基于药物毒性反应等级的Up-and-Down设计

Ⅰ期临床试验主要关心毒性,通常划分毒性为五个水平．简单起见,同时兼顾伦理问题,Ⅰ期临床试验通常采用up-and-down序贯设计(例如BCDⅠ,BCDⅡ,K-in-a-row,Narayana,Improved Narayana)．然而,在分配剂量水平时,该设计没有区分已经试验了的病人的严重毒性水平等级,从而有可能分配给病人更高毒性的剂量水平．因此,本文提出了基于药物毒性等级确定最大耐受剂量的up-and-down设计方法,并进一步研究了该设计方法在各种变化的剂量—毒性关系下的运作特征,并且和标准的up-and-down设计作模拟比较,结果表明该设计方法对Ⅰ期临床试验设计的剂量建议具有重要意义．     

Dose-finding based on feasibility and toxicity in T-cell infusion trials

A new modality for treatment of cancer involves the ex vivo growth of cancer-specific T-cells for subsequent infusion into the patient. The therapeutic aim is selective destruction of cancer cells by the activated infused cells. An important problem in the early phase of developing such a treatment is to determine a maximal tolerated dose (MTD) for use in a subsequent phase II clinical trial. Dose may be quantified by the number of cells infused per unit body weight, and determination of an MTD may be based on the probability of infusional toxicity as a function of dose. As in a phase I trial of a new chemotherapeutic agent, this may be done by treating successive cohorts of patients at different dose levels, with each new level chosen adaptively based on the toxicity data of the patients previously treated. Such a dose-finding strategy is inadequate in T-cell infusion trials because the number of cells grown ex vivo for a given patient may be insufficient for infusing the patient at the current targeted dose. To address this problem, we propose an algorithm for trial conduct that determines a feasible MTD based on the probabilities of both infusibility and toxicity as functions of dose. The method is illustrated by application to a dendritic cell activated lymphocyte infusion trial in the treatment of acute leukemia. A simulation study indicates that the proposed methodology is both safe and reliable.     

A Bayesian approach to jointly modeling toxicity and biomarker expression in a phase I/II dose-finding trial

In this article, we propose a Bayesian approach to phase I/II dose-finding oncology trials by jointly modeling a binary toxicity outcome and a continuous biomarker expression outcome. We apply our method to a clinical trial of a new gene therapy for bladder cancer patients. In this trial, the biomarker expression indicates biological activity of the new therapy. For ethical reasons, the trial is conducted sequentially, with the dose for each successive patient chosen using both toxicity and activity data from patients previously treated in the trial. The modeling framework that we use naturally incorporates correlation between the binary toxicity and continuous activity outcome via a latent Gaussian variable. The dose-escalation/de-escalation decision rules are based on the posterior distributions of both toxicity and activity. A flexible state-space model is used to relate the activity outcome and dose. Extensive simulation studies show that the design reliably chooses the preferred dose using both toxicity and expression outcomes under various clinical scenarios.     

基于药物毒性反应等级的up-and-down自适应设计

Ⅰ期临床试验主要关心药物的毒性,目的是在给定的剂量水平中寻找最大耐受剂量（MTD）．本文提出了基于药物毒性反应等级的up-and-down自适应设计,调查了该设计在各种变化的剂量一毒性关系下的运作特征．结果表明：该设计方法对提高建议MTD的精确度,以及保护病人,防止病人暴露在较高毒性剂量下方面,对Ⅰ期临床试验的设计实现了有意义的改善．     

Continual reassessment method for partial ordering

Summary Much of the statistical methodology underlying the experimental design of phase 1 trials in oncology is intended for studies involving a single cytotoxic agent. The goal of these studies is to estimate the maximally tolerated dose, the highest dose that can be administered with an acceptable level of toxicity. A fundamental assumption of these methods is monotonicity of the dose–toxicity curve. This is a reasonable assumption for single‐agent trials in which the administration of greater doses of the agent can be expected to produce dose‐limiting toxicities in increasing proportions of patients. When studying multiple agents, the assumption may not hold because the ordering of the toxicity probabilities could possibly be unknown for several of the available drug combinations. At the same time, some of the orderings are known and so we describe the whole situation as that of a partial ordering. In this article, we propose a new two‐dimensional dose‐finding method for multiple‐agent trials that simplifies to the continual reassessment method (CRM), introduced by O'Quigley, Pepe, and Fisher (1990, Biometrics 46 , 33–48), when the ordering is fully known. This design enables us to relax the assumption of a monotonic dose–toxicity curve. We compare our approach and some simulation results to a CRM design in which the ordering is known as well as to other suggestions for partial orders.     

