Innovative Solutions for Clinical Trial Follow-up: Adding Value from Nationally Held UK Data

Healthcare systems data in the context of clinical trials - A comparison of cardiovascular data from a clinical trial dataset with routinely collected data

BACKGROUND

Routinely-collected healthcare systems data (HSD) are proposed to improve the efficiency of clinical trials. A comparison was undertaken between cardiovascular (CVS) data from a clinical trial database with two HSD resources.

METHODS

Protocol-defined and clinically reviewed CVS events (heart failure (HF), acute coronary syndrome (ACS), thromboembolic stroke, venous and arterial thromboembolism) were identified within the trial data. Data (using pre-specified codes) was obtained from NHS Hospital Episode Statistics (HES) and National Institute for Cardiovascular Outcomes Research (NICOR) HF and myocardial ischaemia audits for trial participants recruited in England between 2010 and 2018 who had provided consent. The primary comparison was trial data versus HES inpatient (APC) main diagnosis (Box-1). Correlations are presented with descriptive statistics and Venn diagrams. Reasons for non-correlation were explored.

RESULTS

From 1200 eligible participants, 71 protocol-defined clinically reviewed CVS events were recorded in the trial database. 45 resulted in a hospital admission and therefore could have been recorded by either HES APC/ NICOR. Of these, 27/45 (60%) were recorded by HES inpatient (Box-1) with an additional 30 potential events also identified. HF and ACS were potentially recorded in all 3 datasets; trial data recorded 18, HES APC 29 and NICOR 24 events respectively. 12/18 (67%) of the HF/ACS events in the trial dataset were recorded by NICOR.

CONCLUSION

Concordance between datasets was lower than anticipated and the HSD used could not straightforwardly replace current trial practices, nor directly identify protocol-defined CVS events. Further work is required to improve the quality of HSD and consider event definitions when designing clinical trials incorporating HSD.

Driving quality improvement through better data: The story of New Zealand's radiation oncology collection

Aotearoa/New Zealand is one of the first nations in the world to develop a comprehensive, high-quality collection of radiation therapy data (the Radiation Oncology Collection, ROC) that is able to report on treatment delivery by health region, patient demographics and service provider. This has been guided by radiation therapy leaders, who have been instrumental in overseeing the establishment of clear and robust data definitions, a centralised database and outputs delivered via an online tool. In this paper, we detail the development of the ROC, provide examples of variation in practice identified from the ROC and how these changed over time, then consider the ramifications of the ROC in the wider context of cancer care quality improvement. In addition to a review of relevant literature, primary data were sourced from the ROC on radiation therapy provided nationally in New Zealand between 2017 and 2020. The total intervention rate, number of fractions and doses are reported for select cancers by way of examples of national variation in practice. Results from the ROC have highlighted areas of treatment variation and have prompted increased uptake of hypofractionation for curative prostate and breast cancer treatment and for palliation of bone metastases. Future development of the ROC will increase its use for quality improvement and ultimately link to a real time cancer services database.

Using routinely recorded data in a UK RCT: a comparison to standard prospective data collection methods

BACKGROUND

Routinely recorded data held in electronic health records can be used to inform the conduct of randomised controlled trials (RCTs). However, limitations with access and accuracy have been identified.

OBJECTIVE

Using epilepsy as an exemplar condition, we assessed the attributes and agreement of routinely recorded data compared to data collected using case report forms in a UK RCT assessing antiepileptic drug treatments for individuals newly diagnosed with epilepsy.

METHODS

The case study RCT is the Standard and New Antiepileptic Drugs II (SANAD II) trial, a pragmatic, UK multicentre RCT assessing the clinical and cost-effectiveness of antiepileptic drugs as treatments for epilepsy. Ninety-eight of 470 eligible participants provided consent for access to routinely recorded secondary care data that were retrieved from NHS Digital Hospital Episode Statistics (N=71) and primary and secondary care data from The Secure Anonymised Information Linkage Databank (N=27). We assessed data items relevant to the identification of individuals eligible for inclusion in SANAD II, baseline and follow-up visits. The attributes of routinely recorded data were assessed including the degree of missing data. The agreement between routinely recorded data and data collected on case report forms in SANAD II was assessed using calculation of Cohen's kappa for categorical data and construction of Bland-Altman plots for continuous data.

RESULTS

There was a significant degree of missing data in the routine record for 15 of the 20 variables assessed, including all clinical variables. Agreement was poor for the majority of comparisons, including the assessments of seizure occurrence and adverse events. For example, only 23/62 (37%) participants had a date of first-ever seizure identified in routine datasets. Agreement was satisfactory for the date of prescription of antiepileptic drugs and episodes of healthcare resource use.

