Harnessing the Power of Collaboration and Training Within Clinical Data Science to Generate Real‐World Evidence in the Era of Precision Oncology

2019 ◽  
Vol 106 (1) ◽  
pp. 60-66 ◽  
Author(s):  
Donna R. Rivera ◽  
Jerry S. H. Lee ◽  
Elizabeth Hsu ◽  
Muin J. Khoury ◽  
Frank Meng ◽  
...  
Keyword(s):  
Clinical Data ◽  
Real World ◽  
Data Science ◽  
Precision Oncology ◽  
Real World Evidence ◽  
And Training

scholarly journals Developing a multi-center clinical data mart of ACEI and ARB for real-world evidence (RWE)

2018 ◽  
Vol 24 (1) ◽  
Author(s):  
Hun-Sung Kim ◽  
Sue Hyun Lee ◽  
Tong Min Kim ◽  
Ju Han Kim
Keyword(s):  
Clinical Data ◽  
Real World ◽  
Data Mart ◽  
Real World Evidence

scholarly journals Real-World Evidence and Randomized Studies in the Precision Oncology Era: The Right Balance

2017 ◽  
pp. 1-5 ◽  
Author(s):  
Bishal Gyawali ◽  
Sandeep Parsad ◽  
Bruce A. Feinberg ◽  
Chadi Nabhan
Keyword(s):  
Real World ◽  
Precision Oncology ◽  
Randomized Studies ◽  
Real World Evidence ◽  
The Right

scholarly journals Erenumab in highly therapy-refractory migraine patients First German Real-world evidence

2020 ◽  
Author(s):  
Armin Scheffler ◽  
Olga Messel ◽  
Sebastian Wurthmann ◽  
Michael Nsaka ◽  
Christoph Kleinschnitz ◽  
...  
Keyword(s):  
Clinical Data ◽  
Real World ◽  
Therapeutic Option ◽  
Medication Overuse Headache ◽  
Routine Data ◽  
Wilcoxon Test ◽  
University Hospital ◽  
Real World Evidence ◽  
Acute Medication ◽  
Refractory Migraine

Abstract Background: Calcitonin gene related peptide (CGRP) monoclonal antibodies (mAB) are the first specific migraine prophylactic medication. Erenumab is the only CGRP mAB targeting the CGRP receptor. Clinical data regarding efficacy and tolerability of erenumab in highly therapy-refractory patients are not available, yet, although many patients treated with CGRP mAB under real world conditions can be considered as highly therapy-refractory.Methods: Clinical routine data of highly therapy-refractory migraine patients treated with erenumab 70mg for three months between November 2018 and December 2019 in the West German Headache Center, University Hospital Essen, Germany, were analysed. Monthly migraine days (MMD), monthly headache days (MHD) and days of acute medication intake (AMD) were assessed. Statistical analysis was performed using the Wilcoxon test. Descriptive statistics were performed to evaluate changes of vegetative symptoms, acute medication response, side effects, as well as treatment satisfaction.Results: Complete clinical data were available for 26 episodic (EM) and 74 chronic (CM) migraineurs. Sixty-six % (n=49) of CM patients had an additional medication overuse headache (MOH). After three months 57.7 % of EM patients and 41.9 % of CM patients had a 50% or greater reduction of MMD. The mean number of MMD was reduced by 3.43 (SE 1.26) in EM, and by 4.72 (SE 0.87) in CM. Thirty-nine patients (52.7%) returned from chronic to episodic course of migraine. After three months, 23 patients (46.9%) were not suffering from a MOH anymore.Conclusions: Erenumab seems to be a promising therapeutic option in highly therapy-refractory migraine patients.Trial registration: Retrospective registered.

scholarly journals Erenumab in highly therapy-refractory migraine patients: First German Real-world evidence

2020 ◽  
Author(s):  
Armin Scheffler ◽  
Olga Messel ◽  
Sebastian Wurthmann ◽  
Michael Nsaka ◽  
Christoph Kleinschnitz ◽  
...  
Keyword(s):  
Clinical Data ◽  
Real World ◽  
Therapeutic Option ◽  
Medication Overuse Headache ◽  
Routine Data ◽  
Wilcoxon Test ◽  
University Hospital ◽  
Real World Evidence ◽  
Acute Medication ◽  
Refractory Migraine

Abstract Background Calcitonin gene related peptide (CGRP) monoclonal antibodies (mAB) are the first specific migraine prophylactic medication. Erenumab is the only CGRP mAB targeting the CGRP receptor. Clinical data regarding efficacy and tolerability of erenumab in highly therapy-refractory patients are not available, yet, although many patients treated with CGRP mAB under real world conditions can be considered as highly therapy-refractory. Methods Clinical routine data of highly therapy-refractory migraine patients treated with erenumab 70mg for three months between November 2018 and December 2019 in the West German Headache Center, University Hospital Essen, Germany, were analysed. Monthly migraine days (MMD), monthly headache days (MHD) and days of acute medication intake (AMD) were assessed. Statistical analysis was performed using the Wilcoxon test. Descriptive statistics were performed to evaluate changes of vegetative symptoms, acute medication response, side effects, as well as treatment satisfaction. Results Complete clinical data were available for 26 episodic (EM) and 74 chronic (CM) migraineurs. Sixty-six % (n=49) of CM patients had an additional medication overuse headache (MOH). After three months 57.7% of EM patients and 41.9% of CM patients had a 50% or greater reduction of MMD. The mean number of MMD was reduced by 3.43 (SE 1.26) in EM, and by 4.72 (SE 0.87) in CM. Thirty-nine patients (52.7%) returned from chronic to episodic course of migraine. After three months, 23 patients (46.9%) were not suffering from a MOH anymore. Conclusions Erenumab seems to be a promising therapeutic option in highly therapy-refractory migraine patients.

