Comparison of visual status of Iranian military and commercial drivers

Background There is no legal requirement for Iranian military truck drivers to undergo regular visual checkups as compared to commercial truck drivers. Objectives This study aimed to evaluate the impact of drivers’ visual checkups by comparing the visual function of Iranian military and commercial truck drivers. Patients and Methods In this comparative cross-sectional study, two hundred military and 200 commercial truck drivers were recruited and their Visual Acuity (VA), Visual Field (VF), color vision and Contrast Sensitivity (CS) were assessed and compared using the Snellen chart, confrontation screening method, D15 test and Pelli-Robson letter chart, respectively. A questionnaire regarding driving exposure and history of motor-vehicle crashes (MVCs) was also filled by drivers. Results were analyzed using an independent samples t-test, one-way ANOVA (assessing difference in number of MVCs across different age groups), chi-square test and Pearson correlation at statistical significance level of P < 0.05. Results Mean age was 41.6 ± 9.2 for the military truck drivers and 43.4 ± 10.9 for commercial truck drivers (P > 0.05). No significant difference between military and commercial drivers was found in terms of driving experience, number of MVCs, binocular VA, frequency of color vision defects and CS scores. In contrast, the last ocular examination was significantly earlier in military drivers than commercial drivers (P < 0.001). In addition, 4% of military drivers did not meet the national standards to drive as opposed to 2% of commercial drivers. There was a significant but weak correlation between binocular VA and age (r = 0.175, P < 0.001). However, CS showed a significantly moderate correlation with age (r = -0.488, P < 0.001). Conclusions The absence of legal requirement for regular eye examination in military drivers caused the incompetent drivers to be missed in contrast to commercial drivers. The need for scientific revision of VA standard for Iranian drivers is also discussed. The CS measurement in visual checkups of older drivers deserves to be investigated more thoroughly.

Comparator clinical trials of surrogate endpoints with albiglutide are in HARMONY

Introduction: Agonists of glucagon-like peptide-1 (GLP-1) receptors are used in the treatment of type 2 diabetes. Albiglutide is a new long acting GLP-1 receptor agonist being developed for once-weekly use. Areas covered: This evaluation is of 2 clinical trials in the HARMONY clinical trials series. HARMONY 3 compares albiglutide to sitagliptin and glimepiride in subjects with type 2 diabetes poorly controlled with metformin, and HARMONY 6 compares albiglutide to insulin lispro in subjects poorly controlled with slow/medium release preparations of insulin. Expert opinion: Both studies showed that albiglutide lowered HbA1c, and had advantages over its comparator drugs. However, questions remain about the safety of albiglutide. Albiglutide is not being used in subjects with a history of thyroid cancer, as it is not known whether this is a rare adverse effect with albiglutide. Also, the safety of albiglutide in subjects with type 2 diabetes and high cardiovascular risk is unknown.

Are we waiting too long for the cardiovascular outcome trials with the glucagon-like peptide-1 receptor agonists?

Several new medicines are in development for the treatment of type 2 diabetes, and cardiovascular outcome trials are the gold standard for these medicines. This editorial demonstrates that despite being available for over 10 years, there are no cardiovascular outcome studies for any of the glucagon-like peptide-1 (GLP-1) receptor agonists, which demonstrate cardiovascular safety or benefit in subjects with high cardiovascular risk. The author argues that the FDA should be ensuring that clinical outcome studies for subjects with type 2 diabetes and high cardiovascular risk be undertaken in a timelier manner.

After 10 years of clinical trials with liraglutide, do we know whether it is beneficial in diabetes?

Type 2 diabetes remains an escalating world-wide problem, despite a range of treatments. The revelation that insulin secretion is under the control of a gut hormone, glucagon-like peptide 1 (GLP-1), led to a new paradigm in the management of type 2 diabetes. Liraglutide is a long acting GLP-1 receptor agonist used in the treatment of type 2 diabetes. The review considers the clinical trials with liraglutide. There are many comparator trials between liraglutide and other medicines for the treatment of type 2 diabetes, and these trials have shown that liraglutide lowers HbA1c and body weight, and is well tolerated. A large cardiovascular safety trial with liraglutide is presently being undertaken. After 10 years of clinical trials with liraglutide, we do not know whether liraglutide has cardiovascular safety in subjects with type 2 diabetes and high cardiovascular risk. Although this is not a requirement for registration by the Food and Drug Administration (FDA), in my opinion, they should reconsider this. We also do not presently know whether liraglutide has any beneficial effects on clinical cardiovascular outcomes.

