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Pharmaceutical Statistics

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https://www.readbyqxmd.com/read/29667367/how-to-use-prior-knowledge-and-still-give-new-data-a-chance
#1
Kristina Weber, Rob Hemmings, Armin Koch
A common challenge for the development of drugs in rare diseases and special populations, eg, paediatrics, is the small numbers of patients that can be recruited into clinical trials. Extrapolation can be used to support development and licensing in paediatrics through the structured integration of available data in adults and prospectively generated data in paediatrics to derive conclusions that support licensing decisions in the target paediatric population. In this context, Bayesian analyses have been proposed to obtain formal proof of efficacy of a new drug or therapeutic principle by using additional information (data, opinion, or expectation), expressed through a prior distribution...
April 17, 2018: Pharmaceutical Statistics
https://www.readbyqxmd.com/read/29635777/practical-experiences-of-adopting-assurance-as-a-quantitative-framework-to-support-decision-making-in-drug-development
#2
Adam Crisp, Sam Miller, Douglas Thompson, Nicky Best
All clinical trials are designed for success of their primary objectives. Hence, evaluating the probability of success (PoS) should be a key focus at the design stage both to support funding approval from sponsor governance boards and to inform trial design itself. Use of assurance-that is, expected success probability averaged over a prior probability distribution for the treatment effect-to quantify PoS of a planned study has grown across the industry in recent years, and has now become routine within the authors' company...
April 10, 2018: Pharmaceutical Statistics
https://www.readbyqxmd.com/read/29624854/an-evaluation-of-the-trimmed-mean-approach-in-clinical-trials-with-dropout
#3
Ming-Dauh Wang, Jiajun Liu, Geert Molenberghs, Craig Mallinckrodt
The trimmed mean is a method of dealing with patient dropout in clinical trials that considers early discontinuation of treatment a bad outcome rather than leading to missing data. The present investigation is the first comprehensive assessment of the approach across a broad set of simulated clinical trial scenarios. In the trimmed mean approach, all patients who discontinue treatment prior to the primary endpoint are excluded from analysis by trimming an equal percentage of bad outcomes from each treatment arm...
April 6, 2018: Pharmaceutical Statistics
https://www.readbyqxmd.com/read/29603614/better-decision-making-in-drug-development-through-adoption-of-formal-prior-elicitation
#4
Nigel Dallow, Nicky Best, Timothy H Montague
With the continued increase in the use of Bayesian methods in drug development, there is a need for statisticians to have tools to develop robust and defensible informative prior distributions. Whilst relevant empirical data should, where possible, provide the basis for such priors, it is often the case that limitations in data and/or our understanding may preclude direct construction of a data-based prior. Formal expert elicitation methods are a key technique that can be used to determine priors in these situations...
March 30, 2018: Pharmaceutical Statistics
https://www.readbyqxmd.com/read/29473295/bayesian-joint-modelling-of-benefit-and-risk-in-drug-development
#5
Maria J Costa, Thomas Drury
To gain regulatory approval, a new medicine must demonstrate that its benefits outweigh any potential risks, ie, that the benefit-risk balance is favourable towards the new medicine. For transparency and clarity of the decision, a structured and consistent approach to benefit-risk assessment that quantifies uncertainties and accounts for underlying dependencies is desirable. This paper proposes two approaches to benefit-risk evaluation, both based on the idea of joint modelling of mixed outcomes that are potentially dependent at the subject level...
February 22, 2018: Pharmaceutical Statistics
https://www.readbyqxmd.com/read/29473291/bayesian-approach-for-assessing-noninferiority-in-a-three-arm-trial-with-binary-endpoint
#6
Santu Ghosh, Ram C Tiwari, Samiran Ghosh
With the recent advancement in many therapeutic areas, quest for better and enhanced treatment options is ever increasing. While the "efficacy" metric plays the most important role in this development, emphasis on other important clinical factors such as less intensive side effects, lower toxicity, ease of delivery, and other less debilitating factors may result in the selection of treatment options, which may not beat current established treatment option in terms efficacy, yet prove to be desirable for subgroups of patients...
February 22, 2018: Pharmaceutical Statistics
https://www.readbyqxmd.com/read/29460413/bayesian-statistical-models-to-estimate-eq-5d-utility-scores-from-eortc-qlq-data-in-myeloma
#7
Samer A Kharroubi, Richard Edlin, David Meads, Christopher McCabe
It is well documented that the modelling of health-related quality of life data is difficult as the distribution of such data is often strongly right/left skewed and it includes a significant percentage of observations at one. The objective of this study is to develop a series of two-part models (TPMs) that deal with these issues. Data from the UK Medical Research Council Myeloma IX trial were used to examine the relationship between the European Organization for Research and Treatment of Cancer (EORTC) QLQ-C30/QLQ-MY20 scores and the European QoL-5 Dimensions (EQ-5D) utility score...
