Read by QxMD icon Read

Pharmaceutical Statistics

Rengyi Xu, Devan V Mehrotra, Pamela A Shaw
The stratified Cox model is commonly used for stratified clinical trials with time-to-event endpoints. The estimated log hazard ratio is approximately a weighted average of corresponding stratum-specific Cox model estimates using inverse-variance weights; the latter are optimal only under the (often implausible) assumption of a constant hazard ratio across strata. Focusing on trials with limited sample sizes (50-200 subjects per treatment), we propose an alternative approach in which stratum-specific estimates are obtained using a refined generalized logrank (RGLR) approach and then combined using either sample size or minimum risk weights for overall inference...
January 31, 2019: Pharmaceutical Statistics
Deli Wang, Weining Robieson, Jun Zhao, Catherine Wiener, Gary Koch
There has been a paradigm shift in diagnostic conceptualization of Alzheimer's disease (AD) based on the current evidence suggesting that structure and biology changes start to occur before clinical symptoms emerge. Consequently, therapeutic drug development is also shifting to treat early AD patients using biomarkers for enrichment in clinical trials. A similar paradigm shift is occurring for Parkinson disease. In the absence of acceptable biomarkers that could be combined with a clinical endpoint to demonstrate a disease modification (DM) effect in neurodegenerative disorders, a delayed-start design can be applied to demonstrate a lasting effect on the disease course...
January 29, 2019: Pharmaceutical Statistics
Enrico Ripamonti, Chris J Lloyd
Applied statisticians and pharmaceutical researchers are frequently involved in the design and analysis of clinical trials where at least one of the outcomes is binary. Treatments are judged by the probability of a positive binary response. A typical example is the noninferiority trial, where it is tested whether a new experimental treatment is practically not inferior to an active comparator with a prespecified margin δ. Except for the special case of δ = 0, no exact conditional test is available although approximate conditional methods (also called second-order methods) can be applied...
January 28, 2019: Pharmaceutical Statistics
Ufuk Beyaztas
This paper proposes a sufficient bootstrap method, which uses only the unique observations in the resamples, to assess the individual bioequivalence under 2 × 4 randomized crossover design. The finite sample performance of the proposed method is illustrated by extensive Monte Carlo simulations as well as a real-experimental data set, and the results are compared with those obtained by the traditional bootstrap technique. Our records reveal that the proposed method is a good competitor or even better than the classical percentile bootstrap confidence limits...
January 20, 2019: Pharmaceutical Statistics
Tim Friede, Harald Pohlmann, Heinz Schmidli
No abstract text is available yet for this article.
January 16, 2019: Pharmaceutical Statistics
Silke Jörgens, Gernot Wassmer, Franz König, Martin Posch
Adaptive trial methodology for multiarmed trials and enrichment designs has been extensively discussed in the past. A general principle to construct test procedures that control the family-wise Type I error rate in the strong sense is based on combination tests within a closed test. Using survival data, a problem arises when using information of patients for adaptive decision making, which are under risk at interim. With the currently available testing procedures, either no testing of hypotheses in interim analyses is possible or there are restrictions on the interim data that can be used in the adaptation decisions as, essentially, only the interim test statistics of the primary endpoint may be used...
January 16, 2019: Pharmaceutical Statistics
Jorge Quiroz, Richard Montes, Heliang Shi, Satrajit Roychoudhury
Assessment of analytical similarity of tier 1 quality attributes is based on a set of hypotheses that tests the mean difference of reference and test products against a margin adjusted for standard deviation of the reference product. Thus, proper assessment of the biosimilarity hypothesis requires statistical tests that account for the uncertainty associated with the estimations of the mean differences and the standard deviation of the reference product. Recently, a linear reformulation of the biosimilarity hypothesis has been proposed, which facilitates development and implementation of statistical tests...
January 15, 2019: Pharmaceutical Statistics
Lieven Nils Kennes, Gisela Volkers, Georg Kralidis
