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Pharmaceutical Statistics

Qingzhao Yu, Lin Zhu, Han Zhu
Bayesian sequential and adaptive randomization designs are gaining popularity in clinical trials thanks to their potentials to reduce the number of required participants and save resources. We propose a Bayesian sequential design with adaptive randomization rates so as to more efficiently attribute newly recruited patients to different treatment arms. In this paper, we consider 2-arm clinical trials. Patients are allocated to the 2 arms with a randomization rate to achieve minimum variance for the test statistic...
October 4, 2017: Pharmaceutical Statistics
Pål Haugen, Gunnar Skov Simonsen, Raul Primicerio, Anne-Sofie Furberg, Lars Småbrekke
High antibiotic consumption rates are associated to high prevalence of antimicrobial resistance. Geographical differences in dispensing rates of antibiotics are frequently analysed using statistical methods addressing the central tendency of the data. Yet, examining extreme quantiles may be of equal or greater interest if the problem relates to the extremes of consumption rates, as is the case for antimicrobial resistance. The objective of this study was to investigate how geographic location (latitude) and municipality population size affect antibiotic consumption in Norway...
September 29, 2017: Pharmaceutical Statistics
Shinjo Yada, Chikuma Hamada
Many new anticancer agents can be combined with existing drugs, as combining a number of drugs may be expected to have a better therapeutic effect than monotherapy owing to synergistic effects. Furthermore, to drive drug development and to reduce the associated cost, there has been a growing tendency to combine these as phase I/II trials. With respect to phase I/II oncology trials for the assessment of dose combinations, in the existing methodologies in which efficacy based on tumor response and safety based on toxicity are modeled as binary outcomes, it is not possible to enroll and treat the next cohort of patients unless the best overall response has been determined in the current cohort...
August 25, 2017: Pharmaceutical Statistics
Douglas F Arbetter, Purva Jain, Megan K Yee, Nathan Michalak, Adrian F Hernandez, Russell D Hull, Samuel Z Goldhaber, Robert A Harrington, Alex Gold, Alexander T Cohen, C Michael Gibson
Competing risk methods are time-to-event analyses that account for fatal and/or nonfatal events that may potentially alter or prevent a subject from experiencing the primary endpoint. Competing risk methods may provide a more accurate and less biased estimate of the incidence of an outcome but are rarely applied in cardiology trials. APEX investigated the efficacy of extended-duration betrixaban versus standard-duration enoxaparin to prevent a composite of symptomatic deep-vein thrombosis (proximal or distal), nonfatal pulmonary embolism, or venous thromboembolism (VTE)-related death in acute medically ill patients (n = 7513)...
August 24, 2017: Pharmaceutical Statistics
Fei Gao, Guanghan F Liu, Donglin Zeng, Lei Xu, Bridget Lin, Guoqing Diao, Gregory Golm, Joseph F Heyse, Joseph G Ibrahim
In clinical trials, missing data commonly arise through nonadherence to the randomized treatment or to study procedure. For trials in which recurrent event endpoints are of interests, conventional analyses using the proportional intensity model or the count model assume that the data are missing at random, which cannot be tested using the observed data alone. Thus, sensitivity analyses are recommended. We implement the control-based multiple imputation as sensitivity analyses for the recurrent event data. We model the recurrent event using a piecewise exponential proportional intensity model with frailty and sample the parameters from the posterior distribution...
August 22, 2017: Pharmaceutical Statistics
Gu Mi
Because of the complexity of cancer biology, often the target pathway is not well understood at the time that phase III trials are initiated. A 2-stage trial design was previously proposed for identifying a subgroup of interest in a learn stage, on the basis of 1 or more baseline biomarkers, and then subsequently confirming it in a confirmation stage. In this article, we discuss some practical aspects of this type of design and describe an enhancement to this approach that can be built into the study randomization to increase the robustness of the evaluation...
