Evidence map›Paper›PMID 33355252›Full record

ReviewCold Spring Harbor perspectives in medicine2021

Triangulating Evidence through the Inclusion of Genetically Informed Designs.

Marcus R Munafò, Julian P T Higgins, George Davey Smith

Abstract readReview
In one paragraph

Review in Cold Spring Harbor perspectives in medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers.

0numbers the graph read from it
0cells of the map it votes in
44citing 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

44 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Estimating returns to education using the genetic lottery.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  6. Article
  7. Article
  8. Article
  9. The rapid growth in Mendelian randomization studies.European journal of epidemiology · 2025
    Article
  10. Article
  11. Chronic low back pain causal risk factors identified by Mendelian randomization: a cross-sectional cohort analysis.The spine journal : official journal of the North American Spine Society · 2025
    Observational
  12. Noise and the risk of tinnitus: A two-sample Mendelian randomized study.World journal of otorhinolaryngology - head and neck surgery · 2025
    Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Mendelian Randomization Analysis of the Causal Effect of Cigarette Smoking on Hospital Costs.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2024
    Article
  19. Article
  20. 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

3 authors.

Marcus R MunafòSchool of Psychological Science, University of Bristol, Bristol BS8 1TU, United Kingdom.
Julian P T HigginsMRC Integrative Epidemiology Unit at the University of Bristol, Bristol BS8 2BN, United Kingdom.
George Davey SmithMRC Integrative Epidemiology Unit at the University of Bristol, Bristol BS8 2BN, United Kingdom.

Funding

Medical Research Council MC_UU_00011/1Medical Research Council MC_UU_00011/7
6 · The paper itself

Abstract

Much research effort is invested in attempting to determine causal influences on disease onset and progression to inform prevention and treatment efforts. However, this is often dependent on observational data that are prone to well-known limitations, particularly residual confounding and reverse causality. Several statistical methods have been developed to support stronger causal inference. However, a complementary approach is to use design-based methods for causal inference, which acknowledge sources of bias and attempt to mitigate these through the design of the study rather than solely through statistical adjustment. Genetically informed methods provide a novel and potentially powerful extension to this approach, accounting by design for unobserved genetic and environmental confounding. No single approach will be absent from bias. Instead, we should seek and combine evidence from multiple methodologies that each bring different (and ideally uncorrelated) sources of bias. If the results of these different methodologies align-or triangulate-then we can be more confident in our causal inference. To be truly effective, this should ideally be done prospectively, with the sources of evidence specified in advance, to protect against one final source of bias-our own cognitions, expectations, and fondly held beliefs.

Indexed as

CausalityGeneticsResearch DesignDisease

Identifiers

PMID33355252
PMCPMC8327826

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.