scholarly journals Common data model-based real-world data for practical clinical practice guidelines: clinical pharmacology perspectives

2020 ◽  
Vol 28 (2) ◽  
pp. 67
Author(s):  
Yoomin Jeon ◽  
Yoona Choi ◽  
Esther Hehsun Kim ◽  
SeonYeong Oh ◽  
Howard Lee
Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 4839-4839
Author(s):  
Kristina Bardenheuer ◽  
Alun Passey ◽  
Maria d'Errico ◽  
Barbara Millier ◽  
Carine Guinard-Azadian ◽  
...  

Abstract Introduction: The Haematology Outcomes Network in EURope (HONEUR) is an interdisciplinary initiative aimed at improving patient outcomes by analyzing real world data across hematological centers in Europe. Its overarching goal is to create a secure network which facilitates the development of a collaborative research community and allows access to big data tools for analysis of the data. The central paradigm in the HONEUR network is a federated model whereby the data stays at the respective sites and the analysis is executed at the local data sources. To allow for a uniform data analysis, the common data model 'OMOP' (Observational Medical Outcomes Partnership) was selected and extended to accommodate specific hematology data elements. Objective: To demonstrate feasibility of the OMOP common data model for the HONEUR network. Methods: In order to validate the architecture of the HONEUR network and the applicability of the OMOP common data model, data from the EMMOS registry (NCT01241396) have been used. This registry is a prospective, non-interventional study that was designed to capture real world data regarding treatments and outcomes for multiple myeloma at different stages of the disease. Data was collected between Oct 2010 and Nov 2014 on more than 2,400 patients across 266 sites in 22 countries. Data was mapped to the OMOP common data model version 5.3. Additional new concepts to the standard OMOP were provided to preserve the semantic mapping quality and reduce the potential loss of granularity. Following the mapping process, a quality analysis was performed to assess the completeness and accuracy of the mapping to the common data model. Specific critical concepts in multiple myeloma needed to be represented in OMOP. This applies in particular for concepts like treatment lines, cytogenetic observations, disease progression, risk scales (in particular ISS and R-ISS). To accommodate these concepts, existing OMOP structures were used with the definition of new concepts and concept-relationships. Results: Several elements of mapping data from the EMMOS registry to the OMOP common data model (CDM) were evaluated via integrity checks. Core entities from the OMOP CDM were reconciled against the source data. This was applied for the following entities: person (profile of year of birth and gender), drug exposure (profile of number of drug exposures per drug, at ATC code level), conditions (profile of number of occurrences of conditions per condition code, converted to SNOMED), measurement (profile of number of measurements and value distribution per (lab) measurement, converted to LOINC) and observation (profile of number of observations per observation concept). Figure 1 shows the histogram of year of birth distribution between the EMMOS registry and the OMOP CDM. No discernible differences exist, except for subjects which have not been included in the mapping to the OMOP CDM due to lacking confirmation of a diagnosis of multiple myeloma. As additional part of the architecture validation, the occurrence of the top 20 medications in the EMMOS registry and the OMOP CDM were compared, with a 100% concordance for the drug codes, which is shown in Figure 2. In addition to the reconciliation against the different OMOP entities, a comparison was also made against 'derived' data, in particular 'time to event' analysis. Overall survival was plotted from calculated variables in the analysis level data from the EMMOS registry and derived variables in the OMOP CDM. Probability of overall survival over time was virtually identical with only one day difference in median survival and 95% confidence intervals identically overlapping over the period of measurement (Figure 3). Conclusions: The concordance of year of birth, drug code mapping and overall survival between the EMMOS registry and the OMOP common data model indicates the reliability of mapping potential in HONEUR, especially where auxiliary methods have been developed to handle outcomes and treatment data in a way that can be harmonized across platform datasets. Disclosures No relevant conflicts of interest to declare.


Author(s):  
Eleonora De Matteis ◽  
Raffaele Ornello ◽  
Simona Sacco

2020 ◽  
Vol 19 (s) ◽  
pp. 1-1
Author(s):  
K. Taraldsen ◽  
S. Mellone

2018 ◽  
Vol 28 (1) ◽  
pp. 52-55 ◽  
Author(s):  
Melania Brzozowska ◽  
Waldemar Wierzba ◽  
Andrzej Śliwczyński ◽  
Marcin Świerkowski ◽  
Piotr Potemski ◽  
...  

PLoS ONE ◽  
2010 ◽  
Vol 5 (4) ◽  
pp. e10265 ◽  
Author(s):  
Ana Paula Ribeiro Bonilauri Ferreira ◽  
Rodrigo Fernando Ferreira ◽  
Dimple Rajgor ◽  
Jatin Shah ◽  
Andrea Menezes ◽  
...  

10.2196/16810 ◽  
2020 ◽  
Vol 22 (3) ◽  
pp. e16810 ◽  
Author(s):  
Benjamin Scott Glicksberg ◽  
Shohei Burns ◽  
Rob Currie ◽  
Ann Griffin ◽  
Zhen Jane Wang ◽  
...  

Background Efficiently sharing health data produced during standard care could dramatically accelerate progress in cancer treatments, but various barriers make this difficult. Not sharing these data to ensure patient privacy is at the cost of little to no learning from real-world data produced during cancer care. Furthermore, recent research has demonstrated a willingness of patients with cancer to share their treatment experiences to fuel research, despite potential risks to privacy. Objective The objective of this study was to design, pilot, and release a decentralized, scalable, efficient, economical, and secure strategy for the dissemination of deidentified clinical and genomic data with a focus on late-stage cancer. Methods We created and piloted a blockchain-authenticated system to enable secure sharing of deidentified patient data derived from standard of care imaging, genomic testing, and electronic health records (EHRs), called the Cancer Gene Trust (CGT). We prospectively consented and collected data for a pilot cohort (N=18), which we uploaded to the CGT. EHR data were extracted from both a hospital cancer registry and a common data model (CDM) format to identify optimal data extraction and dissemination practices. Specifically, we scored and compared the level of completeness between two EHR data extraction formats against the gold standard source documentation for patients with available data (n=17). Results Although the total completeness scores were greater for the registry reports than those for the CDM, this difference was not statistically significant. We did find that some specific data fields, such as histology site, were better captured using the registry reports, which can be used to improve the continually adapting CDM. In terms of the overall pilot study, we found that CGT enables rapid integration of real-world data of patients with cancer in a more clinically useful time frame. We also developed an open-source Web application to allow users to seamlessly search, browse, explore, and download CGT data. Conclusions Our pilot demonstrates the willingness of patients with cancer to participate in data sharing and how blockchain-enabled structures can maintain relationships between individual data elements while preserving patient privacy, empowering findings by third-party researchers and clinicians. We demonstrate the feasibility of CGT as a framework to share health data trapped in silos to further cancer research. Further studies to optimize data representation, stream, and integrity are required.


Cancer ◽  
2018 ◽  
Vol 124 (9) ◽  
pp. 1946-1953 ◽  
Author(s):  
Luz Tarín-Arzaga ◽  
Daniela Arredondo-Campos ◽  
Victor Martínez-Pacheco ◽  
Odra Martínez-González ◽  
Alba Ramírez-López ◽  
...  

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