September 2017: Pharmaceutical Statistics
Wai Yin Yeung, Bruno Reigner, Ulrich Beyer, Cheikh Diack, Daniel Sabanés Bové, Giuseppe Palermo, Thomas Jaki
The main purpose of dose-escalation trials is to identify the dose(s) that is/are safe and efficacious for further investigations in later studies. In this paper, we introduce dose-escalation designs that incorporate both the dose-limiting events and dose-limiting toxicities (DLTs) and indicative responses of efficacy into the procedure. A flexible nonparametric model is used for modelling the continuous efficacy responses while a logistic model is used for the binary DLTs. Escalation decisions are based on the combination of the probabilities of DLTs and expected efficacy through a gain function...
July 9, 2017: Pharmaceutical Statistics
Peter F Thall, Peter Mueller, Yanxun Xu, Michele Guindani
Many commonly used statistical methods for data analysis or clinical trial design rely on incorrect assumptions or assume an over-simplified framework that ignores important information. Such statistical practices may lead to incorrect conclusions about treatment effects or clinical trial designs that are impractical or that do not accurately reflect the investigator's goals. Bayesian nonparametric (BNP) models and methods are a very flexible new class of statistical tools that can overcome such limitations...
July 4, 2017: Pharmaceutical Statistics
Peter J Laud
Several methods are available for generating confidence intervals for rate difference, rate ratio, or odds ratio, when comparing two independent binomial proportions or Poisson (exposure-adjusted) incidence rates. Most methods have some degree of systematic bias in one-sided coverage, so that a nominal 95% two-sided interval cannot be assumed to have tail probabilities of 2.5% at each end, and any associated hypothesis test is at risk of inflated type I error rate. Skewness-corrected asymptotic score methods have been shown to have superior equal-tailed coverage properties for the binomial case...
June 22, 2017: Pharmaceutical Statistics
Devan V Mehrotra, Fang Liu, Thomas Permutt
In some randomized (drug versus placebo) clinical trials, the estimand of interest is the between-treatment difference in population means of a clinical endpoint that is free from the confounding effects of "rescue" medication (e.g., HbA1c change from baseline at 24 weeks that would be observed without rescue medication regardless of whether or when the assigned treatment was discontinued). In such settings, a missing data problem arises if some patients prematurely discontinue from the trial or initiate rescue medication while in the trial, the latter necessitating the discarding of post-rescue data...
June 20, 2017: Pharmaceutical Statistics
Qing Kang, Christopher I Vahl
Traditional bioavailability studies assess average bioequivalence (ABE) between the test (T) and reference (R) products under the crossover design with TR and RT sequences. With highly variable (HV) drugs whose intrasubject coefficient of variation in pharmacokinetic measures is 30% or greater, assertion of ABE becomes difficult due to the large sample sizes needed to achieve adequate power. In 2011, the FDA adopted a more relaxed, yet complex, ABE criterion and supplied a procedure to assess this criterion exclusively under TRR-RTR-RRT and TRTR-RTRT designs...
June 16, 2017: Pharmaceutical Statistics
Harriet Sommer, Martin Wolkewitz, Martin Schumacher
A variety of primary endpoints are used in clinical trials treating patients with severe infectious diseases, and existing guidelines do not provide a consistent recommendation. We propose to study simultaneously two primary endpoints, cure and death, in a comprehensive multistate cure-death model as starting point for a treatment comparison. This technique enables us to study the temporal dynamic of the patient-relevant probability to be cured and alive. We describe and compare traditional and innovative methods suitable for a treatment comparison based on this model...
June 9, 2017: Pharmaceutical Statistics
Isaac Gravestock, Leonhard Held
Incorporating historical information into the design and analysis of a new clinical trial has been the subject of much discussion as a way to increase the feasibility of trials in situations where patients are difficult to recruit. The best method to include this data is not yet clear, especially in the case when few historical studies are available. This paper looks at the power prior technique afresh in a binomial setting and examines some previously unexamined properties, such as Box P values, bias, and coverage...
