Evidence map›Paper›PMID 37202547›Full record

ReviewReviews in endocrine & metabolic disorders2023

Individualised prescription of medications for treatment of obesity in adults.

Samantha Hocking, Priya Sumithran

Open access · hybridAbstract readReview
In one paragraph

Review in Reviews in endocrine & metabolic disorders, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.9field-weighted citation impact, top 10% of its field
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

8 citing papers in PubMed, 12 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Pathophysiology of Maternal Obesity and Hypertension in Pregnancy.Journal of cardiovascular development and disease · 2025
    Review
  5. Deep phenotyping obesity using EHR data: Promise, Challenges, and Future Directions.medRxiv : the preprint server for health sciences · 2024
    Article
  6. Review
  7. Review
  8. Phenotyping the obesities: reality or utopia?Reviews in endocrine & metabolic disorders · 2023
    Review
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

2 authors at 2 institutions in 1 country.

Samantha HockingFaculty of Medicine and Health, University of Sydney, Camperdown, New South Wales, Australia.ORCID http://orcid.org/0000-0002-2514-9392
Priya SumithranDepartment of Medicine, (St Vincent's Hospital), University of Melbourne, VIC, Fitzroy, Australia. priya.sumithran@monash.edu.ORCID http://orcid.org/0000-0002-9576-1050
The University of Melbourne · AUThe University of Sydney · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Obesity continues to increase in prevalence globally, driven by changes in environmental factors which have accelerated the development of obesity in individuals with an underlying predisposition to weight gain. The adverse health effects and increased risk for chronic disease associated with obesity are ameliorated by weight loss, with greater benefits from larger amounts of weight reduction. Obesity is a heterogeneous condition, with the drivers, phenotype and complications differing substantially between individuals. This raises the question of whether treatments for obesity, specifically pharmacotherapy, can be targeted based on individual characteristics. This review examines the rationale and the clinical data evaluating this strategy in adults. Individualised prescribing of obesity medication has been successful in rare cases of monogenic obesity where medications have been developed to target dysfunctions in leptin/melanocortin signalling pathways but has been unsuccessful in polygenic obesity due to a lack of understanding of how the gene variants associated with body mass index affect phenotype. At present, the only factor consistently associated with longer-term efficacy of obesity pharmacotherapy is early weight loss outcome, which cannot inform choice of therapy at the time of medication initiation. The concept of matching a therapy for obesity to the characteristics of the individual is appealing but as yet unproven in randomised clinical trials. With increasing technology allowing deeper phenotyping of individuals, increased sophistication in the analysis of big data and the emergence of new treatments, it is possible that precision medicine for obesity will eventuate. For now, a personalised approach that takes into account the person's context, preferences, comorbidities and contraindications is recommended.

Indexed as

ObesityWeight LossComorbidityHumansObesity medicationsPharmacotherapyPrecision medicineWeight loss

Identifiers

PMID37202547
PMCPMC10492708
OpenAlexW4377047194

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.