Real-world effects of ACE inhibitors and Angiotensin Receptor Blockers: protocol for an emulation study of the ONTARGET trial using electronic health records

ABSTRACTIntroductionCardiovascular disease (CVD) is a leading cause of death globally, responsible for nearly 18 million deaths worldwide in 2017. Medications to reduce the risk of cardiovascular events are prescribed based upon evidence from clinical trials which explore treatment effects in an indicated sample of the general population. However, these results may not be fully generalisable because of trial eligibility criteria that generally restrict to younger patients with fewer comorbidities. Therefore, evidence of effectiveness of medications for groups underrepresented in clinical trials such as those over 75 years, from ethnic minority backgrounds or with low kidney function may be limited.The ONTARGET trial studied the effects of an angiotensin-converting-enzyme (ACE) inhibitor and an angiotensin II receptor blocker (ARB) separately and in combination on cardiovascular event reduction. Using individual anonymised data from this study, in collaboration with the original trial investigators, we aim to investigate clinical trial replicability within routinely-collected patient data. If the original trial results are replicable, we will assess treatment effects and risk in groups underrepresented and excluded from the original clinical trial.Methods and analysisWe will develop a cohort analogous to the ONTARGET trial within CPRD between 1 January 2001 to 31 July 2019 using the trial eligibility criteria and propensity score matching. The primary outcome, as in the trial, is a composite of cardiovascular death, non-fatal MI, non-fatal stroke and hospitalisation for congestive heart-failure, examined in a time-to-event analysis. If results from the cohort study fall within pre-specified limits, we will expand the cohort to include those with advanced kidney dysfunction and increase the proportion of elderly participants and those from ethnicity minority backgrounds.We will then compare the risk of adverse events and association with long-term outcomes in the clinical trial, with that seen in a directly comparable sample of those attending NHS primary care.STRENGTHS AND LIMITATIONSStrengthsLarge cohort study giving power to look at effects within subgroups underrepresented in the clinical trialAccess to individual patient level data from a landmark trial to support creation of a trial-analogous cohortNovelty of studying treatment effects of dual therapy in real-world settingsLimitationsThere may be differences between the trial population and the observational cohort due to the level of detail on inclusion/exclusion criteria provided by the trialDrug-specific effects are unlikely to be able to be investigated due to small numbers in the dual-therapy arm: class-specific effects will be studied insteadMisclassification by primary care coding may lead to inaccurate replication of trial inclusion and exclusion criteria.

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119 A Descriptive Epidemiological Study of Clinical Trials, Comparing Trials Targeted At Older People to Adults of All Ages

Age and Ageing ◽

10.1093/ageing/afab030.80 ◽

2021 ◽

Vol 50 (Supplement_1) ◽

pp. i12-i42

Author(s):

J P Renton ◽

D McAllister

Keyword(s):

Clinical Trial ◽

Clinical Trials ◽

Adverse Events ◽

Older People ◽

Exclusion Criterion ◽

Trial Participation ◽

Exclusion Criteria ◽

Eligibility Criteria ◽

Serious Adverse Events ◽

Icd 10

Abstract Introduction Fewer clinical trials are carried out in older people. It is unclear how representative and applicable clinical trials carried out exclusively in older people are. We compared clinical trials recruiting older people exclusively “older trials” to those recruiting adults of all ages “all age trials”, using anti-hypertensives acting on the renin-angiotensin aldosterone system (RAAS drugs) as an exemplar. Method We searched the US clinical trials register 1, to identify all trials carried out exclusively in those aged over 60. From these we selected trials of RAAS drugs. These were matched in a 2:1 ratio to trials carried out in adults of all ages. Data regarding baseline characteristics, adverse events and eligibility criteria were collected from clinical trial reports and clinicaltrials.gov. Estimated associations were calculated for age, sex and adverse events. Eligibility criteria were described and ICD- 10 coded, as appropriate. Results 71 clinical trials were carried out exclusively in older people.13 related to RAAS drugs. Participants in “Older trials” had higher mean age (73.1 and 55.9 respectively), mean difference 16.17 (CI 15.31–17.02). Older trials had fewer male participants. Participants in older trials had lower mean body mass index (BMI). A higher rate of participants in older trials experienced serious adverse events. (2.07, CI 1.55–2.75.) Few older trials had upper age limits (23.1% V 27% all age trials). All trials had exclusion criteria in multiple ICD blocks. Concurrent medications were a more common exclusion criterion in older trials (61.5% v 40.9%). Conclusions Clinical trials carried out exclusively in older people are representative in terms of age, serious adverse events and eligibility. Although there are multiple exclusion criteria for clinical trial participation in both groups, this is not prohibitive. This supports carrying out more trials exclusively in older people. References 1. NIH, US national library of medicine.ClinicalTrials.gov Available at https://clinicaltrials.gov/

