Predicting survival outcomes for patients with a new diagnosis of cancer
What is the aim of the study and why is it important?
Outcomes for patients with cancer in the UK tend to be worse than those for similar developed countries worldwide. The reason for this isn’t fully understood but may reflect delays in diagnosis and variations in uptake of cancer treatments. Improving cancer survival is a key challenge identified in 'Improving outcomes: a strategy for cancer' (Department of Health 2011) since it has been estimated that if cancer survival was made comparable with the European average then 5000 cancer deaths could be avoided annually.
In this study we will use data from primary care linked to cancer registrations, mortality and hospital episode statistics to identify factors associated with variations in cancer survival. We will classify cancers into the most common cancers in men and women including the following colorectal, lung, gastric, oesophageal cancer, liver cancer, brain cancer, skin cancer, pancreas, ovary, uterine, cervix, and prostate. Using the linked data, we will be able to investigate the contribution of demographic characteristics (including age, sex, deprivation, ethnicity), co-morbidity, concurrent medication, stage and grade of tumour (where recorded) and selected cancer treatments (mainly operative procedures as identified on hospital data).
Once the key factors have been identified, we will identify those factors which are most predictive of variation in cancer survival in order to develop and validate a predictive tool to quantify cancer survival taking account of those factors at individual level. This can then be used to help provide better information to patients and their clinicians.
How is the research being done?
This is a study to describe the development and validation of a set of prediction equations to quantify absolute survival for patients with different types of cancers taking account of other clinical factors available through routine linkage of cancer registry data to primary care electronic health records. We will also include estimates of conditional survival since it may be a more accurate measure of survival among those surviving the first year, especially when the initial prognosis is poor, such as with advanced stage colorectal cancer. Such estimates can be used to provide better information for patients and doctors to help inform treatment and other life decisions
Professor Julia Hippisley-Cox
Location of research
Date on which research approved
Project reference ID
Generic ethics approval reference
Are all data accessed are in anonymised form?
Brief summary of the dataset to be released (including any sensitive data)
Risk factors and symptoms which affect the survival for people who have a diagnosis of cancer. This is linked to diagnoses of cancer from GP, hospital, mortality and cancer records.
Professor Julia Hippisley-Cox (Chief Investigator), Professor Carol Coupland
Date research project approved
Development and validation of risk prediction equations to estimate survival in patients with colorectal cancer: cohort study
Authors: Hippisley-Cox J, Coupland C.
Ref: BMJ 2017;357 doi: 10.1136/bmj.j2497