scholarly journals Comparing SDTM and FHIR® for Real World Data from Electronic Health Records for Clinical Trial Submissions

2021 ◽  
Author(s):  
Sarah Riepenhausen ◽  
Cornelia Mertens ◽  
Martin Dugas
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Electronic Health Records ◽  
Real World ◽  
Clinical Trial Data ◽  
Trial Data ◽  
Real World Data ◽  
Health Records ◽  
World Data ◽  
Data Submission

Real world data for use in clinical trials is promising. We compared the SDTM for clinical trial data submission with FHIR® for routine documentation. After categorization of variables by relevance, clinically relevant SDTM items were mapped to FHIR®. About 30% in both were seen as clinically relevant. The majority of these SDTM items were mappable to FHIR® Observation resource.

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.

scholarly journals Contemporary use of real-world data for clinical trial conduct in the United States: a scoping review

2020 ◽  
Author(s):  
James R Rogers ◽  
Junghwan Lee ◽  
Ziheng Zhou ◽  
Ying Kuen Cheung ◽  
George Hripcsak ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Electronic Health Records ◽  
Scoping Review ◽  
Real World ◽  
Administrative Claims ◽  
Real World Data ◽  
Health Records ◽  
World Data ◽  
Trial Process

Abstract Objective Real-world data (RWD), defined as routinely collected healthcare data, can be a potential catalyst for addressing challenges faced in clinical trials. We performed a scoping review of database-specific RWD applications within clinical trial contexts, synthesizing prominent uses and themes. Materials and Methods Querying 3 biomedical literature databases, research articles using electronic health records, administrative claims databases, or clinical registries either within a clinical trial or in tandem with methodology related to clinical trials were included. Articles were required to use at least 1 US RWD source. All abstract screening, full-text screening, and data extraction was performed by 1 reviewer. Two reviewers independently verified all decisions. Results Of 2020 screened articles, 89 qualified: 59 articles used electronic health records, 29 used administrative claims, and 26 used registries. Our synthesis was driven by the general life cycle of a clinical trial, culminating into 3 major themes: trial process tasks (51 articles); dissemination strategies (6); and generalizability assessments (34). Despite a diverse set of diseases studied, &lt;10% of trials using RWD for trial process tasks evaluated medications or procedures (5/51). All articles highlighted data-related challenges, such as missing values. Discussion Database-specific RWD have been occasionally leveraged for various clinical trial tasks. We observed underuse of RWD within conducted medication or procedure trials, though it is subject to the confounder of implicit report of RWD use. Conclusion Enhanced incorporation of RWD should be further explored for medication or procedure trials, including better understanding of how to handle related data quality issues to facilitate RWD use.

Estimate of Real-World Medical Costs Avoidance When New Oral Anticoagulants Are Used Vs. Standard Therapy for the Treatment of Patients with Venous Thromboembolism in the U.S

Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 687-687
Author(s):  
Alpesh N Amin ◽  
Amanda Bruno ◽  
Jeffrey Trocio ◽  
Jay Lin ◽  
Melissa Lingohr-Smith
Keyword(s):  
Clinical Trial ◽  
Medical Cost ◽  
Real World ◽  
Standard Therapy ◽  
Clinical Trial Data ◽  
Medical Costs ◽  
Trial Data ◽  
Real World Data ◽  
World Data ◽  
Event Rates

