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Letters |
Clinical Data Interchange, Standards Consortium, PO Box 162033, Austin, TX 78716-2033, Fax 512-301-5480
E-mail s.bassion{at}worldnet.att.net
To the Editor:
In 2001, an estimated 2.3 million people in the United States participated in and completed a clinical trial: 750 000 in government-sponsored clinical trials, 850 000 in industry-sponsored Phase I to III clinical trials, and 700 000 in industry sponsored Phase IV clinical trials (1). Major medical center participation in the conduct of clinical trials grew strongly in 2001. More than 65% of academic health centers have established centralized clinical trial offices that encourage and support the involvement of their departments and staff in the conduct of clinical trials (1). Many of the laboratories in those institutions are asked to support investigator participation. Clinical chemistry testing is the mainstay of the drug-safety tests that underlie all clinical trials, and laboratory data derived from tests of both drug safety and efficacy have been estimated to be as much as 60–80% of the data generated during the conduct of clinical trials. Because of this, laboratories are extremely important players in the clinical trial process.
Much time and effort is involved in the transfer of clinical trial laboratory data among the parties involved: the reference, performing, or central laboratory; contract-research organization (CRO); pharmaceutical company; and pharmaceutical partners. Some central clinical laboratories are now required to support hundreds of different interfaces to accommodate the different data requirements of pharmaceutical and biotechnology companies and CROs. Each series of database formats requires development and validation, staff training, formal maintenance, and appropriate quality control.
Players involved in conducting or supporting clinical trials for drug research and development would benefit from a common interchange standard for all types of clinical trial data, particularly clinical laboratory data. At present, data collected in support of clinical trials are collected and handled separate from data collected to support clinical care, although both sets of information share many (but not all) data elements. Clinical care data tend to be transactional (i.e., one patient, one or few tests, one or few results transferred). Clinical trial data require the transfer of large volumes of data (i.e., many patients, many tests). Clinical trial data also include increased numbers of identifiers and substantial metadata including those data elements needed to support an audit trail.
The standardization of data collected in support of clinical trials is the focus of the Clinical Data Interchange Standards Consortium (CDISC), a not-for-profit organization with hundreds of active participants and liaison groups in Europe and Japan. More than 80 companies provide funding as corporate sponsors and members. The work of CDISC is accomplished through multidisciplinary volunteer teams that have focused on the development of models to support the various types of electronic data interchange that support clinical trials. CDISC recognizes that the standardization of data collection in clinical trials is an important step in linking clinical research to clinical care.
The CDISC Lab Team, composed of representatives from central clinical laboratories, pharmaceutical companies, CROs, and technology-application developers, has developed a model to support the acquisition and interchange of clinical laboratory data from a performing, reference, or central laboratory into an operational database at a central laboratory, sponsor pharmaceutical or biotechnology company, or CRO.
The team considered existing data standards and the limitations that have prevented their adoption to handle laboratory data generated during the conduct of clinical research. Existing standards include those of ASTM International, Health Level 7 (HL7), the Association for Clinical Data Management (ACDM), and X12. These existing standards are not well known in the drug-development community. In addition (with the exception of the ACDM standards), they have not been applied to the large volumes of data generated in drug-development research and are unsupported by pharmaceutical companies. Many handle general healthcare and transactional data transfers well but may be inflexible, inefficient, have inadequate field definitions (and thus too much variability), or have population rules that do not match the structures and relationships of clinical trials. Thus, the Lab Team pursued the development of a well-considered, flexible, but structured standard that would serve the needs of the drug-development user group.
The Lab Team then worked to define "clinical laboratory data" within the context of a clinical trial, building a superset of data items that fully describe its laboratory elements. Wherever possible, appropriate existing standards (including LOINC and HL 7 code lists) were used because CDISC is committed to working with other professional groups to share information and minimize duplication of effort. The Lab Team determined that the model content should have a main core to handle "simple" laboratory tests with a classic "one test, one result" structure. More complex testing would require the development of extensions. The model was also developed as a multilayer creation with first the content layer and, above that, an implementation layer. In this way, content could be constant, even if the implementation approach changed. This approach enhances flexibility and creates a model that is independent of implementation. Default implementation is a bar-delimited ASCII format. Both SAS and XML implementations are also supported. In addition, the team is also looking at ways to represent the model as an HL7 message (the mainstay of messaging in a clinical-care environment) that would serve to better link clinical trials in an integrated full-care context from bedside through drug-regulatory approval.
The CDISC Laboratory Model consists of a superset of data fields that are separated into 10 logical levels as follows: Good Transmission Practice, Study, Site, Subject, Visit, Accession, Container, Panel, Test, Results. These levels were chosen because they follow the recognizable hierarchy of clinical laboratory data generated during clinical trials. The model has been reviewed by experts and extensively tested. Detailed information on the CDISC Laboratory Model and on each of these levels is available on the website (http://www.CDISC.org) and at CDISC (P.O. Box 162033, Austin TX 78716-2033). The CDISC Lab Team is interested in wider feedback on its Laboratory Model from the clinical laboratory community that is working in support of pharmaceutical clinical trial research. If the newly proposed clinical laboratory data interchange model is to be successful, it must meet the needs of all laboratories involved in supporting clinical trials.
References
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