Pitavastatin therapy in polymedicated patients is associated with a low risk of drug-drug interactions: analysis of real-world and phase 3 clinical trial data

2015 ◽  
Vol 53 (08) ◽  
pp. 635-646 ◽  
Author(s):  
Masahiko Gosho ◽  
Masaya Tanahashi ◽  
Neil Hounslow ◽  
Tamio Teramoto
Keyword(s):  
Clinical Trial ◽  
Drug Interactions ◽  
Real World ◽  
Clinical Trial Data ◽  
Trial Data ◽  
Low Risk ◽  
Phase 3

scholarly journals Early clinical trial data and real‐world assessment of COVID‐19 vaccines: Insights from the Society of Infectious Diseases Pharmacists

2021 ◽  
Vol 41 (10) ◽  
pp. 837-850
Author(s):  
Nimish Patel ◽  
Jeannette Bouchard ◽  
Meredith B. Oliver ◽  
Melissa E. Badowski ◽  
Joseph J. Carreno ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Infectious Diseases ◽  
Real World ◽  
Clinical Trial Data ◽  
Trial Data ◽  
Early Clinical Trial

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 ASO Author Reflections: Bridging the Gap between Clinical Trial Data and Real-World Cancer Care

2020 ◽  
Vol 27 (7) ◽  
pp. 2276-2277
Author(s):  
Judy C. Boughey ◽  
Amanda B. Francescatti ◽  
Ko Un Park ◽  
Kelly K. Hunt
Keyword(s):  
Clinical Trial ◽  
Real World ◽  
Cancer Care ◽  
Clinical Trial Data ◽  
Trial Data

scholarly journals PMU8 A SYSTEMATIC APPROACH FOR SYNTHETIC REPLICATION OF CLINICAL TRIAL COHORTS USING RETROSPECTIVE REAL-WORLD AND CLINICAL TRIAL DATA

2019 ◽  
Vol 22 ◽  
pp. S250
Author(s):  
A. Galaznik ◽  
M. Berger ◽  
B. Lempernesse ◽  
J. Ransom ◽  
A. Shilnikova
Keyword(s):  
Clinical Trial ◽  
Real World ◽  
Systematic Approach ◽  
Clinical Trial Data ◽  
Trial Data

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.

Response to checkpoint inhibitors (CPI) in sarcomatoid renal cell carcinoma (sRCC).

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e17095-e17095
Author(s):  
Iris Yeong- Fung Sheng ◽  
Wei Wei ◽  
Kunal Desai ◽  
Kimberly D. Allman ◽  
Allison Martin ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Real World ◽  
Systemic Therapy ◽  
Checkpoint Inhibitors ◽  
Cleveland Clinic ◽  
Clinical Trial Data ◽  
Trial Data ◽  
Rank Test ◽  
World Population ◽  
Related Factors

e17095 Background: sRCC have a generally poor prognosis though recent clinical trial data suggest improved outcomes with CPI. We present a real-world experience of metastatic sRCC patients (pts) treated with a variety of CPI. Methods: Pts with sRCC treated with CPI Cleveland Clinic from 1/1/2015 to 12/31/2019 were identified. Overall survival (OS) was estimated using Kaplan-Meier and compared by log rank test. Results: Of 28 eligible pts identified with sRCC, median age 58, 82% Caucasian, all KPS score > 80%, 86% had IMDC intermediate/poor risk disease, 75% were clear cell, and 71% had prior nephrectomy. 46.4% had prior non-CPI systemic therapy. CPI therapy in this cohort included: 46% nivolumab monotherapy, 18% axitinib/pembrolizumab, 21% ipilimumab/nivolumab, 4% atezolizumab/bevacizumab, 7% atezolizumab, 4% carboplatin/pemetrexed/pembrolizumab. At a median follow up of 13.6 months (range 6.5-31.4), ORR was 36% (4% CR, 32% PR) and median OS was 13.8 months (95% CI: 9.23-NA). Median time to response was 3.2 months (range 2.4-13.1) and median duration of response was 8.1 months (range 0-25.5). Ten of the 13 patients started subsequent therapy due to progression. At the time of analysis, 39% were still alive and 25% of patients were still on initial I/O therapy (7+ -30+ months). There were no clear correlations between specific disease-related factors (including IMDC risk, time-to treatment of > or < 1 year, or prior systemic therapy) and response (all were p > 0.05). Conclusions: ORR and CR rates were lower in this real-world population of metastatic sRCC pts compared to clinical trial data, which should be a result of various CPI treatments and lines of treatment. However, these data highlight the heterogeneity of sRCC in general and need for additional investigations into impact of percentage of sarcomatoid features, genomic analyses, line of therapy, and CPI choice to optimize outcomes in sRCC pts.

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