Abstract Introduction: Clinical trials have demonstrated that the new oral anticoagulants (NOACs), dabigatran, rivaroxaban, apixaban, and edoxaban are noninferior to standard therapies for treatment of acute symptomatic venous thromboembolism (VTE). We have previously published the medical costs avoided when NOACs are used instead of standard therapies based on rates of clinical events reported in clinical trials. However, the rates of recurrent VTE and major bleeding (MB) in the real-world settings may differ from those from the clinical trials. In this study, we estimated the real-world medical cost avoidance from a U.S. payer perspective when NOACs are used instead of standard therapy for the treatment of patients with VTE. Methods: Reduction of real-world event rates of recurrent VTE and MB were obtained by applying rate reductions observed in clinical studies to the Worcester population. Incremental annual medical costs among patients with VTE and MB from a U.S. payer perspective were obtained from the literature or healthcare claims databases and inflation adjusted to 2013 costs. Differences in total medical costs associated with clinical endpoints for patients treated with NOACs vs. standard therapy were then estimated. One-way univariate and Monte Carlo sensitivity analyses were additionally carried out. Univariate analysis varied the estimates of the clinical event rates between the ranges of confidence intervals and the estimates of event costs ±30% when such confidence intervals were not reported. Ten thousand cycles of Monte-Carlo simulations were used for additional sensitivity analysis where all model parameters were allowed to vary simultaneously. Results: Real-world event rates of recurrent VTE and MB in the Worcester VTE study were 11.2% and 10.8% respectively. Differences in real-world event rates of recurrent VTE among VTE patients treated with NOACs instead of standard therapy were estimated at -1.80% for apixaban, -1.23% for rivaroxaban, -2.02% for edoxaban, and 1.02% for dabigatran. Differences in real-world event rates of MB among VTE patients treated with NOACs instead of standard therapy were estimated at -7.48% for apixaban, -4.97% for rivaroxaban, -1.73% for edoxaban, and -2.57% for dabigatran. Based on the real-world data, the annual total medical cost avoidances vs. standard therapy were greatest for VTE patients treated with apixaban (-$4,440 per patient year-ppy), followed by those treated with rivaroxaban (-$2,971 ppy), edoxaban (-$1,957 ppy), and dabigatran (-$572 ppy). In comparison to data previously reported based on clinical trials, these medical cost avoidances are substantially greater for any of the NOACs vs. standard therapy (Table). The medical cost avoidances remained consistent under univariate (one-way) sensitivity. Additionally, the mean cost estimates of 10,000 random cycles of Monte-Carlo simulations for each of the NOACs were similar to the default estimated medical cost avoidances, demonstrating the robustness of the model estimates. Conclusions: Based on real-world data, when any of the evaluated NOACs are used instead of standard therapy for treatment of patients with acute VTE annual medical costs are reduced. In the real-world setting, the use of NOACs vs. standard therapy is predicted to be associated with even greater annual medical cost reductions than that previously estimated based on clinical trial data. Of the NOACs, apixaban has the greatest real-world medical cost avoidance, as its use is associated with substantial reductions in both VTE and MB event rates. Abstract 687. Table 1 Estimates of Medical Cost Differences Among VTE Patients Treated with NOACs vs. Standard Therapy Based on Clinical Trial Data vs. Real-World Data Outcome Apixaban ($/patient-yr) Rivaroxaban ($/patient-yr) Edoxaban ($/patient-yr) Dabigatran ($/patient-yr) Recurrent VTE* Clinical trial data -$252 -$132 -$197 $114 Real-world data -$1,047 -$717 -$1,173 $595 Major bleedings* Clinical trial data -$572 -$354 -$109 -$195 Real-world data -$3,392 -$2,254 -$784 -$1,167 Total Medical Cost* Clinical trial data -$824 -$486 -$306 -$80 Real-world data -$4,440 -$2,971 -$1,957 -$572 *Negative values mean the NOAC is associated with lower total medical cost vs. standard therapy. Disclosures Amin: Bristol-Myers Squibb, Pfizer: Consultancy. Off Label Use: Apixaban and edoxaban for the indication of VTE. Bruno:Bristol-Myers Squibb: Employment, Equity Ownership. Trocio:Pfizer: Employment, Equity Ownership. Lin:Bristol-Myers Squibb, Pfizer: Consultancy, Research Funding. Lingohr-Smith:Bristol-Myers Squibb, Pfizer: Consultancy, Research Funding.

