EDC System Research Articles

Research on power supply recovery control technology of distribution network embedding with DC links

The flexible interconnection device (FID) enables multiple distribution feeders in closed-loop mode to support a higher proportion of distributed generation (DG) and large-scale new loads connected to the distribution network (DN). Moreover, the closed-loop operation mode based on FIDs provides an effective technology roadmap for high-quality and highly reliable power users, especially the quick restoration of power supply after the failure of DN. This paper proposes a new supply shape in which the multi-terminal DC links are flexibly embedded in the AC DN (EDC-DN) to realize closed-loop operation, achieving lower investment costs than the existing mode that replaces tie switches with soft open points (SOPs). Meanwhile, a two-stage power supply quick recovery control technology is proposed for the EDC-DN, including the fast power supply recovery stage based on EDC and the optimizing restoration stage based on network reconfiguration. Firstly, the role of EDC in the process of power supply restoration of three different faults on AC feeder is analyzed. Secondly, a detailed power supply recovery process is proposed, which is based on a distribution automation system (DAS) and the real-time control capability of EDC. Thirdly, the power supply restoration second stage is implemented, which is based on network reconfiguration with switch combination and EDC continuous variable optimization. Finally, a 58-node DN with an EDC system was constructed using PSCAD/MTDC simulation software to verify the effectiveness of the two-stage strategy for EDC-DN power restoration.© 2017 Elsevier Inc. All rights reserved.

Technology-enabled clinical trials: Intentional capture of source data (IDC) in the electronic-health record (EHR) and direct transfer to trial database (electronic data capture [EDC]) in a phase II multicenter trial.

1568 Background: Traditional data collection for clinical trials can be cumbersome and inefficient. FDA guidance now promotes capturing clinical trial source data in electronic form and transmitting it to the EDC, recognizing that this should reduce double data entry and improve data quality and timeliness. Electronic data originators can include the EHR, which can be used during routine clinical care and for gathering data during a clinical investigation. We evaluated a pilot of structured EHR data transfer to EDC in a clinical trial setting. Methods: IDC capability in the EHR was developed and applied to a subset of patients for an open label prospective Phase II study. EHR variables, that include free text, standard dictionaries (eg CTCAEv5, CDISC, First Databank), and derived responses, were mapped to the electronic case report form (eCRF). Bulk transmission of IDC clinical data (adverse events, AEs; concomitant medications, CMs; past medical history, PMH) from the EHR to EDC was executed at a designated time point during study conduct. We assessed the quantity (records) and quality (queries) of data captured and transferred, and timeliness of entry. Data to be used for the production analysis of the trial was collected via eCRF in an EDC system in parallel per usual standards. Results: Data for 102 patients across 8 sites of care by 99 different users was captured in the EHR via IDC from 3/1/2021 to 9/9/2022 and transferred from EHR to EDC in bulk on 9/9/22. 3,958 data records were transferred (852 AEs; 1,581 CMs; 1,525 PMHs). Of the AEs, 99% had an associated grade. Of the CMs and PMHs, none were copy-forwarded (all were entered de novo). Regarding queries in the EDC for transcription error validation among matching records, EHR data produced 205 opened edit check queries from 12 edit checks across all domains (149 AEs, 0 CMs, and 56 PMHs). Regarding timeliness, 95% of matched records were entered in IDC prior to entry in the production EDC. Conclusions: For an open label Phase II study, clinical trial source data was captured electronically through IDC using the EHR as the data originator, and directly bulk-transmitted to EDC. This may enable the elimination of transcription of source data entry into eCRF and result in more timely access to the data in the EDC. Additional investigation into how IDC with EHR-to-EDC compares in quality to traditional EDC is warranted. Planned follow up research includes interviewing site users to evaluate their experiences with IDC data entry.

