Assessing the potential for prevention or earlier detection of on-site monitoring findings from randomised controlled trials: Further analyses of findings from the prospective TEMPER triggered monitoring study

BACKGROUND/AIMS: Clinical trials should be designed and managed to minimise important errors with potential to compromise patient safety or data integrity, employ monitoring practices that detect and correct important errors quickly, and take robust action to prevent repetition. Regulators highlight the use of risk-based monitoring, making greater use of centralised monitoring and reducing reliance on centre visits. The TEMPER study was a prospective evaluation of triggered monitoring (a risk-based monitoring method), whereby centres are prioritised for visits based on central monitoring results. Conducted in three UK-based randomised cancer treatment trials of investigational medicine products with time-to-event outcomes, it found high levels of serious findings at triggered centre visits but also at visits to matched control centres that, based on central monitoring, were not of concern. Here, we report a detailed review of the serious findings from TEMPER centre visits. We sought to identify feasible, centralised processes which might detect or prevent these findings without a centre visit. METHODS: The primary outcome of this study was the proportion of all 'major' and 'critical' TEMPER centre visit findings theoretically detectable or preventable through a feasible, centralised process. To devise processes, we considered a representative example of each finding type through an internal consensus exercise. This involved (a) agreeing the potential, by some described process, for each finding type to be centrally detected or prevented and (b) agreeing a proposed feasibility score for each proposed process. To further assess feasibility, we ran a consultation exercise, whereby the proposed processes were reviewed and rated for feasibility by invited external trialists. RESULTS: In TEMPER, 312 major or critical findings were identified at 94 visits. These findings comprised 120 distinct issues, for which we proposed 56 different centralised processes. Following independent review of the feasibility of the proposed processes by 87 consultation respondents across eight different trial stakeholder groups, we conclude that 306/312 (98%) findings could theoretically be prevented or identified centrally. Of the processes deemed feasible, those relating to informed consent could have the most impact. Of processes not currently deemed feasible, those involving use of electronic health records are among those with the largest potential benefit. CONCLUSIONS: This work presents a best-case scenario, where a large majority of monitoring findings were deemed theoretically preventable or detectable by central processes. Caveats include the cost of applying all necessary methods, and the resource implications of enhanced central monitoring for both centre and trials unit staff. Our results will inform future monitoring plans and emphasise the importance of continued critical review of monitoring processes and outcomes to ensure they remain appropriate

Dynamic methods for ongoing assessment of site-level risk in risk-based monitoring of clinical trials: A scoping review

BACKGROUND/AIMS: It is increasingly recognised that reliance on frequent site visits for monitoring clinical trials is inefficient. Regulators and trialists have recently encouraged more risk-based monitoring. Risk assessment should take place before a trial begins to define the overarching monitoring strategy. It can also be done on an ongoing basis, to target sites for monitoring activity. Various methods have been proposed for such prioritisation, often using terms like 'central statistical monitoring', 'triggered monitoring' or, as in the International Conference on Harmonization Good Clinical Practice guidance, 'targeted on-site monitoring'. We conducted a scoping review to identify such methods, to establish if any were supported by adequate evidence to allow wider implementation, and to guide future developments in this field of research. METHODS: We used seven publication databases, two sets of methodological conference abstracts and an Internet search engine to identify methods for using centrally held trial data to assess site conduct during a trial. We included only reports in English, and excluded reports published before 1996 or not directly relevant to our research question. We used reference and citation searches to find additional relevant reports. We extracted data using a predefined template. We contacted authors to request additional information about included reports. RESULTS: We included 30 reports in our final dataset, of which 21 were peer-reviewed publications. In all, 20 reports described central statistical monitoring methods (of which 7 focussed on detection of fraud or misconduct) and 9 described triggered monitoring methods; 21 reports included some assessment of their methods' effectiveness, typically exploring the methods' characteristics using real trial data without known integrity issues. Of the 21 with some effectiveness assessment, most contained limited information about whether or not concerns identified through central monitoring constituted meaningful problems. Several reports demonstrated good classification ability based on more than one classification statistic, but never without caveats of unclear reporting or other classification statistics being low or unavailable. Some reports commented on cost savings from reduced on-site monitoring, but none gave detailed costings for the development and maintenance of central monitoring methods themselves. CONCLUSION: Our review identified various proposed methods, some of which could be combined within the same trial. The apparent emphasis on fraud detection may not be proportionate in all trial settings. Despite some promising evidence and some self-justifying benefits for data cleaning activity, many proposed methods have limitations that may currently prevent their routine use for targeting trial monitoring activity. The implementation costs, or uncertainty about these, may also be a barrier. We make recommendations for how the evidence-base supporting these methods could be improved