PP81 Real World Data: The Early Access To Medicines Scheme Catches The Worm

2019 ◽  
Vol 35 (S1) ◽  
pp. 53-53
Author(s):  
Adam Hall ◽  
Lok Wan Liu ◽  
Richard Macaulay ◽  
Sean Walsh
Keyword(s):  
Clinical Trial ◽  
Clinical Practice ◽  
Real World ◽  
Clinical Trial Data ◽  
Access To Medicines ◽  
Trial Data ◽  
Real World Data ◽  
World Data ◽  
Early Access ◽  
Nice Guidance

IntroductionThe Early Access to Medicines Scheme (EAMS) aims to provide access to medicines prior to market authorization for patients with severe, life-threatening diseases who do not have adequate treatment options. An EAMS designation enables the potential collection of United Kingdom-specific real world evidence (RWE) prior to health technology assessment (HTA) by the National Institute for Health and Care Excellence (NICE). This research evaluates whether RWE is being gathered through the EAMS and utilized to support HTA submissions.MethodsAll EAMS designations as of 7 November 2018 were identified from the Medicines and Healthcare products Regulatory Agency website. For products with final NICE guidance, all publicly-available NICE documentation was reviewed.ResultsSixteen product and indication pairings with an EAMS designation were identified, with 12 having received final NICE guidance (11 were recommended, 3 were recommended for temporary reimbursement via the Cancer Drugs Fund, and 2 were not recommended). Of the 11 recommended products, seven had references to the number of patients or sites with product access through the EAMS, but only one (dupilumab for atopic dermatitis) had detailed data collected during the EAMS period. The manufacturer of dupilumab reported baseline demographics and disease characteristics from a cohort of 35 patients treated under the EAMS to inform the generalizability of trial populations for clinical practice. Follow-up results from this cohort demonstrated that real-world data on dupilumab effectiveness was comparable with the clinical trial data, despite a higher proportion of patients in the real-world cohort receiving immunosuppressant therapy, which makes improvements in efficacy harder to achieve. The committee also noted that the RWE presented supported the understanding of dupilumab's long-term clinical effectiveness and informed assumptions for the economic model.ConclusionsTo date, the majority of products receiving an EAMS designation have not presented RWE at NICE reappraisal. The case of dupilumab illustrated how RWE collected through the EAMS can be used to reduce uncertainty around how clinical trial data can be translated into clinical practice. In the future, RWE may increasingly be used to help inform NICE decisions.

Assessing function of electronic health records for real-world data generation

2018 ◽  
Vol 24 (3) ◽  
pp. 95-98 ◽  
Author(s):  
Daphne Guinn ◽  
Erin E Wilhelm ◽  
Grazyna Lieberman ◽  
Sean Khozin
Keyword(s):  
Electronic Health Records ◽  
Real World ◽  
Data Generation ◽  
Real World Data ◽  
Health Records ◽  
World Data ◽  
Electronic Health

scholarly journals The impact of patient-reported outcome (PRO) data from clinical trials: a systematic review and critical analysis

2019 ◽  
Vol 17 (1) ◽  
Author(s):  
Samantha Cruz Rivera ◽  
Derek G. Kyte ◽  
Olalekan Lee Aiyegbusi ◽  
Anita L. Slade ◽  
Christel McMullan ◽  
...  
Keyword(s):  
Systematic Review ◽  
Clinical Trial ◽  
Clinical Trials ◽  
Case Studies ◽  
Real World ◽  
Clinical Trial Data ◽  
Research Impact ◽  
Trial Data ◽  
Patient Reported ◽  
The Impact

