caCORE version 3: Implementation of a model driven, service-oriented architecture for semantic interoperability.

One of the requirements for a federated information system is interoperability, the ability of one computer system to access and use the resources of another system. This feature is particularly important in biomedical research systems, which need to coordinate a variety of disparate types of data. In order to meet this need, the National Cancer Institute Center for Bioinformatics (NCICB) has created the cancer Common Ontologic Representation Environment (caCORE), an interoperability infrastructure based on Model Driven Architecture. The caCORE infrastructure provides a mechanism to create interoperable biomedical information systems. Systems built using the caCORE paradigm address both aspects of interoperability: the ability to access data (syntactic interoperability) and understand the data once retrieved (semantic interoperability). This infrastructure consists of an integrated set of three major components: a controlled terminology service (Enterprise Vocabulary Services), a standards-based metadata repository (the cancer Data Standards Repository) and an information system with an Application Programming Interface (API) based on Domain Model Driven Architecture. This infrastructure is being leveraged to create a Semantic Service-Oriented Architecture (SSOA) for cancer research by the National Cancer Institute's cancer Biomedical Informatics Grid (caBIG).

The cancer translational research informatics platform.

BACKGROUND: Despite the pressing need for the creation of applications that facilitate the aggregation of clinical and molecular data, most current applications are proprietary and lack the necessary compliance with standards that would allow for cross-institutional data exchange. In line with its mission of accelerating research discoveries and improving patient outcomes by linking networks of researchers, physicians, and patients focused on cancer research, caBIG (cancer Biomedical Informatics Grid) has sponsored the creation of the caTRIP (Cancer Translational Research Informatics Platform) tool, with the purpose of aggregating clinical and molecular data in a repository that is user-friendly, easily accessible, as well as compliant with regulatory requirements of privacy and security. RESULTS: caTRIP has been developed as an N-tier architecture, with three primary tiers: domain services, the distributed query engine, and the graphical user interface, primarily making use of the caGrid infrastructure to ensure compatibility with other tools currently developed by caBIG. The application interface was designed so that users can construct queries using either the Simple Interface via drop-down menus or the Advanced Interface for more sophisticated searching strategies to using drag-and-drop. Furthermore, the application addresses the security concerns of authentication, authorization, and delegation, as well as an automated honest broker service for deidentifying data. CONCLUSION: Currently being deployed at Duke University and a few other centers, we expect that caTRIP will make a significant contribution to further the development of translational research through the facilitation of its data exchange and storage processes.

The caCORE Software Development Kit: streamlining construction of interoperable biomedical information services.

BACKGROUND: Robust, programmatically accessible biomedical information services that syntactically and semantically interoperate with other resources are challenging to construct. Such systems require the adoption of common information models, data representations and terminology standards as well as documented application programming interfaces (APIs). The National Cancer Institute (NCI) developed the cancer common ontologic representation environment (caCORE) to provide the infrastructure necessary to achieve interoperability across the systems it develops or sponsors. The caCORE Software Development Kit (SDK) was designed to provide developers both within and outside the NCI with the tools needed to construct such interoperable software systems. RESULTS: The caCORE SDK requires a Unified Modeling Language (UML) tool to begin the development workflow with the construction of a domain information model in the form of a UML Class Diagram. Models are annotated with concepts and definitions from a description logic terminology source using the Semantic Connector component. The annotated model is registered in the Cancer Data Standards Repository (caDSR) using the UML Loader component. System software is automatically generated using the Codegen component, which produces middleware that runs on an application server. The caCORE SDK was initially tested and validated using a seven-class UML model, and has been used to generate the caCORE production system, which includes models with dozens of classes. The deployed system supports access through object-oriented APIs with consistent syntax for retrieval of any type of data object across all classes in the original UML model. The caCORE SDK is currently being used by several development teams, including by participants in the cancer biomedical informatics grid (caBIG) program, to create compatible data services. caBIG compatibility standards are based upon caCORE resources, and thus the caCORE SDK has emerged as a key enabling technology for caBIG. CONCLUSION: The caCORE SDK substantially lowers the barrier to implementing systems that are syntactically and semantically interoperable by providing workflow and automation tools that standardize and expedite modeling, development, and deployment. It has gained acceptance among developers in the caBIG program, and is expected to provide a common mechanism for creating data service nodes on the data grid that is under development.

