Patients with acute psychiatric symptoms are often referred to the emergency department (ED) for medical evaluation to exclude medical causes before psychiatric admission. The absence of a prospectively validated medical screening tool leads to wide practice variation. This study aims to develop a new, evidence-based and consensus-based medical screening tool through a collaborative, interdisciplinary, international Delphi approach.

This modified Delphi study will include representatives from emergency medicine and psychiatry societies across four continents, as well as patient representatives with prior experience of medical screening in the ED. A minimum sample size of 24 participants is planned to account for potential dropouts. The Delphi procedure consists of four rounds. Round 1 will present current evidence and identify key items for the new medical screening tool. Round 2 will evaluate and refine statements from Round 1. Round 3 will seek consensus on the variables to be included in a medical screening tool. In Round 4, hypothetical clinical vignettes will be used to assess the agreement on the recommendations of the newly developed medical screening tool in order to test for content and construct validity. Surveys will be conducted via Research Electronic Data Capture (REDCap), with participants rating statements on a 6-point Likert scale. Response stability will be evaluated using the intraclass correlation coefficient, and consensus defined as ≥80% agreement. Results will be reported according to the ACcurate COnsensus Reporting Document guidelines and the Guidance for Reporting Involvement of Patients and the Public 2 short form.

The Ethics Committee of Northwestern and Central Switzerland exempted the project from committee approval under the Human Research Act on 11 September 2024. Written consent will be obtained from all participants. Results of this study will be summarised as a medical screening tool which will be validated in a prospective, multicentre study in a second step.

NCT06936826.

To quantify and describe the use of real-world data (RWD) in National Institute for Health and Care Excellence (NICE) oncology technology appraisal (TA) final appraisal determination documents.

A systematic literature review was conducted on pharmaceutical NICE oncology TAs published between April 2000 and March 2024 (covering financial years 2000/2001 to 2023/2024 inclusive) extracted on 22 August 2023 (2000/2001 - 2022/2023) and 8 August 2024 (2023/2024).

NICE TA final appraisal determination documents.

All pharmaceutical oncology TAs published between April 2000 and March 2024 (financial years 2000/2001 to 2023/2024) that did not go on to be terminated.

The data required for eligibility screening was extracted from an Excel file directly from the NICE website, where data related to each TA was extracted using an automated script derived from published sources. TAs were assessed based on prespecified review criteria covering whether an RWD submission was reported by the committee, and if so, which RWD sources were used, alongside the methods reported and any feedback from the committee regarding the use of RWD. Bias was not assessed as part of the study.

Of 310 TAs identified, 135 (48.0%) used RWD. A variety of RWD types were used, mostly from UK or US data sources. 47 TAs (34.8%) leveraged RWD from multiple sources. RWD was mostly used in comparisons of survival (41.5%), to inform utility values (26.7%) and to compare baseline characteristics (19.3%), with matched adjusted indirect comparisons (MAICs) and external control arms (ECAs), seen from 2015 and 2018, respectively. The committee expressed concerns around the RWD presented by the company in 53 TAs (39.2%), the most common being a lack of generalisability to the UK population and/or National Health Service practice and comprehensiveness of the RWD.

This study quantifies the increasing use of diverse RWD sources in NICE oncology TAs, as well as the shift towards more complex methods like MAICs and ECAs. The feedback of the NICE committee highlights key areas of improvement as the generalisability and maturity of the RWD presented.

Severe mental disorders are associated with increased risk of metabolic dysfunction. Identifying those subgroups at higher risk may help to inform more effective early intervention. The objective of this study was to compare metabolic profiles across three proposed pathophysiological subtypes of common mood disorders (‘hyperarousal-anxious depression’, ‘circadian-bipolar spectrum’ and ‘neurodevelopmental-psychosis’).

751 young people (aged 16–25 years; mean age 19.67±2.69) were recruited from early intervention mental health services between 2004 and 2024 and assigned to two mood disorder subgroups (hyperarousal-anxious depression (n=656) and circadian-bipolar spectrum (n=95)). We conducted cross-sectional assessments and between-group comparisons of metabolic and immune risk factors. Immune-metabolic markers included body mass index (BMI), fasting glucose (FG), fasting insulin, Homeostasis Model Assessment-Insulin Resistance (HOMA2-IR), C reactive protein and blood lipids.

Individuals in the circadian-bipolar spectrum subgroup had significantly elevated FG (F=5.75, p=0.04), HOMA2-IR (F=4.86, p=0.03) and triglycerides (F=4.98, p=0.03) as compared with those in the hyperarousal-anxious depression subgroup. As the larger hyperarousal-anxious depression subgroup is the most generic type, and weight gain is also a characteristic of the circadian-bipolar subgroup, we then differentiated those with the hyperarousal-anxious subtype on the basis of low versus high BMI (2 vs ≥25 kg/m², respectively). The ‘circadian-bipolar’ group had higher FG, FI and HOMA2-IR than those in the hyperarousal-anxious-depression group with low BMI.

Circadian disturbance may be driving increased rates of metabolic dysfunction among youth with emerging mood disorders, while increased BMI also remains a key determinant. Implications for assessment and early interventions are discussed.