Abstract Background Patient-reported outcomes (PROs) are commonly collected in clinical trials and should provide impactful evidence on the effect of interventions on patient symptoms and quality of life. However, it is unclear how PRO impact is currently realised in practice. In addition, the different types of impact associated with PRO trial results, their barriers and facilitators, and appropriate impact metrics are not well defined. Therefore, our objectives were: i) to determine the range of potential impacts from PRO clinical trial data, ii) identify potential PRO impact metrics and iii) identify barriers/facilitators to maximising PRO impact; and iv) to examine real-world evidence of PRO trial data impact based on Research Excellence Framework (REF) impact case studies. Methods Two independent investigators searched MEDLINE, EMBASE, CINAHL+, HMIC databases from inception until December 2018. Articles were eligible if they discussed research impact in the context of PRO clinical trial data. In addition, the REF 2014 database was systematically searched. REF impact case studies were included if they incorporated PRO data in a clinical trial. Results Thirty-nine publications of eleven thousand four hundred eighty screened met the inclusion criteria. Nine types of PRO trial impact were identified; the most frequent of which centred around PRO data informing clinical decision-making. The included publications identified several barriers and facilitators around PRO trial design, conduct, analysis and report that can hinder or promote the impact of PRO trial data. Sixty-nine out of two hundred nine screened REF 2014 case studies were included. 12 (17%) REF case studies led to demonstrable impact including changes to international guidelines; national guidelines; influencing cost-effectiveness analysis; and influencing drug approvals. Conclusions PRO trial data may potentially lead to a range of benefits for patients and society, which can be measured through appropriate impact metrics. However, in practice there is relatively limited evidence demonstrating directly attributable and indirect real world PRO-related research impact. In part, this is due to the wider challenges of measuring the impact of research and PRO-specific issues around design, conduct, analysis and reporting. Adherence to guidelines and multi-stakeholder collaboration is essential to maximise the use of PRO trial data, facilitate impact and minimise research waste. Trial registration Systematic Review registration PROSPERO CRD42017067799.

scholarly journals A Distribution-based Method for Assessing The Differences between Clinical Trial Target Populations and Patient Populations in Electronic Health Records

2014 ◽  
Vol 05 (02) ◽  
pp. 463-479 ◽  
Author(s):  
P. Ryan ◽  
Y. Zhang ◽  
F. Liu ◽  
J. Gao ◽  
J.T. Bigger ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Clinical Trial ◽  
Clinical Trials ◽  
Electronic Health Records ◽  
Real World ◽  
World Population ◽  
Health Records ◽  
Target Populations ◽  
Electronic Health

SummaryObjective: To improve the transparency of clinical trial generalizability and to illustrate the method using Type 2 diabetes as an example.Methods: Our data included 1,761 diabetes clinical trials and the electronic health records (EHR) of 26,120 patients with Type 2 diabetes who visited Columbia University Medical Center of New-York Presbyterian Hospital. The two populations were compared using the Generalizability Index for Study Traits (GIST) on the earliest diagnosis age and the mean hemoglobin A1c (HbA1c) values.Results: Greater than 70% of Type 2 diabetes studies allow patients with HbA1c measures between 7 and 10.5, but less than 40% of studies allow HbA1c<7 and fewer than 45% of studies allow HbA1c>10.5. In the real-world population, only 38% of patients had HbA1c between 7 and 10.5, with 12% having values above the range and 52% having HbA1c<7. The GIST for HbA1c was 0.51. Most studies adopted broad age value ranges, with the most common restrictions excluding patients >80 or <18 years. Most of the real-world population fell within this range, but 2% of patients were <18 at time of first diagnosis and 8% were >80. The GIST for age was 0.75. Conclusions: We contribute a scalable method to profile and compare aggregated clinical trial target populations with EHR patient populations. We demonstrate that Type 2 diabetes studies are more generalizable with regard to age than they are with regard to HbA1c. We found that the generalizability of age increased from Phase 1 to Phase 3 while the generalizability of HbA1c decreased during those same phases. This method can generalize to other medical conditions and other continuous or binary variables. We envision the potential use of EHR data for examining the generaliz-ability of clinical trials and for defining population-representative clinical trial eligibility criteria.Citation: Weng C, Li Y, Ryan P, Zhang Y, Liu F, Gao J, Bigger JT, Hripcsak G. A distribution-based method for assessing the differences between clinical trial target populations and patient populations in electronic health records. Appl Clin Inf 2014; 5: 463–479 http://dx.doi.org/10.4338/ACI-2013-12-RA-0105

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