Use of proton pump inhibitors (PPI) in glioblastoma (GBM) and relationship to overall survival in a national real-world evidence (RWE) database.

e14027 Background: Aldehyde dehydrogenase-1A1 ( ALDH1A1) mediates therapy resistance and poor prognosis in multiple cancers. In GBM, ALDH1A1 expression above vs. below the mean is associated with a significant reduction in survival.1 ALDH enzymes activate transcriptional programs that induce the cancer stem cell phenotype, detoxify anticancer drugs, and function as antioxidants by reversing lipid peroxidation and etheno-DNA adducts, thus conferring chemotherapy and radiation resistance. PPI have been shown to increase enzyme activity of ALDH1A1 up to 6-fold, suggesting a potentially hazardous effect on tumor biology and survival. However, no prospective randomized data are available to address these concerns. Thus, we turned to XCELSIOR, an observational database that prospectively collects medical records including medication usage. Methods: Patients with GBM were e-consented to XCELSIOR ( NCT03793088 ), a nationwide observational research protocol that leverages patient consent to permit gathering of medical records from all sites of care. Clinical data were abstracted from medical documents into a central EDC system, source-verified, and standardized to generate comprehensive longitudinal histories for aggregate analysis. Identified patient records permitted the definitive identification of dates of diagnosis and death. Overall survival (OS) was calculated and stratified based for PPI exposure, extent of surgical resection (EOR), and MGMT methylation status. Results: XCELSIOR contained 320 GBM patients from 222 treatment sites. We stratified patients based on exposure to PPI and assessed median OS (mOS). For the entire population, mOS was substantially better for patients not receiving PPI. (TABLE) The 5-yr survival was 29.9% [21.0 – 42] and 6.6% [1.4 – 32.0] for patients not receiving vs. receiving PPI. In a multivariate analysis considering EOR and MGMT methylation, PPI exposure yielded a hazard ratio (HR) of 1.57 (p=0.009). For the interaction of m-MGMT and PPI exposure together, the HR is 2.63 (p=0.043), significant as the HR of m-MGMT alone is 0.40 (p=0.0028). Conclusions: In this RWE dataset, PPI use in GBM appeared detrimental to survival. This is strongly consistent with the hypothesis that PPI antagonizes chemotherapy. Additionally, use of PPI appeared to completely abrogate the survival benefit of chemotherapy associated with methylated-MGMT. While we recognize the utility of PPI in managing acute UGI bleeding, these data suggest avoiding PPIs in GBM patients. 1) Schmidt-Graf F, et al. Neuro Oncol. 2012;14(12):1452–1464. [Table: see text]

Electronic Data Capture System (REDCap) for Health Care Research and Training in a Resource-Constrained Environment: Technology Adoption Case Study.

BackgroundElectronic data capture (EDC) in academic health care organizations provides an opportunity for the management, aggregation, and secondary use of research and clinical data. It is especially important in resource-constrained environments such as the South African public health care sector, where paper records are still the main form of clinical record keeping.ObjectiveThe aim of this study was to describe the strategies followed by the University of the Witwatersrand Faculty of Health Sciences (Wits FHS) during the period from 2013 to 2021 to overcome resistance to, and encourage the adoption of, the REDCap (Research Electronic Data Capture; Vanderbilt University) system by academic and clinical staff. REDCap has found wide use in varying domains, including clinical studies and research projects as well as administrative, financial, and human resource applications. Given REDCap’s global footprint in >5000 institutions worldwide and potential for future growth, the strategies followed by the Wits FHS to support users and encourage adoption may be of importance to others using the system, particularly in resource-constrained settings.MethodsThe strategies to support users and encourage adoption included top-down organizational support; secure and reliable application, hosting infrastructure, and systems administration; an enabling and accessible REDCap support team; regular hands-on training workshops covering REDCap project setup and data collection instrument design techniques; annual local symposia to promote networking and awareness of all the latest software features and best practices for using them; participation in REDCap Consortium activities; and regular and ongoing mentorship from members of the Vanderbilt University Medical Center.ResultsDuring the period from 2013 to 2021, the use of the REDCap EDC system by individuals at the Wits FHS increased, respectively, from 129 active user accounts to 3447 active user accounts. The number of REDCap projects increased from 149 in 2013 to 12,865 in 2021. REDCap at Wits also supported various publications and research outputs, including journal articles and postgraduate monographs. As of 2020, a total of 233 journal articles and 87 postgraduate monographs acknowledged the use of the Wits REDCap system.ConclusionsBy providing reliable infrastructure and accessible support resources, we were able to successfully implement and grow the REDCap EDC system at the Wits FHS and its associated academic medical centers. We believe that the increase in the use of REDCap was driven by offering a dependable, secure service with a strong end-user training and support model. This model may be applied by other academic and health care organizations in resource-constrained environments planning to implement EDC technology.

