Evidence map›Paper›PMID 34874005›Full record

SynthesiseLife2021

Investigating the replicability of preclinical cancer biology.

Timothy M Errington, Maya Mathur, Courtney K Soderberg, Alexandria Denis, Nicole Perfito, Elizabeth Iorns, Brian A Nosek

Abstract readMeta-Analysis
In one paragraph

Synthesis in eLife, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 153 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
153citing papers in PubMed, 3 pooled it
–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

153 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
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  3. Pooled it
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  7. Observational
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  17. Target identification and assessment in the era of AI.Nature reviews. Drug discovery · 2026
    Review
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  19. Review
  20. Article

93 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Timothy M ErringtonCenter for Open Science, Charlottesville, United States.ORCID https://orcid.org/0000-0002-4959-5143
Maya MathurQuantitative Sciences Unit, Stanford University, Stanford, United States.ORCID https://orcid.org/0000-0001-6698-2607
Courtney K SoderbergCenter for Open Science, Charlottesville, United States.
Alexandria DenisCenter for Open Science, Charlottesville, United States.
Nicole PerfitoCenter for Open Science, Charlottesville, United States.
Elizabeth IornsScience Exchange, Palo Alto, United States.ORCID https://orcid.org/0000-0002-5515-1258
Brian A NosekCenter for Open Science, Charlottesville, United States.ORCID https://orcid.org/0000-0001-6797-5476

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Replicability is an important feature of scientific research, but aspects of contemporary research culture, such as an emphasis on novelty, can make replicability seem less important than it should be. The Reproducibility Project: Cancer Biology was set up to provide evidence about the replicability of preclinical research in cancer biology by repeating selected experiments from high-impact papers. A total of 50 experiments from 23 papers were repeated, generating data about the replicability of a total of 158 effects. Most of the original effects were positive effects (136), with the rest being null effects (22). A majority of the original effect sizes were reported as numerical values (117), with the rest being reported as representative images (41). We employed seven methods to assess replicability, and some of these methods were not suitable for all the effects in our sample. One method compared effect sizes: for positive effects, the median effect size in the replications was 85% smaller than the median effect size in the original experiments, and 92% of replication effect sizes were smaller than the original. The other methods were binary - the replication was either a success or a failure - and five of these methods could be used to assess both positive and null effects when effect sizes were reported as numerical values. For positive effects, 40% of replications (39/97) succeeded according to three or more of these five methods, and for null effects 80% of replications (12/15) were successful on this basis; combining positive and null effects, the success rate was 46% (51/112). A successful replication does not definitively confirm an original finding or its theoretical interpretation. Equally, a failure to replicate does not disconfirm a finding, but it does suggest that additional investigation is needed to establish its reliability.

Indexed as

NeoplasmsReproducibility of ResultsAnimalsBiomedical ResearchHumansResearch Designcancer biologycomputational biologycredibilityhumanmeta-analysismousereplicationreproducibilityreproducibility in cancer biologyReproducibility Project: Cancer Biologysystems biologytransparency

Identifiers

PMID34874005
PMCPMC8651293

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.