scholarly journals Real-world evidence for postgraduate students and professionals in healthcare: protocol for the design of a blended massive open online course

BMJ Open ◽  
2018 ◽  
Vol 8 (9) ◽  
pp. e025196 ◽  
Author(s):  
Edward Meinert ◽  
Abrar Alturkistani ◽  
Josip Car ◽  
Alison Carter ◽  
Glenn Wells ◽  
...  
Keyword(s):  
Real World ◽  
Data Science ◽  
Healthcare Professionals ◽  
Course Design ◽  
Primary Objective ◽  
Learning Theories ◽  
Design Development ◽  
Massive Open Online ◽  
Postgraduate Students ◽  
Real World Evidence

IntroductionThere is an increased need for improving data science skills of healthcare professionals. Massive open online courses (MOOCs) provide the opportunity to train professionals in a sustainable and cost-effective way. We present a protocol for the design and development of a blended MOOC on real-world evidence (RWE) aimed at improving RWE data science skills. The primary objective is to provide the opportunity to understand the fundamentals of RWE data science and to implement methods for analysing RWD. The blended format of MOOC will combine the expertise of healthcare professionals joining the course online with the on-campus students. We expect learners to take skills taught in MOOC and use them to seek new employment or to explore entpreneurship activities in these domains.Methods and analysisThe proposed MOOC will be developed through a blended format using the Analysis, Design, Development, Implementation and Evaluation instructional design model and following the connectivist–heutagogical learning theories (as a hybrid MOOC). The target learners will include postgraduate students and professionals working in the health-related roles with interest in data science. An evaluation of MOOC will be performed to assess MOOCs success in meeting its intended outcomes and to improve future iterations of the course.Ethics and disseminationThe education course design protocol was approved by EIT Health (grant 18654) as part of the EIT Health CAMPUS Deferred Call for Innovative Education 2018. Results will be published in a peer-reviewed journal.

scholarly journals Automating Electronic Clinical Data Capture for Quality Improvement and Research: The CERTAIN Validation Project of Real World Evidence

2018 ◽  
Vol 6 (1) ◽  
pp. 8
Author(s):  
Emily Beth Devine ◽  
Erik Van Eaton ◽  
Megan E. Zadworny ◽  
Rebecca Symons ◽  
Allison Devlin ◽  
...  
Keyword(s):  
Quality Improvement ◽  
Clinical Data ◽  
Real World ◽  
Data Capture ◽  
Real World Evidence

Generating real-world evidence: Using automated data extraction to replace manual chart review.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e18096-e18096 ◽  
Author(s):  
Jennifer H. Law ◽  
Christopher Pettengell ◽  
Lisa W Le ◽  
Steven Aviv ◽  
Patricia DeMarco ◽  
...  
Keyword(s):  
Data Collection ◽  
Clinical Data ◽  
Real World ◽  
Chart Review ◽  
Clinical Decision Making ◽  
Data Extraction ◽  
Clinical Care ◽  
Data Abstraction ◽  
Real World Evidence

e18096 Background: Real world evidence is a valuable resource to help guide clinical care beyond evidence generated from clinical trials, for example safety and effectiveness of novel treatments in special populations. Administrative databases often lack sufficient clinical detail to address gaps in the improvement of patient management and quality of care. Detailed clinical data collection and curation are resource intensive, limiting the ability to generate and maintain large informative cancer databases. Darwen, novel technology developed by Pentavere, enables the automation of data abstraction from unstructured hospital electronic medical records and may eliminate the need for manual chart review. Methods: Health records were identified through an institutional cancer registry from patients with stage IIIB/IV lung cancer (NSCLC or SCLC) diagnosed and treated at the Princess Margaret Cancer Centre between 01/01/2015 and 31/12/2017. Cases underwent automated data extraction including demographics, comorbidities, treatment, concurrent medications and outcomes until 30/06/2018. Agreement with data fields extracted using manual data collection in an external validation set of patients is planned. Results: Of 1210 patients identified, 538 were eligible for analysis. From automated data abstraction, 9.9% were reported to have SCLC, 67.5% adenocarcinoma, 11.2% squamous carcinoma, 28% EGFR mutations, 5.8% ALK fusions and 9.3% tumour PDL1 > = 50%. Of the 304 (56.5%) that received systemic therapy, initial treatment was chemotherapy for 55.6%, targeted therapy in 34.2% and immunotherapy in 10.2%. Additional outcome data and agreement with manually curated data fields will be presented. Conclusions: Automated software to extract clinical data is a powerful new tool to generate and maintain databases that yield high quality real world clinical evidence. This is a critical next step to improve clinical decision making, inform evidence-based practice and improve quality of cancer care.