CODEX Meets RACOON - A Concept for Collaborative Documentation of Clinical and Radiological COVID-19 Data.

Within the scope of the two NUM projects CODEX and RACOON we developed a preliminary technical concept for documenting clinical and radiological COVID-19 data in a collaborative approach and its preceding findings of a requirement analysis. At first, we provide an overview of NUM and its two projects CODEX and RACOON including the GECCO data set. Furthermore, we demonstrate the foundation for the increased collaboration of both projects, which was additionally supported by a survey conducted at University Hospital Frankfurt. Based on the survey results mint Lesion™, developed by Mint Medical and used at all project sites within RACOON, was selected as the "Electronic Data Capture" (EDC) system for CODEX. Moreover, to avoid duplicate entry of GECCO data into both EDC systems, an early effort was made to consider a collaborative and efficient technical approach to reduce the workload for the medical documentalists. As a first effort we present a preliminary technical concept representing the current and possible future data workflow of CODEX and RACOON. This concept includes a software component to synchronize GECCO data sets between the two EDC systems using the HL7 FHIR standard. Our first approach of a collaborative use of an EDC system and its medical documentalists could be beneficial in combination with the presented synchronization component for all participating project sites of CODEX and RACOON with regard to an overall reduced documentation workload.

Maximizing CDISC standards for specification of submission deliverable documents

CDSIC standards were originally developed for documentation purposes in the form of metadata standards describing submission deliverables. Many tools, vendors, and sponsor efforts have gone into verifying that submission documents adhere to those standards. By turning the beast on its head, the very same metadata can be used to create those submission deliverables from the specifications using validated computer code, thus eliminating the bulk of controls and verification for a study.The core principle is that the task of ensuring that two documents are identical (or similar) by comparing and checking, can be eliminated by creating one from the other in a systematic and automatic way by computer code.ODM-XML is the primary specification document for eCRF derivates from CDISC, a pure XML metadata specification documenting the collection of clinical data, not the actual collected clinical data itself. The corresponding submission deliverables are the blank CRF (bcrf.pdf) and the SDTM annotated CRF (acrf.pdf). A CDISC compliant EDC systems ought to be able to use the ODM-XML itself more or less directly to set the eCRF by a simple upload of the ODM-XML into the systems.Bridging the gap from ODM-XML to submission deliverables is quite simply done by  applying a style sheet (a special translating style sheet) to the ODM-XML file to display it as either an eCRF specification, one of the submission documents, or as another XML file for uploading into a specific EDC system. Whenever the desired document is of the same file format, the same stylesheet can be applied varying only in a specified parameter, guaranteeing the similarity of those documents as they originate from the same source.Define-xml is a well-established standard for documenting submission data. The standard way of displaying define-xml is through a similar style sheet provided by CDISC, containing links into targets in the SDTM annotated CRF (acrf.pdf) document.This article demonstrates how the submission documents can be created through careful definition of the ODM-XML, and applying a style sheet creating targets in the SDTM annotated CRF (acrf.pdf) for enhanced linking between this document and the define-xml document. Furthermore, this technique will demonstrate creation of an SDTM annotated specification for setting up an eCRF, as well as creation of the blank CRF (bcrf.pdf) document, all from a single source of metadata.

ATRI EDC: a novel cloud-native remote data capture system for large multicenter Alzheimer's disease and Alzheimer's disease-related dementias clinical trails.

