The Use of CDISC Standards for Real-World Data (RWD): Expert Perspectives from a Qualitative Delphi Survey (Preprint)

2021 ◽  
Author(s):  
Rhonda Facile ◽  
Erin Elizabeth Muhlbradt ◽  
Mengchun Gong ◽  
Qing-Na Li ◽  
Vaishali B. Popat ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Clinical Research ◽  
Real World ◽  
Data Science ◽  
Health Data ◽  
Delphi Survey ◽  
Data Standards ◽  
Real World Data ◽  
World Data

BACKGROUND Real World Data (RWD) and Real World Evidence (RWE) have an increasingly important role in clinical research and health care decision making in many countries. In order to leverage RWD and generate reliable RWE, a framework must be in place to ensure that the data is well-defined and structured in a way that is semantically interoperable and consistent across stakeholders. The adoption of data standards is one of the cornerstones supporting high-quality evidence for clinical medicine and therapeutics development. CDISC data standards are mature, globally recognized and heavily utilized by the pharmaceutical industry for regulatory submission in the US and Japan and are recommended in Europe and China. Against this backdrop, the CDISC RWD Connect Initiative was initiated to better understand the barriers to implementing CDISC standards for RWD and to identify the tools and guidance needed to more easily implement CDISC standards for this purpose. We believe that bridging the gap between RWD and clinical trial generated data will benefit all stakeholders. OBJECTIVE The aim of this project was to understand the barriers to implementing CDISC standards for Real World Data (RWD) and to identify what tools and guidance may be needed to more easily implement CDISC standards for this purpose. METHODS We conducted a qualitative Delphi survey involving an Expert Advisory Board (EAB) with multiple key stakeholders, with three rounds of input and review. RESULTS In total, 66 experts participated in round 1, 56 participated in round 2 and 49 participated in round 3 of the Delphi Survey. Their input was collected and analyzed culminating in group statements. It was widely agreed that the standardization of RWD is highly necessary, and the primary focus should be on its ability to improve data-sharing and the quality of RWE. The priorities for RWD standardization include electronic health records, such as data shared using HL7 FHIR, and data stemming from observational studies. With different standardization efforts already underway in these areas, a gap analysis should be performed to identify areas where synergies and efficiencies are possible and then collaborate with stakeholders to create, or extend existing, mappings between CDISC and other standards, controlled terminologies and models to represent data originating across different sources. CONCLUSIONS There are many ongoing data standardization efforts that span the spectrum of human health data related activities including, but not limited to, those related to healthcare, public health, product or disease registries and clinical research, each with different definitions, levels of granularity and purpose. Amongst these standardization efforts, CDISC has been successful in standardizing clinical trial-based data for regulation worldwide. However, the complexity of the CDISC standards, and the fact that they were developed for different purposes, combined with the lack of awareness and incentives to using a new standard, insufficient training and implementation support are significant barriers for setting up the use of CDISC standards for RWD. The collection and dissemination of use cases showing in detail how to effectively implement CDISC standards for RWD, developing tools and support systems specifically for the RWD community, and collaboration with other standards development organizations and initiatives are potential steps towards connecting RWD to research. The integrity of RWE is dependent on the quality of the RWD and the data standards utilized in its collection, integration, processing, exchange and reporting. Using CDISC as part of the database schema will help to link clinical trial data and RWD and promote innovation in health data science. The authors believe that CDISC standards, if adapted carefully and presented appropriately to the RWD community, can provide “FAIR” structure and semantics for common clinical concepts and domains and help to bridge the gap between RWD and clinical trial generated data. CLINICALTRIAL Not Applicable

scholarly journals Gap between real-world data and clinical research within hospitals in China: a qualitative study

BMJ Open ◽  
2020 ◽  
Vol 10 (12) ◽  
pp. e038375
Author(s):  
Feifei Jin ◽  
Chen Yao ◽  
Xiaoyan Yan ◽  
Chongya Dong ◽  
Junkai Lai ◽  
...  
Keyword(s):  
Qualitative Study ◽  
Clinical Research ◽  
Real World ◽  
Data Standards ◽  
Medical Record Data ◽  
Real World Data ◽  
World Data ◽  
Electronic Medical Record Data ◽  
Research Platform ◽  
Record Data

ObjectiveTo investigate the gap between real-world data and clinical research initiated by doctors in China, explore the potential reasons for this gap and collect different stakeholders’ suggestions.DesignThis qualitative study involved three types of hospital personnel based on three interview outlines. The data analysis was performed using the constructivist grounded theory analysis process.SettingSix tertiary hospitals (three general hospitals and three specialised hospitals) in Beijing, China, were included.ParticipantsIn total, 42 doctors from 12 departments, 5 information technology managers and 4 clinical managers were interviewed through stratified purposive sampling.ResultsElectronic medical record data cannot be directly downloaded into clinical research files, which is a major problem in China. The lack of data interoperability, unstructured electronic medical record data and concerns regarding data security create a gap between real-world data and research data. Updating hospital information systems, promoting data standards and establishing an independent clinical research platform may be feasible suggestions for solving the current problems.ConclusionsDetermining the causes of gaps and targeted solutions could contribute to the development of clinical research in China. This research suggests that updating the hospital information system, promoting data standards and establishing a clinical research platform could promote the use of real-world data in the future.