February 20, 2018: Pharmaceutical Statistics
https://www.readbyqxmd.com/read/29424120/longitudinal-assessment-of-the-impact-of-multiple-switches-between-a-biosimilar-and-its-reference-product-on-efficacy-parameters
#8
Johanna Mielke, Heike Woehling, Byron Jones
Patients, physicians, and health care providers in Europe have more than 10 years of experience with biosimilars. However, there are still debates if switching between a biosimilar and its reference product influences the efficacy of the treatment. In this paper, we address this uncertainty by developing a formal statistical test that can be used for showing that switching has no negative impact on the efficacy of biosimilars. For that, we first introduce a linear mixed-effects model that is used for defining the null hypothesis (switching influences the efficacy) and the alternative hypothesis (switching has no influence on the efficacy)...
February 8, 2018: Pharmaceutical Statistics
https://www.readbyqxmd.com/read/29372582/bayesian-dose-finding-phase-i-trial-design-incorporating-historical-data-from-a-preceding-trial
#9
Kentaro Takeda, Satoshi Morita
We consider the problem of incorporating historical data from a preceding trial to design and conduct a subsequent dose-finding trial in a possibly different population of patients. In oncology, for example, after a phase I dose-finding trial is completed in Caucasian patients, investigators often conduct a further phase I trial to determine the maximum tolerated dose in Asian patients. This may be due to concerns about possible differences in treatment tolerability between populations. In this study, we propose to adaptively incorporate historical data into prior distributions assumed in a new dose-finding trial...
January 25, 2018: Pharmaceutical Statistics
https://www.readbyqxmd.com/read/29359427/tobit-regression-for-modeling-mean-survival-time-using-data-subject-to-multiple-sources-of-censoring
#10
Qi Gong, Douglas E Schaubel
Mean survival time is often of inherent interest in medical and epidemiologic studies. In the presence of censoring and when covariate effects are of interest, Cox regression is the strong default, but mostly due to convenience and familiarity. When survival times are uncensored, covariate effects can be estimated as differences in mean survival through linear regression. Tobit regression can validly be performed through maximum likelihood when the censoring times are fixed (ie, known for each subject, even in cases where the outcome is observed)...
March 2018: Pharmaceutical Statistics
https://www.readbyqxmd.com/read/29322659/integrating-dose-estimation-into-a-decision-making-framework-for-model-based-drug-development
#11
James Dunyak, Patrick Mitchell, Bengt Hamrén, Gabriel Helmlinger, James Matcham, Donald Stanski, Nidal Al-Huniti
Model-informed drug discovery and development offers the promise of more efficient clinical development, with increased productivity and reduced cost through scientific decision making and risk management. Go/no-go development decisions in the pharmaceutical industry are often driven by effect size estimates, with the goal of meeting commercially generated target profiles. Sufficient efficacy is critical for eventual success, but the decision to advance development phase is also dependent on adequate knowledge of appropriate dose and dose-response...
March 2018: Pharmaceutical Statistics
https://www.readbyqxmd.com/read/29297979/development-of-predictive-signatures-for-treatment-selection-in-precision-medicine-with-survival-outcomes
#12
Yu-Chuan Chen, Un Jung Lee, Chen-An Tsai, James J Chen
For survival endpoints in subgroup selection, a score conversion model is often used to convert the set of biomarkers for each patient into a univariate score and using the median of the univariate scores to divide the patients into biomarker-positive and biomarker-negative subgroups. However, this may lead to bias in patient subgroup identification regarding the 2 issues: (1) treatment is equally effective for all patients and/or there is no subgroup difference; (2) the median value of the univariate scores as a cutoff may be inappropriate if the sizes of the 2 subgroups are differ substantially...
March 2018: Pharmaceutical Statistics
https://www.readbyqxmd.com/read/29282862/use-of-a-historical-control-group-in-a-noninferiority-trial-assessing-a-new-antibacterial-treatment-a-case-study-and-discussion-of-practical-implementation-aspects
#13
David Dejardin, Paul Delmar, Charles Warne, Katie Patel, Joost van Rosmalen, Emmanuel Lesaffre
When recruitment into a clinical trial is limited due to rarity of the disease of interest, or when recruitment to the control arm is limited due to ethical reasons (eg, pediatric studies or important unmet medical need), exploiting historical controls to augment the prospectively collected database can be an attractive option. Statistical methods for combining historical data with randomized data, while accounting for the incompatibility between the two, have been recently proposed and remain an active field of research...
