Exploring Data Quality Management within Clinical Trials

Houston, Lauren; Probst, Yasmine; Yu, Ping; Martin, Allison

doi:10.1055/s-0037-1621702

Cited by 32 publications

(24 citation statements)

References 34 publications

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“…Across trials it is observed that those with 2 arms and a 1:1 randomization to drug or placebo have smaller placebo responses (and larger drug-placebo differences) than multi-arm trials [ 98 ]. Central review of the collection of the primary outcomes measures and the entry criteria (at randomization) helps ensure that the behavioral changes are accurately rated and sufficiently severe to meet the randomization criteria [ 99 ]. Central reviewers listen to a recorded audio tape of the interview or may watch a videotaped interview.…”

Section: Reviewmentioning

confidence: 99%

New approaches to symptomatic treatments for Alzheimer’s disease

Cummings

2021

Mol Neurodegeneration

136

114

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Background Successful development of agents that improve cognition and behavior in Alzheimer’s disease (AD) is critical to improving the lives of patients manifesting the symptoms of this progressive disorder. Discussion There have been no recent approvals of cognitive enhancing agents for AD. There are currently 6 cognitive enhancers in Phase 2 trials and 4 in phase 3. They represent a variety of novel mechanisms. There has been progress in developing new treatments for neuropsychiatric symptoms in AD with advances in treatment of insomnia, psychosis, apathy, and agitation in AD. There are currently 4 AD-related psychotropic agents in Phase 2 trials and 7 in Phase 3 trials. Many novel mechanisms are being explored for the treatment of cognitive and behavioral targets. Progress in trial designs, outcomes measures, and population definitions are improving trial conduct for symptomatic treatment of AD. Conclusions Advances in developing new agents for cognitive and behavioral symptoms of AD combined with enhanced trial methods promise to address the unmet needs of patients with AD for improved cognition and amelioration of neuropsychiatric symptoms.

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Section: Reviewmentioning

confidence: 99%

New approaches to symptomatic treatments for Alzheimer’s disease

Cummings

2021

Mol Neurodegeneration

136

114

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“…Previous studies about clinical drug trial quality usually focused on specific aspects, such as trial design, 5 subject recruitment, 6,7 rights protection, [8][9][10][11][12][13][14] role of nurses, [15][16][17][18] control of side effects 16,19 and trial data 20,21 from a micro-perspective. Further, Moher et al, 2 Verhagen et al, 22 Maher et al 23 and Liu et al 24 undertook comprehensive studies that analysed the components, determinants and evaluation instruments with respect to quality of clinical trials: such efforts emphasize the design or implementation of trials at the micro-level.…”

Section: What Is K Nown and Objec Tivementioning

confidence: 99%

Quality of phase I clinical drug trials: Influence of organizational management factors

2020

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What is known and Objective Focusing on the tolerance and pharmacokinetics of new drugs, phase I clinical drug trials are characterized by high risk, poor compliance and management difficulties. High‐quality clinical drug trials ensure subjects' safety while extending new drug research and development. Many studies have examined micro‐level concerns of trial design and implementation rather than macro‐level factors. Accordingly, we evaluated the quality of phase I clinical drug trials (trial quality) and analysed the influence of organizational management factors from a macro‐level perspective. Methods We surveyed staff at clinical trial institutions engaged in phase I clinical drug trials in China using convenience sampling. We employed a five‐point Likert‐scale questionnaire, comprising five items on phase I clinical drug trial quality and items on organizational management factors. Data from 604 questionnaires were analysed. We utilized a logistic regression model to estimate the influence of organizational management factors on trial quality, using individual demographic factors as controlling variables. Results and discussion The trial quality score was 3.81, which indicates that substantial improvement is required. Government regulation, industry management and medical institution management had a positive effect on trial quality: β = 0.842, 0.691 and 0.579, respectively; P < .01. Contract research organization management had a negative effect on trial quality: β = −0.476; P = .013. Research team management had no effect on trial quality: β = 0.325; P = .141. What is new and Conclusion This study is the first to model the influence of organizational management factors on the quality of phase I drug trials involving different organizations from a macro‐perspective. Efforts are needed to help research teams take responsibility for trial quality and to correct the negative impact of contract research organizations on trial quality.

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“…Unlike randomized clinical trials (RCTs), data validation for critical variables is rarely reported in observational studies. Although many data monitoring and auditing methods in RCTs have been frequently reported and compared [ 9 – 11 ], on-site source data verification (SDV) is still a common procedure to ensure high data quality in RCTs [ 12 ]. Since SDV is a very expensive and personnel-intensive method [ 13 ] and observational studies are often limited in its financial, time, and personnel resources, this approach is not feasible in most cases.…”

Section: Introductionmentioning

confidence: 99%

Implementing an automated monitoring process in a digital, longitudinal observational cohort study

et al. 2021

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Background Clinical data collection requires correct and complete data sets in order to perform correct statistical analysis and draw valid conclusions. While in randomized clinical trials much effort concentrates on data monitoring, this is rarely the case in observational studies- due to high numbers of cases and often-restricted resources. We have developed a valid and cost-effective monitoring tool, which can substantially contribute to an increased data quality in observational research. Methods An automated digital monitoring system for cohort studies developed by the German Rheumatism Research Centre (DRFZ) was tested within the disease register RABBIT-SpA, a longitudinal observational study including patients with axial spondyloarthritis and psoriatic arthritis. Physicians and patients complete electronic case report forms (eCRF) twice a year for up to 10 years. Automatic plausibility checks were implemented to verify all data after entry into the eCRF. To identify conflicts that cannot be found by this approach, all possible conflicts were compiled into a catalog. This “conflict catalog” was used to create queries, which are displayed as part of the eCRF. The proportion of queried eCRFs and responses were analyzed by descriptive methods. For the analysis of responses, the type of conflict was assigned to either a single conflict only (affecting individual items) or a conflict that required the entire eCRF to be queried. Results Data from 1883 patients was analyzed. A total of n = 3145 eCRFs submitted between baseline (T0) and T3 (12 months) had conflicts (40–64%). Fifty-six to 100% of the queries regarding eCRFs that were completely missing were answered. A mean of 1.4 to 2.4 single conflicts occurred per eCRF, of which 59–69% were answered. The most common missing values were CRP, ESR, Schober’s test, data on systemic glucocorticoid therapy, and presence of enthesitis. Conclusion Providing high data quality in large observational cohort studies is a major challenge, which requires careful monitoring. An automated monitoring process was successfully implemented and well accepted by the study centers. Two thirds of the queries were answered with new data. While conventional manual monitoring is resource-intensive and may itself create new sources of errors, automated processes are a convenient way to augment data quality.

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Exploring Data Quality Management within Clinical Trials

Abstract: Clinical trial sites are implementing ad hoc methods pragmatically to ensure data quality. Findings highlight the necessity for further research into "standard practice" focusing on developing and implementing publically available data quality monitoring procedures.

Cited by 32 publications

References 34 publications

New approaches to symptomatic treatments for Alzheimer’s disease

New approaches to symptomatic treatments for Alzheimer’s disease

Quality of phase I clinical drug trials: Influence of organizational management factors

Implementing an automated monitoring process in a digital, longitudinal observational cohort study

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