'Considering the totality of evidence: Combining real‐world data with clinical trial results to better inform decision‐making

2021 ◽  
Author(s):  
Ronac Mamtani ◽  
Jennifer Lund ◽  
Rebecca A. Hubbard
Keyword(s):  
Clinical Trial ◽  
Decision Making ◽  
Real World ◽  
Real World Data ◽  
World Data ◽  
Clinical Trial Results ◽  
Inform Decision Making ◽  
Totality Of Evidence

scholarly journals Harnessing Real-World Data to Inform Decision-Making: Multiple Sclerosis Partners Advancing Technology and Health Solutions (MS PATHS)

2020 ◽  
Vol 11 ◽  
Author(s):  
Ellen M. Mowry ◽  
Robert A. Bermel ◽  
James R. Williams ◽  
Tammie L. S. Benzinger ◽  
Carl de Moor ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Decision Making ◽  
Real World ◽  
Real World Data ◽  
World Data ◽  
Inform Decision Making

Quality criteria for Real-World Data in pharmaceutical research and healthcare decision making. An Austrian Expert Consensus (Preprint)

2021 ◽  
Author(s):  
Peter Klimek ◽  
Dejan Baltic ◽  
Martin Brunner ◽  
Alexander Degelsegger-Marquez ◽  
Gerhard Garhöfer ◽  
...  
Keyword(s):  
Decision Making ◽  
Medical Research ◽  
Real World ◽  
Pharmaceutical Medicine ◽  
Pharmaceutical Research ◽  
Quality Criteria ◽  
Clinical Decision ◽  
European Medicines Agency ◽  
Real World Data ◽  
World Data

UNSTRUCTURED Real-world data (RWD) collected in routine healthcare processes and transformed to real-world evidence (RWE) has become increasingly interesting within research and medical communities to enhance medical research and support regulatory decision making. Despite numerous European initiatives, there is still no cross-border consensus or guideline determining which quality RWD must meet in order to be acceptable for decision making within regulatory or routine clinical decision support. An Austrian expert group led by GPMed (Gesellschaft für Pharmazeutische Medizin, Austrian Society for Pharmaceutical Medicine) reviewed drafted guidelines, published recommendations or viewpoints to derive a consensus statement on quality criteria for RWD to be used more effectively for medical research purposes beyond registry-based studies discussed in the European Medicines Agency (EMA) guideline for registry-based studies

Automated Diagnosis through Ontologies and Logical Descriptions

2013 ◽  
pp. 117-134
Author(s):  
Alejandro Rodríguez-González ◽  
Ángel García-Crespo ◽  
Ricardo Colomo-Palacios ◽  
José Emilio Labra Gayo ◽  
Juan Miguel Gómez-Berbís ◽  
...  
Keyword(s):  
Decision Making ◽  
Health Systems ◽  
Real World ◽  
Information Age ◽  
Semantic Technologies ◽  
Automated Diagnosis ◽  
Real World Data ◽  
World Data ◽  
Degree Of Maturity ◽  
Automate Diagnosis

The combination of the burgeoning interest in efficient and reliable Health Systems and the advent of the Information Age represent both a challenge and an opportunity for new paradigms and cutting-edge technologies reaching a certain degree of maturity. Hence, the use of Semantic Technologies for Automated Diagnosis could leverage the potential of current solutions by providing inference-based knowledge and support on decision-making. This paper presents the ADONIS approach, which harnesses the use of ontologies and the underlying logical mechanisms to automate diagnosis and provide significant quality results in its evaluation on real-world data scenarios.

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 .

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