ObjectiveThe Alzheimer’s Therapeutic Research Institute (ATRI) developed a novel clinical data management system, the ATRI electronic data capture system (ATRI EDC), to address the complex regulatory, operational, and data requirements that arise in the conduct of multicenter Alzheimer’s disease and Alzheimer’s disease-related dementias (AD/ADRDs) clinical trials. We describe the system, its utility, and the broader implications for the field of clinical trials and clinical research informatics.Materials and MethodsThe ATRI EDC system was developed, tested, and validated using community-based agile software development methods and cloud-native single-page application design principles. It offers an increasing number of application modules, supports a high degree of study-specific configuration, and empowers study teams to effectively communicate and collaborate on the accurate and timely completion of study activities.ResultsTo date, the ATRI EDC system supports 10 clinical studies, collecting study data for 4596 participants. Three case descriptions further illustrate how the system’s capabilities support diverse study-specific requirements.DiscussionThe ATRI EDC system has several advantages: its modular capabilities can accommodate rapidly evolving research designs and technologies; its community-based agile development approach and community-friendly licensing model encourage collaboration per the principles of open science; finally, with continued development and community building efforts, the system has the potential to facilitate the effective conduct of clinical studies beyond the field of AD/ADRD.ConclusionBy effectively addressing the requirements of multicenter AD/ADRD studies, the ATRI EDC system supports ATRI’s scientific mission of rigorously testing new AD/ADRD therapies and facilitating the effective conduct of multicenter clinical studies.

Reviewing my career as a hematologist-oncologist and a quality control specialist in clinical trials

After a long-term hospitalization following a ski accident in college, I decided to choose a specialty in hematology and oncology. In graduate school, after learning the basics of biostatistics and the methodology of clinical trials, I had the opportunity to go through a series of clinical trial tasks, from launching to writing a clinical study report, which led to the study drug approval. This has greatly motivated me to be actively involved in this field. At the Dana-Farber Cancer Institute, I studied outcomes research under a supervisor, and at a time of difficulty, my good role model, Dr. Stephanie Lee, had urged me, saying, "That which does not kill you makes you stronger." Subsequently, I devoted myself to the establishment of a data center for a Japanese pediatric leukemia/lymphoma study group, currently a subcommittee of the Japan Children's Cancer Group, and to develop an academic research organization for conducting ICH-GCP-compliant international clinical trials, including the originally developed EDC system. I was struggling in balancing work and parenting. Fortunately, I was supported by my encounters with respectable people.

Enroll-HD: An Integrated Clinical Research Platform and Worldwide Observational Study for Huntington's Disease.

Established in July 2012, Enroll-HD is both an integrated clinical research platform and a worldwide observational study designed to meet the clinical research requirements necessary to develop therapeutics for Huntington's disease (HD). The platform offers participants a low-burden entry into HD research, providing a large, well-characterized, research-engaged cohort with associated clinical data and biosamples that facilitates recruitment into interventional trials and other research studies. Additional studies that use Enroll-HD data and/or biosamples are built into the platform to further research on biomarkers and outcome measures. Enroll-HD is now operating worldwide in 21 countries at 159 clinical sites across four continents—Europe, North America, Latin America, and Australasia—and has recruited almost 25,000 participants, generating a large, rich clinical database with associated biosamples to expedite HD research; any researcher at a verifiable research organization can access the clinical datasets and biosamples from Enroll-HD and nested studies. Important operational features of Enroll-HD include a strong emphasis on standardization, data quality, and protecting participant identity, a single worldwide study protocol, a flexible EDC system capable of integrating multiple studies, a comprehensive monitoring infrastructure, an online portal to train and certify site personnel, and standardized study documents including informed consent forms and contractual agreements.