Engineering Anthrax Toxin Variants That Exclusively Form Octamers and Their Application to Targeting Tumors

Anthrax toxin protective antigen (PA) delivers its effector proteins into the host cell cytosol through formation of an oligomeric pore, which can assume heptameric or octameric states. By screening a highly directed library of PA mutants, we identified variants that complement each other to exclusively form octamers. These PA variants were individually nontoxic and demonstrated toxicity only when combined with their complementary partner. We then engineered requirements for activation by matrix metalloproteases and urokinase plasminogen activator into two of these variants. The resulting therapeutic toxin specifically targeted cells expressing both tumor associated proteases and completely stopped tumor growth in mice when used at a dose far below that which caused toxicity. This scheme for obtaining intercomplementing subunits can be employed with other oligomeric proteins and potentially has wide application.     

A two-stage stepwise estimation procedure

Summary .   This article proposes a two-stage simultaneous confidence procedure for the comparisons of k pairs of population means, without using multiplicity adjustment of more than two populations. The proposed procedure can be broadly applied to parametric or nonparametric models. It is robust and versatile because its derivation only utilizes a partitioning approach in conjunction with a bivariate adjustment, without any assumption on the underlying distribution. To elucidate the application, the proposed procedure is intertwined with the estimation of the therapeutic window of a drug. It provides confidence limits for the efficacy and the toxicity of the effective doses, highest ineffective dose, safe doses, and lowest unsafe dose, simultaneously. Such estimation information facilitates follow-up studies in clinical trials. As an illustrative example, the new procedure is applied to analyze a data set on molecular cancer therapeutics regarding the apoptotic killing effects of different chemical compounds on two leukemia cell lines.     

A utility approach to individualized optimal dose selection using biomarkers

In many settings, including oncology, increasing the dose of treatment results in both increased efficacy and toxicity. With the increasing availability of validated biomarkers and prediction models, there is the potential for individualized dosing based on patient specific factors. We consider the setting where there is an existing dataset of patients treated with heterogenous doses and including binary efficacy and toxicity outcomes and patient factors such as clinical features and biomarkers. The goal is to analyze the data to estimate an optimal dose for each (future) patient based on their clinical features and biomarkers. We propose an optimal individualized dose finding rule by maximizing utility functions for individual patients while limiting the rate of toxicity. The utility is defined as a weighted combination of efficacy and toxicity probabilities. This approach maximizes overall efficacy at a prespecified constraint on overall toxicity. We model the binary efficacy and toxicity outcomes using logistic regression with dose, biomarkers and dose–biomarker interactions. To incorporate the large number of potential parameters, we use the LASSO method. We additionally constrain the dose effect to be non-negative for both efficacy and toxicity for all patients. Simulation studies show that the utility approach combined with any of the modeling methods can improve efficacy without increasing toxicity relative to fixed dosing. The proposed methods are illustrated using a dataset of patients with lung cancer treated with radiation therapy.     

Informed consent in human experimentation before the Nuremberg code.

The issue of ethics with respect to medical experimentation in Germany during the 1930s and 1940s was crucial at the Nuremberg trials and related trials of doctors and public health officials. Those involved in horrible crimes attempted to excuse themselves by arguing that there were no explicit rules governing medical research on human beings in Germany during the period and that research practices in Germany were not different from those in allied countries. In this context the Nuremberg code of 1947 is generally regarded as the first document to set out ethical regulations in human experimentation based on informed consent. New research, however, indicates that ethical issues of informed consent in guidelines for human experimentation were recognised as early as the nineteenth century. These guidelines shed light on the still contentious issue of when the concepts of autonomy, informed consent, and therapeutic and non-therapeutic research first emerged. This issue assumes renewed importance in the context of current attempts to assess liability and responsibility for the abuse of people in various experiments conducted since the second world war in the United States, Canada, Russia, and other nations.     

A flexible design for advanced Phase I/II clinical trials with continuous efficacy endpoints

There is growing interest in integrated Phase I/II oncology clinical trials involving molecularly targeted agents (MTA). One of the main challenges of these trials are nontrivial dose–efficacy relationships and administration of MTAs in combination with other agents. While some designs were recently proposed for such Phase I/II trials, the majority of them consider the case of binary toxicity and efficacy endpoints only. At the same time, a continuous efficacy endpoint can carry more information about the agent's mechanism of action, but corresponding designs have received very limited attention in the literature. In this work, an extension of a recently developed information‐theoretic design for the case of a continuous efficacy endpoint is proposed. The design transforms the continuous outcome using the logistic transformation and uses an information–theoretic argument to govern selection during the trial. The performance of the design is investigated in settings of single‐agent and dual‐agent trials. It is found that the novel design leads to substantial improvements in operating characteristics compared to a model‐based alternative under scenarios with nonmonotonic dose/combination–efficacy relationships. The robustness of the design to missing/delayed efficacy responses and to the correlation in toxicity and efficacy endpoints is also investigated.     

