Developing an effective and compliant plan for billing clinical trials.
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ABSTRACT:
SUBMITTER: Pitler LR
PROVIDER: S-EPMC2793665 | biostudies-literature | 2006 Nov
REPOSITORIES: biostudies-literature
Publications
Developing an effective and compliant plan for billing clinical trials.
Pitler Lisa R LR Bonomi Philip D PD
Journal of oncology practice 20061101 6
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Project description:BackgroundA recent survey has shown that data management in clinical trials performed by academic trial units still faces many difficulties (e.g. heterogeneity of software products, deficits in quality management, limited human and financial resources and the complexity of running a local computer centre). Unfortunately, no specific, practical and open standard for both GCP-compliant data management and the underlying IT-infrastructure is available to improve the situation. For that reason the "Working Group on Data Centres" of the European Clinical Research Infrastructures Network (ECRIN) has developed a standard specifying the requirements for high quality GCP-compliant data management in multinational clinical trials.MethodsInternational, European and national regulations and guidelines relevant to GCP, data security and IT infrastructures, as well as ECRIN documents produced previously, were evaluated to provide a starting point for the development of standard requirements. The requirements were produced by expert consensus of the ECRIN Working group on Data Centres, using a structured and standardised process. The requirements were divided into two main parts: an IT part covering standards for the underlying IT infrastructure and computer systems in general, and a Data Management (DM) part covering requirements for data management applications in clinical trials.ResultsThe standard developed includes 115 IT requirements, split into 15 separate sections, 107 DM requirements (in 12 sections) and 13 other requirements (2 sections). Sections IT01 to IT05 deal with the basic IT infrastructure while IT06 and IT07 cover validation and local software development. IT08 to IT015 concern the aspects of IT systems that directly support clinical trial management. Sections DM01 to DM03 cover the implementation of a specific clinical data management application, i.e. for a specific trial, whilst DM04 to DM12 address the data management of trials across the unit. Section IN01 is dedicated to international aspects and ST01 to the competence of a trials unit's staff.ConclusionsThe standard is intended to provide an open and widely used set of requirements for GCP-compliant data management, particularly in academic trial units. It is the intention that ECRIN will use these requirements as the basis for the certification of ECRIN data centres.
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Project description:Following European regulation 1394/2007, mesenchymal stromal cell (MSCs) have become an advanced therapy medicinal product (ATMP) that must be produced following the good manufacturing practice (GMP) standards. We describe the upgrade of our existing clinical-grade MSC manufacturing process to obtain GMP certification. Staff organization, premises/equipment qualification and monitoring, raw materials management, starting materials, technical manufacturing processes, quality controls, and the release, thawing and infusion were substantially reorganized. Numerous studies have been carried out to validate cultures and demonstrate the short-term stability of fresh or thawed products, as well their stability during long-term storage. Detailed results of media simulation tests, validation runs and early MSC batches are presented. We also report the validation of a new variant of the process aiming to prepare fresh MSCs for the treatment of specific lesions of Crohn's disease by local injection. In conclusion, we have successfully ensured the adaptation of our clinical-grade MSC production process to the GMP requirements. The GMP manufacturing of MSC products is feasible in the academic setting for a limited number of batches with a significant cost increase, but moving to large-scale production necessary for phase III trials would require the involvement of industrial partners.
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Project description:Clinical trials are essential for generating reliable medical evidence, but often suffer from expensive and delayed patient recruitment because the unstructured eligibility criteria description prevents automatic query generation for eligibility screening. In response to the COVID-19 pandemic, many trials have been created but their information is not computable. We included 700 COVID-19 trials available at the point of study and developed a semi-automatic approach to generate an annotated corpus for COVID-19 clinical trial eligibility criteria called COVIC. A hierarchical annotation schema based on the OMOP Common Data Model was developed to accommodate four levels of annotation granularity: i.e., study cohort, eligibility criteria, named entity and standard concept. In COVIC, 39 trials with more than one study cohorts were identified and labelled with an identifier for each cohort. 1,943 criteria for non-clinical characteristics such as "informed consent", "exclusivity of participation" were annotated. 9767 criteria were represented by 18,161 entities in 8 domains, 7,743 attributes of 7 attribute types and 16,443 relationships of 11 relationship types. 17,171 entities were mapped to standard medical concepts and 1,009 attributes were normalized into computable representations. COVIC can serve as a corpus indexed by semantic tags for COVID-19 trial search and analytics, and a benchmark for machine learning based criteria extraction.
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Project description:A major issue in oncology is the high failure rate of translating preclinical results in successful clinical trials. Using a virtual clinical trial simulations approach, we present a mathematical framework to estimate the added value of combinatorial treatments in ovarian cancer. This approach was applied to identify effective targeted therapies that can be combined with the platinum-taxane regimen and overcome platinum resistance in high-grade serous ovarian cancer. We modeled and evaluated the effectiveness of three drugs that target the main platinum resistance mechanisms, which have shown promising efficacy in vitro, in vivo, and early clinical trials. Our results show that drugs resensitizing chemoresistant cells are superior to those aimed at triggering apoptosis or increasing the bioavailability of platinum. Our results further show that the benefit of using biomarker stratification in clinical trials is dependent on the efficacy of the drug and tumor composition. The mathematical framework presented herein is suitable for systematically testing various drug combinations and clinical trial designs in solid cancers.