A method for matching patients to advanced prostate cancer clinical trials

Objective: To illustrate a new method for simplifying patient recruitment for advanced prostate cancer clinical trials using natural language processing techniques. Background: The identification of eligible participants for clinical trials is a critical factor to increase patient recruitment rates and an important issue for discovery of new treatment interventions. The current practice of identifying eligible participants is highly constrained due to manual processing of disparate sources of unstructured patient data. Informatics-based approaches can simplify the complex task of evaluating patient’s eligibility for clinical trials. We show that an ontology-based approach can address the challenge of matching patients to suitable clinical trials. Methods: The free-text descriptions of clinical trial criteria as well as patient data were analysed. A set of common inclusion and exclusion criteria was identified through consultations with expert clinical trial coordinators. A research prototype was developed using Unstructured Information Management Architecture (UIMA) that identified SNOMED CT concepts in the patient data and clinical trial description. The SNOMED CT concepts model the standard clinical terminology that can be used to represent and evaluate patient’s inclusion/exclusion criteria for the clinical trial. Results: Our experimental research prototype describes a semi-automated method for filtering patient records using common clinical trial criteria. Our method simplified the patient recruitment process. The discussion with clinical trial coordinators showed that the efficiency in patient recruitment process measured in terms of information processing time could be improved by 25%. Conclusion: An UIMA-based approach can resolve complexities in patient recruitment for advanced prostate cancer clinical trials.

Manufacturing and use of human placenta-derived mesenchymal stromal cells for phase I clinical trials: Establishment and evaluation of a protocol

Background/Aim. Mesenchymal stromal cells (MSCs) have been utilised in many clinical trials as an experimental treatment in numerous clinical settings. Bone marrow remains the traditional source tissue for MSCs but is relatively hard to access in large volumes. Alternatively, MSCs may be derived from other tissues including the placenta and adipose tissue. In an initial study no obvious differences in parameters such as cell surface phenotype, chemokine receptor display, mesodermal differentiation capacity or immunosuppressive ability, were detected when we compared human marrow derived- MSCs to human placenta-derived MSCs. The aim of this study was to establish and evaluate a protocol and related processes for preparation placenta-derived MSCs for early phase clinical trials. Methods. A full-term placenta was taken after delivery of the baby as a source of MSCs. Isolation, seeding, incubation, cryopreservation of human placentaderived MSCs and used production release criteria were in accordance with the complex regulatory requirements applicable to Code of Good Manufacturing Practice manufacturing of ex vivo expanded cells. Results. We established and evaluated instructions for MSCs preparation protocol and gave an overview of the three clinical areas application. In the first trial, MSCs were co-transplanted iv to patient receiving an allogeneic cord blood transplant as therapy for treatmentrefractory acute myeloid leukemia. In the second trial, MSCs were administered iv in the treatment of idiopathic pulmonary fibrosis and without serious adverse effects. In the third trial, MSCs were injected directly into the site of tendon damage using ultrasound guidance in the treatment of chronic refractory tendinopathy. Conclusion. Clinical trials using both allogeneic and autologous cells demonstrated MSCs to be safe. A described protocol for human placenta-derived MSCs is appropriate for use in a clinical setting, relatively inexpensive and can be relatively easily adjusted to a different set of regulatory requirements, as applicable to early phase clinical trials.

Submission to the External Independent Review of the United Nations Response to Allegations of Sexual Exploitation and Abuse and Other Serious Crimes by Members of Foreign Military Forces Not Under United Nations Command in the Central African Republic

In 2015 the UN Secretary-General established an External Independent Review to review how the United Nations has responded to allegations of child sexual exploitation and child sexual abuse, and to make recommendations concerning how the United Nations should respond to allegations in the future. This submission to the Review Panel draws on literature regarding children's rights, the nature of child sexual abuse, international instruments and policy, the nature of institutional child sexual abuse, and the CAR case itself. It makes recommendations for reform of UN protocols and procedures to better prevent child sexual abuse, and to improve responses to future occurrences.

A simple Bayesian decision-theoretic design for dose-finding trials

A flexible and simple Bayesian decision-theoretic design for dose-finding trials is proposed in this paper. In order to reduce the computational burden, we adopt a working model with conjugate priors, which is flexible to fit all monotonic dose-toxicity curves and produces analytic posterior distributions. We also discuss how to use a proper utility function to reflect the interest of the trial. Patients are allocated based on not only the utility function but also the chosen dose selection rule. The most popular dose selection rule is the one-step-look-ahead (OSLA), which selects the best-so-far dose. A more complicated rule, such as the two-step-look-ahead, is theoretically more efficient than the OSLA only when the required distributional assumptions are met, which is, however, often not the case in practice. We carried out extensive simulation studies to evaluate these two dose selection rules and found that OSLA was often more efficient than two-step-look-ahead under the proposed Bayesian structure. Moreover, our simulation results show that the proposed Bayesian method's performance is superior to several popular Bayesian methods and that the negative impact of prior misspecification can be managed in the design stage.

