In a small percentage of patients, pulmonary nodules found on CT scans are early lung cancers. Lung cancer detected at an early stage has a much better prognosis. The British Thoracic Society guideline on managing pulmonary nodules recommends using multivariable malignancy risk prediction models to assist in management. While these guidelines seem to be effective in clinical practice, recent data suggest that artificial intelligence (AI)-based malignant-nodule prediction solutions might outperform existing models.

This study is a prospective, observational multicentre study to assess the clinical utility of an AI-assisted CT-based lung cancer prediction tool (LCP) for managing incidental solid and part solid pulmonary nodule patients vs standard care. Two thousand patients will be recruited from 12 different UK hospitals. The primary outcome is the difference between standard care and LCP-guided care in terms of the rate of benign nodules and patients with cancer discharged straight after the assessment of the baseline CT scan. Secondary outcomes investigate adherence to clinical guidelines, other measures of changes to clinical management, patient outcomes and cost-effectiveness.

This study has been reviewed and given a favourable opinion by the South Central—Oxford C Research Ethics Committee in UK (REC reference number: 22/SC/0142).

Study results will be available publicly following peer-reviewed publication in open-access journals. A patient and public involvement group workshop is planned before the study results are available to discuss best methods to disseminate the results. Study results will also be fed back to participating organisations to inform training and procurement activities.

NCT05389774.

Existing literature examines barriers to the provision of ethnically diverse dietary advice, however, is not specific to total diet replacement (TDR). There is a lack of literature from the UK, limiting the potential applicability of existing findings and themes to the UK context. This study addresses this gap in research by interviewing participants of South Asian ethnicity who have undertaken the National Health Service (NHS) low-calorie diet programme (LCD) for people with type 2 diabetes living with overweight or obesity. This study explores factors that may affect the uptake and acceptability of its TDR, food reintroduction and weight maintenance stages. This aims to provide rich data that can inform effective tailoring of future programmes with South Asian participants.

To explore the perspectives of individuals of South Asian ethnicity on an NHS programme using TDR approaches for the management of type 2 diabetes (T2D).

Qualitative study.

Individuals in the community undertaking the NHS LCD programme.

Twelve one-to-one interviews were conducted with individuals from a South Asian ethnicity participating in the NHS LCD.

Qualitative semistructured interviews conducted through different stages of the programme. Reflexive thematic analysis was used to analyse the transcripts.

Key themes highlighted positive and negative experiences of the programme: (1) more work is needed in the programme for person centeredness; (2) it is not the same taste; (3) needing motivation to make changes and feel better; (4) a mixed relationship with the coach; (5) social experiences; (6) culture-related experiences.

This study provides important experience-based evidence of the need for culturally tailored T2D programmes. Action to address these findings and improve the tailoring of the NHS LCD may improve experience, retention and outcomes on the programme for people of South Asian ethnicity and thereby reduce inequalities.