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Identifying Breast Cancer Treatment Biomarkers Using Transcriptomics
Published in Shazia Rashid, Ankur Saxena, Sabia Rashid, Latest Advances in Diagnosis and Treatment of Women-Associated Cancers, 2022
Transcriptomics-based biomarkers are adding a new layer of information in the clinical decision-making process for breast, ovarian and other cancer types. This is especially the case with non-evasive liquid biopsies that can make things much easier for patients, reducing risks. In general, NGS-based testing can improve response rate and progression-free survival. Cell-free DNA methylation coupled with transcriptional splicing has provided deeper insights, more biomarkers and causal genes for real-world testing. However, the tissue collection strategy for NGS will still be a matter of debate for some time to come. Costs, privacy and clinical data management will surely be the key areas to look for in the future.
Clinical Data Management and Statistical Design in the Clinical Research Process
Published in Gary M. Matoren, The Clinical Research Process in the Pharmaceutical Industry, 2020
Joseph R. Assenzo, Thomas W. Teal
Among the needs and objectives of clinical data management are the following: Maximizing accuracy in data transfer from the CRFs to the computer master file [verified by quality control audit prior to submission of each New Drug Application (NDA)]. Essentially, the master file should represent the physician's intentions as well as his writing. This implies that data discrepancies in CRFs, elicited through computer algorithms, be reconciled with the investigator to ensure an accurate recording of his intended response. An example of this would be an absent decimal point in a clinical laboratory value.Fast and economical transfer of the data from the CRF to the computer master file.The computer master file organized in a manner readily amenable to retrieval and manipulation for various management and analytical purposes.Master file and subsets of master files organized in a manner which will provide ready access for an extended period of time.A clinical data system that supports management in monitoring and administering the clinical trials from which the clinical data are developed.
Overview of Data Quality and Compliance Checks
Published in Sunil Gupta, Clinical Data Quality Checks for CDISC Compliance Using SAS, 2019
In clinical studies, when data issues from missing values in a required variable or duplicate records based on key variables exist, SAS program errors and warnings may occur since the programs do not expect them. This is because, in general, SAS programs assume data integrity to link related datasets together as well as meet data quality requirements to be meaningful. The non-missing, missing and duplicate records chart shows possible challenging LB cases when applying analysis windows. Often when these cases are found, clinical data management needs to be queried to determine how best to address these records. In addition, Statistical Analysis Plan (SAP) should also document this process. In Figure 1.6, this chart reviews the logic that needs to be applied to handle missing and duplicate records.
The Texas Immuno-Oncology Biorepository, a statewide biospecimen collection and clinical informatics system to enable longitudinal tumor and immune profiling
Published in Baylor University Medical Center Proceedings, 2023
Ronan J. Kelly, Timothy G. Whitsett, G. Jackson Snipes, Sheila M. Dobin, Jennifer Finholt, Natalie Settele, Elisa L. Priest, Kenneth Youens, Lucy B. Wallace, Gary Schwartz, Lucas Wong, Sherronda M. Henderson, Alan C. Gowan, Ekokobe Fonkem, Maria I. Juarez, Christal E. Murray, Jeffrey Wu, Kendall Van Keuren-Jensen, Patrick Pirrotte, Sarah Highlander, Tania Contente, Angela Baker, Jose Victorino, Michael E. Berens
The TIOB is building a scalable, flexible platform to meet current and evolving needs. This infrastructure involves multiple components including biospecimen management and tracking, clinical data management, patient-reported data, incident reporting, and results from sample analysis. Infrastructure for the TIOB is being developed following the software development lifecycle with explicit steps for requirements gathering, design, testing and validation, and maintenance. The TIOB utilizes a scalable cloud-based platform to integrate the different components, all linked through distinct study IDs. Biospecimen inventory and tracking is performed on the Freezerworks Summit platform. The software is accessed in a secure, role-specific, tiered-permission access information technology environment that assigns a unique sample identifier for each specimen or derivative. The software supports individual specimen check-in, check-out, and real-time inventory for each sample, in each location, in each freezer. The software also tracks specimen IDs, aliases, limited demographics, aliquots, and derivatives and relevant preanalytic variables for individual projects for each specimen and supports the production and tracking of individualized project-specific sample collection kits. Clinical data and patient-reported data are collected and managed using REDCap electronic data capture tools hosted at Baylor Scott & White Health.5,6
Traditional Use of Banisteriopsis caapi Alone and Its Application in a Context of Drug Addiction Therapy
Published in Journal of Psychoactive Drugs, 2021
Matteo Politi, Fabio Friso, Gary Saucedo, Jaime Torres
The clinical data management system of Takiwasi is an information and communication technology used for the collection, storage and management of the different data generated along the therapeutic process of SUD patients in residential treatment, with a focus on ritual sessions with medicinal plants (Saucedo et al. 2018). This system allows the registration of case report protocols that have been designed in accordance with the Center’s therapeutic protocol. At hospitalization, all patients sign an informed consent for the use of their de-identified data for research purposes; this allows the research to be exempt from an Institutional Review Board (IRB) evaluation (Office for Human Research Protections 2009).
The real-time secondary information support to improve bed utilization and the decision-making
Published in International Journal of Healthcare Management, 2020
The computers were used to support clinical data management activities in 1950. Although most of early systems were created to provide financial and repayment goals, but they were the founder of modern electronic records [14]. Hospital information system (HIS) is the most widely adopted information system in the hospital environment, and just one instance of health information systems [2,6].