Cohort profile: radiotherapy dataset (RTDS) in England.

PURPOSE: The purpose of the Radiotherapy Dataset (RTDS) is to collect consistent and comparable data across all providers of National Health Service (NHS)-funded radiotherapy and to provide intelligence for service planning, commissioning, clinical practice and research. PARTICIPANTS: The RTDS is a mandated dataset requiring providers to collect and submit data monthly for patients treated in England. Data is available from 01 April 2009 to 2 months behind the calendar month.The National Disease Registration Service (NDRS) started receiving data from 01 April 2016. Prior to this, the National Clinical Analysis and Specialised Applications Team (NATCANSAT) were responsible for the RTDS. NDRS holds a copy of the NATCANSAT data for English NHS providers.The RTDS contains clinical information on the primary disease being treated, modality and intent of treatment, dose fractionation and hospital appointment details. Due to constraints in RTDS coding, linkage to the English National Cancer Registration dataset is beneficial. FINDINGS TO DATE: The RTDS has been linked to the English National Cancer Registration and Systemic Anti-Cancer Therapy (SACT) datasets and to Hospital Episode Statistics (HES) to provide a more complete picture of the patient cancer pathway. Findings include a study to compare outcomes for patients treated with radical radiotherapy, an investigation of factors influencing 30-day mortality, assessing sociodemographic variation in the use of treatment and a study to assess the service impact of the COVID-19 pandemic. A range of other studies have been completed or are ongoing currently. FUTURE PLANS: The RTDS can be used for a variety of functions including cancer epidemiological studies to investigate inequalities in treatment access; provide service planning intelligence; monitor clinical practice; and support clinical trial design and recruitment. Collection is to continue indefinitely, with regular updates to the data specification to enable capture of more detailed information on radiotherapy planning and delivery.

Novel methods to define invasive procedures at the end of life were developed to improve quality of end of life care research: a population-based cohort study in colorectal cancer.

BACKGROUND: Understanding the use of invasive procedures (IPs) at the end of life (EoL) is important to avoid undertreatment and overtreatment, but epidemiologic analysis is hampered by limited methods to define treatment intent and EoL phase. This study applied novel methods to report IPs at the EoL using a colorectal cancer case study. METHODS: An English population-based cohort of adult patients diagnosed between 2013 and 2015 was used with follow-up to 2018. Procedure intent (curative, noncurative, diagnostic) by cancer site and stage at diagnosis was classified by two surgeons independently. Joinpoint regression modeled weekly rates of IPs for 36 subcohorts of patients with incremental survival of 0-36 months. EoL phase was defined by a significant IP rate change before death. Zero-inflated Poisson regression explored associations between IP rates and clinical/sociodemographic variables. RESULTS: Of 87,731 patients included, 41,972 (48%) died. Nine thousand four hundred ninety two procedures were classified by intent (inter-rater agreement 99.8%). Patients received 502,895 IPs (1.39 and 3.36 per person year for survivors and decedents). Joinpoint regression identified significant increases in IPs 4 weeks before death in those living 3-6 months and 8 weeks before death in those living 7-36 months from diagnosis. Seven thousand nine hundred eight (18.8%) patients underwent IPs at the EoL, with stoma formation the most common major procedure. Younger age, early-stage disease, men, lower comorbidity, those receiving chemotherapy, and living longer from diagnosis were associated with IPs. CONCLUSION: Methods to identify and classify IPs at the EoL were developed and tested within a colorectal cancer population. This approach can be now extended and validated to identify potential undertreatment and overtreatment.