Title: Improving statistical methods for individualised predictions and understanding population variation in survival for colorectal cancer patients.
Funder: Department of Health and Social Care

Abstract: BackgroundColorectal cancer is the fourth most common cancer in the UK for both males and females with approximately 41,000 new cases diagnosed each year. Despite the severity of the disease and the significant efforts that have been made, there is still a strong demand for better understanding of the disease. There is large variation in treatment, prognosis and outcomes following a colorectal cancer diagnosis and further research should focus in investigating the determinants of this variation. Furthermore, there is an emerging need to understand the prognostic factors that affect each patient's prognosis and progress of disease.AimsThe project aims to improve understanding and communication surrounding colorectal cancer by exploring variation in survival with the ultimate aim of improving clinical management by making use of a unique data resource. This will be achieved by developing and applying new statistical methods. The research to be undertaken will investigate colorectal cancer both at the individual and population level. To ensure the use of the findings in practice, a free access webtool will be developed to present results in ways that are easy to understand.Plan of investigationThe project can be summarised into three clinical (C1-C3) and three methodological components (M1-M3) that will help answer these clinical questions.C1 Develop and validate prognostic models for colorectal cancer patients for use in improving the clinical management, including making treatment decisions and communicating the impact of a diagnosis of cancer. (Individual level)C2 Explore the underlying determinants of inequalities seen across population groups through the extension and development of methods for mediation analysis. (Population level)C3 Communication of results to healthcare professionals, patients, scientists and decision-makers through developing webtools. (Both individual and population level)M1 - Development and evaluation of multiple imputation approaches in the context of time-to-event data to feed into the models developed for C1 and C2.M2 Development and application of standardised (marginal) survival estimates for use in both individual and population predictions (see C1 and C2), including mediation analysis approaches.M3 Further development of methods for the estimation of loss in expectation of life, a measure that will be used both as an output of the prognostic model (C3) and the marginal estimates obtained in the mediation analysis (C2).Patient and NHS benefitThe developed webtool will improve understanding and communication of colorectal cancer prognosis. The prognostic model will make it possible for clinicians and patients to obtain a patient's specific prognosis and to base decisions such as choosing the optimal available treatment around the most appropriate data possible. The findings from the mediation analysis will detect the determinants for the observed inequalities across population groups. Thus, those with the worst prognosis will be targeted and the best policy interventions to alter modifiable factors can be identified and introduced in order to decrease inequalities.The methods developed as part of this proposal will also be applicable in other clinical settings and relevant software will be developed to help their wider application. The available methods will encourage research for other clinical areas and eventually benefit more patients.

Lay abstract: Colorectal cancer (CRC) is the fourth most common cancer and accounts for 12% of all new cancer cases in the UK with around 41,000 new cases per year, i.e. 110 cases diagnosed each day. The number of CRC new cases has increased by 14% in Great Britain since the late 1970s, with current annual detection and management costs reaching approximately 1.1 billion. CRC incidence (new cases) and prognosis (outcome) vary according to many characteristics such as sex, age, stage at diagnosis and deprivation group. In particular, CRC is more common among men, in ages 70 and over and in the most deprived areas. The prognosis of cancer for each patient depends on the individual and cancer characteristics and can differ greatly among patients. CRC prognosis also varies significantly by population groups. For example, those who live in poor areas (most deprived) tend to have worse prognosis. Appreciation of the characteristics that drive variation both for individual patients and population groups will enable clinicians to make better informed decisions for patients and will lead to targeted interventions that reduce inequality and improve life expectancy for the most vulnerable groups in society. A unique and rich data resource of over 500,000 individuals, CORECT-R, which is available provides an ideal opportunity for exploring this variation. CORECT-R covers all CRC patients diagnosed from 1998 in the UK and will be updated during the fellowship. The dataset consists of detailed information on cancer (e.g. stage, grade, tumour type and size) and patient characteristics (including comorbidity). Aims and Methods This project aims to develop and apply statistical methods to report and understand variation and eventually address important clinical questions. At the individual level (for individual patients), a detailed, up-to-date prognostic model for CRC will be developed, specifically tailored to UK patients. In prognostic models, specific information about the patient, rather than subgroups of the population, are used. Prognostic models provide scores that enable the prediction of the risk of future events for a patient. For example, the developed model could predict the probability of being alive 10 years following diagnosis for a 57 year old male diagnosed with colon cancer, with advanced cancer stage and a tumour size of 4.5cm. The model will help clinicians and patients to understand patient risk and will aid in clinical decisions such as identifying the best available treatment. At the population level (for the whole UK population), the project will explore the characteristics that influence differences in prognosis among different groups of CRC patients. Understanding variation of cancer at the population level will help develop and improve policy and awareness campaigns to help eliminate the observed inequalities. For example, if differences in prognosis across deprivation groups are largely driven by differences in stage at diagnosis, then policies could be implemented to encourage earlier detection in the most vulnerable groups. This will be achieved through the development of methods known in statistics as mediation analysis. The complexity of the dataset will introduce some additional challenges and therefore new methods will be developed to enable the clinical aims to be addressed. Such issues include the development of alternative reporting measures for the outcomes so that they are easy to understand and methods for appropriately dealing with missing data in CORECT-R. Dissemination To ensure the widest possible dissemination of the findings, in addition to the papers that will be submitted and the conferences at which I will present my work, I will work with patients to develop a webtool. The webtool will communicate the results obtained from the models developed in this work, with a view to improving the clinical and societal management of the cancer. It will be accessible by scientists, doctors, patients and people involved in decision making. Statistical details will be clearly explained and a specific tool will be aimed at patients. Patient and Public involvement A group of patients has already provided feedback on the designing of this research proposal and I will continue to work with them on the applications of the project and especially for the designing of the webtool. Discussions will involve the measures that should be available to users and will help evaluate the tool's usefulness and clear communication to a broad audience. Advice will also be provided by members of an advisory panel of both scientists and medical experts, who have been carefully selected to ensure that expertise knowledge will be available for each aspect of this project.

Research activity codes: 4.4 POPULATION SCREENING
Health categories: CANCER AND NEOPLASMS