No abstract text is available yet for this article.
January 8, 2019: Pharmaceutical Statistics
José L Jiménez, Viktoriya Stalbovskaya, Byron Jones
Proportional hazards are a common assumption when designing confirmatory clinical trials in oncology. This assumption not only affects the analysis part but also the sample size calculation. The presence of delayed effects causes a change in the hazard ratio while the trial is ongoing since at the beginning we do not observe any difference between treatment arms, and after some unknown time point, the differences between treatment arms will start to appear. Hence, the proportional hazards assumption no longer holds, and both sample size calculation and analysis methods to be used should be reconsidered...
December 27, 2018: Pharmaceutical Statistics
Aaron Dane, Amy Spencer, Gerd Rosenkranz, Ilya Lipkovich, Tom Parke
Subgroup by treatment interaction assessments are routinely performed when analysing clinical trials and are particularly important for phase 3 trials where the results may affect regulatory labelling. Interpretation of such interactions is particularly difficult, as on one hand the subgroup finding can be due to chance, but equally such analyses are known to have a low chance of detecting differential treatment effects across subgroup levels, so may overlook important differences in therapeutic efficacy. EMA have therefore issued draft guidance on the use of subgroup analyses in this setting...
December 27, 2018: Pharmaceutical Statistics
Yoichi Ii
In a human bioequivalence (BE) study, the conclusion of BE is usually based on the ratio of geometric means of pharmacokinetic parameters between a test and a reference products. The "Guideline for Bioequivalence Studies of Generic Products" (2012) issued by the Japanese health authority and other similar guidelines across the world require a 90% confidence interval (CI) of the ratio to fall entirely within the range of 0.8 to 1.25 for the conclusion of BE. If prerequisite conditions are satisfied, the Japanese guideline provides for a secondary BE criterion that requires the point estimate of the ratio to fall within the range of 0...
December 26, 2018: Pharmaceutical Statistics
Paul Meyvisch, Ariel Alonso, Wim Van der Elst, Geert Molenberghs
The individual causal association (ICA) has recently been introduced as a metric of surrogacy in a causal-inference framework. The ICA is defined on the unit interval and quantifies the association between the individual causal effect on the surrogate (ΔS) and true (ΔT) endpoint. In addition, the ICA offers a general assessment of the surrogate predictive value, taking value 1 when there is a deterministic relationship between ΔT and ΔS, and value 0 when both causal effects are independent. However, when one moves away from the previous two extreme scenarios, the interpretation of the ICA becomes challenging...
December 21, 2018: Pharmaceutical Statistics
Kun Jin, Briana Cameron, Billy Dunn
Recent research on finding appropriate composite endpoints for preclinical Alzheimer's disease has focused considerable effort on finding "optimized" weights in the construction of a weighted composite score. In this paper, several proposed methods are reviewed. Our results indicate no evidence that these methods will increase the power of the test statistics, and some of these weights will introduce biases to the study. Our recommendation is to focus on identifying more sensitive items from clinical practice and appropriate statistical analyses of a large Alzheimer's data set...
December 18, 2018: Pharmaceutical Statistics
Junjing Lin, Margaret Gamalo-Siebers, Ram Tiwari
Drug developers are required to demonstrate substantial evidence of effectiveness through the conduct of adequate and well-controlled (A&WC) studies to obtain marketing approval of their medicine. What constitutes A&WC is interpreted as the conduct of randomized controlled trials (RCTs). However, these trials are sometimes unfeasible because of their size, duration, and cost. One way to reduce sample size is to leverage information on the control through a prior. One consideration when forming data-driven prior is the consistency of the external and the current data...
December 9, 2018: Pharmaceutical Statistics
Kaspar Rufibach
