One can model: This model specification shrinks the adjusted response rates in different baskets toward a common value thus borrows strength across baskets. To illustrate the construction of an informative prior, recycle the notation θ and let it denote the parameter of interest of the control arm of the current study. Before any new treatment is used with people in clinical trials, researchers work for many years to understand its effects on cancer cells in the lab and in animals. NEW YORK--(BUSINESS WIRE)-- Massive Bio, Inc., a leader in precision medicine and artificial intelligence (AI)-enabled patient-centric oncology clinical trial Suppose, more generally, J historical studies are available (J can be 1). He led a publication in Nature Methods and invention of a tool called TCGA-Assembler, which has been downloaded more than 10,000 times worldwide. For the former, one can use flexible models to capture the relationship among Y, T, and X, e.g., E(Y|θ) = ⨍(T, X, θ), where ⨍ is a Bayesian additive regression tree model, and θ denotes additional parameters. Efficacy is typically evaluated based on outcomes that can be measured in a relatively short amount of time after treatment, such as tumor shrinkage. With a continuous response variable, the tree model may be constructed as: E(Y|) = Σm=1 [βm ∙ 1(X ∈ m) + ηm ∙ T ∙ 1(X∈ m)]. The posterior distributions reflect the renewed knowledge about trial parameters (e.g., treatment effects) and are used for decision-making in clinical trials. Therefore, although the CRM design has many desirable statistical properties in principle, it has not been able to overtake simple designs like the 3+3 in practice. The exploratory trial enrolls patients from a broad population with the goal of finding promising subgroups, and the confirmatory trial aims to establish health benefits with rigorous control of statistical error in the identified subgroups. At each interim analysis, one can stop accrual for basket j early if Pr(θj > θ0j | data) < pF, where pF is a pre-specified futility stopping threshold, e.g., 0.05. Otherwise, it is impossible to make a Type I error for that trial and that decision. Clinical Trials in Oncology The following medical conditions affect the medical, surgical and radiation treatment of tumors, cancerous especially. Figure 3(a) shows this posterior density with different choices of α. Hierarchical Models. This often creates added complexity and potential errors in practice. It is an exciting era to be a trialist, due to the explosive innovation in the development of novel trial designs. A Phase I trial investigates the safety profile of the drug and finds an appropriate dose level for further testing. Prior elicitation requires subject-matter expertise and good understanding of the probability model. When α = 1, πPP(∙) corresponds to the posterior distribution of θ from the previous study; when α = 0, πPP(∙) reduces to the initial prior and does not involve the historical data. Figure 4. Nugent, C., Guo, W., Müller, P., and Ji, Y. For example, platform trials usually use response-adaptive randomization, so that better-performing treatments within a specific molecular signature would be preferentially assigned within that signature and will progress through the trial more rapidly. Figure 2: (a) Spiral evolution of dose-finding designs (1989—2019). CenterWatch. This feature is crucial in helping resolve some challenges for COVID-era trials, in which unplanned interim analyses may be needed due to the pandemic. Starting from a Beta(1, 1) prior on the control ORR before the historical study, the power α prior is Beta(1 + 4 ∙ α, 1 + 6 ∙ α), which can be used as an informative prior for the current control arm. Since these trials are concerned with multiple treatments in a heterogeneous patient population, methods for subgroup analysis also apply to the design and analysis of these trials. In other words, statistical modeling seems unnecessary for dose-finding designs to generate desirable frequentist’s operating characteristics. The CRM design. As an example, consider a randomized controlled Phase II trial with the primary endpoint being the overall response rate (ORR). This increases the burden of using Bayesian methods in clinical trials. A new oncology drug usually goes through three phases of clinical trials before it can be approved by regulatory agencies as a commercial product. 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. There is a lot to consider when deciding whether to participate in a clinical trial. 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 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. Introduction– Christian Dittrich Under-reporting of harm in clinical trials– Alberto Ocana Fernandez Unplanned versus pre-specified subgroup analysis reporting– Doug Altman Quality of meta-analyses and why they sometimes lead to different conclusions– Jean-Pierre Pignon Early reporting of efficacy endpoints and its potential impact: Biostatistical part– Jan Bogaerts Early reporting of efficacy endpoints and its potential impact: Clinical part– Fatima Cardoso Conclusions– Denis Lacombe His research interests include clinical trial designs, statistical genomics, missing data, and infectious diseases. Guidance in the new ICH E9(R1) could be helpful to alleviate some issues from the frequentist point of view. 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. Ji is the author of more than 140 publications in peer-reviewed medical and statistical journals, conference papers, book chapters, and abstracts. However, it is also true that θ̃d is simply the observed toxicity rate at dose level d, free from any statistical model. This will help reduce the approval of potentially ineffective drugs that have failed in multiple prior trials but with positive results in a new confirmatory trial (e.g., the recent Alzheimer’s disease trials). 