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Using Computable Phenotypes in Point-of-Care Clinical Trial Recruitment

Studies in Health Technology and Informatics - Public Health and Informatics ◽

10.3233/shti210233 ◽

2021 ◽

Author(s):

Martin Chapman ◽

Jesús Domínguez ◽

Elliot Fairweather ◽

Brendan C. Delaney ◽

Vasa Curcin

Keyword(s):

Primary Care ◽

Clinical Trial ◽

Clinical Trials ◽

Otitis Media ◽

Point Of Care ◽

Acute Otitis Media ◽

Trial Recruitment ◽

Eligibility Criteria ◽

Clinical Trial Recruitment

A key challenge in point-of-care clinical trial recruitment is to autonomously identify eligible patients on presentation. Similarly, the aim of computable phenotyping is to identify those individuals within a population that exhibit a certain condition. This synergy creates an opportunity to leverage phenotypes in identifying eligible patients for clinical trials. To investigate the feasibility of this approach, we use the Transform clinical trial platform and replace its archetype-based eligibility criteria mechanism with a computable phenotype execution microservice. Utilising a phenotype for acute otitis media with discharge (AOMd) created with the Phenoflow platform, we compare the performance of Transform with and without the use of phenotype-based eligibility criteria when recruiting AOMd patients. The parameters of the trial simulated are based on those of the REST clinical trial, conducted in UK primary care.

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Triptan use after starting prophylactic migraine treatment: A retrospective cohort study in a primary care population

Cephalalgia ◽

10.1177/0333102414521511 ◽

2014 ◽

Vol 34 (11) ◽

pp. 927-932 ◽

Cited By ~ 2

Author(s):

Antonia FH Smelt ◽

Willem JJ Assendelft ◽

Christel E van Dijk ◽

Jeanet W Blom

Keyword(s):

Primary Care ◽

Clinical Trials ◽

Cohort Study ◽

Retrospective Cohort ◽

Daily Practice ◽

Rank Test ◽

Migraine Treatment ◽

Prophylactic Effect ◽

Primary Care Population ◽

Wilcoxon Rank Test

Background Clinical trials on the prophylactic effect of propranolol and metoprolol for migraine show that starting this medication leads to a decrease in the use of attack medication of 0.9–8.9 doses per month. However, studies in daily practice are lacking. Methods We compared the number of triptans prescribed in the six months before and the six months after the start of propranolol/metoprolol in a Dutch national representative primary care cohort. Results Of the 168 triptan-using patients who started with propranolol or metoprolol, the number of triptans prescribed before starting was 4.6 doses per month. The number of triptans prescribed six months before compared with six months after starting propranolol/metoprolol decreased with 1.0 dose per month (Wilcoxon rank test; p = 0.000). Conclusion In this primary care population, although the number of triptans prescribed decreased after starting propranolol or metoprolol, the decrease is relatively small compared to data from clinical trials.

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LDL-cholesterol change and goal attainment following statin intensity titration among Asians in primary care: a retrospective cohort study

Lipids in Health and Disease ◽

10.1186/s12944-020-01427-z ◽

2021 ◽

Vol 20 (1) ◽

Author(s):

Hao Sen Andrew Fang ◽

Qiao Gao ◽

Mong Li Lee ◽

Wynne Hsu ◽

Ngiap Chuan Tan

Keyword(s):

