Development of a core patient-centred outcome set for adults living with obesity: a modified delphi-based international consensus
Bibliographic record
Abstract
Background: Obesity is a chronic disease linked to over 200 health conditions, reduced quality of life, and increased mortality. Despite the availability of multimodal treatments, there is a lack of standardised, patient-centred outcome measures to effectively assess and improve clinical care. This project aimed to define a core set of standardised outcome measures for adults with obesity, incorporating both patient-reported and clinician-reported outcomes. Additional objectives included determining the optimal measurement frequency and identifying case-mix variables essential for risk adjustment. Methods: The International Consortium for Health Outcomes Measurement (ICHOM) established the Obesity Working Group (OWG), composed of 29 international experts and individuals living with obesity. Members were selected based on their expertise in obesity care and research and represented 21 countries. The development process, conducted from May 2023 to July 2024, began with a kick-off meeting to define scope, followed by eight virtual meetings. A comprehensive literature review informed the identification of relevant clinical outcomes, patient-reported outcomes, treatment-related complications, and case-mix variables. A three-round Delphi process was used to reach consensus on key outcomes and follow-up intervals. Outcomes were included in the final set if at least 80% of OWG members rated them between 7 and 9 on a 9-point scale. Validation was conducted through surveys with 95 patients and 106 healthcare professionals from fields such as dietetics, obesity medicine, and general practice. Findings: The OWG developed a standardised set of 20 outcome measures, comprising 17 core measures and 3 population-specific measures. These span domains including physical health, psychosocial well-being, health behaviours, body functioning, and adverse events. Specific measures were also developed for bariatric surgery and female reproductive health (both pregnant and non-pregnant individuals). Key case-mix factors and appropriate follow-up periods were defined to support global consistency in reporting. Interpretation: Adoption of this standardised outcome set enables clinicians, patients, and stakeholders to identify care gaps, monitor outcomes, and evaluate the quality of obesity care against global benchmarks. Implementation can support the creation of a robust international data resource to guide research, inform clinical practice, and shape policy and guidelines for adult obesity treatment. Limitations include limited geographical diversity in validation surveys, the exclusion of internalised weight bias due to a lack of validated measurement tools, and limited applicability to individuals with obesity and multiple comorbidities. Funding: Novo Nordisk, Eli Lilly, and Boehringer Ingelheim International GmbH.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.261 | 0.204 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.008 | 0.004 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.006 | 0.020 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
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.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".