A draft addendum to ICH E9 has been released for public consultation in August 2017. The addendum focuses on two topics particularly relevant for randomized confirmatory clinical trials: estimands and sensitivity analyses. The need to amend ICH E9 grew out of the realization of a lack of alignment between the objectives of a clinical trial stated in the protocol and the accompanying quantification of the "treatment effect" reported in a regulatory submission. We embed time-to-event endpoints in the estimand framework and discuss how the four estimand attributes described in the addendum apply to time-to-event endpoints...
November 26, 2018: Pharmaceutical Statistics
Jianrong Wu, Li Chen, Jing Wei, Heidi Weiss, Rachel W Miller, John L Villano
Molecularly targeted, genomic-driven, and immunotherapy-based clinical trials continue to be advanced for the treatment of relapse or refractory cancer patients, where the growth modulation index (GMI) is often considered a primary endpoint of treatment efficacy. However, there little literature is available that considers the trial design with GMI as the primary endpoint. In this article, we derived a sample size formula for the score test under a log-linear model of the GMI. Study designs using the derived sample size formula are illustrated under a bivariate exponential model, the Weibull frailty model, and the generalized treatment effect size...
November 20, 2018: Pharmaceutical Statistics
Steffen Unkel, Marjan Amiri, Norbert Benda, Jan Beyersmann, Dietrich Knoerzer, Katrin Kupas, Frank Langer, Friedhelm Leverkus, Anja Loos, Claudia Ose, Tanja Proctor, Claudia Schmoor, Carsten Schwenke, Guido Skipka, Kristina Unnebrink, Florian Voss, Tim Friede
The analysis of adverse events (AEs) is a key component in the assessment of a drug's safety profile. Inappropriate analysis methods may result in misleading conclusions about a therapy's safety and consequently its benefit-risk ratio. The statistical analysis of AEs is complicated by the fact that the follow-up times can vary between the patients included in a clinical trial. This paper takes as its focus the analysis of AE data in the presence of varying follow-up times within the benefit assessment of therapeutic interventions...
November 20, 2018: Pharmaceutical Statistics
Paola Berchialla, Sarah Zohar, Ileana Baldi
The Simon's two-stage design is the most commonly applied among multi-stage designs in phase IIA clinical trials. It combines the sample sizes at the two stages in order to minimize either the expected or the maximum sample size. When the uncertainty about pre-trial beliefs on the expected or desired response rate is high, a Bayesian alternative should be considered since it allows to deal with the entire distribution of the parameter of interest in a more natural way. In this setting, a crucial issue is how to construct a distribution from the available summaries to use as a clinical prior in a Bayesian design...
November 15, 2018: Pharmaceutical Statistics
Gosuke Homma, Takashi Daimon
In placebo-controlled, double-blinded, randomized clinical trials, the presence of placebo responders reduces the effect size for comparison of the active drug group with the placebo group. An attempt to resolve this problem is to use the sequential parallel comparison design (SPCD). Although there are SPCDs with dichotomous or continuous outcomes, an SPCD with negative binomial outcomes-with which investigators deal eg, in clinical trials involving multiple sclerosis, where the investigators are still concerned about the presence of placebo responders-has not yet been discussed...
November 8, 2018: Pharmaceutical Statistics
Steven A Julious
For any estimate of response, confidence intervals are important as they help quantify a plausible range of values for the population response. However, there may be instances in clinical research when the population size is finite, but we wish to take a sample from the population and make inference from this sample. Instances where you can have a fixed population size include when undertaking a clinical audit of patient records or in a clinical trial a researcher could be checking for transcription errors against patient notes...
November 8, 2018: Pharmaceutical Statistics
Fetch more papers »
Fetching more papers... Fetching...
Read by QxMD. Sign in or create an account to discover new knowledge that matter to you.
Remove bar
Read by QxMD icon Read

Search Tips

Use Boolean operators: AND/OR

diabetic AND foot
diabetes OR diabetic

Exclude a word using the 'minus' sign

Virchow -triad

Use Parentheses

water AND (cup OR glass)

Add an asterisk (*) at end of a word to include word stems

Neuro* will search for Neurology, Neuroscientist, Neurological, and so on

Use quotes to search for an exact phrase

"primary prevention of cancer"
(heart or cardiac or cardio*) AND arrest -"American Heart Association"