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Project description:BackgroundThe failure to retain patients or collect primary-outcome data is a common challenge for trials and reduces the statistical power and potentially introduces bias into the analysis. Identifying strategies to minimise missing data was the second highest methodological research priority in a Delphi survey of the Directors of UK Clinical Trial Units (CTUs) and is important to minimise waste in research. Our aim was to assess the current retention practices within the UK and priorities for future research to evaluate the effectiveness of strategies to reduce attrition.MethodsSeventy-five chief investigators of NIHR Health Technology Assessment (HTA)-funded trials starting between 2009 and 2012 were surveyed to elicit their awareness about causes of missing data within their trial and recommended practices for improving retention. Forty-seven CTUs registered within the UKCRC network were surveyed separately to identify approaches and strategies being used to mitigate missing data across trials. Responses from the current practice surveys were used to inform a subsequent two-round Delphi survey with registered CTUs. A consensus list of retention research strategies was produced and ranked by priority.ResultsFifty out of seventy-five (67%) chief investigators and 33/47 (70%) registered CTUs completed the current practice surveys. Seventy-eight percent of trialists were aware of retention challenges and implemented strategies at trial design. Patient-initiated withdrawal was the most common cause of missing data. Registered CTUs routinely used newsletters, timeline of participant visits, and telephone reminders to mitigate missing data. Whilst 36 out of 59 strategies presented had been formally or informally evaluated, some frequently used strategies, such as site initiation training, have had no research to inform practice. Thirty-five registered CTUs (74%) participated in the Delphi survey. Research into the effectiveness of site initiation training, frequency of patient contact during a trial, the use of routinely collected data, the frequency and timing of reminders, triggered site training and the time needed to complete questionnaires was deemed critical. Research into the effectiveness of Christmas cards for site staff was not of critical importance.ConclusionThe surveys of current practices demonstrates that a variety of strategies are being used to mitigate missing data but with little evidence to support their use. Six retention strategies were deemed critically important within the Delphi survey and should be a primary focus of future retention research.
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Project description:BackgroundThere is wide recognition that pragmatic randomised trials are the best vehicle for economic evaluation. This is because trials provide the best chance of ensuring internal validity, not least through the rigorous prospective collection of patient-specific data. Furthermore the marginal cost of collecting economic data alongside clinical data is typically modest. UK Clinical Research Collaboration (UKCRC) does not require a standard operating procedure (SOP) for economic evaluation as a prerequisite for trial unit registration. We judge that such a SOP facilitates the integration of health economics into trials.MethodsA collaboration between health economists and trialists at Bangor University led to the development of a SOP for economic evaluation alongside pragmatic trials, in addition to the twenty SOPs required by UKCRC for registration, which include randomisation, data management and statistical analysis.ResultsOur recent telephone survey suggests that no other UKCRC-registered trials unit currently has an economic SOP.ConclusionWe argue that UKCRC should require, from all Trials Units undertaking economic evaluation and seeking registration or re-registration, a SOP for economic evaluation as one of their portfolio of supporting SOPs.
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Project description:Background and purposeThe efficacy of clinical trials and the outcome of patient treatment are dependent on the quality assurance (QA) of radiation therapy (RT) plans. There are two widely utilized approaches that include plan optimization guidance created based on patient-specific anatomy. This study examined these two techniques for dose-volume histogram predictions, RT plan optimizations, and prospective QA processes, namely the knowledge-based planning (KBP) technique and another first principle (FP) technique.MethodsThis analysis included 60, 44, and 10 RT plans from three Radiation Therapy Oncology Group (RTOG) multi-institutional trials: RTOG 0631 (Spine SRS), RTOG 1308 (NSCLC), and RTOG 0522 (H&N), respectively. Both approaches were compared in terms of dose prediction and plan optimization. The dose predictions were also compared to the original plan submitted to the trials for the QA procedure.ResultsFor the RTOG 0631 (Spine SRS) and RTOG 0522 (H&N) plans, the dose predictions from both techniques have correlation coefficients of >0.9. The RT plans that were re-optimized based on the predictions from both techniques showed similar quality, with no statistically significant differences in target coverage or organ-at-risk sparing. The predictions of mean lung and heart doses from both methods for RTOG1308 patients, on the other hand, have a discrepancy of up to 14 Gy.ConclusionsBoth methods are valuable tools for optimization guidance of RT plans for Spine SRS and Head and Neck cases, as well as for QA purposes. On the other hand, the findings suggest that KBP may be more feasible in the case of inoperable lung cancer patients who are treated with IMRT plans that have spatially unevenly distributed beam angles.
| S-EPMC8504592 | biostudies-literature