Linkage of the CHHiP randomised controlled trial with primary care data: a study investigating ways of supplementing cancer trials and improving evidence-based practice.

BACKGROUND: Randomised controlled trials (RCTs) are the gold standard for evidence-based practice. However, RCTs can have limitations. For example, translation of findings into practice can be limited by design features, such as inclusion criteria, not accurately reflecting clinical populations. In addition, it is expensive to recruit and follow-up participants in RCTs. Linkage with routinely collected data could offer a cost-effective way to enhance the conduct and generalisability of RCTs. The aim of this study is to investigate how primary care data can support RCTs. METHODS: Secondary analysis following linkage of two datasets: 1) multicentre CHHiP radiotherapy trial (ISRCTN97182923) and 2) primary care database from the Royal College of General Practitioners Research and Surveillance Centre. Comorbidities and medications recorded in CHHiP at baseline, and radiotherapy-related toxicity recorded in CHHiP over time were compared with primary care records. The association of comorbidities and medications with toxicity was analysed with mixed-effects logistic regression. RESULTS: Primary care records were extracted for 106 out of 2811 CHHiP participants recruited from sites in England (median age 70, range 44 to 82). Complementary information included longitudinal body mass index, blood pressure and cholesterol, as well as baseline smoking and alcohol usage but was limited by the considerable missing data. In the linked sample, 9 (8%) participants were recorded in CHHiP as having a history of diabetes and 38 (36%) hypertension, whereas primary care records indicated incidence prior to trial entry of 11 (10%) and 40 (38%) respectively. Concomitant medications were not collected in CHHiP but available in primary care records. This indicated that 44 (41.5%) men took aspirin, 65 (61.3%) statins, 14 (13.2%) metformin and 46 (43.4%) phosphodiesterase-5-inhibitors at some point before or after trial entry. CONCLUSIONS: We provide a set of recommendations on linkage and supplementation of trials. Data recorded in primary care are a rich resource and linkage could provide near real-time information to supplement trials and an efficient and cost-effective mechanism for long-term follow-up. In addition, standardised primary care data extracts could form part of RCT recruitment and conduct. However, this is at present limited by the variable quality and fragmentation of primary care data.

Linking CHHiP prostate cancer RCT with GP records: A study proposal to investigate the effect of co-morbidities and medications on long-term symptoms and radiotherapy-related toxicity.

BACKGROUND: Patients receiving cancer treatment often have one or more co-morbid conditions that are treated pharmacologically. Co-morbidities are recorded in clinical trials usually only at baseline. However, co-morbidities evolve and new ones emerge during cancer treatment. The interaction between multi-morbidity and cancer recovery is significant but poorly understood. PURPOSE: To investigate the effect of co-morbidities (e.g. cardiovascular and diabetes) and medications (e.g. statins, antihypertensives, metformin) on radiotherapy-related toxicity and long-term symptoms in order to identify potential risk factors. The possible protective effect of medications such as statins or antihypertensives in reducing radiotherapy-related toxicity will also be explored. METHODS: Two datasets will be linked. (1) CHHiP (Conventional or Hypofractionated High Dose Intensity Modulated Radiotherapy for Prostate Cancer) randomised control trial. CHHiP contains pelvic symptoms and radiation-related toxicity reported by patients and clinicians. (2) GP (General Practice) data from RCGP RSC (Royal College of General Practitioners Research and Surveillance Centre). The GP records of CHHiP patients will be extracted, including cardiovascular co-morbidities, diabetes and prescription medications. Statistical analysis of the combined dataset will be performed in order to investigate the effect. CONCLUSIONS: Linking two sources of healthcare data is an exciting area of big healthcare data research. With limited data in clinical trials (not all clinical trials collect information on co-morbidities or medications) and limited lengths of follow-up, linking different sources of information is increasingly needed to investigate long-term outcomes. With increasing pressures to collect detailed information in clinical trials (e.g. co-morbidities, medications), linkage to routinely collected data offers the potential to support efficient conduct of clinical trials.