Kidney function as a complicator of cancer treatment

Among people diagnosed with cancer, chronic kidney disease (CKD) is extremely common and a strong predictor of premature death, particularly in women. In people with cancer and CKD, premature death is not explained by presentation with cancer at more invasive stage. I hypothesise that CKD drives premature death through cautious selection, reduced efficacy, and increased harms from cancer treatments, that these effects are exacerbated by flawed creatinine-based estimation of kidney function and are more pronounced in women. This project harnesses the power of existing patient data to define the current landscape of cancer treatment in men and women with CKD. I will extend my skills and collaborative networks to understand how cancer diagnoses, treatment pathways, benefits and harms change according to kidney function, and how new tools for estimating kidney function could improve outcomes in people with cancer. Trial data are unrepresentative; observational data are liable to confounding by indication: maximum impact will be achieved by using state-of-the-art data science methodologies in a unique tapestry of datasets to attenuate and overcome these limitations. Successful completion will offer diverse opportunities for further study, and create transferable tools to understand decision-making, benefits and harms across a range of disease processes and treatment interventions.