Primary Care ◽

Clinical Trials ◽

Cohort Study ◽

Real World ◽

Retrospective Cohort Study ◽

Retrospective Cohort ◽

Goal Attainment ◽

Real World Data ◽

World Data ◽

Asian Patients

Abstract Background Clinical trials have demonstrated that either initiating or up-titrating a statin dose substantially reduce Low-Density Lipoprotein-Cholesterol (LDL-C) levels. However, statin adherence in actual practice tends to be suboptimal, leading to diminished effectiveness. This study aims to use real-world data to determine the effect on LDL-C levels and LDL-C goal attainment rates, when selected statins are titrated in Asian patients. Methods A retrospective cohort study over a 5-year period, from April 2014 to March 2019 was conducted on a cohort of multi-ethnic adult Asian patients with clinical diagnosis of Dyslipidaemia in a primary care clinic in Singapore. The statins were classified into low-intensity (LI), moderate-intensity (MI) and high-intensity (HI) groups according to the 2018 American College of Cardiology and American Heart Association (ACC/AHA) Blood Cholesterol Guidelines. Patients were grouped into “No statin”, “Non-titrators” and “Titrators” cohorts based on prescribing patterns. For the “Titrators” cohort, the mean percentage change in LDL-C and absolute change in LDL-C goal attainment rates were computed for each permutation of statin intensity titration. Results Among the cohort of 11,499 patients, with a total of 266,762 visits, there were 1962 pairs of LDL-C values associated with a statin titration. Initiation of LI, MI and HI statin resulted in a lowering of LDL-C by 21.6% (95%CI = 18.9–24.3%), 28.9% (95%CI = 25.0–32.7%) and 25.2% (95%CI = 12.8–37.7%) respectively. These were comparatively lower than results from clinical trials (30 to 63%). The change of LDL-C levels due to up-titration, down-titration, and discontinuation were − 12.4% to − 28.9%, + 13.2% to + 24.6%, and + 18.1% to + 32.1% respectively. The improvement in LDL-C goal attainment ranged from 26.5% to 47.1% when statin intensity was up-titrated. Conclusion In this study based on real-world data of Asian patients in primary care, it was shown that although statin titration substantially affected LDL-C levels and LDL-C goal attainment rates, the magnitude was lower than results reported from clinical trials. These results should be taken into consideration and provide further insight to clinicians when making statin adjustment recommendations in order to achieve LDL-C targets in clinical practice, particularly for Asian populations.

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A Framework for Systematic Assessment of Clinical Trial Population Representativeness Using Electronic Health Records Data

Applied Clinical Informatics ◽

10.1055/s-0041-1733846 ◽

2021 ◽

Vol 12 (04) ◽

pp. 816-825

Author(s):

Yingcheng Sun ◽

Alex Butler ◽

Ibrahim Diallo ◽

Jae Hyun Kim ◽

Casey Ta ◽

...

Keyword(s):

Clinical Trial ◽

Clinical Trials ◽

Electronic Health Records ◽

The United States ◽

Design Stage ◽

Common Data Model ◽

Free Text ◽

Eligibility Criteria ◽

Health Records ◽

Electronic Health

Abstract Background Clinical trials are the gold standard for generating robust medical evidence, but clinical trial results often raise generalizability concerns, which can be attributed to the lack of population representativeness. The electronic health records (EHRs) data are useful for estimating the population representativeness of clinical trial study population. Objectives This research aims to estimate the population representativeness of clinical trials systematically using EHR data during the early design stage. Methods We present an end-to-end analytical framework for transforming free-text clinical trial eligibility criteria into executable database queries conformant with the Observational Medical Outcomes Partnership Common Data Model and for systematically quantifying the population representativeness for each clinical trial. Results We calculated the population representativeness of 782 novel coronavirus disease 2019 (COVID-19) trials and 3,827 type 2 diabetes mellitus (T2DM) trials in the United States respectively using this framework. With the use of overly restrictive eligibility criteria, 85.7% of the COVID-19 trials and 30.1% of T2DM trials had poor population representativeness. Conclusion This research demonstrates the potential of using the EHR data to assess the clinical trials population representativeness, providing data-driven metrics to inform the selection and optimization of eligibility criteria.

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Are clinical trial eligibility criteria an accurate reflection of a real-world population of advanced non-small-cell lung cancer patients?

Current Oncology ◽

10.3747/co.25.3978 ◽

2018 ◽

Vol 25 (4) ◽

Cited By ~ 12

Author(s):

K. Al-Baimani ◽

H. Jonker ◽

T. Zhang ◽

G.D. Goss ◽

S.A. Laurie ◽

...