Electronic Data Capture-Study Implementation and Start-up

Web-based Electronic Data Capture is a mainstay of form-based data collection and management in clinical studies. This chapter reviews the implementation and start-up tasks for clinical studies using web-based EDC for form-based data collection and management (hereafter EDC.) Topics covered include designing, developing, testing, and implementing workflow and data flow in clinical studies using EDC systems. Topics of focus include data collection, work flow, and data flow associated with data collection and processing, data processing such as exchange, integration, cleaning, and coding in EDC systems, implementation at study sites including training and account management, and working with EDC system vendors. The chapter emphasizes common responsibilities of Clinical Data Management (CDM) professional in the implementation of an EDC application for a clinical study.

Efficacy of Self-Cut Titanium-Coated Polypropylene Mesh Versus Mesh-Kit for Transvaginal Treatment of Severe Pelvic Organ Prolapse: A Multicenter Randomized Non-Inferiority Trial

Background: Transvaginal mesh can increase the durability of surgery for pelvic organ prolapse. However, commercial mesh kits can be expensive. We assessed the efficacy of a much cheaper self-cut titanium-coated polypropylene mesh with a mesh-kit for treating symptomatic pelvic organ prolapse. Methods: We conducted a multicenter, randomized, non-inferiority trial. Patients were randomized to either self-cut mesh or commercial mesh-kit. Patients with symptomatic stage III-IV pelvic organ prolapse were enrolled at 11 centers between January 2018 and November 2019. The primary outcome measure was composite success at one year defined by absence of vaginal bulge symptoms, and no additional re-treatment for POP, and no vaginal prolapse at or beyond the hymen. Secondary outcomes included symptom-specific pelvic floor function and quality of life measures, complications and costs. Findings: A total of 336 participants were randomized. In the intention-to-treat analysis, 95∙9% (162/169) met the definition of surgical success in the self-cut group, which was noninferior to the 87∙4% (146/167) surgical success in the mesh-kit group (risk difference, 8∙5 [95%CI 2∙2 to 14∙3]). The frequency of Clavien-Dindo grade I-III complications were not significant between groups (12 [7∙2%] vs 20 [12∙4%], P=0∙14). Vaginal mesh exposure rates in women examined within 1 year [self-cut group 4/169 (2∙4%) vs mesh-kit group 8/167 (4∙8%)] were similar (P=0∙23). Interpretation: This trial demonstrated that composite surgical success of a self-cut mesh procedure was non-inferior to a commercial mesh-kit procedure using the same mesh. The use of self-cut mesh was effective and safe, while reducing the hospitalization expense by approximately 40%. Clinical Trial Registration Details: Clinicaltrials.gov, NCT03283124. Funding Information: Chinese Academy of Medical Science Initiative for Innovative Medicine(CAMS-2017-12M-1-002). Medstron Medical(shanghai) Co. Ltd, the agent of Tiloop® products in China, provided monetary support for this research including interim meeting and third party (LinkDoc Beijing company) EDC system. Declaration of Interests: We declare no competing interests. Ethics Approval Statement: The study was approved by the Institutional Review Board of Peking Union Medical College Hospital (JS-1278).

EDC: Improving the Performance and Space Efficiency of Flash-Based Storage Systems with Elastic Data Compression

By leveraging data reduction technologies, such as data compression, all flash-based storage systems can have the same total cost of ownership (TCO) as traditional HDD-based storage systems. Thus, data compression has become a commodity feature for space efficiency and reliability in flash-based storage systems by reducing write traffic and space capacity demand. However, it introduces noticeable processing overheads on the critical I/O path, which degrades the system performance significantly. Existing data compression schemes for flash-based storage systems use fixed compression algorithms for all the incoming write data, failing to recognize and exploit the significant diversity in compressibility and access patterns of data and missing an opportunity to improve the system performance, the space efficiency or both. To achieve a reasonable trade-off between these two important design objectives, in this paper we introduce an Elastic Data Compression scheme, called EDC, which exploits the data compressibility and access intensity characteristics by judiciously matching data of different compressibility with different compression algorithms while leveraging the access idleness. Specifically, for compressible data blocks EDC exploits the compression diversity of the workload, and employs algorithms of higher compression rate in periods of lower system utilization and algorithms of lower compression rate in periods of higher system utilization. For non-compressible (or very lowly compressible) data blocks, it will write them through to the flash storage directly without any compression. The experiments conducted on our lightweight prototype implementation of the EDC system show that EDC saves storage space by up to 38.7 percent, with an average of 33.7 percent . In addition, it significantly outperforms the fixed compression schemes in the I/O performance measure by up to 61.4 percent, with an average of 36.7 percent.

