Due to improvements in cancer diagnosis and medical care, nowadays many patients who experience cancer survive and live to an older age. However, it is unclear whether people who survive cancer are more likely to experience other health problems (such as bone fractures or develop diabetes) Due to the ageing population, there is also an increasing number of patients diagnosed with cancers at an older age. It is also unclear whether older people with cancer should be treated in the same way as younger people, or whether other treatments are more beneficial for older cancer patients. Therefore, this study aims to find out how experiencing cancer affects the chances of developing other health problems by comparing the occurrence of these events between cancer survivors to individuals without a history of cancer. We also plan to examine the effects and related costs of different treatments for patients with breast cancer or lung cancer and compare the results between older and younger cancer patients.
With advances in cancer diagnosis and treatments, the life expectancy of people who experience cancer has significantly increased but the epidemiology of other chronic diseases after cancer treatment and associated the risk factors is still under-studied. In addition, an increasing number of patients are diagnosed with cancer at an older age (e.g. breast cancer) due to the ageing population and the growing innovative treatments applied to cancer care (e.g. for lung cancer) have resulted in marked increases in healthcare costs. Examining the clinical and cost effectiveness of different treatment strategies for cancer considering the age and cancer staging of patients will help to inform the future development of treatment stratification tools to optimise cancer treatments. This study aims to investigate the risk of bone fracture and endocrine disorders in patients surviving following the treatment of site-specific cancers and evaluate the treatment pathways and medical resource use in adult patients with lung and breast cancer. A retrospective matched cohort study design will be used to compare the incidence of bone fracture and endocrine disorders in cancer survivors and their age, gender and practice-matched controls (1:5 matching) and the association between different site-specific cancers and risks of bone fracture or endocrine disorder events will be estimated. Cox proportional hazard models will calculate the hazard ratios for each outcome comparing survival in cancer survivors and control patients. For those cohorts of patients with breast or lung cancers, we will examine other clinical outcomes (all-cause mortality and cancer-specific mortality, survival time) and health resource use taking account of different treatment strategies. Cox proportional hazards models will be used to analyse the mortality outcomes and generalized linear models will be used to analyse the costs by adjusting for relevant factors, such as cancer staging. The results will provide evidence to inform clinical decision-making in relation to treatment optimisation for cancer patients.
The primary outcome of this study is the incidence of mortality and morbidity associated with cancer (e.g. cancer-related and all-cause mortality; cancer progression, recurrence or metastasis of cancer) or development of other specific conditions, namely bone disorders (fractures, osteoporosis, osteopenia); diabetes and endocrine disorders (hypopituitarism, adrenal failure (Addison?s), Adrenocorticotropic hormone (ACTH) deficiency, hypogonadism, hypothyroidism).
The secondary outcomes of interests include the treatment strategies for patients with either breast or lung cancer (i.e. initial and subsequent treatments and the combinations of different treatment strategies), treatments for concomitant conditions, and medical resources use (e.g. referral, admission to accident and emergency; all-cause hospitalisation; secondary care outpatient visit; primary care visit; medicine prescriptions).
Li-Chia Chen - Chief Investigator - University of Manchester
Yubo Wang - Corresponding Applicant - University of Manchester
Cheryl Jones - Collaborator - University of Manchester
Christos Grigoroglou - Collaborator - University of Manchester
Claire Higham - Collaborator - The Christie NHS Foundation Trust
Darren Ashcroft - Collaborator - University of Manchester
Douglas Steinke - Collaborator - University of Manchester
Katherine Payne - Collaborator - University of Manchester
Matthew Carr - Collaborator - University of Manchester
Safwaan Adam - Collaborator - The Christie NHS Foundation Trust
Salina Tsui - Collaborator - The Christie NHS Foundation Trust
Sean Gavan - Collaborator - University of Manchester
Teng-Chou Chen - Collaborator - University of Manchester
Thamer Ba Dhafari - Collaborator - University of Manchester
Thomas Allen - Collaborator - University of Manchester
Victoria Chatzimavridou-Grigoriadou - Collaborator - The Christie NHS Foundation Trust
Alex Trafford - Collaborator - University of Manchester
Stuart Wright - Collaborator - University of Manchester
HES Accident and Emergency;HES Admitted Patient Care;HES Outpatient;NCRAS Cancer Registration Data;NCRAS National Radiotherapy Dataset (RTDS) data;NCRAS Systemic Anti-Cancer Treatment (SACT) data;ONS Death Registration Data;Patient Level Index of Multiple Deprivation