scholarly journals Use of Social Media in the Assessment of Relative Effectiveness: Explorative Review With Examples From Oncology (Preprint)

2017 ◽  
Author(s):  
Rachel R.J. Kalf ◽  
Amr Makady ◽  
Renske M.T. ten Ham ◽  
Kim Meijboom ◽  
Wim G. Goettsch ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Social Media ◽  
Adverse Events ◽  
Real World ◽  
Relative Effectiveness ◽  
Health Data ◽  
Real World Data ◽  
World Data ◽  
Effectiveness Assessment

BACKGROUND An element of health technology assessment constitutes assessing the clinical effectiveness of drugs, generally called relative effectiveness assessment. Little real-world evidence is available directly after market access, therefore randomized controlled trials are used to obtain information for relative effectiveness assessment. However, there is growing interest in using real-world data for relative effectiveness assessment. Social media may provide a source of real-world data. OBJECTIVE We assessed the extent to which social media-generated health data has provided insights for relative effectiveness assessment. METHODS An explorative literature review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines to identify examples in oncology where health data were collected using social media. Scientific and grey literature published between January 2010 and June 2016 was identified by four reviewers, who independently screened studies for eligibility and extracted data. A descriptive qualitative analysis was performed. RESULTS Of 1032 articles identified, eight were included: four articles identified adverse events in response to cancer treatment, three articles disseminated quality of life surveys, and one study assessed the occurrence of disease-specific symptoms. Several strengths of social media-generated health data were highlighted in the articles, such as efficient collection of patient experiences and recruiting patients with rare diseases. Conversely, limitations included validation of authenticity and presence of information and selection bias. CONCLUSIONS Social media may provide a potential source of real-world data for relative effectiveness assessment, particularly on aspects such as adverse events, symptom occurrence, quality of life, and adherence behavior. This potential has not yet been fully realized and the degree of usefulness for relative effectiveness assessment should be further explored.

The rate of tumor growth, g, as a biomarker for overall survival (OS) in prostate cancer (PC) in clinical trials as well as in real-world data from the Veterans Administration Medical Centers (VAMCs).

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. 5074-5074
Author(s):  
Harshraj Leuva ◽  
Mengxi Zhou ◽  
Julia Wilkerson ◽  
Keith Sigel ◽  
Ta-Chueh Hsu ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Clinical Trial ◽  
Overall Survival ◽  
Clinical Trials ◽  
Tumor Growth ◽  
Real World ◽  
Clinical Trial Data ◽  
Trial Data ◽  
Real World Data ◽  
World Data

5074 Background: Novel assessments of efficacy are needed to improve determination of treatment outcomes in clinical trials and in real-world settings. Methods: Cancer treatments usually lead to concurrent regression and growth of the drug-sensitive and drug-resistant fractions of a tumor, respectively. We have exploited novel methods of analysis that assess these two simultaneous processes and have estimated rates of tumor growth ( g) and regression ( d) in over 30,000 patients (pts) with diverse tumors. Results: In prostate cancer (PC) we have analyzed both clinical trial and real-world data from Veterans. Using clinical trial data from 6819 pts enrolled in 15 treatment arms we have established separately and by combining all the data that g correlates highly (p<0.0001) with overall survival (OS) – slower g associated with better OS. In PC, abiraterone (ABI) and docetaxel (DOC) are superior to placebo, prednisone and mitoxantrone. ABI (median g =0.0017) is superior to DOC ( g=0.0021) in first line (p=0.0013); and ABI in 2nd line ( g=0.0034) is inferior to ABI in 1st line ( g=0.0017; p<0.0001). Finally, using combined clinical trial data as a benchmark we could assess the efficacy of novel therapies in as few as 30-40 patients. Amongst 7457 Veterans, the median g on a taxane ( g=0.0022) was similar to that from clinical trials ( g=0.0012). Although only 258 Veterans received cabazitaxel (CAB), g values for CAB ( g=0.0018) and DOC ( g=0.0023) were indistinguishable (p=0.3) consistent with their identical mechanism of action. Finally, outcomes with DOC in African American (AA) ( g=0.00212) and Caucasian ( g=0.00205) Veterans were indistinguishable (p=0.9) and comparable across all VAMCs. Conclusions: The rate of tumor growth, g, is an excellent biomarker for OS both in clinical trials and in real-world settings. g allows comparisons between trials and for large trial data sets to be used as benchmarks of efficacy. Real-world outcomes in the VAMCs are similar to those in clinical trials. In the egalitarian VAMCs DOC efficacy in PC is comparable in AA and Caucasian Veterans -- indicating inferior outcomes reported in AAs are likely due to differential health care access, not differences in biology.

Tumor response and growth rate of nivolumab treatment in advanced gastric cancer: Real-world data from a large observational/translational study, JACCRO GC-08 (deliver trial).

