Issues in the Design and Analysis of Oncology Clinical Trials

2014 ◽  
pp. 249-282 ◽  
Keyword(s):  
Clinical Trials ◽  
Oncology Clinical Trials

scholarly journals COVID-19 vaccine guidance for patients with cancer participating in oncology clinical trials

2021 ◽  
Author(s):  
Aakash Desai ◽  
◽  
Justin F. Gainor ◽  
Aparna Hegde ◽  
Alison M. Schram ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Patients With Cancer ◽  
Oncology Clinical Trials

Z max test for delayed effect in immuno-oncology clinical trials

2019 ◽  
Vol 30 (2) ◽  
pp. 244-266 ◽  
Author(s):  
Miao Yang ◽  
Zhaowei Hua ◽  
Lan Xue ◽  
Mingxiu Hu
Keyword(s):  
Clinical Trials ◽  
Delayed Effect ◽  
Oncology Clinical Trials

Dedicated clinical trial tissue tracking database to improve turn-around time at high-volume center.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 1543-1543
Author(s):  
Peter Blankenship ◽  
David DeLaRosa ◽  
Marc Burris ◽  
Steven Cusson ◽  
Kayla Hendricks ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Tissue Sample ◽  
High Volume ◽  
Trial Participation ◽  
Fresh Tissue ◽  
Oncology Clinical Trials ◽  
The Status ◽  
Unique Source

1543 Background: Tissue requirements in oncology clinical trials are increasingly complex due to prescreening protocols for patient selection and serial biopsies to understand molecular-level treatment effects. Novel solutions for tissue processing are necessary for timely tissue procurement. Based on these needs, we developed a Tissue Tracker (TT), a comprehensive database for study-related tissue tasks at our high-volume clinical trial center. Methods: In this Microsoft Access database, patients are assigned an ID within the TT that is associated with their name, medical record number, and study that follows their request to external users: pathology departments, clinical trial coordinators and data team members. To complete tasks in the TT, relevant information is required to update the status. Due to the high number of archival tissue requests from unique pathology labs, the TT has a “Follow-Up Dashboard” that organizes information needed to conduct follow-up on all archival samples with the status “Requested”. This results in an autogenerated email and pdf report sent to necessary teams. The TT also includes a kit inventory system and a real-time read only version formatted for interdepartmental communication, metric reporting, and other data-driven efforts. The primary outcome in this study was to evaluate our average turnaround time (ATAT: average time from request to shipment) for archival and fresh tissue samples before and after TT development. Results: Before implementing the TT, between March 2016 and March 2018, we processed 2676 archival requests from 235 unique source labs resulting in 2040 shipments with an ATAT of 19.29 days. We also processed 1099 fresh biopsies resulting in 944 shipments with an ATAT of 7.72 days. After TT implementation, between April 2018 and April 2020, we processed 2664 archival requests from 204 unique source labs resulting in 2506 shipments (+28.0%) with an ATAT of 14.78 days (-23.4%). During that same period, we processed 1795 fresh biopsies (+63.3%) resulting in 2006 shipments (+112.5%) with an ATAT of 6.85 days (-11.3%). Conclusions: Oncology clinical trials continue to evolve toward more extensive tissue requirements for prescreening and scientific exploration of on-treatment molecular profiling. Timely results are required to optimize patient trial participation. During the intervention period, our tissue sample volume and shipments increased, but the development and implementation of an automated tracking system allowed improvement in ATAT of both archival and fresh tissue. This automation not only improves end-user expectations and experiences for patients and trial sponsors but this allows our team to adapt to the increasing interest in tissue exploration.

A systematic review of noninferiority margins in oncology clinical trials

2021 ◽  
Vol 10 (6) ◽  
pp. 443-455
Author(s):  
Mahmoud Hashim ◽  
Talitha Vincken ◽  
Florint Kroi ◽  
Samron Gebregergish ◽  
Mike Spencer ◽  
...  
Keyword(s):  
Systematic Review ◽  
Clinical Trials ◽  
Absolute Rate ◽  
Time To Event ◽  
End Points ◽  
Patients With Cancer ◽  
Randomized Controlled ◽  
Noninferiority Trials ◽  
Oncology Clinical Trials ◽  
Noninferiority Margin

Aim: A systematic literature review was conducted to identify and characterize noninferiority margins for relevant end points in oncology clinical trials. Materials & methods: Randomized, controlled, noninferiority trials of patients with cancer were identified in PubMed and Embase. Results: Of 2284 publications identified, 285 oncology noninferiority clinical trials were analyzed. The median noninferiority margin was a hazard ratio of 1.29 (mean: 1.32; range: 1.05–2.05) for studies that reported time-to-event end points (n = 192). The median noninferiority margin was 13.0% (mean: 12.7%; range: 5.0–20.0%) for studies that reported response end points as absolute rate differences (n = 31). Conclusion: Although there was consistency in the noninferiority margins’ scale, variability was evident in noninferiority margins across trials. Increased transparency may improve consistency in noninferiority margin application in oncology clinical trials.

scholarly journals Insurance Clearance for Early-Phase Oncology Clinical Trials Following the Affordable Care Act

2017 ◽  
Vol 23 (15) ◽  
pp. 4155-4162 ◽  
Author(s):  
Kenneth L. Kehl ◽  
Cheryl P. Fullmer ◽  
Siqing Fu ◽  
Goldy C. George ◽  
Kenneth R. Hess ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Affordable Care Act ◽  
Early Phase ◽  
Oncology Clinical Trials ◽  
The Affordable Care Act

scholarly journals Indicadores (Outcomes) Primários e Secundários em Ensaios Clínicos Oncológicos: Definição e Usos

2014 ◽  
Vol 27 (4) ◽  
pp. 498
Author(s):  
António Vaz-Carneiro ◽  
Ricardo Da Luz ◽  
Margarida Borges ◽  
João Costa
Keyword(s):  
Clinical Trials ◽  
Methodological Issue ◽  
Objective Response ◽  
Disease Free Survival ◽  
Progression Free Survival ◽  
Free Survival ◽  
Patient Reported ◽  
Oncology Clinical Trials ◽  
Alternative Drug ◽  
Selection Of

<strong>Introduction:</strong> The proof of efficacy from a therapeutic intervention in oncology must be defined through well conducted clinical trials. One of the most important methodological issue is the outcome selection needed to calculate measures of association allowing definition of clinical efficacy.<br /><strong>Material and Methods:</strong> We designed a narrative revision based on some of the international regulatory instructions from drug agencies, as well as consensus papers from scientific oncology societies, listing and critically assessing each outcome used in oncology clinical trials.<br /><strong>Results:</strong> We identified as being the most important outcomes in oncology trials the overall survival, the progression free survival/ disease-free survival, the toxicity, the quality of life/patient- reported outcomes and the objective response rate.<br /><strong>Discussion:</strong> The selection of the primary outcome must be based on therapeutic efficacy as well as toxicity, expected survival, alternative drug regimens and even disease prevalence.<br /><strong>Conclusion:</strong> The selection of efficacy outcomes for clinical trials in oncology is very important and its selection must be well justified, and depends on the type of disease, the patients and the drug being studied.<br /><strong>Keywords:</strong> Clinical Trials as Topic; Neoplasms; Medical Oncology; Treatment Outcome.

scholarly journals Reimagining Global Oncology Clinical Trials for the Postpandemic Era: A Call to Arms

2020 ◽  
pp. 1357-1362
Author(s):  
Kamal S. Saini ◽  
Begoña de las Heras ◽  
Ruth Plummer ◽  
Victor Moreno ◽  
Marco Romano ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Oncology Clinical Trials
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