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. With recent advances in genomics, molecular engineering, and immunology, the paradigm of cancer treatment is shifting from “one size fits all” (e.g., cytotoxic chemotherapy) to targeted and precision therapies that aim to correct specific molecular or immune aberrations. Register as a volunteer and receive email notifications for clinical trials relevant to you. 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. 2018. The mTPI design. Pharmaceutical industry is developing new targeted agents generating many clinical studies, including target combinations. With over 20 years of experience in clinical development, Treximo is your partner of choice for Project Management. 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. If the null is not rejected, there is no Type I error and the Type I error rate is zero. In practice, the weight α may be pre-specified by the investigator or estimated from the observed data. These consider multiple treatments in a single cancer (sub)type and typically include a common control arm. It includes a data… Motivated by these challenges, a new class of designs was developed. These decisions may cause severe and costly public health and economic setbacks for society and drug developers. The resources in this section address this disparity and suggest ways to improve clinical trial design to increase the participation of older adults with cancer and generate more research on their needs and potential therapies. Seamless designs allow two or more trials in different phases to be conducted within the same study. Please note that if you select one of these websites, you will leave Cancer.Net. He is the inventor of many innovative Bayesian adaptive designs, such as the mTPI and i3+3 designs, which have been widely applied in dose-finding clinical trials worldwide, including trials published in Lancet Oncology, JAMA Oncology, and JCO. 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. The power prior approach is a commonly used method to construct an informative prior for θ. The mTPI design assigns independent uniform priors on θ‘d s. After DLT data are accumulated, the posterior distribution of θd is also independent given by. Next, denote the historical data by yH, and let π0(θ) denote the initial prior distribution for θ before the historical data are observed, e.g., a non-informative prior. Consider a binary tree with each internal node corresponding to a splitting rule of a covariate Xk. There are two main Bayesian methods for incorporating historical data. 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. Basket trials. Who can take part in a clinical trial . The type of cancer Tyler was treated for and her outcome made her an ideal candidate for a clinical trial at Lexington Oncology. Dose-finding studies aim to identify a safe and efficacious dose of a new medical product. Because the posterior distributions of the DLT probabilities at different dose levels are independent of each other, all the dose assignment decisions can be pre-calculated in a two-way table, which makes it easy for non-statisticians to design and conduct Phase I clinical trials. At the end of the trial, a dose is selected as the MTD, which is defined as the highest dose with DLT probability no more than a pre-specified target θT. Click on a condition below to find clinical trials actively recruiting research study volunteers in your area. For the latter, one can introduce a utility function u(S, θ) for the action of reporting a certain subgroup S, which usually has a preference for a large effect size, a large subgroup size, and a parsimonious description of the subgroup. Through oncology CME and CE, oncologists and other healthcare providers can stay up to date with all of the latest breakthroughs in novel therapies and multidisciplinary strategies that are improving outcomes for patients. 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. Clinical trials are vital for doctors to understand how to identify and manage side effects. Conventionally, cancers are categorized based on the anatomic location of the primary tumor (e.g., breast, lung), and clinical trials in oncology are conducted to evaluate a single treatment in a certain cancer type. The mTPI design and a later variation called the mTPI-2 design have been widely applied in oncology Phase I trials (e.g., the KEYNOTE-029 trial), due to their simplicity and good performance. Oncology clinical trials provide patients the opportunity for a better outcome and quality of life, while playing a vital role in the fight against cancer. However, practical restrictions and strong emphasis on patient safety may cancel out the benefits of borrowing information, which is observed in subsequent methodology development. Basket trials are usually planned with a pre-specified number of interim analyses. Due to random error and sampling noise in the trial data, statistical inference is always associated with the risk of Type I errors. Assume the prior distribution of α is π0(α). The introduction of the continual reassessment method (CRM) in 1990 pioneered model-based designs for dose-finding trials. A new oncology drug usually goes through three phases of clinical trials before it can be approved by regulatory agencies as a commercial product. Yuan Ji is a professor of biostatistics at the University of Chicago and an NIH-funded PI focusing on innovative computational and statistical methods for translational cancer