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. 4527-4527
Author(s):  
Ryohei Kawabata ◽  
Yasuhiro Sakamoto ◽  
Eisuke Inoue ◽  
Atsushi Ishiguro ◽  
Yusuke Akamaru ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Clinical Trial ◽  
Growth Rate ◽  
Tumor Growth ◽  
Real World ◽  
Fold Increase ◽  
Real World Data ◽  
World Data ◽  
Translational Study ◽  
Before And After

4527 Background: Nivolumab (Nivo) demonstrated survival benefit in previously treated gastric cancer (GC) patients (pts), with a response rate (RR) of 11% and a disease control rate (DCR) of 40% (Kang YK, et al. Lancet 2017). There are few real-world data of Nivo and its predictive markers are needed in GC. It has been demonstrated that some tumors grow rapidly after Nivo treatment, but the proportion is uncertain. Methods: DELIVER trial was a prospective, multicenter, observational/translational study which assessed pts with advanced GC treated with Nivo alone and ECOG Performance Status (PS) 0-2 (UMIN000030850). The aims were to evaluate the efficacy and safety of Nivo in real world, and to discover novel host-related immune-biomarkers (gut microbiome, genetic polymorphism, gene expression, and metabolome) using fecal and blood samples which were collected before and after Nivo treatment. The RR, DCR, progression-free survival, overall survival, and tumor growth rate (TGR) were estimated as the efficacy. The response was evaluated by first imaging based on RECIST version 1.1. The TGR was calculated as a percentage increase in tumor volume during 1 month (Champiat et al. Clin Cancer Res 2017). Results: A total of 501 pts was enrolled in this study from Mar 2018 to Aug 2019, and 487 pts were evaluable for analysis (median age 70-y, 71% male, ECOG PS0/1/2 42%/44%/14%, tub/por/sig 45%/41%/5%, 21% HER2-pos, 42% pts with ascites). The DCR was 39.2% (95%CI 34.9-43.7) in evaluable pts. In 282 pts with measurable lesions, the RR was 6.7% (95%CI 4.1-10.3) and DCR was 36.5%. Sub-analysis by patient background indicated that DCR was 41% for PS0, 42% for PS1, and 24% for PS2. In addition, the DCR was lower in pts with ascites compared to those without ascites (28.6% vs. 47.0%, p= 0.005). The TGR decreased after introduction of Nivo in 124 (56.6%) of 219 evaluable pts for TGR; however, 20.5% pts were identified as experiencing hyper-progressive disease (HPD) which was defined as a ≥2-fold increase of the TGR before and after Nivo. When defining HPD as a ≥2-fold increase of tumor growth kinetics ratio and 50% increase of tumor burden, 9.6% pts experienced it. Conclusions: The real-word data of the large observational trial showed a comparable DCR to that of clinical trial in advanced GC treated with Nivo. This trial revealed the tumor behavior and some pts who experienced rapid tumor growth after Nivo treatment in clinical practice; biomarkers for HPD and the definition should be established. Clinical trial information: UMIN000030850 .

scholarly journals Blockchain-Authenticated Sharing of Genomic and Clinical Outcomes Data of Patients With Cancer: A Prospective Cohort Study

10.2196/16810 ◽  
2020 ◽  
Vol 22 (3) ◽  
pp. e16810 ◽  
Author(s):  
Benjamin Scott Glicksberg ◽  
Shohei Burns ◽  
Rob Currie ◽  
Ann Griffin ◽  
Zhen Jane Wang ◽  
...  
Keyword(s):  
Real World ◽  
Web Application ◽  
Data Extraction ◽  
Data Representation ◽  
Health Data ◽  
Common Data Model ◽  
Patient Privacy ◽  
Real World Data ◽  
World Data ◽  
Patients With Cancer

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.

scholarly journals Real-world data: how they can help to improve quality of care

2021 ◽  
Vol 8 ◽  
pp. 134-139
Author(s):  
Giovanni Corrao ◽  
Giovanni Alquati ◽  
Giovanni Apolone ◽  
Andrea Ardizzoni ◽  
Giuliano Buzzetti ◽  
...  
Keyword(s):  
Public Health ◽  
Quality Of Care ◽  
Real World ◽  
Ethical Issues ◽  
Data Availability ◽  
Quality Data ◽  
Real World Data ◽  
World Data ◽  
Critical Issues

The current COVID pandemic crisis made it even clearer that the solutions to several questions that public health must face require the access to good quality data. Several issues of the value and potential of health data and the current critical issues that hinder access are discussed in this paper. In particular, the paper (i) focuses on “real-world data” definition; (ii) proposes a review of the real-world data availability in our country; (iii) discusses its potential, with particular focus on the possibility of improving knowledge on the quality of care provided by the health system; (iv) emphasizes that the availability of data alone is not sufficient to increase our knowledge, underlining the need that innovative analysis methods (e.g., artificial intelligence techniques) must be framed in the paradigm of clinical research; and (v) addresses some ethical issues related to their use. The proposal is to realize an alliance between organizations interested in promoting research aimed at collecting scientifically solid evidence to support the clinical governance of public health.

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