A new application of basket trials is in multiple expansion cohort trials that proceed a dose-finding trial. Coronavirus disease 2019 (COVID-19) is an ongoing pandemic affecting more than 200 countries and regions. That is, the approval could be false. The development of novel dose-finding designs for Phase I trials has been through a “spiral evolution” that evolves from Class 1 to Class 2 to Class 3, and back to Class 1 but with smarter rules. The second is to model the current control arm parameters and the historical control parameters as random samples from a common population distribution, i.e., hierarchical modeling. Complex immuno-oncology drug development requires innovation, commitment and expertise. The hierarchical modeling approach is another way to borrow historical information. Lastly, the posterior distribution for the parameter of interest does not have a closed-form expression in many situations, and computationally intensive Monte Carlo methods are necessary for inference. Specifically, DLT events are evaluated by following patients post-treatment for a certain time window; say, 28 days. Phase I trials usually involve a small number of participants (approx. 2018. The subgroup effect can be characterized by the interaction between T and X. Geriatric patients with cancer are underrepresented in oncology clinical trials for many reasons—yet this population has a high cancer burden. However, practical restrictions and strong emphasis on patient safety may cancel out the benefits of borrowing information, which is observed in subsequent methodology development. Then, the probability of assigning the patient to treatment t can be proportional to Pr(q̃t > q̃t’ for all t’ ≠ t | x̃, data)α, where α∈[0, 1] is a pre-specified tuning parameter. With the accumulation of DLT data, the posterior distribution of α is given by. However, the mTPI design maintains good frequentist performance by using a sensible decision framework based on toxicity probability intervals. The challenges of subgroup analysis include the issue of multiple testing, lack of power, and the possibility of data dredging. Usually, massive computer simulations are required to understand the frequentist properties of a Bayesian method, and calibration of the Bayesian method (e.g., calibration of the prior and probability threshold for decision-making) is needed to achieve desirable frequentist performance. Center for Information and Study on Clinical Research Participation (CISCRP). This has been shown by the simulation results in the i3+3 design, along with its dose-assignment decision table in comparison with the aforementioned model-based designs. Clinical Trials & Testing In the last five years, Covance’s expertise, insights and market impact have been demonstrated in excess of 975 oncology studies (300 in immuno-oncology) across nearly 19,000 sites in 83 countries with more than 104,000 oncology patients. Figure 3(a) shows this posterior density with different choices of α. Hierarchical Models. A Phase II trial aims to establish the “proof of concept” and the initial efficacy profile of the drug. It also allows estimation of the entire dose-response curve. Here, ϵ1 and ϵ2 are elicited from collaborating physicians, which reflect a clinically acceptable toxicity range for defining the MTD. The ORR in each substudy of a basket trial is compared with a historical control rate, and substudies with promising responses would warrant further investigation or conditional marketing approval. The probability of making a false rejection is unknown, but under the Bayesian framework, it can be estimated as the posterior probability of the null hypothesis, given the observed data. The first is to construct an informative prior for the parameters in the current control arm based on the historical data. Suppose, more generally, J historical studies are available (J can be 1). Make sure you understand the risks before participating. Even though the mTPI design has greatly simplified trial conduct, there is still room for further simplification, which is manifested in the cumulative cohort design (CCD) and later the Bayesian optimal interval (BOIN) design. First, the choice of the prior distribution has an impact on posterior inference. Second, Bayesian methods do not necessarily have desirable frequentist properties; i.e., operating characteristics over possible repetitions of the same experiment. The 3+3 design (Storer. Suppose further that we observe 6 responses out of 12 patients in the current control, the posterior of the control ORR is Beta(7 + 4 ∙ α, 7 + 6 ∙ α). Viele, K., Berry, S., Neuenschwander, B., Amzal, B., Chen, F., et al. 2010. For example, for trials with a binary endpoint, θ is the control response rate; for trials with a continuous endpoint, θ is the mean response of the control arm. Those who are not infected with COVID-19 may experience treatment discontinuations or interruptions