Evidence map›Paper›PMID 32091429›Full record

ArticleEpidemiology (Cambridge, Mass.)2020

Aim for Clinical Utility, Not Just Predictive Accuracy.

Michael C Sachs, Arvid Sjölander, Erin E Gabriel

Abstract read
In one paragraph

Article in Epidemiology (Cambridge, Mass.), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Trial
  2. Trial
  3. Article
  4. Article
  5. Evaluation of clinical utility in emulated clinical trials.European journal of epidemiology · 2026
    Article
  6. Article
  7. Article
  8. Observational
  9. Article
  10. Review
  11. Article
  12. The origins of unpredictability in life outcome prediction tasks.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  13. Article
  14. Can Machine Learning from Real-World Data Support Drug Treatment Decisions? A Prediction Modeling Case for Direct Oral Anticoagulants.Medical decision making : an international journal of the Society for Medical Decision Making · 2022
    Article
  15. Review
  16. Article
  17. 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.

Michael C SachsFrom the Department of Medicine, Solna Eugeniahemmet, T2, Karolinska Universitetssjukhuset, Stockholm, Sweden.
Arvid SjölanderDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
Erin E GabrielDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The predictions from an accurate prognostic model can be of great interest to patients and clinicians. When predictions are reported to individuals, they may decide to take action to improve their health or they may simply be comforted by the knowledge. However, if there is a clearly defined space of actions in the clinical context, a formal decision rule based on the prediction has the potential to have a much broader impact. The use of a prediction-based decision rule should be formalized and preferably compared with the standard of care in a randomized trial to assess its clinical utility; however, evidence is needed to motivate such a trial. We outline how observational data can be used to propose a decision rule based on a prognostic prediction model. We then propose a framework for emulating a prediction driven trial to evaluate the clinical utility of a prediction-based decision rule in observational data. A split-sample structure is often feasible and useful to develop the prognostic model, define the decision rule, and evaluate its clinical utility. See video abstract at, http://links.lww.com/EDE/B656.

Indexed as

Clinical Decision-MakingModels, StatisticalPrognosisHumansObservational Studies as TopicRandomized Controlled Trials as Topic

Identifiers

PMID32091429
PMCPMC7144757

What OpenQuestion holds

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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.