Weight loss as a predictor of cancer and serious disease in primary care: an ISAC-approved CPRD protocol for a retrospective cohort study using routinely collected primary care data from the UK - Nicholson, B; Aveyard, P; Hobbs, R; Smith, M; Fuller, A; Perera, R; Stevens, S; Bankhead, C (BioMed Central, 2018)
Background: Unexpected weight loss is a symptom of serious disease in primary care, for example between 1 in 200 and 1 in 30 patients with unexpected weight loss go on to develop cancer. However, it remains unclear how and when General Practitioners (GPs) should investigate unexpected weight loss. Without clarification, GPs may wait too long before referring (choosing to watch and wait and potentially missing a diagnosis) or not long enough (overburdening hospital services and exposing patients to the risks of investigation). The overall aim of this study is to provide the evidence necessary to allow GPs to more effectively manage patients with unexpected weight loss. Methods: A retrospective cohort analysis of UK Clinical Practice Research Datalink (CPRD) data to: 1) describe how often in UK primary care the symptom of reported weight loss is coded, when weight is measured, and how GPs respond to a patient attending with unexpected weight loss; 2) identify the predictive value of recorded weight loss for cancer and serious disease in primary care by comparing the incidence of cancer and serious disease over time in those with and without a weight loss code, using cumulative incidence plots to compare outcomes between subgroups and Cox regression to explore and adjust for covariates. Preliminary work in CPRD estimates that weight loss as a symptom is recorded for approximately 148,000 eligible patients >18 years, and is distributed evenly across decades of age, providing adequate statistical power and precision in relation to cancer overall and common cancers individually. Further stratification by cancer stage will be attempted but may not be possible as not all practices within CPRD are eligible for cancer registry linkage and staging information is often incomplete. The feasibility of using multiple imputation to address missing covariate values will be explored. Discussion: This will be the largest reported retrospective cohort of primary care patients with weight measurements and unexpected weight loss codes used to understand the association between weight measurement, unexpected weight loss, and serious disease including cancer. Our findings will directly inform international guidelines for the management of unexpected weight loss in primary care populations.