due to the possibility of being exposed to infection, travel restrictions, or prioritization of COVID-19 patients. Pharmaceutical Statistics 13(1), 41–54. The Alliance has been awarded a grant by the National Cancer Institute (NCI) as a member of the NCI National Clinical Trials Network (NCTN). (See FDA draft guidance in Further Reading.) Clinical trials bridge the gap between research and effective cancer treatment. The mTPI design assigns the next cohort of patients to dose (d + 1), d, and (d − 1) if the UI, EI, or OI has the largest unit probability mass (UPM), where the UPM of interval I at dose d is defined as Pr(θd ϵ I | data) / length (I). More importantly, implementing CRM requires constant interaction between the clinical operation team and statisticians because the adaptive decisions from CRM must be carried out by statisticians via software or in-house computer programs. Please note that if you select one of these websites, you will leave Cancer.Net. Phase 1 Clinical Trials NEXT Oncology is dedicated to the advancement of Phase 1 cancer research through clinical trials of anticancer agents with the goal of providing innovative developments in cancer treatment. Impact of COVID-19. In a basket trial, the substudies are typically conducted in a single-arm fashion without concurrent controls. Illustrations of (a) the basket trial of larotrectinib in different NTRK fusion-positive tumor types and (b) the I-SPY 2 platform trial for breast cancer. It is only possible to commit a Type I error when the null is rejected. The statistical inference uses posterior distributions, which are obtained using Bayes’ theorem to combine the prior and the likelihood function for observed data. When frequentist properties are strictly enforced, such as in confirmatory clinical trials, Bayesian methods are usually considered as supportive, although there has been fierce debate recently over whether frequentist properties (e.g., p-values) are the best criteria for decision-making. Let θj and θ0j denote the treatment and historical control response rates in basket j, respectively. Here, ηm represents the treatment effect within subspace m (subgroup m), and the difference in ηm reflects subgroup effects. His research interests include clinical trial designs, statistical genomics, missing data, and infectious diseases. Food and Drug Administration. Assume the prior distribution of α is π0(α). A Phase I trial investigates the safety profile of the drug and finds an appropriate dose level for further testing. Find out what you need to know before taking part. 1989), as the origin of modern dose-finding designs, has been the most-popular choice in clinical practice for the past 30 years. The type of cancer Tyler was treated for and her outcome made her an ideal candidate for a clinical trial at Lexington Oncology. The staff at CISCRPwill conduct free clinical trial searches. See Figure 3(b). More generally, platform trials may involve both multiple treatments and multiple cancer (sub)types and also include a notion of a perpetual process with treatment arms being added or dropped over time. The outbreak of COVID-19 can have an impact on oncology clinical trials in many aspects. It’s no secret that pharmaceutical and clinical trial industries are reluctant to adapt to technological changes. It consists of a set of dose-assignment rules and does not rely on a statistical model. He earned his PhD in statistics from the University of Texas at Austin and received the Savage Award (honorable mention) for outstanding doctoral dissertations in Bayesian econometrics and statistics. Consider again the randomized controlled Phase II trial example. On the other hand, future Bayesian designs and methods could incorporate repeated trials into multiplicity adjustment. This modeling setup initially appears to be overly simplified. More complex and powerful models may replace N(μ, τ2) with a finite or infinite mixture distribution to induce a cluster-like structure. In effect, the estimated mean response for the current control arm is shrunk toward the overall mean μ across all studies. Any clinical trial includes risks, which the study doctor will review with you. CenterWatch. A popular choice of primary endpoint for exploratory cancer studies is the objective response rate (ORR), which can be observed relatively soon after treatment. Abdominal Cancer 42 total 8 updated In particular, Bayesian methods are ideal for “unplanned” interim looks, borrowing prior information, and calibrated posterior inference based on skeptical priors, which could potentially bridge the needs to use as much fragmented information from COVID-era trials and the desire to maintain statistical rigor, whether Bayesian or frequentist. Any new processes need to be painstakingly assessed to ensure that replacing tried and tested processes doesn’t result in any new risks. For example, Phase I/II seamless designs