Research and Innovation is a key strand to the Liverpool University Hospitals Trust's strategic framework - Our Future Together.
Its aim is to grow its existing portfolio of high-quality research and innovation and provide widened access to research opportunities for our patients and staff through clinical trials and translational research. This will be achieved by embedding a culture of research and innovation across the organisation and by growing our research capacity and capability.
In 1992, St Paul's moved from its Old Hall Street site to the Royal Liverpool University Hospital. The move enabled St Paul's to forge greater relations with other medical specialities and the University of Liverpool to pioneer new detection and diagnostic methods and treatments. Over the years, Liverpool has developed an internationally-acclaimed team of scientists and clinicians focusing on the prevention of vision loss through a combination of excellent general and specialist services, and fundamental and translational science. It has the second-largest ophthalmology and vision science group in the UK, and one of the only ocular oncology pathology research units in the world.
The Liverpool Ocular Oncology Centre (LOOC) at St Paul’s Eye Unit led by Professor Heinrich Heimann is one of 4 supra regional highly specialised centres in the UK treating eye cancers, managing almost 50% of the UK’s uveal melanoma cases every year. Here is a very brief outline of one of our biggest impact research projects in this field.
Background
Uveal melanoma is a rare intraocular tumour but is the most common primary eye cancer in adults. Although the eye tumour treatment is usually successful, half of patients die after developing secondary tumours in the liver.
The University of Liverpool, together with its NHS supra regional referral centre for eye cancer at St Paul's Eye Unit spearheaded the development and implementation of prognostic tests to predict the likelihood of developing metastases in individual patients. Metastatic lesions typically develop within the liver and are most successfully treated surgically when detected early, making the development of effective predictive screening tests critical.
Historically, it was not possible to classify patients into high and low risk groups due to imprecise prognostic methods. Therefore, patients were routinely screened for metastases using low resolution imaging techniques (e.g. ultrasound) for approximately ten years following treatment of the primary tumour. Using ultrasound, detection rates of metastatic UM are low, particularly in patients with a large BMI, until there is advanced metastatic disease, making it an inefficient practice. However, by classifying UM patients into high and low-risk groups, appropriate screening practices can be implemented to benefit healthcare providers and patients.
Research in partnership
Professor Sarah Coupland, Professor Azzam Taktak and Dr Antonio Eleuteri of the Liverpool Ocular Oncology Research Group (LOORG) at the University of Liverpool, in collaboration with the clinical teams at LOOC, have shown that by classifying UM patients into high and low metastatic risk groups, appropriate screening can be implemented, benefitting both patients and healthcare providers.
They have spearheaded the development and implementation of prognostic tests to predict the likelihood of metastases in individual patients. Their freely available prognostication tool: 'Liverpool Uveal Melanoma Prognosticator Online' (LUMPO), which is now recommended for use in NICE guidelines, is now being used around the world in ocular oncology units.
In 1999, LOOC was the first ocular oncology centre worldwide to implement cytogenetic prognostic testing for uveal melanoma into routine clinical practice. Since 2013, over 1200 patients have received a LUMPO prognosis, resulting in patient stratification and personalised screening strategies.
Research with impact
Research by Professor Coupland and colleagues has contributed to two key texts - 'Tumour-Node-Metastasis (AJCC) 8th edition' and to the 'WHO Classification of the Tumours of the Eye (4th edition)', which are the globally recognised standard in clinical oncology, guiding patient diagnosis, treatment and prognosis.
These classifications are utilised as clinical prediction factors for risk of metastatic disease, however in an unquantifiable manner. In 2015, the use of stratification tools such as LUMPO were recommended in NICE-accredited guidelines which consolidates clinical and cytogenetic risk factors into an accurate predictive model. To date LUMPO has been applied to an estimated 9000 patients worldwide.
The use of the LUMPO tool has resulted in patient stratification and changes in the management of metastatic screening. It has been demonstrated that patients who undergo surgery following detection of metastasis have a prolonged life expectancy compared to those who do not. Furthermore, there is evidence to suggest that the majority of UM patients feel better for knowing their outlook, even when it is poor.
Use of the tool has led to:
- Cost savings for health services - an estimated £100,000 per year
- Improved quality of life and optimised patient management
- Prolonged life expectancy due to earlier detection and more effective treatment of metastasis - a recent audit at University Hospital Southampton found that patients who received a LUMPO prognosis survived longer on average than those referred for treatment of metastatic disease.
"Using the LUMPO prognosticator patients can be stratified in a more trusted and appropriate fashion. Patients will immediately benefit from reduced anxiety levels and those deemed high-risk can start to take steps to prepare for what may happen in the future without the same shadow of doubt. For medical teams this is invaluable at a time where resources are stretched. Firstly, the right patients receive regular scans so that clinic time can be reduced and, secondly, the scanning regimen is determined by clinical need and strongly justified and underpinned by LUMPO."OcuMel-UK Managing Director (patient support group).