Evidence map›Paper›PMID 36639571›Full record

ArticleDiabetologia2023

Missing the forest-plot for the trees.

Deirdre K Tobias

Abstract read
PubMed Publisher
In one paragraph

Article in Diabetologia, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Deirdre K TobiasDivision of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA. dtobias@bwh.harvard.edu.ORCID 0000-0003-0020-9552

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Systematic reviews and meta-analyses are methods increasingly used in biomedical research since their introduction in the 1970s. They serve to replace other non-systematic and cherry-picked narrative reviews, which are highly variable in their approach, structure and content. Their increase in popularity parallels the increase in overall scientific output, and when properly conducted, systematic reviews can contribute highly impactful summaries of a fast-growing evidence base. Meta-analyses offer statistical summaries, called forest plots, which similarly provide a powerful synopsis unachievable by individual studies. Thus, it is not difficult to imagine why systematic reviews are published more often. Should scientists be concerned by the accelerated output of research, from systematic reviews or other? If quantity comes at the expense of quality, then yes, of course; but should important manuscripts be rationed out otherwise? A new scientific technique can seem scary at first, especially to the researcher who is unfamiliar with its application or uncertain of its validity. In that case, we should become familiar with new and popular methods, and understand their strengths and limitations. There is a rightful place for systematic reviews and meta-analyses among respectable research tools. Importantly, however, despite standard operating procedures and best practices, the quality of systematic reviews today is highly variable, warranting serious concerns for quantity exceeding quality. Therefore, the appropriate response should be to instil researchers with an appreciation for the complexity of conducting and interpreting a systematic review and meta-analysis, to create more knowledgeable authors, reviewers and editors, who collectively will improve, rather than dismiss, these important scientific contributions.

Indexed as

Biomedical ResearchMeta-Analysis as TopicSystematic Reviews as TopicMeta-analysisSystematic review

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.