Bio-monitoring of ozone by young students

The inquiry-based approach is an important component of secondary school biology curricula. However, we found that common Australian texts included little coverage of controlled experimentation in ecological practical work. The logistical and ethical difficulties in designing suitable ecological practicals may be a factor in these observations, as well as a perception that investigations of the complex interrelationships in ecology require scientific approaches other than experimentation. We argue that because controlled experiments are used extensively by professional ecologists to solve both theoretical and applied problems, experimentation should be a key component of secondary school ecology curricula. We suggest five teaching principles to guide secondary school biology teachers in providing a more realistic view of the possibilities and limitations of ecological experimentation. We also review ways in which computer simulations and microcosm experiments can be used to overcome logistical and ethical problems and allow students to design and implement ecological experiments. Whether based in the classroom or the field, the use of experimental approaches in secondary school ecology curricula illustrates ecological concepts, reinforces principles of experimental design and highlights the value of the inquiry-based approach in biological education.     

A human rights approach to low data reporting in clinical trials of psychiatric deep brain stimulation

The reporting of clinical trial data is necessary not only for doctors to determine treatment efficacy, but also to explore new questions without unnecessarily repeating trials, and to protect patients and the public from dangers when data are withheld. This issue is particularly salient in those trials involving invasive neurosurgical interventions, such as deep brain stimulation (DBS), for ‘treatment refractory’ psychiatric disorders. Using the federal database ClinicalTrials.gov, it was discovered that out of the completed or unknown‐status trials related to psychiatric DBS up to November 2018, only two had submitted results to ClinicalTrials.gov. These results suggest that, despite federal requirements to report clinical trial data, reporting on psychiatric DBS trials is problematically minimal. It is argued that a human rights approach to this problem establishes a legal and ethical foundation for the need to report clinical trial results in this area.     

Dose finding for continuous and ordinal outcomes with a monotone objective function: a unified approach

Summary .  In many phase I trials, the design goal is to find the dose associated with a certain target toxicity rate. In some trials, the goal can be to find the dose with a certain weighted sum of rates of various toxicity grades. For others, the goal is to find the dose with a certain mean value of a continuous response. In this article, we describe a dose-finding design that can be used in any of the dose-finding trials described above, trials where the target dose is defined as the dose at which a certain monotone function of the dose is a prespecified value. At each step of the proposed design, the normalized difference between the current dose and the target is computed. If that difference is close to zero, the dose is repeated. Otherwise, the dose is increased or decreased, depending on the sign of the difference.     

Optimizing preclinical study design in oncology research

The current drug development pathway in oncology research has led to a large attrition rate for new drugs, in part due to a general lack of appropriate preclinical studies that are capable of accurately predicting efficacy and/or toxicity in the target population. Because of an obvious need for novel therapeutics in many types of cancer, new compounds are being investigated in human Phase I and Phase II clinical trials before a complete understanding of their toxicity and efficacy profiles is obtained. In fact, for newer targeted molecular agents that are often cytostatic in nature, the conventional preclinical evaluation used for traditional cytotoxic chemotherapies utilizing primary tumor shrinkage as an endpoint may not be appropriate. By utilizing an integrated pharmacokinetic/pharmacodynamic approach, along with proper selection of a model system, the drug development process in oncology research may be improved leading to a better understanding of the determinants of efficacy and toxicity, and ultimately fewer drugs that fail once they reach human clinical trials.     

The rise of model protozoa

It is timely to evaluate the role of protozoa as model organisms given their diversity, abundance and versatility as well as the economic and ethical pressures placed on animal-based experimentation. We first define the term model organism and then examine through examples why protozoa make good models. Our examples reflect major issues including evolution, ecology, population and community biology, disease, the role of organelles, ageing, space travel, toxicity and teaching. We conclude by recognising that although protozoa may in some cases not completely mimic tissue- or whole-animal-level processes, they are extremely flexible and their use should be embraced. Finally, we offer advice on obtaining emergent model protozoa.     

Dose-levels and first signs of efficacy in contemporary oncology phase 1 clinical trials

Purpose

Phase 1 trials play a crucial role in oncology by translating laboratory science into efficient therapies. Molecular targeted agents (MTA) differ from traditional cytotoxics in terms of both efficacy and toxicity profiles. Recent reports suggest that higher doses are not essential to produce the optimal anti-tumor effect. This study aimed to assess if MTA could achieve clinical benefit at much lower dose than traditional cytotoxics in dose seeking phase 1 trials.

Patients and Methods

We reviewed 317 recent phase 1 oncology trials reported in the literature between January 1997 and January 2009. First sign of efficacy, maximum tolerated dose (MTD) and their associated dose level were recorded in each trial.