allow a Phase I dose-finding trial and a Phase II trial to be included in a single protocol, while Phase II/III designs combine Phase II and Phase III trials. Data … George Clinical is a leading provider of oncology trial, scientific, and operational solutions throughout the Asia-Pacific, USA and Europe. The 3+3 design. With a continuous response variable, the regression model has the form: The regression coefficient η reflects subgroup effects, and testing “whether there is a subgroup effect” is equivalent to testing “whether η = 0“. Dose-finding studies aim to identify a safe and efficacious dose of a new medical product. For example, it may be of interest to explore whether a new treatment is effective in a particular subgroup of patients, given that the treatment is shown to be ineffective in the overall population through a randomized controlled trial. However, it is a great opportunity to revisit Bayesian adaptive designs that use accumulated data and posterior probabilities for interim and final decision making for clinical trials. A treatment arm would be dropped early (or be graduated), if this probability is low for all signatures (or is sufficiently high for some signatures) (see Figure 4(b)). π (α|data) ∝ π0(α) ∙ ΠDd=1 {π (d, α)nd [1 − ψ (d, α)]md}. This organizationprovides information on clinical trials. The mTPI design uses simple Bayesian hierarchical models to achieve two goals: (1) maintaining desirable frequentist operating characteristics of the design, and (2) providing a user-friendly implementation for clinicians. The premise is that efficacy and toxicity increase with dose levels, and therefore, the MTD is the dose that can be well-tolerated and has the best chance of inducing anti-disease response among patients. Complete blinding is needed to reduce potential bias if the trial is not stopped during interim analyses. Otherwise, it is impossible to make a Type I error for that trial and that decision. Priors can be constructed to favor parsimonious models. The mTPI design. *Napabucasin is also known as BBI-608. At each interim analysis, each treatment’s posterior predictive probability of success in a Phase III confirmatory trial is calculated for each molecular signature. American Oncology Partner practices bring innovative treatment options to patients, close to home. Since the same drug is tested, it is commonly assumed that the treatment effect of the drug in a certain basket can provide information about the treatment effects in other baskets. The introduction of the continual reassessment method (CRM) in 1990 pioneered model-based designs for dose-finding trials. In the future, trials are expected to become more adaptive, embracing modern computing power and adaptive decision-making. It includes a data… In the case of Phase I/II seamless design, such decisions graduate promising doses from Phase I to Phase II for further evaluation. As a member of US Oncology Research, we have access to cutting-edge and innovative research trials. The CRM design. Falls Church, VA 22046, USA, Phone: 617.948.5100 In addition, the rules are clinically derived with clear logic, such as escalating the dose if no DLT is observed or deescalating the dose if excessive DLT is seen. Develop your novel agents and companion diagnostics using comprehensive preclinical models and biomarker identification strategies. In oncology clinical trials, many different endpoints can be used as primary or secondary endpoints. By placing priors on μ and τ, these parameters can be estimated from the data. While Bayesian methods are appealing in the design and analysis of clinical trials, they have their own caveats. Use of Historical Control Data for Assessing Treatment Effects in Clinical Trials. Figure 3. To identify the MTD through a clinical trial, a grid of discrete dose levels is usually pre-specified, and an ethical and efficient statistical design assigns patients sequentially and in cohorts to different doses. Patients will always receive treatment on a clinical trial if an approved treatment already exists. The I-SPY 2 trial (Figure 4(b)) is a prominent example of a platform trial, which evaluates multiple neoadjuvant treatments for high-risk breast cancer. Certificate Program in Oncology Clinical Trials (CPOCT) This online & self-paced certificate course will provide you comprehensive training to coordinate, manage, and monitor oncology clinical trials in compliance with ICH-GCP and applicable regulatory guidelines. Types of clinical trials. To be specific, suppose a new patient with molecular signature x̃ is eligible for enrollment, and let q̃t denote the probability of response for this patient under treatment t, t∈{1,…,T}. Motivated by these challenges, a new class of designs was developed. On the other hand, a cancer (sub)type may harbor different aberrations that may be targeted by various therapeutics. 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