Use of routinely collected health data in randomised clinical trials: comparison of trial-specific death data in the BOSS trial with NHS Digital data

Background: A promising approach to reduce the increasing costs of clinical trials is the use of routinely collected health data as participant data. However, the quality of this data could limit its usability as trial participant data. Methods: The BOSS trial is a randomised controlled trial comparing regular endoscopies versus endoscopies at need in patients with Barrett’s oesophagus with primary endpoint death. Data on death and cancer collected every 2 years after randomisation (trial-specific data) were compared to data received annually (all patients on one date) from the routinely collected health data source National Health Service (NHS) Digital. We investigated completeness, agreement and timeliness and looked at the implications for the primary trial outcome. Completeness and agreement were assessed by evaluating the number of reported and missing cases and any disparities between reported dates. Timeliness was considered by graphing the year a death was first reported in the trial-specific data against that for NHS Digital data. Implications on the primary trial outcome, overall survival, of using one of the data sources alone were investigated using Kaplan-Meier graphs. To assess the utility of cause of death and cancer diagnoses, oesophageal cancer cases were compared. Results: NHS Digital datasets included more deaths and often reported them sooner than the trial-specific data. The number reported as being from oesophageal cancer was similar in both datasets. Due to time lag in reporting and missing cases, the event rate appeared higher using the NHS Digital data. Conclusion: NHS Digital death data is useful for calculating overall survival where trial-specific follow-up is only every 2 years from randomisation and the follow-up requires patient response. The cancer data was not a large enough sample to assess usability. We suggest that this assessment of registry data is done for more phase III RCTs and for more registry data to get a more complete picture of when RCHD would be useful in phase III RCT. Trial registration: ISRCTN54190466 (BOSS) 1 Oct 2009

Why are feasibility studies accessing routinely collected health data? A systematic review

BACKGROUND: Feasibility trials are often undertaken to determine whether a larger randomised controlled trial (RCT) is achievable. In a recent review, 15 feasibility trials accessed routinely collected health data (RCHD) from UK national databases and registries. This paper looks at attributes of these trials and the reasons why they accessed RCHD. METHODS: We extracted data from all publicly available sources for the 15 feasibility studies found in a previous review of trials successfully accessing RCHD in the UK between 2013–2018 for the purpose of informing or supplementing participant data. We extracted trial characteristics, the registry accessed, and the way the RCHD was used. RESULTS: The 15 feasibility RCTs were conducted in a variety of disease areas, and were generally small (median sample size 100, range 41–4061) and individually randomised (60%, 9/15). The primary trial outcome was predominantly administrative (non-clinical) (80%, 12/15) such as feasibility of patient recruitment. They were more likely to recruit from secondary care (67%, 10/15) settings than primary (33%, 5/15). NHS Digital was the most commonly accessed registry (33% (5/15)) with SAIL databank (20% (3/15)), electronic Data Research and Innovation Service (eDRIS) and Paediatric Intensive Care Audit Network (PICANET) (each 13% 2/15) also being accessed. Where the information was clear, the trials used RCHD for data collection during the trial (47%, 7/15), follow-up after the trial (27%, 4/15) and recruitment (13%, 2/15). CONCLUSIONS: Between 2013 and 2018, 15 feasibility trials successfully accessed UK RCHD. Feasibility trials would benefit, as with other trials, from guidance on reporting the use of RCHD in protocols and publications

Accessing HE for non-traditional students: 'Outside of my position'

Widening participation within higher education and increasing social mobility have been high on the agendas of former and current governments. This paper examines the admissions procedure of a Foundation degree in Early Years programme using Bourdieu's concept of capital as a vehicle for analysis. During the process of an admissions interview, the interviewer is required to make decisions regarding a student's suitability to fit into the existing field of the programme as they often feel it is outside of their position. The stories of three non-traditional students are explored to highlight existing capital and dispositions that they bring to the programme. Research findings showed that there are many variables that impact on a student's ability to gain entry and be successful on an HE programme, including accumulation of capital, emotional drivers and potential to acquire capital throughout the programme. © 2014 Further Education Research Association

Herschel/HIFI observations of spectrally resolved methylidyne signatures toward the high-mass star-forming core NGC6334I