An optimal design for screening trials

Yao, Begg, and Livingston (1996, Biometrics 52, 992-1001) considered the optimal group size for testing a series of potentially therapeutic agents to identify a promising one as soon as possible for given error rates. The number of patients to be tested with each agent was fixed as the group size. We consider a sequential design that allows early acceptance and rejection, and we provide an optimal strategy to minimize the sample sizes (patients) required using Markov decision processes. The minimization is under the constraints of the two types (false positive and false negative) of error probabilities, with the Lagrangian multipliers corresponding to the cost parameters for the two types of errors. Numerical studies indicate that there can be a substantial reduction in the number of patients required.

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

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.

Decision-theoretic designs for dose-finding clinical trials with multiple outcomes

A decision-theoretic framework is proposed for designing sequential dose-finding trials with multiple outcomes. The optimal strategy is solvable theoretically via backward induction. However, for dose-finding studies involving k doses, the computational complexity is the same as the bandit problem with k-dependent arms, which is computationally prohibitive. We therefore provide two computationally compromised strategies, which is of practical interest as the computational complexity is greatly reduced: one is closely related to the continual reassessment method (CRM), and the other improves CRM and approximates to the optimal strategy better. In particular, we present the framework for phase I/II trials with multiple outcomes. Applications to a pediatric HIV trial and a cancer chemotherapy trial are given to illustrate the proposed approach. Simulation results for the two trials show that the computationally compromised strategy can perform well and appear to be ethical for allocating patients. The proposed framework can provide better approximation to the optimal strategy if more extensive computing is available.

A Bayesian decision approach for sample size determination in phase II trials

Stallard (1998, Biometrics 54, 279-294) recently used Bayesian decision theory for sample-size determination in phase II trials. His design maximizes the expected financial gains in the development of a new treatment. However, it results in a very high probability (0.65) of recommending an ineffective treatment for phase III testing. On the other hand, the expected gain using his design is more than 10 times that of a design that tightly controls the false positive error (Thall and Simon, 1994, Biometrics 50, 337-349). Stallard's design maximizes the expected gain per phase II trial, but it does not maximize the rate of gain or total gain for a fixed length of time because the rate of gain depends on the proportion: of treatments forwarding to the phase III study. We suggest maximizing the rate of gain, and the resulting optimal one-stage design becomes twice as efficient as Stallard's one-stage design. Furthermore, the new design has a probability of only 0.12 of passing an ineffective treatment to phase III study.

Isotonic designs for phase I trials

The purpose of a phase I trial in cancer is to determine the level (dose) of the treatment under study that has an acceptable level of adverse effects. Although substantial progress has recently been made in this area using parametric approaches, the method that is widely used is based on treating small cohorts of patients at escalating doses until the frequency of toxicities seen at a dose exceeds a predefined tolerable toxicity rate. This method is popular because of its simplicity and freedom from parametric assumptions. In this payer, we consider cases in which it is undesirable to assume a parametric dose-toxicity relationship. We propose a simple model-free approach by modifying the method that is in common use. The approach assumes toxicity is nondecreasing with dose and fits an isotonic regression to accumulated data. At any point in a trial, the dose given is that with estimated toxicity deemed closest to the maximum tolerable toxicity. Simulations indicate that this approach performs substantially better than the commonly used method and it compares favorably with other phase I designs.

Analysis of human immunodeficiency virus type 1 drug resistance in children receiving nucleoside analogue reverse-transcriptase inhibitors plus nevirapine, nelfinavir, or ritonavir (Pediatric AIDS Clinical Trials Group 377)

In Pediatric AIDS Clinical Trials Group 377, antiretroviral therapy-experienced children were randomized to 4 treatment arms that included different combinations of stavudine, lamivudine (3TC), nevirapine (Nvp), nelfinavir (Nfv), and ritonavir (Rtv). Previous treatment with zidovudine (Zdv), didanosine (ddI), or zalcitabine (ddC) was acceptable. Drug resistance ((R)) mutations were assessed before study treatment (baseline) and at virologic failure. Zdv(R), ddI(R), and ddC(R) mutations were detected frequently at baseline but were not associated with virologic failure. Children with drug resistance mutations at baseline had greater reductions in virus load over time than did children who did not. Nvp(R) and 3TC(R) mutations were detected frequently at virologic failure, and Nvp(R) mutations were more common among children receiving 3-drug versus 4-drug Nvp-containing regimens. Children who were maintained on their study regimen after virologic failure accumulated additional Nvp(R) and 3TC(R) mutations plus Rtv(R) and Nfv(R) mutations. However, Rtv(R) and Nfv(R) mutations were detected at unexpectedly low rates.

Sequential allocation in clinical trials

Suppose two treatments with binary responses are available for patients with some disease and that each patient will receive one of the two treatments. In this paper we consider the interests of patients both within and outside a trial using a Bayesian bandit approach and conclude that equal allocation is not appropriate for either group of patients. It is suggested that Gittins indices should be used (using an approach called dynamic discounting by choosing the discount rate based on the number of future patients in the trial) if the disease is rare, and the least failures rule if the disease is common. Some analytical and simulation results are provided.