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Statistics in Biopharmaceutical Research

Cody Chiuzan, Elizabeth Garrett-Mayer, Michael Nishimura
Dose-finding in cancer clinical trials has been dominated by algorithmic designs on the principle that the highest tolerable dose is also the most effective dose. This assumption no longer applies to the biologic treatments that are characterized by different toxicity and/or efficacy profiles to the extent that the best therapeutic dose might be well below any dose that produces serious toxicity. As such, we propose a two-stage design with focus on immunotherapy trials, incorporating both safety and efficacy information...
2018: Statistics in Biopharmaceutical Research
Jianrong Wu, Xiaoping Xiong
For randomized group sequential survival trial designs with unbalanced treatment allocation, the widely used Schoenfeld formula is inaccurate, and the commonly used information time as the ratio of number of events at interim look to the number of events at the end of trial can be biased. In this paper, a sample size formula for the two-sample log-rank test under the proportional hazards model is proposed that provides more accurate sample size calculation for unbalanced survival trial designs. Furthermore, a new information time is introduced for the sequential survival trials such that the new information time is more accurate than the traditional information time when the allocation of enrollments is unbalanced in groups...
2017: Statistics in Biopharmaceutical Research
Jianrong Wu
For designing single-arm phase II trials with time-to-event endpoints, a sample size formula is derived for the modified one-sample log-rank test under the proportional hazards model. The derived formula enables new methods for designing trials that allow a flexible choice of the underlying survival distribution. Simulation results showed that the proposed formula provides an accurate estimation of sample size. The sample size calculation has been implemented in an R function for the purpose of trial design...
2017: Statistics in Biopharmaceutical Research
Scott R Evans, Dean Follmann
In the future, clinical trials will have an increased emphasis on pragmatism, providing a practical description of the effects of new treatments in realistic clinical settings. Accomplishing pragmatism requires better summaries of the totality of the evidence in ways that clinical trials consumers---patients, physicians, insurers---find transparent and allow for informed benefit:risk decision-making. The current approach to the analysis of clinical trials is to analyze efficacy and safety separately and then combine these analyses into a benefit:risk assessment...
2016: Statistics in Biopharmaceutical Research
Youyi Fong, Xuesong Yu
Many modern serial dilution assays are based on fluorescence intensity (FI) readouts. We study optimal transformation model choice for fitting five parameter logistic curves (5PL) to FI-based serial dilution assay data. We first develop a generalized least squares-pseudolikelihood type algorithm for fitting heteroscedastic logistic models. Next we show that the 5PL and log 5PL functions can approximate each other well. We then compare four 5PL models with different choices of log transformation and variance modeling through a Monte Carlo study and real data...
2016: Statistics in Biopharmaceutical Research
Alexia Iasonos, John O'Quigley
A rapidly increasing number of Phase I dose-finding studies, and in particular those based on the standard 3+3 design, are being prolonged with the inclusion of dose expansion cohorts (DEC) in order to better characterize the toxicity profiles of experimental agents and to study disease-specific cohorts. These trials consist of two phases: the usual dose escalation phase that aims to establish the maximum tolerated dose (MTD), and the dose expansion phase that accrues additional patients, often with different eligibility criteria, and where additional information is collected...
2016: Statistics in Biopharmaceutical Research
Byron J Gajewski, C Shane Reese, John Colombo, Susan E Carlson
Docosahexaenoic acid (DHA) is a good source of fat that can be taken up through food, such as fish, or taken as a supplement. Evidence is building that DHA provides a high yield, low risk strategy to reduce preterm birth and/or low birth weight. These births are great costs to society. A recently completed phase III trial revealed that higher birth weight and gestational age were associated with DHA dosed at 600 mg/day. In this paper we take a posterior predictive approach to assess impacts of these findings on public health...
2016: Statistics in Biopharmaceutical Research
Fang Xia, Stephen L George, Xiaofei Wang
In designing a clinical trial for comparing two or more treatments with respect to overall survival (OS), a proportional hazards assumption is commonly made. However, in many cancer clinical trials, patients pass through various disease states prior to death and because of this may receive treatments other than originally assigned. For example, patients may crossover from the control treatment to the experimental treatment at progression. Even without crossover, the survival pattern after progression may be very different than the pattern prior to progression...
2016: Statistics in Biopharmaceutical Research
Ou Bai, Min Chen, Xinlei Wang
Meta-analysis has been widely applied to rare adverse event data because it is very difficult to reliably detect the effect of a treatment on such events in an individual clinical study. However, it is known that standard meta-analysis methods are often biased, especially when the background incidence rate is very low. A recent work by Bhaumik et al. (2012) proposed new moment-based approaches under a natural random effects model, to improve estimation and testing of the treatment effect and the between-study heterogeneity parameter...
2016: Statistics in Biopharmaceutical Research
Janet Wittes, Brenda Crowe, Christy Chuang-Stein, Achim Guettner, David Hall, Qi Jiang, Daniel Odenheimer, H Amy Xia, Judith Kramer
In March 2011, a Final Rule for expedited reporting of serious adverse events took effect in the United States for studies conducted under an Investigational New Drug (IND) application. In December 2012, the U.S. Food and Drug Administration (FDA) promulgated a final Guidance describing the operationalization of this Final Rule. The Rule and Guidance clarified that a clinical trial sponsor should have evidence suggesting causality before defining an unexpected serious adverse event as a suspected adverse reaction that would require expedited reporting to the FDA...