Apatinib as third-line or beyond therapy in patients with chemotherapy-refractory advanced or metastatic adenocarcinoma of stomach or gastroesophageal junction: An open-label, multicenter, post-marketing phase IV study (Ahead-G201).

103 Background: The clinical benefit and safety profile of apatinib in advanced gastric cancer have been established in the randomised controlled phase III clinical trial (J Clin Oncol. 34(13):1448-54). A post-marketing study to confirm the safety and efficacy of apatinib is ongoing in a broad range of patients (pts). Methods: This is a single-arm, open-label, multi-center, Phase IV trial with the target sample size of 2000+ (ClinicalTrials.gov Identifier: NCT02426034). Pts were recruited to receive oral apatinib until disease progression, death or unacceptable toxicity. The primary objective was safety, and the secondary objectives included overall response rate (ORR), disease control rate (DCR), progression free survival (PFS) and overall survival (OS). Results: Herein, we report the preliminary data as documented in the EDC System. As of Jul 10, 2017, 1037 pts were enrolled from 138 hospitals across China. Pts characteristics were: median age 59 yrs, male/female 72.0/28.0%, ECOG PS 0/1/≥2 16.6/66.2/17.2%, stage IV 91.0%. 336 (32.4%) pts interrupted treatment and dose modification occurred in 172 (16.6%) pts (reduction 132/12.7%; rise 87/8.4%). Eventually, the mean dosage was 526.2 mg/d. 652 (62.9%) pts had 4407 drug-related adverse events (DRAEs). Grade ≥3 DRAEs occurred in 300 (28.9%) pts. Severe AEs were reported by 221 (21.3%) pts. The most common DRAEs were proteinuria (19.3%), hypertension (18.8%), leukocyte decrease (16.4%), fatigue (14.2%), platelet decrease (13.6%), hand-foot-skin reaction (11.1%) and neutrophil decrease (10.1%). 820 pts were evaluable for efficacy analysis. The best ORR and DCR were 10.7% and 70.0%, respectively. The median PFS and OS were 4.60 (95%CI, 3.25–4.73) and 6.57 (95%CI, 5.78–7.59) months, respectively. Conclusions: Apatinib monotherapy is effective and has a favorable toxicity profile in real-world clinical setting. The preliminary results of this Phase IV study confirmed the safety and efficacy of apatinib demonstrated in the Phase II and III trials. Updated results will be discussed. Clinical trial information: NCT02426034.

The RaDiCo AC‐OEIL : a French rare disease cohort dedicated to ocular developmental anomalies in children

PurposeOcular development may be disrupted at various stages, leading to a wide range of congenital ocular dysgenesis. Incidence of such defects is estimated to 1‐2 in 10.000. They may be isolated or associated with extra‐ocular malformations. In addition, psychomotor delay may be present, secondary to the sensory involvement or linked to a cerebral developmental anomaly leading to intellectual disability. Visual outcome, frequency of extra‐ocular features and psychomotor delay are still poorly known. Given the rarity of these malformations, available data concern very heterogeneous groups of patients, which make their utility limited in clinical practice. It is thus difficult to anticipate visual and neurologic outcomes when a congenital ocular developmental anomaly is diagnosed.MethodsRaDiCo‐AC‐ŒIL is an observational study launched in May 2017 sponsored by Inserm, relying on the French Rare Diseases healthcare networks SENSGENE and ANDDI‐Rare for patients’ enrolment, and supported by patients ‘associations. Patients will have a maximum of three clinical examinations (at time of diagnosis, at 5‐7‐year‐old, and at 9‐11‐year‐old) during which visual, neuro‐developmental and quality‐of‐life data will be collected in addition to the usual clinical data, using REDCap EDC system. It will extend to other EU countries once regulatory requirements will be fulfilled.ResultsAbout 800 patients are expected to be enrolled during a recruitment period of 10 years. ConclusionsRaDiCo‐AC‐ŒIL will improve i) our knowledge on the natural history of ocular developmental defects in children ii) the identification of prognostic factors for ocular and neurodevelopmental outcome iii) genetics counselling and iv) the design of optimised management protocols. This project will also pave the way to clinical and basic research in a homogeneous cohort.

