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PREDICT is a prognostication and treatment benefit decision aid aimed at aiding the breast cancer multi-disciplinary team in the management of women with early breast cancer. The user-friendly, web-based tool was developed in collaboration with the Cambridge Breast Unit multi-disciplinary team, the Eastern Cancer Registration and Information Centre. Implemented online, PREDICT is hosted on a NHS web-server. Since 2012 PREDICT has been used widely by clinicians throughout the UK and world-wide.
Basic and applied research at the University of Cambridge has culminated in a widely-used risk prediction algorithm ("BOADICEA") for familial breast and ovarian cancer. This user-friendly web-based tool predicts the likelihood of carrying mutations in breast and ovarian cancer high-risk genes (BRCA1 and BRCA2), and the risks of developing breast or ovarian cancer. BOADICEA has been adopted by several national bodies including NICE in the UK (2006 until present), the American Cancer Society and the Ontario Breast Screening Program (both since 2011) for identifying women who would benefit from BRCA1/2 mutation screening, intensified breast cancer screening and chemoprevention.
Impact: Health and welfare; additional effective therapy for women with advanced, HER2+ breast cancer.
Significance: Allows approximately 10,000 patients a year, whose disease is no longer being controlled by trastuzumab, to receive a more effective therapy than chemotherapy with capecitabine alone.
Beneficiaries: Patients with incurable metastatic HER2+ subtype breast cancer; policy-makers; commerce.
Attribution: Cameron (UoE) was joint chief-investigator on the global pivotal registration trial that led to the marketing authorisation of the drug lapatinib in combination with capecitabine.
Reach: World-wide: the drug is approved in >100 countries and generated >£650M in sales for manufacturer GlaxoSmithKline.
Loudness is the subjective magnitude of a sound as perceived by human listeners and it plays an important role in many human activities. It is determined jointly by the physical characteristics of a sound and by characteristics of the human auditory system. A model for predicting the loudness of sounds from their physical spectra was developed in the laboratory of Professor Brian Moore with support from an MRC programme grant.
The model formed the basis for an American National Standard and is currently being prepared for adoption as a standard by the International Organization for Standardisation (ISO). In addition, the model has been widely used in industry worldwide for prediction of the loudness of sounds, for example: noise from heating, ventilation and air-conditioning; inside and outside cars, and from aircraft; and from domestic appliances and machinery.
Now-casting is the prediction of the present, the very near future, and the very recent past. It has been developed within a research programme led by Lucrezia Reichlin at LBS. It is relevant because key economic statistics, particularly quarterly measures such as GDP, are available only with a delay. Now-casting exploits information which is published early and at higher frequencies than the target variable and generates early estimates before the offb01cial fb01gures become available.
Now-casting has signifb01cant infb02uence and impact. The techniques reported in this case study are in widespread use by central banks and policy institutions. Furthermore, this research has achieved successful commercial impact via Now-Casting Economics Limited.
The School of Mathematics at Cardiff University has developed important statistical and mathematical models for forecasting consumer buying behaviour. Enhancements to classical models, inspired by extensively studying their statistical properties, have allowed us to exploit their vast potential to benefit the sales and marketing strategies of manufacturing and retail organisations. The research has been endorsed and applied by Nielsen, the #1 global market research organisation that provides services to clients in 100 countries. Nielsen has utilised the models to augment profits and retain their globally leading corporate position. This has led to a US$30 million investment and been used to benefit major consumer goods manufacturers such as Pepsi, Kraft, Unilever, Nestlé and Procter & Gamble. Therefore the impact claimed is financial. Moreover, impact is also measurable in terms of public engagement since the work has been disseminated at a wide range of national and international corporate events and conferences. Beneficiaries include Tesco, Sainsbury's, GlaxoSmithKline and Mindshare WW.
The core target in the government's national strategy for cancer control in England is to `save 5,000 lives a year by 2015'. This target was taken directly from research done by LSHTM showing that 10,000 cancer-related deaths per annum would be avoidable if five-year relative survival were as high as the highest levels observed in Europe. Current government strategy is entirely focused around `halving the gap' in avoidable premature cancer deaths identified in this research, which also forms the basis for England's National Awareness and Early Diagnosis Initiative.
Breast cancer affects 1/9 women accounting for significant healthcare resources. The Centre for Magnetic Resonance Investigations in Hull have demonstrated that the addition of MRI to conventional triple assessment does not reduce the re-operation rate for most patients, but instead exposes them to unnecessary investigations. These studies have underpinned the formulation of British, European and American Guidelines on optimal utilisation of MRI in women with early breast cancer scheduled for local excision. The knowledge is widely available on Cancer Help web-sites, helping patients to understand their treatment better. The resulting changes in clinical practice have reduced delays in surgery improving patient treatment whilst saving healthcare resources.
This impact case study is based on a Knowledge Transfer Partnership (KTP) between the School of Mathematics, Statistics and Actuarial Science, University of Kent and KROHNE Ltd, a world leading manufacturer of industrial measuring instruments. These precision instruments (typically flow meters and density meters) need to be calibrated accurately before being used and this is an expensive and time-consuming process.
The purpose of the KTP was to use Bayesian methodology developed by Kent statisticians to establish a novel calibration procedure that improves on the existing procedure by incorporating historical records from calibration of previous instruments of the same type. This reduces substantially the number of test runs needed to calibrate a new instrument and will increase capacity by up to 50%.
The impact of the KTP, which was graded as `Outstanding', has been to change the knowledge and capability of the Company, so that they can improve the performance of their manufacturing process by implementing this novel calibration method. This has been achieved by adapting the underpinning Kent research to the specific context of the calibration problem, by running many calibrations to demonstrate the effectiveness of the method in practice, and by supporting the implementation of the new calibration method within the Company's core software.
Moreover, the project has changed the Company's thinking on fundamental science, particularly industrial mathematics. The value of historical data, and the usefulness of Bayesian methods, is now widely appreciated and training for staff in Bayesian Statistics is being introduced. Thus the project has not only changed the protocols of the Company, it has also changed their practice.
The research led by Professor Graham Ball at Nottingham Trent University has developed new bioinformatics techniques for mining complex post genomic bio-profile data. The approach allows development of predictive models to answer clinical questions using an optimum biomarker panel. The impact of this work is through the filing of four patents associated with algorithms, breast cancer and tuberculosis, subsequently licensed to a spin-out company. To date three clinical trials have been supported with others in the pipeline. Through the spin-out company the approach is being applied to stratify patients in clinical collaborations and to optimise biomarker panels for diagnostics companies.