2024-25 Project (Forbes & Carreira & Bhaskaran)

Exploring long-term mental health, quality of life and cognitive health outcomes among cancer survivors.

SUPERVISORY TEAM

Supervisor

Dr Harriet Forbes at LSHTM
Email: harriet.forbes@lshtm.ac.uk

Co-Supervisor

Dr Helena Carreira at LSHTM
Email: Helena.Carreira@lshtm.ac.uk

Co-Supervisor

Professor Krishnan Bhaskaran at LSHTM
Email: krishnan.bhaskaran@lshtm.ac.uk

PROJECT SUMMARY

Project Summary

Cancer treatments are improving and more people are living for many years following cancer. However, the effects of the cancer itself and the anti-cancer treatments can have important impacts on longer-term health and wellbeing.   Previous research has shown that mental health, cognitive and quality of life related outcomes such as chronic pain are key concerns for cancer survivors, with evidence of raised risks.    Electronic healthcare records with linkages to cancer registrations and new sources of cancer treatment data offer a great opportunity to investigate how these outcomes are associated with cancer history, and cancer treatment.    There are several methodological challenges, such as defining and validating outcomes; quantifying potential biases due to inconsistent reporting and differential detection in cancer survivors; processing complex cancer treatment data; addressing confounding by indication when investigating treatment questions; and considering the impact of survivorship bias.    This PhD will develop optimal methods for the investigation of cancer-related effects on mental health and related outcomes, including an opportunity to apply methods to a topical and important clinical question in this field.

Project Key Words

EHR data; cancer; statistics; mental health; cognition; quality of life.

MRC LID Themes

  • Global Health = No
  • Health Data Science = Yes
  • Infectious Disease = No
  • Translational and Implementation Research = No

Skills

MRC Core Skills

  • Quantitative skills = Yes
  • Interdisciplinary skills = No
  • Whole organism physiology = No

Skills we expect a student to develop/acquire whilst pursuing this project

– Obtaining ethical approval to utilise electronic healthcare data 
– Designing epidemiological studies 
– Management of large-scale health datasets 
– Advanced coding in software packages such as STATA  
– Statistical analysis of longitudinal data  
– Identifying best methods to deal with confounding and bias in electronic healthcare record data 
– Writing papers for publications 
– Presenting scientific work at relevant conferences 
– Engaging with the public to develop and disseminate their work

Routes

Which route/s is this project available for?

  • 1+4 = No
  • +4 = Yes

Full-time/Part-time Study

Is this project available for full-time study? Yes
Is this project available for part-time study? Yes

Eligibility/Requirements

Particular prior educational requirements for a student undertaking this project

  • LSHTM’s standard institutional eligibility criteria for doctoral study.
  • Masters-level training in epidemiology or statistics

Other useful information

  • Potential CASE conversion? = No

PROJECT IN MORE DETAIL

Scientific description of this research project

Background: 
Cancer treatments have improved dramatically and many more people are surviving for many years after cancer.  However, cancer itself, and anti-cancer treatments, can lead to long term impacts, particularly on mental health, cognition and quality of life. These impacts are cited as among the most important concerns to cancer survivors. Electronic health records data allow us to quickly assemble large cohorts of cancer survivors with long follow-up, presenting an ideal opportunity to study these outcomes, but working with large-scale real-world data presents a number of methodological challenges.   

Project objectives 
– To investigate the associations between cancer survivorship and a range of mental health, cognitive and quality of life related outcomes. 
– To identify optimal methods to define mental health/cognitive outcomes, and to deal with key potential sources of error such as survivorship bias and confounding by indication.   

Techniques to be used 
– Literature review:  
– Definitions and algorithms will be developed to best define the outcomes under investigation.  
– Advanced statistical and epidemiological methods to minimise bias and confounding, and to quantify residual bias through quantitative bias analysis.    

Confirmed availability of any required databases or specialist materials 
Electronic health record data from the UK will be made available. This is called the Clinical Practice Research Datalink (CPRD) and has linked data to Hospital Episode Statistics, Office of National Statistics, and Cancer Registries.   

Potential risks to the project and plans for their mitigation 
LSHTM has continuously held a license for Clinical Practice Research Datalink (CPRD) and linked datasets for over 10 years, so risks for accessing UK data are minimal. In theory, there is a risk of a shortfall in funding preventing renewal of the LSHTM CPRD licence. We have budgeted for a contribution to licence costs from the RTSG; a fallback option would be to instead use these funds to access alternative data resources for this specific project, such as The Health Improvement Network (THIN), OpenSAFELY, or relevant cohort data such as UK Biobank.

Further reading

(Relevant preprints and/or open access articles)

Additional information from the supervisory team

MRC LID LINKS