Keyword(s):

Lung Cancer ◽

Clinical Trial ◽

Clinical Trials ◽

Small Cell Lung Cancer ◽

Cell Lung Cancer ◽

Advanced Nsclc ◽

Small Cell ◽

Small Cell Lung ◽

Eligibility Criteria ◽

Ecog Ps

Background Advanced non-small-cell lung cancer (nsclc) represents a major health issue globally. Systemic treatment decisions are informed by clinical trials, which, over years, have improved the survival of patients with advanced nsclc. The applicability of clinical trial results to the broad lung cancer population is unclear because strict eligibility criteria in trials generally select for optimal patients.Methods We performed a retrospective chart review of all consecutive patients with advanced nsclc seen in outpatient consultation at our academic institution between September 2009 and September 2012, collecting data about patient demographics and cancer characteristics, treatment, and survival from hospital and pharmacy records. Two sets of arbitrary trial eligibility criteria were applied to the cohort. Scenario A stipulated Eastern Cooperative Oncology Group performance status (ecog ps) 0–1, no brain metastasis, creatinine less than 120 μmol/L, and no second malignancy. Less-strict scenario B stipulated ecog ps 0–2 and creatinine less than 120 μmol/L. We then used the two scenarios to analyze treatment and survival of patients by trial eligibility status.Results The 528 included patients had a median age of 67 years, with 55% being men and 58% having adenocarcinoma. Of those 528 patients, 291 received at least 1 line of palliative systemic therapy. Using the scenario A eligibility criteria, 73% were trial-ineligible. However, 46% of “ineligible” patients actually received therapy and experienced survival similar to that of the “eligible” treated patients (10.2 months vs. 11.6 months, p = 0.10). Using the scenario B criteria, only 35% were ineligible, but again, the survival of treated patients was similar in the ineligible and eligible groups (10.1 months vs. 10.9 months, p = 0.57).Conclusions Current trial eligibility criteria are often strict and limit the enrolment of patients in clinical trials. Our results suggest that, depending on the chosen drug, its toxicities and tolerability, eligibility criteria could be carefully reviewed and relaxed.

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Key Barriers to Clinical Trial Enrolment: A Survey of Clinical Trial Staff at an NCI Designated Cancer Center

Blood ◽

10.1182/blood-2019-126257 ◽

2019 ◽

Vol 134 (Supplement_1) ◽

pp. 5864-5864

Author(s):

Amany R. Keruakous ◽

Adam S. Asch

Keyword(s):

Clinical Trial ◽

Clinical Trials ◽

Cultural Bias ◽

Cancer Center ◽

Exclusion Criteria ◽

Strict Inclusion ◽

Trial Protocols ◽

Trial Staff ◽

Disease Site ◽

Patient Enrolment

Background: Clinical trials, key elements of the processes that account for many of the recent advances in cancer care, are becoming more complex and challenging to conduct. The Stephenson Cancer Center (SCC) has been the lead accruer to NCI-LAP trials over the past three years, and in addition, fields investigator initiated and industry sponsored trials. To identify opportunities for continued improvement in clinical trial enrolment, we sought to identify the obstacles encountered by our clinical trial staff in these activities. Method: We conducted a survey of our research staff including all research nurses and disease site coordinators who participate in recruitment, screening, consenting, data collection and compliance. The survey, sent by email to the clinical trial list-serve at SCC (90 staff member), invited respondents to enumerate obstacles to patient participation in clinical trials. We then performed a follow up meeting with our research coordinators to clarify responses. A total of 26 responses from 90 respondents were received and tabulated by disease site. Results: The most commonly reported obstacles to enrolment were, in descending order: communication/language barriers, cultural bias, time/procedure commitment, and complexity of the trial protocol, financial logistics, comorbidities, and stringent trial criteria. Respondents identified 83 obstacles as frequently encountered obstacles to enrolment. The 83 reported obstacles were classified into 9 categories and organized by disease site as presented in tabular format (below). The most commonly identified obstacles to patient enrolment were communication and language barriers. In patients for whom Spanish is the primary language this was a universal obstacle, as there is a lack of consistent Spanish consents across the clinical trial portfolio. Cultural bias, as an obstacle was manifested as a general mistrust by prospective trial participants of experimental therapies and clinical trials. After communication and cultural bias as barriers, travel requirements and the associated expenses playing a role in patients from rural areas were identified as the most commonly encountered barrier. The complexity of trial protocols and the associated large number of clinic visits, frequent laboratory and imaging tests were also identified as common obstacles. Clinical trial complexity with strict inclusion and exclusion criteria and trial-specified biopsies were frequently cited. Implications: In this descriptive study, common barriers to patient enrolment in clinical trials were identified by clinical trial staff. Assessing barriers encountered by clinical trial staff is infrequently used as a metric for improving clinical trial enrolment, but provides important perspective. In our study, some obstacles are inherent in our patient populations, others appear to be actionable. Development of Spanish language consents and specific programs to overcome negative bias regarding clinical trials are potential areas for improvement. The complexity of clinical trial protocols and the increasingly strict inclusion/exclusion criteria, are issues that will require consideration and action at the level of the cooperative groups and industry. Disclosures No relevant conflicts of interest to declare.