scholarly journals The quality of research with real-world evidence

2019 ◽  
pp. 39-41
Author(s):  
Mauricio Palacios Gómez
Keyword(s):  
Clinical Trials ◽  
Clinical Data ◽  
Real World ◽  
Clinical Care ◽  
Medical Science ◽  
Clinical Information ◽  
Real World Data ◽  
Real World Evidence ◽  
Definition Of ◽  
Time Required

Most of the medical practice has not been proven by controlled clinical trials, and there are no plans to conduct such trials in order to decrease clinician uncertainty. This happens partly due to the difficulty of making designs with scientific and ethical validity, the costs of this type of research and the time required to generate results, which can be several years. Clinical trials do not have the capability to generate information that allows to make decisions in some sectors of clinical care and public health, such as when an epidemic occurs. Therefore, medical science is based on observational studies, past practices and therapeutic tradition (1). Observation of clinical data that have defined a clinical behavior precedes the clinical trial. The knowledge about scurvy, the fact that this pathology is considered a nutritional deficiency and its treatment with citrus fruits, originated thanks to the collection of clinical data on sailors, soldiers and prisoners of the British Crown in the 18th and 19th centuries (2). This clinical information, which was collected uniformly and served to produce new knowledge, is what is now known as Real World Data (RWD). A modern definition of RWD would be one that talks about data obtained by any non-interventionist methodology that is collected prospectively and retrospectively from observations of routine clinical practice, and which comes from various sources including data from patients, doctors, hospitals, payers, social data, etc (3).

Real-world genomic and treatment landscape in advanced colorectal cancer identifies treatment differences pre- and post-ctDNA genomic profiling.

2021 ◽  
Vol 39 (3_suppl) ◽  
pp. 39-39
Author(s):  
Junhua Yu ◽  
Kanwal Pratap Singh Raghav ◽  
Aparna Raj Parikh ◽  
David Hanna ◽  
Enrique Marino ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Combination Therapy ◽  
Clinical Data ◽  
Real World ◽  
Advanced Colorectal Cancer ◽  
Health Claims ◽  
Precision Oncology ◽  
Genomic Profiling ◽  
Pharmacy Claims ◽  
Clinical Genomic

39 Background: Clinical insights gained from real-world data have led to numerous advances in oncology including new and expanded drug approvals and an understanding of real-world clinical utilization. In this precision oncology age, integrating real-world clinical data with genomic data can lead to further advancements. We aimed to understand the genomic and treatment landscape in advanced colorectal cancer (aCRC) by leveraging a uniquely large and detailed clinical-genomic database. Methods: The GuardantINFORM (Guardant Health) database comprises aggregated commercial payer health claims and de-identified records from over 100,000 individuals with comprehensive ctDNA results (Guardant360). GuardantINFORM was queried for patients (pts) with a diagnosis of CRC. Pts with fewer than two pharmacy claims prior to or after the first ctDNA test were excluded from the regimen analysis. Latest claims data was truncated as of 8/31/2020. Results: 10,845 pts had a total of 13,510 ctDNA tests (1 – 19 tests/pt). The first ctDNA test date was from 06/2014 - 06/2020. The majority of pts had one ctDNA test (86.7%) while 5% had three or more tests. 87.9% of ctDNA tests had at least one genomic alteration identified, with the distribution of alterations consistent with prior reports (Table). 78% of pts had at least two pharmacy claims before and/or after the first ctDNA test. Of those pts with at least one CRC treatment, the most commonly prescribed CRC regimens up to one year prior to the first ctDNA test were FOLFOX +/- bevacizumab (16%, 18%), FOLFIRI +/- bevacizumab (17%, 11%), capecitabine (15%), 5-FU (12%), and regorafenib (5.2%). Anti-EGFR mono and combination therapy was reported in 6% and 16% of pts pre ctDNA testing. Immune checkpoint inhibitor (ICPi) mono and combination therapy was reported in 2% and 0.5% of pts. The most commonly prescribed CRC regimens post first ctDNA test were capecitabine (16%), FOLIRI +/- bevacizumab (15%, 13%), tipiracil and trifluridine (15%), FOLFOX +/- bevacizumab (12%, 14%), 5-FU (11%), and regorafenib (10%). Anti-EGFR mono and combination therapy was reported in 8% and 18% of pts post ctDNA testing. ICPi mono and combination therapy was reported in 5% and 1% of pts. Conclusions: Using a large and uniquely detailed clinical-genomic dataset, we produced results that replicate the observed distribution of ctDNA identified mutations present in aCRC. This genomic information combined with real-world clinical data provides valuable insights into the variety of longitudinal treatments, including before and after comprehensive ctDNA genomic profiling, allowing for detailed outcomes research, especially focused on precision oncology. [Table: see text]

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