Letter in response to the Wedlake et al. paper 'Evaluating the efficacy of statins and ACE-inhibitors in reducing gastrointestinal toxicity in patients receiving radiotherapy for pelvic malignancies'

Use of angiotensin converting enzyme inhibitors is associated with reduced risk of late bladder toxicity following radiotherapy for prostate cancer

BACKGROUND AND PURPOSE

Genome-wide association studies (GWAS) of late hematuria following prostate cancer radiotherapy identified single nucleotide polymorphisms (SNPs) near AGT, encoding angiotensinogen. We tested the hypothesis that patients taking angiotensin converting enzyme inhibitors (ACEi) have a reduced risk of late hematuria. We additionally tested genetically-defined hypertension.

MATERIALS AND METHODS

Prostate cancer patients undergoing potentially-curative radiotherapy were enrolled onto two multi-center observational studies, URWCI (N = 256) and REQUITE (N = 1,437). Patients were assessed pre-radiotherapy and followed prospectively for development of toxicity for up to four years. The cumulative probability of hematuria was estimated by the Kaplan-Meier method. Multivariable grouped relative risk models assessed the effect of ACEi on time to hematuria adjusting for clinical factors and stratified by enrollment site. A polygenic risk score (PRS) for blood pressure was tested for association with hematuria in REQUITE and our Radiogenomics Consortium GWAS.

RESULTS

Patients taking ACEi during radiotherapy had a reduced risk of hematuria (HR 0.51, 95%CI 0.28 to 0.94, p = 0.030) after adjusting for prior transurethral prostate and/or bladder resection, heart disease, pelvic node radiotherapy, and bladder volume receiving 70 Gy, which are associated with hematuria. A blood pressure PRS was associated with hypertension (odds ratio per standard deviation 1.38, 95%CI 1.31 to 1.46, n = 5,288, p < 0.001) but not hematuria (HR per standard deviation 0.96, 95%CI 0.87 to 1.06, n = 5,126, p = 0.41).

CONCLUSIONS

Our study is the first to show a radioprotective effect of ACEi on bladder in an international, multi-site study of patients receiving pelvic radiotherapy. Mechanistic studies are needed to understand how targeting the angiotensin pathway protects the bladder.

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.