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Safety and Effectiveness of Favipiravir for Novel Coronavirus (COVID-19): A Rapid Review of Available Evidence

Health Technology Assessment in Action ◽

10.18502/htaa.v4i1.5862 ◽

2021 ◽

Author(s):

Mohammadreza Mobinizadeh ◽

Morteza Arab-Zozani

Keyword(s):

Clinical Trial ◽

Clinical Trials ◽

Therapeutic Potential ◽

Data Extraction ◽

Rapid Review ◽

Eligibility Criteria ◽

Clinical Trial Registration ◽

Registration System ◽

Novel Coronavirus ◽

First Time

Context: Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) appeared for the first time in December 2019 in Wuhan, China. Due to the lack of unified and integrated evidence for Favipiravir, this study was conducted to rapidly review the existing evidence to help evidence-based decision-making on the therapeutic potential of this drug in the treatment of COVID-19 patients. Evidence Acquisition: This study is a rapid Health Technology Assessment (HTA). By searching pertinent databases, the research team collected relevant articles and tried to create a policy guide through a thematic approach. This rapid review was done in four steps: (1) Searching for evidence through databases; (2) screening the evidence considering eligibility criteria; (3) data extraction; and (4) analyzing the data through thematic analysis. Results: After applying the inclusion criteria, four studies were finally found, including three review studies and a clinical trial that was temporarily removed by its publisher from the journal’s website. After searching the sources mentioned in the articles, two ongoing clinical trials were found in China. Also, by searching the clinical trial website, www.clinicaltrials.gov, five clinical trials were found in the search. The result of the search in the clinical trial registration system in Iran showed a study that is in the process of patient recruitment. A limited number of other articles were found, mostly in the form of reflections from physicians or researchers and letters to editors who have predicted the drug’s performance on SARS-CoV-2, which needs further clinical study to be approved. Conclusions: With the available evidence, it is not possible to make a definite conclusion about the safety and efficacy of Favipiravir in the treatment of patients with COVID-19.

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2166

Journal of Clinical and Translational Science ◽

10.1017/cts.2017.59 ◽

2017 ◽

Vol 1 (S1) ◽

pp. 12-12

Author(s):

Jianyin Shao ◽

Ram Gouripeddi ◽

Julio C. Facelli

Keyword(s):