research. Here, ηm represents the treatment effect within subspace m (subgroup m), and the difference in ηm reflects subgroup effects. When the number of historical studies is small (e.g., J = 1), the estimation of τ can be sensitive to the prior specification. Both designs use a point estimate, θ̃d = nd / (nd + md), to conduct statistical inference. Subgroup-driven drug development usually consists of an exploratory trial and a confirmatory trial. Geriatric patients with cancer are underrepresented in oncology clinical trials for many reasons—yet this population has a high cancer burden. Under the Bayesian framework, prior distributions are specified for relevant parameters in a probability model. In a basket trial, the substudies are typically conducted in a single-arm fashion without concurrent controls. was proposed as a design that abandons any models and returns to rule-based inference, but with smarter rules. The exploratory trial may also use response-adaptive randomization with a preference to allocate patients to the treatment arms from which they may be more likely to benefit. This may, at least in part, reflect the high regulatory overhead in drug development, particularly in oncology trials. Advances in cancer treatment have provided longer survival outcomes, particularly in … First, the choice of the prior distribution has an impact on posterior inference. Let θd denote the probability of DLT at dose d. The CRM models θd with a parametric curve, θd = Ψ (d, α), where Ψ is a parametric function of dose level d and depends on parameters α. Impact of COVID-19. They also try to figure out the side effects it may cause. Different investigators might provide different priors that lead to different posterior inference, and thus sensitivity analysis is recommended to examine whether the conclusion would substantially differ under various prior specifications. Motivated by this observation, the i3+3 design (Liu, et al. Novel treatments based on molecular and immune markers and novel platform trial designs open new doors for Bayesian modeling and philosophy. Complete blinding is needed to reduce potential bias if the trial is not stopped during interim analyses. By placing priors on μ and τ, these parameters can be estimated from the data. In these settings, Bayesian designs could help enforce multiplicity control and limit the probability of making a wrong approval due to chance. Specifically, the power prior distribution for θ is defined as: where α∈[0, 1] controls the weight of the historical data. Bayesian Approaches to Subgroup Analysis and Related Adaptive Clinical Trial Designs. 2014. This article focuses on early-phase trials—Phase I and Phase II—with an emphasis on Bayesian methods. On the other hand, future Bayesian designs and methods could incorporate repeated trials into multiplicity adjustment. The Alliance for Clinical Trials in Oncology seeks to reduce the impact of cancer by uniting a broad community of scientists and clinicians who are committed to the prevention and treatment of cancer. The vast majority of dose-finding trials seek the maximum tolerated dose (MTD), which is believed to be the optimal dose that has the best therapeutic effects among all the safe doses. Complex immuno-oncology drug development requires innovation, commitment and expertise. 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. 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. Subgroup analysis can be carried out to inform the design and decision-making of clinical trials. 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). The power prior can be generalized if multiple historical datasets are available. For example, whenever a null hypothesis in a clinical trial is rejected, e.g., a new drug is approved for public use, such approval is associated with a (ideally small) error probability. The BATTLE trial, as an umbrella trial, highlights the potential of combining different targeted treatments for a single cancer type: lung cancer. What clinical trials are. This advancement completes the spiral evolution (Figure 2(a)) of the development of Phase I trial designs in the past three decades, shown as: Rules → Complex Models → Simplified Models → Smart Rules. After the trial completes, the rule for declaring efficacy in basket j can be based on Pr(θj > θ0j | data) > pE, where pE is a prespecified probability threshold for efficacy, e.g., 0.95. The Alliance has been awarded a grant by the National Cancer Institute (NCI) as a member of the NCI National Clinical Trials Network (NCTN). 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“. 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. At Shenandoah Oncology, clinical trials are an integral part of our commitment to providing comprehensive cancer care to our patients in Virginia, West Virginia and Maryland. Conversely, once the rejection of the null hypothesis is made, the trial is usually stopped and no more decisions will be made. A dose-finding design consists of a set of decision rules through which patient enrollments and dose escalations are conducted. At each interim analysis, each treatment’s posterior predictive probability of success in a Phase III confirmatory trial is calculated for each molecular signature. A Phase I trial investigates the safety profile of the drug and finds an appropriate dose level for further testing. Clinical trials are the final step in a long process that begins with research in a lab. Bayesian adaptive designs and methods use posterior distributions and Bayesian inference to make adaptive decisions that may alter the course of a clinical trial. See Table 1 for three examples. 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