July 3, 2015: Statistics in Biopharmaceutical Research
Yuki Ando, Toshimitsu Hamasaki, Scott R Evans, Koko Asakura, Tomoyuki Sugimoto, Takashi Sozu, Yuko Ohno
The effects of interventions are multi-dimensional. Use of more than one primary endpoint offers an attractive design feature in clinical trials as they capture more complete characterization of the effects of an intervention and provide more informative intervention comparisons. For these reasons, multiple primary endpoints have become a common design feature in many disease areas such as oncology, infectious disease, and cardiovascular disease. More specifically in medical product development, multiple endpoints are utilized as co-primary to evaluate the effect of the new interventions...
June 24, 2015: Statistics in Biopharmaceutical Research
A Ivanova, K M Anderson, Gary L Rosner, E Rubin
We congratulate the authors on their comments on innovative approaches to drug development that fall out of the traditional mold and may result in more quickly bringing safe and effective treatments to patients. Changes in the overall clinical develop approach are most relevant to "breakthrough" therapies, which have generally yielded exceptional efficacy data in early clinical studies, motivating exploration of accelerated development and regulatory approaches, as well as a potential ethical need for crossover upon progression in randomized controlled studies (Horning et al...
2015: Statistics in Biopharmaceutical Research
Scott R Evans, Dean Follmann
No abstract text is available yet for this article.
2015: Statistics in Biopharmaceutical Research
Kevin S S Henning, Peter H Westfall
In pharmaceutical research, making multiple statistical inferences is standard practice. Unless adjustments are made for multiple testing, the probability of making erroneous determinations of significance increases with the number of inferences. Closed testing is a flexible and easily explained approach to controlling the overall error rate that has seen wide use in pharmaceutical research, particularly in clinical trials settings. In this article, we first give a general review of the uses of multiple testing in pharmaceutical research, with particular emphasis on the benefits and pitfalls of closed testing procedures...
2015: Statistics in Biopharmaceutical Research
K Odem-Davis, T R Fleming
In non-inferiority trials, acceptable efficacy of an experimental treatment is established by ruling out some defined level of reduced effect relative to an effective active control standard. Serial use of non-inferiority trials may lead to newly approved therapies that provide meaningfully reduced levels of benefit; this phenomenon is called bio-creep. Simulations were designed to facilitate understanding of bio-creep risk when approval of an experimental treatment with efficacy less than some proportion of the effect of the active control treatment would constitute harm, such as when new antibiotics that are meaningfully less effective than the most effective current antibiotic would be used for treatment of Community-Acquired Bacterial Pneumonia...
January 1, 2015: Statistics in Biopharmaceutical Research
Toshimitsu Hamasaki, Koko Asakura, Scott R Evans, Tomoyuki Sugimoto, Takashi Sozu
We discuss the decision-making frameworks for clinical trials with multiple co-primary endpoints in a group-sequential setting. The decision-making frameworks can account for flexibilities such as a varying number of analyses, equally or unequally spaced increments of information and fixed or adaptive Type I error allocation among endpoints. The frameworks can provide efficiency, i.e., potentially fewer trial participants, than the fixed sample size designs. We investigate the operating characteristics of the decision-making frameworks and provide guidance on constructing efficient group-sequential strategies in clinical trials with multiple co-primary endpoints...
2015: Statistics in Biopharmaceutical Research
John O'Quigley, Alexia Iasonos
The idea of bridging in dose-finding studies is closely linked to the problem of group heterogeneity. There are some distinctive features in the case of bridging which need to be considered if efficient estimation of the maximum tolerated dose (MTD) is to be accomplished. The case of two distinct populations is considered. In the bridging setting we usually have in mind two studies, corresponding to the two populations. In some cases, the first of these studies may have been completed while the second has yet to be initiated...
May 1, 2014: Statistics in Biopharmaceutical Research
Maiying Kong, Shesh N Rai, Roberto Bolli
The maximum effective dose (MaxED) is an important quantity for therapeutic drugs. The MaxED for therapeutic drugs is defined as the dose above which no improvement in efficacy is obtained. In this article, we propose two experimental designs and analytic methods (one single-stage design and one two-stage design) to select the MaxED among several fixed doses and to compare the therapeutic effect of the selected MaxED with a control. The selection of MaxED is based on the isotonic regression under the restriction of monotonicity...
January 2, 2014: Statistics in Biopharmaceutical Research
Jianrong Wu, Xiaoping Xiong
In this paper, three non-parametric test statistics are proposed to design single-arm phase II group sequential trials for monitoring survival probability. The small-sample properties of these test statistics are studied through simulations. Sample size formulas are derived for the fixed sample test. The Brownian motion property of the test statistics allowed us to develop a flexible group sequential design using a sequential conditional probability ratio test procedure (Xiong, 1995). An example is given to illustrate the trial design by using the proposed method...
2014: Statistics in Biopharmaceutical Research
Milind A Phadnis, Theresa I Shireman, James B Wetmore, Sally K Rigler, Xinhua Zhou, John A Spertus, Edward F Ellerbeck, Jonathan D Mahnken
In a population of chronic dialysis patients with an extensive burden of cardiovascular disease, estimation of the effectiveness of cardioprotective medication in literature is based on calculation of a hazard ratio comparing hazard of mortality for two groups (with or without drug exposure) measured at a single point in time or through the cumulative metric of proportion of days covered (PDC) on medication. Though both approaches can be modeled in a time-dependent manner using a Cox regression model, we propose a more complete time-dependent metric for evaluating cardioprotective medication efficacy...
2014: Statistics in Biopharmaceutical Research
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