Clinical Trial ◽

Clinical Trials ◽

Power Distribution ◽

Large Scale ◽

Search Space ◽

Free Text ◽

Eligibility Criteria ◽

Clinical Notes ◽

Semantic Concepts ◽

Mimic Iii

OBJECTIVES/SPECIFIC AIMS: This poster presents a detailed characterization of the distribution of semantic concepts used in the text describing eligibility criteria of clinical trials reported to ClincalTrials.gov and patient notes from MIMIC-III. The final goal of this study is to find a minimal set of semantic concepts that can describe clinical trials and patients for efficient computational matching of clinical trial descriptions to potential participants at large scale. METHODS/STUDY POPULATION: We downloaded the free text describing the eligibility criteria of all clinical trials reported to ClinicalTrials.gov as of July 28, 2015, ~195,000 trials and ~2,000,000 clinical notes from MIMIC-III. Using MetaMap 2014 we extracted UMLS concepts (CUIs) from the collected text. We calculated the frequency of presence of the semantic concepts in the texts describing the clinical trials eligibility criteria and patient notes. RESULTS/ANTICIPATED RESULTS: The results show a classical power distribution, Y=210X(−2.043), R2=0.9599, for clinical trial eligibility criteria and Y=513X(−2.684), R2=0.9477 for MIMIC patient notes, where Y represents the number of documents in which a concept appears and X is the cardinal order the concept ordered from more to less frequent. From this distribution, it is possible to realize that from the over, 100,000 concepts in UMLS, there are only ~60,000 and 50,000 concepts that appear in less than 10 clinical trial eligibility descriptions and MIMIC-III patient clinical notes, respectively. This indicates that it would be possible to describe clinical trials and patient notes with a relatively small number of concepts, making the search space for matching patients to clinical trials a relatively small sub-space of the overall UMLS search space. DISCUSSION/SIGNIFICANCE OF IMPACT: Our results showing that the concepts used to describe clinical trial eligibility criteria and patient clinical notes follow a power distribution can lead to tractable computational approaches to automatically match patients to clinical trials at large scale by considerably reducing the search space. While automatic patient matching is not the panacea for improving clinical trial recruitment, better low cost computational preselection processes can allow the limited human resources assigned to patient recruitment to be redirected to the most promising targets for recruitment.

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Strategy for addressing research-site overlap in pragmatic clinical trials: lessons learned from the NIH-DOD-VA Pain Management Collaboratory (PMC)

Trials ◽

10.1186/s13063-020-04941-8 ◽

2020 ◽

Vol 21 (1) ◽

Author(s):

Mary Geda ◽

◽

Steven Z. George ◽

Diana J. Burgess ◽

Dylan V. Scarton ◽

...

Keyword(s):

Clinical Trials ◽

Pain Management ◽

Research Effort ◽

Health Care Systems ◽

Lessons Learned ◽

Exclusion Criteria ◽

Eligibility Criteria ◽

Recruitment Methods ◽

Research Site ◽

Pragmatic Clinical Trials

Abstract Background The Pain Management Collaboratory (PMC) is a multi-site network of pragmatic clinical trials (PCTs) focused on nonpharmacological approaches to pain management, conducted in health care systems of the US Department of Defense (DoD) and Department of Veterans Affairs (VA) and co-funded by the National Institutes of Health (NIH). Concerns about potential research-site overlap prompted the PMC investigator community to consider strategies to avert this problem that could negatively affect recruitment and contaminate interventions and thus pose a threat to trial integrity. Methods We developed a two-step strategy to identify and remediate research-site overlap by obtaining detailed recruitment plans across all PMC PCTs that addressed eligibility criteria, recruitment methods, trial settings, and timeframes. The first, information-gathering phase consisted of a 2-month period for data collection from PIs, stakeholders, and ClinicalTrials.gov. The second, remediation phase consisted of a series of moderated conference calls over a 1-month time period to develop plans to address overlap. Remediation efforts focused on exclusion criteria and recruitment strategies, and they involved collaboration with sponsors and stakeholder groups such as the Military Treatment Facility Engagement Committee (MTFEC). The MTFEC is comprised of collaborating DoD and university-affiliated PIs, clinicians, and educators devoted to facilitating successful pragmatic trials in DoD settings. Results Of 61 recruitment sites for the 11 PMC PCTs, 17 (28%) overlapped. Four PCTs had five overlapping Military Treatment Facilities (MTFs), and eight PCTs had 12 overlapping VA Medical Centers (VAMCs). We developed three general strategies to avoid research-site overlap: (i) modify exclusion criteria, (ii) coordinate recruitment efforts, and/or (iii) replace or avoid any overlapping sites. Potential overlap from competing studies outside of the PMC was apparent at 26 sites, but we were not able to confirm them as true conflicts. Conclusion Proactive strategies can be used to resolve the issue of overlapping research sites in the PMC. These strategies, combined with open and impartial mediation approaches that include researchers, sponsors, and stakeholders, provide lessons learned from this large and complex pragmatic research effort.

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