Evaluation of the IT Infrastructure of the RESIST Study with the Evidence-Based CIPROS Checklist.

Efficient and powerful information systems are substantial to perform medical research projects successfully. Especially, translational medicine poses specific challenges to the corresponding IT infrastructure. The RESIST study is a translational research project in oncology where xenografts inform about patients second-line treatment. DBFORM, an in-house developed system, was used as EDC system. It was enhanced with project specific features. We demonstrate how the CIPROS checklist has the potential to optimize the related requirements engineering process. The CIPROS checklist consists of 72 items, organized within 12 Aspects/Topics and was developed to assess such patient registry software systems. In this paper we use the CIPROS checklist (1) to elucidate the projects requirements and (2) to assess systems features. The application of the CIPROS checklist to fix the RESIST project requirements and system features was successful. The interplay between (1) and (2) helped to accelerate the requirements engineering process and to set up a system suitable to perform the translational research project successful.

Automated Classification of Selected Data Elements from Free-text Diagnostic Reports for Clinical Research.

In the Multiple Myeloma clinical registry at Heidelberg University Hospital, most data are extracted from discharge letters. Our aim was to analyze if it is possible to make the manual documentation process more efficient by using methods of natural language processing for multiclass classification of free-text diagnostic reports to automatically document the diagnosis and state of disease of myeloma patients. The first objective was to create a corpus consisting of free-text diagnosis paragraphs of patients with multiple myeloma from German diagnostic reports, and its manual annotation of relevant data elements by documentation specialists. The second objective was to construct and evaluate a framework using different NLP methods to enable automatic multiclass classification of relevant data elements from free-text diagnostic reports. The main diagnoses paragraph was extracted from the clinical report of one third randomly selected patients of the multiple myeloma research database from Heidelberg University Hospital (in total 737 selected patients). An EDC system was setup and two data entry specialists performed independently a manual documentation of at least nine specific data elements for multiple myeloma characterization. Both data entries were compared and assessed by a third specialist and an annotated text corpus was created. A framework was constructed, consisting of a self-developed package to split multiple diagnosis sequences into several subsequences, four different preprocessing steps to normalize the input data and two classifiers: a maximum entropy classifier (MEC) and a support vector machine (SVM). In total 15 different pipelines were examined and assessed by a ten-fold cross-validation, reiterated 100 times. For quality indication the average error rate and the average F1-score were conducted. For significance testing the approximate randomization test was used. The created annotated corpus consists of 737 different diagnoses paragraphs with a total number of 865 coded diagnosis. The dataset is publicly available in the supplementary online files for training and testing of further NLP methods. Both classifiers showed low average error rates (MEC: 1.05; SVM: 0.84) and high F1-scores (MEC: 0.89; SVM: 0.92). However the results varied widely depending on the classified data element. Preprocessing methods increased this effect and had significant impact on the classification, both positive and negative. The automatic diagnosis splitter increased the average error rate significantly, even if the F1-score decreased only slightly. The low average error rates and high average F1-scores of each pipeline demonstrate the suitability of the investigated NPL methods. However, it was also shown that there is no best practice for an automatic classification of data elements from free-text diagnostic reports.

