Data extraction methods: an analysis of internal reporting discrepancies in single manuscripts and practical advice.

Data extraction from reports about experimental or observational studies is a crucial methodological step informing evidence syntheses, such as systematic reviews (SRs) and overviews of SRs. Reporting discrepancies were defined as pairs of statements that could not both be true. Authors of SRs and overviews of SRs can encounter reporting discrepancies among multiple sources when extracting data-a manuscript and a conference abstract, and a manuscript and a clinical trial registry. However, these discrepancies can also be found within a single manuscript published in a scientific journal. Hereby, we describe examples of internal reporting discrepancies that can be found in a single source, with the aim of raising awareness among authors of SRs and overviews of SRs about such potential methodological issues. Authors of SRs and overviews of SRs should check whether the same information is reported in multiple places within a study and compare that information. Independent data extraction by two reviewers increases the chance of finding discrepancies, if they exist. We provide advice on how to deal with different types of discordances and how to report such discordances when conducting SRs and overviews of SRs. Copyright © 2019 Elsevier Inc. All rights reserved.

Citation

Livia Puljak, Nicoletta Riva, Elena Parmelli, Marien González-Lorenzo, Lorenzo Moja, Dawid Pieper. Data extraction methods: an analysis of internal reporting discrepancies in single manuscripts and practical advice. Journal of clinical epidemiology. 2020 Jan;117:158-164

Mesh Tags

PMID: 31541692

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