The CAP cancer protocols--a case study of caCORE based data standards implementation to integrate with the Cancer Biomedical Informatics Grid.

BACKGROUND: The Cancer Biomedical Informatics Grid (caBIG) is a network of individuals and institutions, creating a world wide web of cancer research. An important aspect of this informatics effort is the development of consistent practices for data standards development, using a multi-tier approach that facilitates semantic interoperability of systems. The semantic tiers include (1) information models, (2) common data elements, and (3) controlled terminologies and ontologies. The College of American Pathologists (CAP) cancer protocols and checklists are an important reporting standard in pathology, for which no complete electronic data standard is currently available. METHODS: In this manuscript, we provide a case study of Cancer Common Ontologic Representation Environment (caCORE) data standard implementation of the CAP cancer protocols and checklists model--an existing and complex paper based standard. We illustrate the basic principles, goals and methodology for developing caBIG models. RESULTS: Using this example, we describe the process required to develop the model, the technologies and data standards on which the process and models are based, and the results of the modeling effort. We address difficulties we encountered and modifications to caCORE that will address these problems. In addition, we describe four ongoing development projects that will use the emerging CAP data standards to achieve integration of tissue banking and laboratory information systems. CONCLUSION: The CAP cancer checklists can be used as the basis for an electronic data standard in pathology using the caBIG semantic modeling methodology.

Development of the National Cancer Institute's patient-reported outcomes version of the common terminology criteria for adverse events (PRO-CTCAE).

The standard approach for documenting symptomatic adverse events (AEs) in cancer clinical trials involves investigator reporting using the National Cancer Institute's (NCI's) Common Terminology Criteria for Adverse Events (CTCAE). Because this approach underdetects symptomatic AEs, the NCI issued two contracts to create a patient-reported outcome (PRO) measurement system as a companion to the CTCAE, called the PRO-CTCAE. This Commentary describes development of the PRO-CTCAE by a group of multidisciplinary investigators and patient representatives and provides an overview of qualitative and quantitative studies of its measurement properties. A systematic evaluation of all 790 AEs listed in the CTCAE identified 78 appropriate for patient self-reporting. For each of these, a PRO-CTCAE plain language term in English and one to three items characterizing the frequency, severity, and/or activity interference of the AE were created, rendering a library of 124 PRO-CTCAE items. These items were refined in a cognitive interviewing study among patients on active cancer treatment with diverse educational, racial, and geographic backgrounds. Favorable measurement properties of the items, including construct validity, reliability, responsiveness, and between-mode equivalence, were determined prospectively in a demographically diverse population of patients receiving treatments for many different tumor types. A software platform was built to administer PRO-CTCAE items to clinical trial participants via the internet or telephone interactive voice response and was refined through usability testing. Work is ongoing to translate the PRO-CTCAE into multiple languages and to determine the optimal approach for integrating the PRO-CTCAE into clinical trial workflow and AE analyses. It is envisioned that the PRO-CTCAE will enhance the precision and patient-centeredness of adverse event reporting in cancer clinical research.

Electronic toxicity monitoring and patient-reported outcomes.

Understanding the potential profile of adverse events associated with cancer treatment is essential in balancing safety versus benefits. Multiple stakeholders make use of this information for decision making, including patients, clinicians, researchers, regulators, and payors. Currently, adverse events are reported by clinical research staff, yet evidence suggests that this may contribute to underreporting of symptom events. Direct patient reporting via electronic interfaces offers a promising mechanism to enhance the efficiency and precision of our current approach and may complement clinician reports of adverse events. The National Cancer Institute has contracted to develop and test an item bank and software system for directly eliciting adverse symptom event information from patients in cancer clinical research, called the Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events. The validity, usability, and scalability of the Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events prototype are currently being examined in academic and community-based settings.

Common data element (CDE) management and deployment in clinical trials.

The NCI provides the cancer Data Standards Repository (caDSR) to support development and deployment of CDEs in cancer research. The caDSR, part of the NCI caCORE infrastructure, supports data management workflow requirements and adherence to ISO/IEC 11179 metadata standards. CDEs are developed using standard terminology from caCORE vocabulary services, and are then deployed to multi-site clinical trials data management systems. Here we describe the caDSR and how CDEs are managed and deployed in clinical research.