Optimal eCRF design, user friendly interface and proper training: quintessential for high quality data in Real World Evidence (RWE) studies

Background: The success of a Real World Evidence (RWE) study lies in collecting and processing high quality data. Data in RWE study can be collected in a paper format as in a Case Report Form (CRF) or electronically in the format of electronic Case Report Form (eCRF). For a multi-country/multi-centric study, eCRF can offer advantages over the conventional paper CRF for collection of data. An approach which is a combination of optimal eCRF design, user friendly interface and proper training can facilitate in collection of high quality data. Aim: The aim of this article is to highlight the significance of optimal eCRF design, user friendly interface and proper training in RWE studies. Conclusion: Implementation of EDC system with eCRF can be advantageous for a multi-country/multi-centric RWE studies, as it facilities real time monitoring, which can yield adequate data of high quality. Implementation of eCRF can be cost and time effective.

An efficient and low toxic human serum albumin conjugated polyethylenimine nano-sized complex for gene delivery

A novel low cytotoxicity and high efficiency transfection reagent, human serum albumin (HSA)-conjugated polyethylenimine (PEI) was prepared to improve the effect of PEI on gene transfection in this study. Transfecting a cell with DNA is a crucial step for DNA vaccination or gene therapy. PEI, a non-viral vector, is one of the popularly used cationic polymers because of its intensive positive charge that condenses DNA as a nano-sized complex, and attaches on the negative-charged cell membrane, triggering cell endocytosis. In this study, we used a zero-length cross-linkage EDC system to chemically conjugate HSA and PEI, and the size of final synthesized product HSA-conjugated PEI (HSA-PEI) was 14 nm with a positive zeta potential 20.8 mV. We also evaluated the characteristics of HSA-PEI in cells. We chose the A549 cell line as our evaluation model because of its GP-60 receptor. Our results showed that HSA-conjugated PEI was easily applied to form a nano-sized complex with plasmid DNA (pDNA) by simply mixing. The functional ligand, HSA, has a large size, much free PEI (or equivalent free PEI effect) and increases the protection of pDNA by stereo-barring, good condensation effect. HSA-PEI also showed good pDNA transfection enhancement in A549 cell lines, and low toxic characteristics.

Development of dementia in a cohort of elderly who frequently use ambulatory health services

capabilities were used to accelerate study startup, facilitate intra-study amendments, and streamline shutdown activities.3. Outline opportunities for future improvement. Conclusions: The ADCS EDC system supports a collaborative design and specification process via an intuitive set of cloud-based spreadsheets which allow multi-disciplinary study teams to manage clinical trial databases without the need for IT staff, thus reducing unnecessary delays and potential errors due to miscommunication. This approach has been used to design and manage databases for more than 20 large, multi-site AD clinical trials as well as several extra-ADCS projects, such as the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and the Dominantly Inherited Alzheimer’s Network (DIAN).

Electronic Data Capture for Registries and Clinical Trials in Orthopaedic Surgery: Open Source versus Commercial Systems

Collection and analysis of clinical data can help orthopaedic surgeons to practice evidence based medicine. Spreadsheets and offline relational databases are prevalent, but not flexible, secure, workflow friendly and do not support the generation of standardized and interoperable data. Additionally these data collection applications usually do not follow a structured and planned approach which may result in failure to achieve the intended goal. Our purposes are (1) to provide a brief overview of EDC systems, their types, and related pros and cons as well as to describe commonly used EDC platforms and their features; and (2) describe simple steps involved in designing a registry/clinical study in DADOS P, an open source EDC system. WHERE ARE WE NOW?: Electronic data capture systems aimed at addressing these issues are widely being adopted at an institutional/national/international level but are lacking at an individual level. A wide array of features, relative pros and cons and different business models cause confusion and indecision among orthopaedic surgeons interested in implementing EDC systems. WHERE DO WE NEED TO GO?: To answer clinical questions and actively participate in clinical studies, orthopaedic surgeons should collect data in parallel to their clinical activities. Adopting a simple, user-friendly, and robust EDC system can facilitate the data collection process. HOW DO WE GET THERE?: Conducting a balanced evaluation of available options and comparing them with intended goals and requirements can help orthopaedic surgeons to make an informed choice.