Reducing Disparities in Cancer Outcomes

Project Details


people have not benefited from the recent improvements in cancer diagnosis and treatment as much as younger patients,
increasing the survival gap. With my interdisciplinary REDICO program I aim to improve cancer outcomes for everyone by
investigating key moments in the cancer pathway where inequalities are likely to occur, namely pre-diagnosis, treatment
decision-making, and active treatment, and to propose recommendations and interventions.
Older adults are a heterogeneous group in terms of health status and fitness. They have unique needs and to address
these, it is crucial to unpack drivers of inequities in cancer outcomes.
Pre-diagnosis: Older adults are more likely to be diagnosed with advanced cancer or in an emergency setting which has
been associated with poor outcomes. One of my aims is therefore to improve early diagnosis. I will investigate factors
influencing time to cancer diagnosis in older adults and develop strategies to reduce the time between the onset of first
symptoms and diagnosis, leading to improved cancer outcomes in older adults.
Treatment decision-making: Clinicians have not historically had access to evidence-based treatment strategies for older
adults because of underrepresentation of older patients in clinical trials. I will use cancer registry data linked to treatment
and hospitalization data to estimate the effect of anti-cancer treatment on toxicity and survival in older patients in England
and Luxembourg to inform treatment.
In addition to improving the quality and types of evidence for treatment decision-making, integrating patient values in a
shared decision-making process is important, particularly because of the complexity of cancer treatment and the high
uncertainty around treatment benefits. Using qualitative (e.g., observation of medical encounters, interviews, and focus
group) and quantitative methods, I will analyze how patient values are integrated in treatment, and how this varies by age.
This will allow me identifying room for improvement and proposing tailored training to medical staff (e.g. health literacy,
ageism awareness).
Active treatment: Chronological age is not a good proxy for physiological age in older patients. However, a comprehensive
geriatric assessment to assess older patients’ fitness showed efficacy in improving cancer outcomes. To facilitate more
widespread use of this tool, I will design a digital decision aid based geriatric assessment items using the digital twin’s
approach, to be used in clinical practice to help oncologists identify older patients who would benefit the most from
treatment and those with vulnerabilities that may need to be addressed before undergoing treatment.
The findings of all these activities will be translated into recommendations and interventions to improve cancer outcomes in
older patients.
The REDICO program fits with the Luxembourg Research Priorities as well as those of the Luxembourg Institute of Health,
the host institution, that fully supports the present application and offers me the infrastructure to conduct my research. The
program will benefit from collaborations with national (LISER, Deep Digital Phenotyping Research Unit at LIH, NCTCR) and
international (University of Oxford, London School of Hygiene and Tropical Medicine) researchers as well as members of
the International Society for Geriatric Oncology.
Eliminating such age inequalities is idealist but reducing them is achievable. I am enthusiastic that my proposed research
contributes to this goal. The support of the FNR ATTRACT Fellowship would provide me with an ideal opportunity to meet
my ambitions.
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