific Misconduct Related to Data Dubious data The data on which the study in question is based on might not be of good quality or might be unreliable. The sources of such data might not be clear. The data might be being used for a different purpose than for which it was collected (thereby compromising quality) and therefore might not be of high quality. There may be issues with collection of data or with inaccurate coding of the data. Particularly, such concerns should be kept in mind when interpreting data collected from routine health-care databases.[78] The primary reason for the retraction of the aforementioned studies on COVID-19 was the lack of access to their data, when this had subsequently been sought for auditing by the concerned journals after complaints were received regarding the potential veracity of such data.[345] Notably, some of the authors of the said studies simply stated that they could no longer guarantee the veracity of the data on which these papers were published.[45] Keeping in mind the principles for authorship espoused by the International Committee of Medical Journal Editors,[9] such individuals should probably have never agreed to be listed as authors on the said manuscript if they could not guarantee the accuracy of the data sources. A review of the literature also reveals that data falsification or data fabrication accounts for between 20% and 40% of retracted publications from certain Asian countries.[10] In the fields of dentistry[11] and genetics,[12] nearly one-fourth of retractions due to research misconduct were due to concerns about the veracity of data.[1112] Dubious analysis of data The data for a particular study might not have been properly analyzed. Either inappropriate methods might have been used (e.g., parametric tests for small numbers), or the results might be too homogenous between groups to be considered truly representative. In the aforementioned retracted papers, unexpected homogeneity of the data raised questions about its veracity.[313] Dubious ethical aspects Studies not conducted ethically should not be considered as relevant, no matter how attractive their results might appear to be. Due consideration toward informed consent (or in its absence, appropriate anonymization of data) and approval by local ethics committees should always be considered by researchers.[14] In the aforementioned retracted publications on COVID-19, lack of information regarding ethics committee review and the outright refusal to share the identities of hospitals that the transcontinental database was supposedly based on were fatal flaws that ultimately rendered the study findings unreliable.[345] Consequences of Data Unreliability, Fabrication, or Misconduct Related to Data Handling Depending on the degree of inappropriate or fraudulent practices related to data handling, journals might either issue expression (s) of concerns (EOC), correct the said papers, or retract them from the published literature. EOC are generally issued when the matter in question is under active investigation by the journal. After the completion of such investigations, EOC might be withdrawn if no evidence of misconduct was found, or the degree of inaccuracy was found to be trivial and not directly affecting the said study and its interpretations. If such inaccuracies are significant, corrections might be issued for the said paper to rectify those parts which are inaccurate. If the said mistakes in data integrity compromise the study and its interpretations and are not amenable to a correction, the said paper might be retracted.[1415] Instances exist of honest mistakes by authors, resulting in retraction and republication of the same paper in the same journal.[16] Responsibility for Integrity of Data Since authors purposefully submit their manuscripts for publication by journals, they should be responsible for the integrity of their published data. Any responsibility for data fabrication or falsification should therefore lie primarily with the authors of the manuscript in question.[2317] Editors have access to all the submitted information and are generally more experienced in dealing with scientific misconduct than peer reviewers; hence, they should also bear responsibility for the manuscripts they approve for publication, after the authors. Peer reviewers often do not have access to the primary data. Ethical statements might also not be available to reviewers when there is double blind peer review. While some reviewers may be statistical experts, many others are technical subject experts and not necessarily able to identify subtle clues toward data fraud. Hence, they should be least held responsible for data fraud and should rather bear responsibility for technical correctness of the manuscripts they review and recommend for publication. Efforts might be made to train reviewers to pick up subtle clues toward data manipulation based on past experiences.[318] Fraudulent behavior with respect to data handling primarily remains the domain of the authors, rather than laying blame to peer reviewers as occurred recently during the prominent COVID-19 retractions.[6] Peer reviewers that volunteer their precious time setting aside their own patient care, teaching and research responsibilities as well as their personal time should be valued more rather than being taken for granted and blamed at the earliest opportunity if published manuscripts are found to have problems.[19]" @default.
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• W3091143399 title "Blaming the peer reviewer: Don't shoot the messenger!!" @default.
• W3091143399 doi "https://doi.org/10.4103/injr.injr_187_20" @default.
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