Evidence map›Paper›PMID 35916901›Full record

ReviewDiabetologia2022

Personalised prevention of type 2 diabetes.

Nicholas J Wareham

Registry-linked trialAbstract readReview
In one paragraph

Review in Diabetologia, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06513026 (Milk for Diabetes Prevention), which is not on this map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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.

NCT06513026 narecruitingnot on this mapstarted 2026, after this paper: background citation

Milk for Diabetes Prevention

TypeinterventionalSponsorAlbert Einstein College of MedicineRan2026 to 2028Enrolled40ConditionsLactose Intolerance, Lactose Intolerant, Lactase Persistence, Pre-DiabetesArmsLactose-Containing Milk, Lactose-Free Milk
3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Trial
  2. Trial
  3. Review
  4. Article
  5. Use of technology in prediabetes and precision prevention.Journal of diabetes investigation · 2025
    Review
  6. Article
  7. Observational
  8. Article
  9. Review
  10. 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

1 author.

Nicholas J WarehamMedical Research Council Epidemiology Unit, Institute of Metabolic Science, University of Cambridge Clinical School, Cambridge, UK. Nick.wareham@mrc-epid.cam.ac.uk.

Funding

Medical Research Council MC_UU_00006/1
6 · The paper itself

Abstract

It is well established from clinical trials that behavioural interventions can halve the risk of progression from prediabetes to type 2 diabetes but translating this evidence of efficacy into effective real-world interventions at scale is an ongoing challenge. A common suggestion is that future preventive interventions need to be more personalised in order to enhance effectiveness. This review evaluates the degree to which existing interventions are already personalised and outlines how greater personalisation could be achieved through better identification of those at high risk, division of type 2 diabetes into specific subgroups and, above all, more individualisation of the behavioural targets for preventive action. Approaches using more dynamic real-time data are in their scientific infancy. Although these approaches are promising they need longer-term evaluation against clinical outcomes. Whatever personalised preventive approaches for type 2 diabetes are developed in the future, they will need to be complementary to existing individual-level interventions that are being rolled out and that are demonstrably effective. They will also need to ideally synergise with, and at the very least not detract attention from, efforts to develop and implement strategies that impact on type 2 diabetes risk at the societal level.

Indexed as

Diabetes Mellitus, Type 2Precision MedicineHumansPersonalised medicinePersonalised preventionPrecision medicinePreventionReviewType 2 diabetes

Identifiers

PMID35916901
PMCPMC9522721

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 Socratic graph.