Risk modelling of 90-day mortality following lung resection in the UK
Research type
Research Study
Full title
Risk modelling of 90-day mortality following lung resection in the UK using prospective data
IRAS ID
285398
Contact name
Alan Gopal
Contact email
Sponsor organisation
Hull University Teaching Hospitals NHS Trust.
Clinicaltrials.gov Identifier
n/a, n/a
Duration of Study in the UK
2 years, 0 months, 1 days
Research summary
Lung cancer is associated with very poor survival. Treatment with surgery offers the best opportunity for long-term survival, although less than 20% of patients diagnosed with lung cancer in the UK undergo surgery, as most patients have advanced cancer at the time of diagnosis, despite efforts for earlier detection. Increasing the number of people undergoing surgery whilst also improving outcomes for these patients has already been shown to improve overall survival figures, because if these patients do not die as a result of surgery, they are much more likely to survive to 5 years and beyond in comparison to patients with more advanced lung cancer.\n\nRisk prediction models are used to help with patient selection for surgery and to inform patient consent & decision-making by estimating a patient’s risk of death as a result of surgery. Inaccurate models can cause low-risk patients to be unfairly denied surgery and high-risk patients to be inappropriately selected for surgery. Existing models have been shown to be inaccurate when predicting mortality after thoracic surgery. Our aim is to develop and validate a new risk model specifically for the UK population to predict short-term mortality after thoracic surgery using prospective patient data from several thoracic surgical centres across the UK.\n
REC name
South West - Central Bristol Research Ethics Committee
REC reference
21/SW/0170
Date of REC Opinion
8 Aug 2022
REC opinion
Further Information Favourable Opinion