Escalation with Overdose Control is More Efficient and Safer than Accelerated Titration for Dose Finding

Bayesian dose escalation with overdose and underdose control utilizing all toxicities in Phase I/II clinical trials

Escalation with overdose control (EWOC) is a commonly used Bayesian adaptive design, which controls overdosing risk while estimating maximum tolerated dose (MTD) in cancer Phase I clinical trials. In 2010, Chen and his colleagues proposed a novel toxicity scoring system to fully utilize patients' toxicity information by using a normalized equivalent toxicity score (NETS) in the range 0 to 1 instead of a binary indicator of dose limiting toxicity (DLT). Later in 2015, by adding underdosing control into EWOC, escalation with overdose and underdose control (EWOUC) design was proposed to guarantee patients the minimum therapeutic effect of drug in Phase I/II clinical trials. In this paper, the EWOUC-NETS design is developed by integrating the advantages of EWOUC and NETS in a Bayesian context. Moreover, both toxicity response and efficacy are treated as continuous variables to maximize trial efficiency. The dose escalation decision is based on the posterior distribution of both toxicity and efficacy outcomes, which are recursively updated with accumulated data. We compare the operation characteristics of EWOUC-NETS and existing methods through simulation studies under five scenarios. The study results show that EWOUC-NETS design treating toxicity and efficacy outcomes as continuous variables can increase accuracy in identifying the optimized utility dose (OUD) and provide better therapeutic effects.

Safety and efficacy of a COVID-19 treatment with nebulized and/or intravenous neutral electrolyzed saline combined with usual medical care vs. usual medical care alone: A randomized, open-label, controlled trial

Coronavirus disease 2019 (COVID-19) is currently the major public health problem worldwide. Neutral electrolyzed saline solution that contains reactive chlorine and oxygen species may be an effective therapeutic. In the present study, the treatment efficacy of intravenous and/or nebulized neutral electrolyzed saline combined with usual medical care vs. usual medical care alone was evaluated in ambulatory patients with COVID-19. A prospective, 2-arm, parallel-group, randomized, open-label, multi-center, phase I-II clinical trial including 214 patients was performed. The following two outcomes were evaluated during the 20-day follow-up: i) The number of patients with disease progression; and ii) the patient acceptable symptom state. Serial severe acute respiratory syndrome coronavirus 2 naso/oro-pharyngeal detection by reverse transcription-quantitative (RT-q) PCR was performed in certain patients of the experimental group. Biochemical and hematologic parameters, as well as adverse effects, were also evaluated in the experimental group. The experimental treatment decreased the risk of hospitalization by 89% [adjusted relative risk (RR)=0.11, 95% confidence interval (CI): 0.03-0.37, P<0.001] and the risk of death by 96% (adjusted RR=0.04, 95% CI: 0.01-0.42, P=0.007) and also resulted in an 18-fold higher probability of achieving an acceptable symptom state on day 5 (adjusted RR=18.14, 95% CI: 7.29-45.09, P<0.001), compared with usual medical care alone. Overall, neutral electrolyzed saline solution was better than usual medical care alone. Of the patients analyzed, >50% were negative for the virus as detected by RT-qPCR in naso/oro-pharyngeal samples on day 4, with only a small number of positive patients on day 6. Clinical improvement correlated with a decrease in C-reactive protein, aberrant monocytes and increased lymphocytes and platelets. Cortisol and testosterone levels were also evaluated and a decrease in cortisol levels and an increase in the testosterone-cortisol ratio were observed on days 2 and 4. The experimental treatment produced no serious adverse effects. In conclusion, neutral electrolyzed saline solution markedly reduced the symptomatology and risk of progression in ambulatory patients with COVID-19. The present clinical trial was registered in the Cuban public registry of clinical trials (RPCEC) database (May 5, 2020; no. TX-COVID19: RPCEC00000309).

Moving Beyond 3+3: The Future of Clinical Trial Design

Misgivings have been raised about the operating characteristics of the canonical 3+3 dose-escalation phase I clinical trial design. Yet, the traditional 3+3 design is still the most commonly used. Although it has been implied that adhering to this design is due to a stubborn reluctance to adopt change despite other designs performing better in hypothetical computer-generated simulation models, the continued adherence to 3+3 dose-escalation phase I strategies is more likely because these designs perform the best in the real world, pinpointing the correct dose and important side effects with an acceptable degree of precision. Beyond statistical simulations, there are little data to refute the supposed shortcomings ascribed to the 3+3 method. Even so, to address the unique nuances of gene- and immune-targeted compounds, a variety of inventive phase 1 trial designs have been suggested. Strategies for developing these therapies have launched first-in-human studies devised to acquire a breadth of patient data that far exceed the size of a typical phase I design and blur the distinction between dose selection and efficacy evaluation. Recent phase I trials of promising cancer therapies assessed objective tumor response and durability at various doses and schedules as well as incorporated multiple expansion cohorts spanning a variety of histology or biomarker-defined tumor subtypes, sometimes resulting in U.S. Food and Drug Administration approval after phase I. This article reviews recent innovations in phase I design from the perspective of multiple stakeholders and provides recommendations for future trials.

Practical considerations for the implementation of adaptive designs for oncology Phase I dose-finding trials

The traditional 3 + 3 design continues to be commonly used for Phase I dose-finding oncology trials, despite increasing criticisms and development of innovative methods. Unfortunately, it is a challenge to convince principal investigators to use novel designs. The goal of this paper is to persuade researchers to break away from 3 + 3 design and provide potential solutions to better designs and implementation strategy. We reviewed the statistical methods for adaptive Phase I designs. The barriers among all the major components of the implementation team have been emphasized and potential solutions have been discussed. Institutional support to the principal investigators and statistician, as well as to other team members is essential to design and implement adaptive trials in academic medical institutions.

A Bayesian adaptive design for cancer phase I trials using a flexible range of doses

We present a Bayesian adaptive design for dose finding in cancer phase I clinical trials. The goal is to estimate the maximum tolerated dose (MTD) after possible modification of the dose range during the trial. Parametric models are used to describe the relationship between the dose and the probability of dose-limiting toxicity (DLT). We investigate model reparameterization in terms of the probabilities of DLT at the minimum and maximum available doses at the start of the trial. Trial design proceeds using escalation with overdose control (EWOC), where at each stage of the trial we seek the dose of the agent such that the posterior probability of exceeding the MTD of this agent is bounded by a feasibility bound. At any time during the trial, we test whether the MTD is below or above the minimum and maximum doses, respectively. If during the trial there is evidence that the MTD is outside the range of doses, we extend the range of doses and complete the trial with the planned sample size. At the end of the trial, a Bayes estimate of the MTD is proposed. We evaluate design operating characteristics in terms of safety of the trial design and efficiency of the MTD estimate under various scenarios and model misspecification. The methodology is further compared to the original EWOC design. We showed by comprehensive simulation studies that the proposed method is safe and can estimate the MTD more efficiently than the original EWOC design.