In contrast to extensively studied dense star-forming cores, little is known about diffuse gas surrounding star-forming regions. We study molecular gas in the high-mass star-forming region NGC6334I, which contains diffuse, quiescent components that are inconspicuous in widely used molecular tracers such as CO. We present Herschel/HIFI observations of CH toward NGC6334I observed as part of the CHESS key program. HIFI resolves the hyperfine components of its J=3/2-1/2 transition, observed in both emission and absorption. The CH emission appears close to the systemic velocity of NGC6334I, while its measured linewidth of 3 km/s is smaller than previously observed in dense gas tracers such as NH3 and SiO. The CH abundance in the hot core is 7 10^-11, two to three orders of magnitude lower than in diffuse clouds. While other studies find distinct outflows in, e.g., CO and H2O toward NGC6334I, we do not detect outflow signatures in CH. To explain the absorption signatures, at least two absorbing components are needed at -3.0 and +6.5 km/s with N(CH)=7 10^13 and 3 10^13 cm^-2. Two additional absorbing clouds are found at +8.0 and 0.0 km/s, both with N(CH)=2 10^13 cm^-2. Turbulent linewidths for the four absorption components vary between 1.5 and 5.0 km/s in FWHM. We constrain physical properties of our CH clouds by matching our CH absorbers with other absorption signatures. In the hot core, molecules such as H2O and CO trace gas that is heated and dynamically influenced by outflow activity, whereas CH traces more quiescent material. The four CH absorbers have column densities and turbulent properties consistent with diffuse clouds: two are located near NGC6334, and two are unrelated foreground clouds. Local density and dynamical effects influence the chemical composition of physical components of NGC6334, causing some components to be seen in CH but not in other tracers, and vice versa.Comment: Accepted by A&A Letters; 5 pages, 1 figure; v2: minor textual and typographical change

Monitoring in practice - How are UK academic clinical trials monitored? A survey

BACKGROUND: Despite the US Food and Drug Administration (FDA) and European Medicines Agency (EMA) encouraging the use of risk-based monitoring for trials in 2013, there remains a lack of evidence-based guidelines on how to monitor. We surveyed the academic United Kingdom Clinical Research Collaboration (UKCRC) registered clinical trials units (CTUs) to find out their policy on monitoring of phase III randomised clinical trials of an investigational medicinal product (CTIMPs). METHODS: An online survey of monitoring policy with sections on the CTU, central monitoring and on-site monitoring was sent to all 50 UKCRC registered CTUs in November 2018. Descriptive data analysis and tabulations are reported using the total number answering each question. RESULTS: A total of 43/50 (86%) of CTUs responded with 38 conducting phase III randomised CTIMP trials. Of these 38 CTUs, 34 finished the survey. Most CTUs (36/37, 97%) use a central monitoring process to guide, target or supplement site visits. More than half (19/36, 53%) of CTUs do not use an automated monitoring report when centrally monitoring trials and all units use trial team knowledge to make a final decision on whether an on-site visit is required. A total of 31/34 (91%) CTUs used triggers to decide whether or not to conduct an on-site monitoring visit. On-site, a mixture of source data verification and checking of processes was carried out. The CTUs overwhelmingly (27/34, 79%) selected optimising central monitoring as their most pressing concern. CONCLUSION: The survey showed a wide variation in phase III randomised CTIMP trial monitoring practices by academic clinical trials units within a single research-active country. We urgently need to develop evidence-based regulator-agreed guidance for CTUs on best practice for both central and on-site monitoring and to develop tools for all CTUs to use

Thigh-length compression stockings and DVT after stroke

Controversy exists as to whether neoadjuvant chemotherapy improves survival in patients with invasive bladder cancer, despite randomised controlled trials of more than 3000 patients. We undertook a systematic review and meta-analysis to assess the effect of such treatment on survival in patients with this disease

Getting our ducks in a row: The need for data utility comparisons of healthcare systems data for clinical trials.

BACKGROUND: Better use of healthcare systems data, collected as part of interactions between patients and the healthcare system, could transform planning and conduct of randomised controlled trials. Multiple challenges to widespread use include whether healthcare systems data captures sufficiently well the data traditionally captured on case report forms. "Data Utility Comparison Studies" (DUCkS) assess the utility of healthcare systems data for RCTs by comparison to data collected by the trial. Despite their importance, there are few published UK examples of DUCkS. METHODS-AND-RESULTS: Building from ongoing and selected recent examples of UK-led DUCkS in the literature, we set out experience-based considerations for the conduct of future DUCkS. Developed through informal iterative discussions in many forums, considerations are offered for planning, protocol development, data, analysis and reporting, with comparisons at "patient-level" or "trial-level", depending on the item of interest and trial status. DISCUSSION: DUCkS could be a valuable tool in assessing where healthcare systems data can be used for trials and in which trial teams can play a leading role. There is a pressing need for trials to be more efficient in their delivery and research waste must be reduced. Trials have been making inconsistent use of healthcare systems data, not least because of an absence of evidence of utility. DUCkS can also help to identify challenges in using healthcare systems data, such as linkage (access and timing) and data quality. We encourage trial teams to incorporate and report DUCkS in trials and funders and data providers to support them