ArticlePLoS biology2017
Can cancer researchers accurately judge whether preclinical reports will reproduce?
Article in PLoS biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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.
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.
Who cites it
13 citing papers in PubMed, 36 citations in OpenAlex.
- Predicting the replicability of social and behavioural science claims in COVID-19 preprints.Nature human behaviour · 2025Article
- Americans harbor much less favorable explicit sentiments toward young adults than toward older adults.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- The impact of feedback training on prediction of cancer clinical trial results.Clinical trials (London, England) · 2024Article
- Predicting and reasoning about replicability using structured groups.Royal Society open science · 2023Article
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- Wisdom of the expert crowd prediction of response for 3 neurology randomized trials.Neurology · 2020Article
- A normalized drug response metric improves accuracy and consistency of anticancer drug sensitivity quantification in cell-based screening.Communications biology · 2020Article
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- How to design preclinical studies in nanomedicine and cell therapy to maximize the prospects of clinical translation.Nature biomedical engineering · 2018Article
- The Mouse Hospital and Its Integration in Ultra-Precision Approaches to Cancer Care.Frontiers in oncology · 2018Article
- Correcting Judgment Correctives in National Security Intelligence.Frontiers in psychology · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
There is vigorous debate about the reproducibility of research findings in cancer biology. Whether scientists can accurately assess which experiments will reproduce original findings is important to determining the pace at which science self-corrects. We collected forecasts from basic and preclinical cancer researchers on the first 6 replication studies conducted by the Reproducibility Project: Cancer Biology (RP:CB) to assess the accuracy of expert judgments on specific replication outcomes. On average, researchers forecasted a 75% probability of replicating the statistical significance and a 50% probability of replicating the effect size, yet none of these studies successfully replicated on either criterion (for the 5 studies with results reported). Accuracy was related to expertise: experts with higher h-indices were more accurate, whereas experts with more topic-specific expertise were less accurate. Our findings suggest that experts, especially those with specialized knowledge, were overconfident about the RP:CB replicating individual experiments within published reports; researcher optimism likely reflects a combination of overestimating the validity of original studies and underestimating the difficulties of repeating their methodologies.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.