CONCLUSIONS

There are currently significant limitations preventing the use of routinely recorded data for participant identification and assessment of clinical outcomes in epilepsy, and potentially other chronic conditions. Further research is urgently required to assess the attributes, agreement, additional benefits, cost-effectiveness and 'optimal mix' of routinely recorded data compared to data collected using standard methods such as case report forms at clinic visits for people with epilepsy.

TRIAL REGISTRATION

Standard and New Antiepileptic Drugs II (SANAD II (EudraCT No: 2012-001884-64, registered 05/09/2012; ISRCTN Number: ISRCTN30294119 , registered 03/07/2012)).

Accessing routinely collected health data to improve clinical trials: recent experience of access

BACKGROUND

Routinely collected electronic health records (EHRs) have the potential to enhance randomised controlled trials (RCTs) by facilitating recruitment and follow-up. Despite this, current EHR use is minimal in UK RCTs, in part due to ongoing concerns about the utility (reliability, completeness, accuracy) and accessibility of the data. The aim of this manuscript is to document the process, timelines and challenges of the application process to help improve the service both for the applicants and data holders.

METHODS

This is a qualitative paper providing a descriptive narrative from one UK clinical trials unit (MRC CTU at UCL) on the experience of two trial teams' application process to access data from three large English national datasets: National Cancer Registration and Analysis Service (NCRAS), National Institute for Cardiovascular Outcomes Research (NICOR) and NHS Digital to establish themes for discussion. The underpinning reason for applying for the data was to compare EHRs with data collected through case report forms in two RCTs, Add-Aspirin (ISRCTN 74358648) and PATCH (ISRCTN 70406718).

RESULTS

The Add-Aspirin trial, which had a pre-planned embedded sub-study to assess EHR, received data from NCRAS 13 months after the first application. In the PATCH trial, the decision to request data was made whilst the trial was recruiting. The study received data after 8 months from NICOR and 15 months for NHS Digital following final application submission. This concluded in May 2020. Prior to application submission, significant time and effort was needed particularly in relation to the PATCH trial where negotiations over consent and data linkage took many years.

CONCLUSIONS

Our experience demonstrates that data access can be a prolonged and complex process. This is compounded if multiple data sources are required for the same project. This needs to be factored in when planning to use EHR within RCTs and is best considered prior to conception of the trial. Data holders and researchers are endeavouring to simplify and streamline the application process so that the potential of EHR can be realised for clinical trials.

Development and validation of a follow-up methodology for a randomised controlled trial, utilising routine clinical data as an alternative to traditional designs: a pilot study to assess the feasibility of use for the BladderPath trial

Background

Bladder cancer outcomes have not changed significantly in 30 years; the BladderPath trial (Image Directed Redesign of Bladder Cancer Treatment Pathway, ISRCTN35296862) proposes to evaluate a modified pathway for diagnosis and treatment ensuring appropriate pathways are undertaken earlier to improve outcomes. We are piloting a novel data collection technique based on routine National Health Service (NHS) data, with no traditional patient-Health Care Professional contact after recruitment, where trial data are traditionally collected on case report forms. Data will be collected from routine administrative sources and validated via data queries to sites. We report here the feasibility and pre-trial methodological development and validation of the schema proposed for BladderPath.

Methods

Locally treated patient cohorts were utilised for routine data validation (hospital interactions data (HID) and administrative radiotherapy department data (RTD)). Single site events of interest were algorithmically extracted from the 2008–2018 HID and validated against reference datasets to determine detection sensitivity. Survival analysis was performed using RTD and HID data. Hazard ratios and survival statistics were calculated estimating treatment effects and further validating and assessing the scope of routine data.

Results

Overall, 829/1042 (sensitivity 0.80) events of interest were identified in the HID, with varying levels of sensitivity; identifying, 202/206 (sensitivity 0.98; PPV 0.96) surgical events but only 391/568 (sensitivity 0.69; PPV 0.95) radiotherapy regimens. An overall temporal quality improvement trend was present: detecting 41/117 events (35%) in 2011 to 104/109 (95%) in 2017 (all event types). Using the RTD, 5-year survival rates were 43% (95% CI 25–59%) in the chemoradiotherapy group and 30% (95% CI 23–36%) in the radiotherapy group; using the HID, the 5-year radical cystectomy survival rate was 57% (95% CI 50–63%).

Conclusions

Routine data are a feasible method for trial data collection. As long as events of interest are pre-validated, very high sensitivities for trial conduct can be achieved and further improved with targeted data queries. Outcomes can also be produced comparable to clinical trial and national dataset results. Given the real-time, obligatory nature of the HID, which forms the Hospital Episode Statistics (HES) data, alongside other datasets, we believe routine data extraction and validation is a robust way of rapidly collecting datasets for trials.

Supplementary Information

Supplementary information accompanies this paper at 10.1186/s40814-020-00713-y.