Effectiveness of adaptive designs for phase II cancer trials

Fors, Martha; Dupuy, Jean‐François; González, Carmen Viada

doi:10.1016/j.cct.2011.09.017

Cited by 5 publications

(4 citation statements)

References 10 publications

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“…Some of the concerns over adaptive trial designs include whether this ‘adaptation’ process can potentially introduce biases and increase false discovery (Type I error). Sometimes the adapted process can lead to positive study results that are difficult to interpret [40]. Adaptive randomization designs, by their very nature, mean that subjects enrolled later in a trial will more likely be assigned to more effective treatments.…”

Section: Innovation In Clinical Trial Designs and Biomarkers In A Wormentioning

confidence: 99%

Ovarian cancer clinical trial endpoints: Society of Gynecologic Oncology white paper

Herzog

Armstrong

Brady

et al. 2014

Gynecologic Oncology

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Objective To explore the value of multiple clinical endpoints in the unique setting of ovarian cancer. Methods A clinical trial workgroup was established by the Society of Gynecologic Oncology to develop a consensus statement via multiple conference calls, meetings and white paper drafts. Results Clinical trial endpoints have profound effects on late phase clinical trial design, result interpretation, drug development, and regulatory approval of therapeutics. Selection of the optimal clinical trial endpoint is particularly provocative in ovarian cancer where long overall survival (OS) is observed. The lack of new regulatory approvals and the lack of harmony between regulatory bodies globally for ovarian cancer therapeutics are of concern. The advantages and disadvantages of the numerous endpoints available are herein discussed within the unique context of ovarian cancer where both crossover and post-progression therapies potentially uncouple surrogacy between progression-free survival (PFS) and OS, the two most widely supported and utilized endpoints. The roles of patient reported outcomes (PRO) and health related quality of life (HRQoL) are discussed, but even these widely supported parameters are affected by the unique characteristics of ovarian cancer where a significant percentage of patients may be asymptomatic. Original data regarding the endpoint preferences of ovarian cancer advocates is presented. Conclusions Endpoint selection in ovarian cancer clinical trials should reflect the impact on disease burden and unique characteristics of the treatment cohort while reflecting true patient benefit. Both OS and PFS have led to regulatory approvals and are clinically important. OS remains the most objective and accepted endpoint because it is least vulnerable to bias; however, the feasibility of OS in ovarian cancer is compromised by the requirement for large trial size, prolonged time-line for final analysis, and potential for unintended loss of treatment effect from active post-progression therapies. A large magnitude of effect in PFS improvement should establish benefit, and further communication with regulatory authorities to clarify acceptable endpoints should be undertaken.

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Section: Innovation In Clinical Trial Designs and Biomarkers In A Wormentioning

confidence: 99%

Ovarian cancer clinical trial endpoints: Society of Gynecologic Oncology white paper

Herzog

Armstrong

Brady

et al. 2014

Gynecologic Oncology

View full text Add to dashboard Cite

show abstract

“…As an additional strategy to meet the challenges outlined in the present article, adaptive trials-introducing flexibility by permitting modifications during the study founded on information available from the trial itself-might be able to attract patients and the pharmaceutical industry. 106 Since common cancers seem to have heterogenic molecular drivers, many of which may constitute fewer than 2% to approximately 10% of the patient population, single diagnostic molecular assays are unlikely to be cost effective or yield adequate information and will exhaust tissue samples. Multi-assay platforms that include both common and rare aberrations in an individual type of cancer will need to be performed at presentation and relapse to define an accurate molecular diagnosis suitable to the era of matched targeted therapy.…”

Section: Discussionmentioning

confidence: 99%

Targeted therapy in rare cancers—adopting the orphans

Muñoz

Kurzrock

2012

Nat Rev Clin Oncol

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Designation of a rare 'orphan' disease is usually conferred by a prevalence of one in 1,500 to 2,500 individuals. Increasingly, orphan diseases are also being defined by their molecular fingerprints. Rare diseases are uniquely challenging from a therapeutic standpoint; it is critical to modify clinical study design of treatments for orphan disorders as well as for the increasingly smaller molecular subsets within frequently occurring cancers. In spite of the immense challenges associated with developing a treatment for a rare disorder, some of the most groundbreaking therapeutic discoveries have been made in orphan malignancies. This situation may be because a limited number of driver molecular aberrations occur in rare disorders, which can be targeted by agents. Here, we describe drug-class examples of targeted therapies for orphan diseases, with particular emphasis on malignancies or tumour-prone nonmalignant conditions, as well as potential therapeutic strategies that can be adopted to treat these orphan conditions.

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“…Evaluation of new therapies for cancer has suffered a paradigm shift in the last years. The use of innovative and more efficient designs is a priority for the scientific community; nevertheless, the use of this kind of design is not yet widespread [ 8 ].Traditional clinical trials require specification of the sample size in advance. This can be inefficient when limited information is available at the design stage, especially regarding the likely effect size.…”

Section: Introductionmentioning

confidence: 99%

Current status of Bayesian clinical trials for oncology, 2020

Fors

González

2020

Contemporary Clinical Trials Communications

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Background Bayesian methods had established a foothold in developing therapies in oncology trials. Methods: We identified clinical trials posted on the ClinicalTrials.gov database focused on Oncology trials with a Bayesian approach in their design. Differences in study characteristics such as design, study phase, randomization, masking, purpose of study, main outcomes, gender, age and funding involvement according to Bayesian approach were assessed using Chi-squared or Fisher's exact tests. Results: We identified 225 studies with Bayesian components in their design addressing oncological diseases. The most common designs were Bayesian Toxicity Monitoring (26.4%), Model-based designs (36%) Model-assisted designs (8%). Statistical methods such as Bayesian logistic regression model (59.4%), Bayesian piecewise exponential survival regression (10.9%) and the Continual reassessment method (9.4%) were the most used. Conclusions: Bayesian trials are more common in the early phases of drug development specifically in phase II trials (43.6%). Cancer institutes or Hospitals funded most of the studies retrieved. This type of design has increased over time and represent an innovative means of increasing trial efficiency.

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Effectiveness of adaptive designs for phase II cancer trials

Cited by 5 publications

References 10 publications

Ovarian cancer clinical trial endpoints: Society of Gynecologic Oncology white paper

Ovarian cancer clinical trial endpoints: Society of Gynecologic Oncology white paper

Targeted therapy in rare cancers—adopting the orphans

Current status of Bayesian clinical trials for oncology, 2020

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