June 2, 2017: Pharmaceutical Statistics
Baoguang Han, Jia Zhan, Z John Zhong, Dawei Liu, Stacy Lindborg
The borrowing of historical control data can be an efficient way to improve the treatment effect estimate of the current control group in a randomized clinical trial. When the historical and current control data are consistent, the borrowing of historical data can increase power and reduce Type I error rate. However, when these 2 sources of data are inconsistent, it may result in a combination of biased estimates, reduced power, and inflation of Type I error rate. In some situations, inconsistency between historical and current control data may be caused by a systematic variation in the measured baseline prognostic factors, which can be appropriately addressed through statistical modeling...
May 31, 2017: Pharmaceutical Statistics
Natalie Dimier, Susan Todd
Clinical trials of experimental treatments must be designed with primary endpoints that directly measure clinical benefit for patients. In many disease areas, the recognised gold standard primary endpoint can take many years to mature, leading to challenges in the conduct and quality of clinical studies. There is increasing interest in using shorter-term surrogate endpoints as substitutes for costly long-term clinical trial endpoints; such surrogates need to be selected according to biological plausibility, as well as the ability to reliably predict the unobserved treatment effect on the long-term endpoint...
May 19, 2017: Pharmaceutical Statistics
Julien Tanniou, Ingeborg van der Tweel, Steven Teerenstra, Kit C B Roes
In drug development, it sometimes occurs that a new drug does not demonstrate effectiveness for the full study population but appears to be beneficial in a relevant subgroup. In case the subgroup of interest was not part of a confirmatory testing strategy, the inflation of the overall type I error is substantial and therefore such a subgroup analysis finding can only be seen as exploratory at best. To support such exploratory findings, an appropriate replication of the subgroup finding should be undertaken in a new trial...
May 15, 2017: Pharmaceutical Statistics
John Ouyang, Kevin J Carroll, Gary Koch, Junfang Li
Missing data cause challenging issues, particularly in phase III registration trials, as highlighted by the European Medicines Agency (EMA) and the US National Research Council. We explore, as a case study, how the issues from missing data were tackled in a double-blind phase III trial in subjects with autosomal dominant polycystic kidney disease. A total of 1445 subjects were randomized in a 2:1 ratio to receive active treatment (tolvaptan), or placebo. The primary outcome, the rate of change in total kidney volume, favored tolvaptan (P < ...
May 4, 2017: Pharmaceutical Statistics
Devan V Mehrotra, Li Fan, Fang Liu, Kuenhi Tsai
Since the implementation of the International Conference on Harmonization (ICH) E14 guideline in 2005, regulators have required a "thorough QTc" (TQT) study for evaluating the effects of investigational drugs on delayed cardiac repolarization as manifested by a prolonged QTc interval. However, TQT studies have increasingly been viewed unfavorably because of their low cost effectiveness. Several researchers have noted that a robust drug concentration-QTc (conc-QTc) modeling assessment in early phase development should, in most cases, obviate the need for a subsequent TQT study...
May 2017: Pharmaceutical Statistics
Benjamin R Saville, Scott M Berry
Response adaptive randomization (RAR) methods for clinical trials are susceptible to imbalance in the distribution of influential covariates across treatment arms. This can make the interpretation of trial results difficult, because observed differences between treatment groups may be a function of the covariates and not necessarily because of the treatments themselves. We propose a method for balancing the distribution of covariate strata across treatment arms within RAR. The method uses odds ratios to modify global RAR probabilities to obtain stratum-specific modified RAR probabilities...
May 2017: Pharmaceutical Statistics
Han Zhu, Qingzhao Yu, Donald E Mercante
Several researchers have proposed solutions to control type I error rate in sequential designs. The use of Bayesian sequential design becomes more common; however, these designs are subject to inflation of the type I error rate. We propose a Bayesian sequential design for binary outcome using an alpha-spending function to control the overall type I error rate. Algorithms are presented for calculating critical values and power for the proposed designs. We also propose a new stopping rule for futility. Sensitivity analysis is implemented for assessing the effects of varying the parameters of the prior distribution and maximum total sample size on critical values...
May 2017: Pharmaceutical Statistics
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