Different Role of PET-CT Evaluation in Newly Diagnosed Follicular Lymphoma Upon Rituximab-Based Chemotherapy and Chemo-Free Immunotherapy.

Newly diagnosed follicular lymphoma (FL) patients usually received first-line rituximab-based immunochemotherapy (R-chemo). Recently, rituximab plus lenalidomide (R2) emerged as an alternative chemo-free immunotherapy. We performed a comparative analysis of positron emission tomography/computed tomography (PET/CT) in FL undergoing R-chemo or R2.

A Bayesian latent-subgroup platform design for dose optimization.

The US Food and Drug Administration launched Project Optimus to reform the dose optimization and dose selection paradigm in oncology drug development, calling for the paradigm shift from finding the maximum tolerated dose to the identification of optimal biological dose (OBD). Motivated by a real-world drug development program, we propose a master-protocol-based platform trial design to simultaneously identify OBDs of a new drug, combined with standards of care or other novel agents, in multiple indications. We propose a Bayesian latent subgroup model to accommodate the treatment heterogeneity across indications, and employ Bayesian hierarchical models to borrow information within subgroups.

Issues and Solutions in Psychiatric Clinical Trial with Case Studies.

The coronavirus disease-2019 pandemic resulted in a major increase in depression and anxiety disorders worldwide, which increased the demand for mental health services. However, clinical interventions for treating mental disorders are currently insufficient to meet this growing demand. There is an urgent need to conduct scientific and standardized clinical research that are consistent with the features of mental disorders in order to deliver more effective and safer therapies in the clinic.

Biological signatures of the International Prognostic Index in diffuse large B-cell lymphoma.

Diffuse large B-cell lymphoma (DLBCL) is a highly aggressive subtype of lymphoma with clinical and biological heterogeneity. The International Prognostic Index (IPI) shows great prognostic capability in the era of rituximab, but the biological signatures of IPI remain to be discovered. In this study, we analyzed the clinical data in a large cohort of 2592 patients with newly diagnosed DLBCL.

Positron emission tomography-adapted therapy in low-risk diffuse large B-cell lymphoma: results of a randomized, phase III, non-inferiority trial.

Background: The current standard of care for non-bulky diffuse large B-cell lymphoma (DLBCL) patients with an International Prognostic Index (IPI) of 0 is four cycles of rituximab plus cyclophosphamide, doxorubicin, vincristine and prednisone (R-CHOP) but whether the same efficacy can be achieved with reduced chemotherapy regimen of four cycles for non-bulky DLBCL patients with an IPI of 1 remains unclear. This study compared four cycles versus six cycles of chemotherapy in non-bulky low-risk DLBCL patients with negative interim positron emission tomography with computed tomography (PET-CT, Deauville 1-3), irrespective of age and other IPI risk factors (IPI 0-1).

Methods: This was an open-label, randomized, phase III, non-inferiority trial.

A dose-finding design for phase I clinical trials based on Bayesian stochastic approximation.

Background: Current dose-finding designs for phase I clinical trials can correctly select the MTD in a range of 30-80% depending on various conditions based on a sample of 30 subjects. However, there is still an unmet need for efficiency and cost saving.

Methods: We propose a novel dose-finding design based on Bayesian stochastic approximation.

An adaptive gBOIN design with shrinkage boundaries for phase I dose-finding trials.

Background: With the emergence of molecularly targeted agents and immunotherapies, the landscape of phase I trials in oncology has been changed. Though these new therapeutic agents are very likely induce multiple low- or moderate-grade toxicities instead of DLT, most of the existing phase I trial designs account for the binary toxicity outcomes. Motivated by a pediatric phase I trial of solid tumor with a continuous outcome, we propose an adaptive generalized Bayesian optimal interval design with shrinkage boundaries, gBOINS, which can account for continuous, toxicity grades endpoints and regard the conventional binary endpoint as a special case.

A Bayesian phase I/II platform design for co-developing drug combination therapies for multiple indications.

There is a growing trend to combine a new targeted or immunotherapy agent with the cancer-specific standard of care to treat different types of cancers. We propose a master-protocol-based, Bayesian phase I/II platform design to co-develop combination (BPCC) therapies in multiple indications. Under the BPCC design, only a single master protocol is needed, and the combined drug is evaluated in different indications in a concurrent or staggered fashion.

A two-stage Bayesian adaptive design for minimum effective dose (MinED)-based dosing-finding trials.

Conventional phase I designs for finding a phase II recommended dose (P2RD) based on toxicity alone is problematic because the maximum tolerated dose (MTD) is not necessarily the optimal dose. Instead, recently attention has been given to find the minimum effective dose (MinED) - defined as the lowest effective dose. Traditional paradigms for the MinED studies are conducted as dose-ranging or dose-response trials which involve several doses and randomize patients among doses to find the MinED.

A Bayesian adaptive design for biosimilar trials with time-to-event endpoint.

A biosimilar drug is a biological product that is highly similar to and at the same time has no clinically meaningful difference from licensed product in terms of safety, purity, and potency. Biosimilar study design is essential to demonstrate the equivalence between biosimilar drug and reference product. However, existing designs and assessment methods are primarily based on binary and continuous endpoints.

A Bayesian adaptive phase I/II platform trial design for pediatric immunotherapy trials.

Immunotherapy is the most promising new cancer treatment for various pediatric tumors and has resulted in an unprecedented surge in the number of novel immunotherapeutic treatments that need to be evaluated in clinical trials. Most phase I/II trial designs have been developed for evaluating only one candidate treatment at a time, and are thus not optimal for this task. To address these issues, we propose a Bayesian phase I/II platform trial design, which accounts for the unique features of immunotherapy, thereby allowing investigators to continuously screen a large number of immunotherapeutic treatments in an efficient and seamless manner.

Predicting events in clinical trials using two time-to-event outcomes.

In clinical trials with time-to-event outcomes, it is of interest to predict when a prespecified number of events can be reached. Interim analysis is conducted to estimate the underlying survival function. When another correlated time-to-event endpoint is available, both outcome variables can be used to improve estimation efficiency.