Results

Trials investigating conventional cytotoxics alone, MTA alone and combination of both represented respectively 63.0% (201/317), 23.3% (74/317) and 13.7% (42/317) of all trials. The MTD was reached in 65.9% (209/317) of all trials and was mostly observed at the fifth dose level. First sign of efficacy was less frequently observed at the first three dose-levels for MTA as compared to conventional cytotoxics or combinations regimens (48.3% versus 63.2% and 61.3%). Sign of efficacy was observed in the same proportion whatever the treatment type (73–82%). MTD was less frequently established in trials investigating MTA alone (51.3%) or combinations (42.8%) as compared to conventional cytotoxic agents (75.6%).

Conclusion

First sign of efficacy was less frequently reported at the early dose-levels and MTD was less frequently reached in trials investigating molecular targeted therapy alone. Similar proportion of trials reported clinical benefit.     

Phase I evaluation of coumarin (1,2-benzopyrone) and cimetidine in patients with advanced malignancies.

Fifty-four patients with advanced malignancies were treated on this phase I trial of coumarin and cimetidine. The dose of coumarin was escalated, with three patients treated at each dose level, while the cimetidine dose was held constant at 300 mg four times daily. Patients received coumarin alone as a single daily oral dose for 14 days; on day 15, cimetidine was added and both drugs were continued until progression of disease. This trial was initiated with patients receiving coumarin at 400 mg daily and closed at 7 g daily with four of five patients on this dose experiencing nausea and vomiting. Treatment was generally well tolerated over a wide range of coumarin doses. Symptomatic side effects were few, mild, and usually self limited. Side effects included insomnia, nausea, vomiting, diarrhea, and dizziness. Two patients withdrew from therapy because of daily nausea and vomiting. Typically, nausea, vomiting, and dizziness occurred 2.5-3 hours after a dose of coumarin. In most patients, these side effects abated spontaneously with continuation of therapy. There was no significant hematologic or renal toxicity. Hepatotoxicity occurred in only one patient and was manifested by asymptomatic abnormal elevations of serum hepatic transaminases. This toxicity was reversible upon interruption of therapy. Objective tumor regressions were observed in six patients with renal cell carcinoma. Responses occurred at coumarin doses ranging from 600 mg to 5 g daily. Coumarin is a relatively nontoxic, oral, outpatient therapy that warrants further investigations for the treatment of human malignancies. Because of its low toxicity, there is potential for combining coumarin with chemotherapeutic and/or biological agents in an attempt to improve on efficacy.(ABSTRACT TRUNCATED AT 250 WORDS)     

Treatment Monitoring of HIV‐Infected Patients based on Mechanistic Models

Summary For most patients, the HIV viral load can be made undetectable by highly active antiretroviral treatments highly active antiretroviral therapy: the virus, however, cannot be eradicated. Thus, the major problem is to try to reduce the side effects of the treatment that patients have to take during their life time. We tackle the problem of monitoring the treatment dose, with the aim of giving the minimum dose that yields an undetectable viral load. The approach is based on mechanistic models of the interaction between virus and the immune system. It is shown that the “activated cells model,” allows making good predictions of the effect of dose changes and, thus, could be a good basis for treatment monitoring. Then, we use the fact that in dynamical models, there is a nontrivial equilibrium point, that is with a virus load larger than zero, only if the reproductive number R₀ is larger than one. For reducing side effects, we may give a dose just above the critical dose corresponding to R₀ equal to 1. A prior distribution of the parameters of the model can be taken as the posterior arising from the analysis of previous clinical trials. Then the observations for a given patient can be used to dynamically tune the dose so that there is a high probability that the reproductive number is below one. The advantage of the approach is that it does not depend on a cost function, weighing side effects and efficiency of the drug. It is shown that it is possible to approach the critical dose if the model is correct. A sensitivity analysis assesses the robustness of the approach.     

Designs for phase I clinical trials with multiple courses of subjects at different doses

Summary .   The goal of this article is to provide a new design framework and its corresponding estimation for phase I trials. Existing phase I designs assign each subject to one dose level based on responses from previous subjects. Yet it is possible that subjects with neither toxicity nor efficacy responses can be treated at higher dose levels, and their subsequent responses to higher doses will provide more information. In addition, for some trials, it might be possible to obtain multiple responses (repeated measures) from a subject at different dose levels. In this article, a nonparametric estimation method is developed for such studies. We also explore how the designs of multiple doses per subject can be implemented to improve design efficiency. The gain of efficiency from "single dose per subject" to "multiple doses per subject" is evaluated for several scenarios. Our numerical study shows that using "multiple doses per subject" and the proposed estimation method together increases the efficiency substantially.