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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.

Original publication

DOI

10.1016/j.tipsro.2017.06.001

Type

Journal article

Journal

Tech Innov Patient Support Radiat Oncol

Publication Date

06/2017

Volume

2

Pages

5 - 12

Keywords

ANOVA, analysis of variance, BNF, British National Formulary, Big data, CHHiP, CHHiP, Conventional or Hypofractionated High Dose Intensity Modulated Radiotherapy for Prostate Cancer, Data linkage, EPIC, Expanded Prostate Cancer Index Composite, FACT-P, Functional Assessment of Cancer Therapy-Prostate, GEE, Generalized Estimating Equations, GP, General Practitioner, ICD10, International Classification of Disease version 10, ICR, Institute of Cancer Research, IMRT, Intensity Modulated Radiotherapy, LENT/SOMA, Late Effects Normal Tissue Toxicity; subjective, objective, management, and analytic, Late-effects, PCa, Prostate cancer, PROs, Patient Reported Outcomes, QOL, Quality of life, RCGP RSC, RCGP, Royal College of General Practitioners, RCT, Randomised Control Trial, REC, Research Ethics Committee, RSC, Research & Surveillance Centre, RTOG, Radiation Therapy Oncology Group, Radiotherapy-related side-effects, SHA2-512, Secure Hash Algorithm 2 with 512 bit hash values, UCLA-PCI, University of California, Los Angeles Prostate Cancer Index, UK, United Kingdom