Mendelian Randomisation and Causal Inference in Observational Epidemiology
Why is this work in the frame?
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
No Canadian affiliation. An affiliation-only frame — the usual design — would never have seen this work. It is one of the works that make the case for inverting the frame.
Machine scores (provisional)
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
- Teacher spread
- 0.210 · how far apart the two teachers sit on this one work
- Validation status
score_only:v0-immature-baseline· verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it
Abstract
The notion of risk is central to epidemiological research, both in its original context of studying conditions thought to be caused by a particular factor and, more broadly, in predicting the probability of a condition for prognostic purposes. For prognostic research, all factors associated with the outcome are of interest, whether they are causal or not. In aetiological research, on the other hand, causality is meaningful. Here, the focus is often on assessing the effect of some modifiable exposure on a disease with a view to informing health interventions at the individual or population level, or health advice for particular risk groups. For such intervention or advice to be effective, it is important to verify that the observed association between the exposure and disease means that the exposure is in fact causal for the disease. For example, once the relationship between periconceptual maternal folate supplementation and risk of neural tube defects was established, the United States, Canada, and Chile implemented mandatory fortification of cereal flour and related foods with folic acid and reported reductions in neural tube defect incidence between 27% and just over 50%. However, observational research has had several high-profile failures when exposures that seemed to affect disease risk were later shown to be non-causal in follow-up randomised controlled trials (RCTs). For instance, observational evidence that seemed to suggest that vitamin E is protective for cardiovascular disease, beta-carotene for cancer, and, more recently, oestrogen for dementia, has now been refuted. Since only candidate causes with the strongest observational support tend to be followed up in RCTs when these are possible, it is likely that many more reported observational findings are not actually causal.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
The record
- Venue
- PLoS Medicine
- Topic
- Genetic Associations and Epidemiology
- Field
- Biochemistry, Genetics and Molecular Biology
- Canadian institutions
- —
- Funders
- European CommissionUniversity of LeicesterMedical Research CouncilGenome Canada
- Keywords
- Mendelian randomizationObservational studyCausal inferenceConfoundingInferenceEpidemiologyMarginal structural modelMedicineBiologyGeneticsComputer scienceInternal medicinePathologyArtificial intelligence
- Has abstract in OpenAlex
- yes