March 2018: Pharmaceutical Statistics
https://www.readbyqxmd.com/read/29266692/response-adaptive-designs-for-binary-responses-how-to-offer-patient-benefit-while-being-robust-to-time-trends
#14
Sofía S Villar, Jack Bowden, James Wason
Response-adaptive randomisation (RAR) can considerably improve the chances of a successful treatment outcome for patients in a clinical trial by skewing the allocation probability towards better performing treatments as data accumulates. There is considerable interest in using RAR designs in drug development for rare diseases, where traditional designs are not either feasible or ethically questionable. In this paper, we discuss and address a major criticism levelled at RAR: namely, type I error inflation due to an unknown time trend over the course of the trial...
March 2018: Pharmaceutical Statistics
https://www.readbyqxmd.com/read/29178367/estimation-of-discrete-survival-function-for-error-prone-diagnostic-tests
#15
Abidemi K Adeniji, Jesse Y Hsu, Abdus S Wahed
The product limit or Kaplan-Meier (KM) estimator is commonly used to estimate the survival function in the presence of incomplete time to event. Application of this method assumes inherently that the occurrence of an event is known with certainty. However, the clinical diagnosis of an event is often subject to misclassification due to assay error or adjudication error, by which the event is assessed with some uncertainty. In the presence of such errors, the true distribution of the time to first event would not be estimated accurately using the KM method...
February 2018: Pharmaceutical Statistics
https://www.readbyqxmd.com/read/29125220/a-dynamic-power-prior-for-borrowing-historical-data-in-noninferiority-trials-with-binary-endpoint
#16
G Frank Liu
Traditionally, noninferiority hypotheses have been tested using a frequentist method with a fixed margin. Given that information for the control group is often available from previous studies, it is interesting to consider a Bayesian approach in which information is "borrowed" for the control group to improve efficiency. However, construction of an appropriate informative prior can be challenging. In this paper, we consider a hybrid Bayesian approach for testing noninferiority hypotheses in studies with a binary endpoint...
February 2018: Pharmaceutical Statistics
https://www.readbyqxmd.com/read/29110389/equivalence-testing-for-similarity-in-bioassays-using-bioequivalence-criteria-on-the-relative-bioactivity
#17
Corine Baljé-Volkers, Thembile Mzolo, Erik Talens, Pieta IJzerman-Boon, Edwin Van den Heuvel
Similarity in bioassays means that the test preparation behaves as a dilution of the standard preparation with respect to their biological effect. Thus, similarity must be investigated to confirm this biological property. Historically, this was typically conducted with traditional hypothesis testing, but this has received substantial criticism. Failing to reject similarity does not imply that the 2 preparations are similar. Also, rejecting similarity when bioassay variability is small might simply demonstrate a nonrelevant deviation in similarity...
February 2018: Pharmaceutical Statistics
https://www.readbyqxmd.com/read/29098766/some-statistical-considerations-in-the-clinical-development-of-cancer-immunotherapies
#18
Bo Huang
Immuno-oncology has emerged as an exciting new approach to cancer treatment. Common immunotherapy approaches include cancer vaccine, effector cell therapy, and T-cell-stimulating antibody. Checkpoint inhibitors such as cytotoxic T lymphocyte-associated antigen 4 and programmed death-1/L1 antagonists have shown promising results in multiple indications in solid tumors and hematology. However, the mechanisms of action of these novel drugs pose unique statistical challenges in the accurate evaluation of clinical safety and efficacy, including late-onset toxicity, dose optimization, evaluation of combination agents, pseudoprogression, and delayed and lasting clinical activity...
February 2018: Pharmaceutical Statistics
https://www.readbyqxmd.com/read/29094519/the-plan-of-enrichment-designs-for-dealing-with-high-placebo-response
#19
Xiangmin Zhang, Yeh-Fong Chen, Roy Tamura
To deal with high placebo response in clinical trials for psychiatric and other diseases, different enrichment designs, such as the sequential parallel design, two-way enriched design, and sequential enriched design, have been proposed and implemented recently. Depending on the historical trial information and the trial sponsors' resources, detailed design elements are needed for determining which design to adopt. To assist in making more suitable decisions, we perform evaluations for selecting required design elements in terms of power optimization and sample size planning...
February 2018: Pharmaceutical Statistics
https://www.readbyqxmd.com/read/29094501/a-simple-doubly-robust-efficient-estimator-for-survival-functions-using-pseudo-observations
#20
Jixian Wang
Survival functions are often estimated by nonparametric estimators such as the Kaplan-Meier estimator. For valid estimation, proper adjustment for confounding factors is needed when treatment assignment may depend on confounding factors. Inverse probability weighting is a commonly used approach, especially when there is a large number of potential confounders to adjust for. Direct adjustment may also be used if the relationship between the time-to-event and all confounders can be modeled. However, either approach requires a correctly specified model for the relationship between confounders and treatment allocation or between confounders and the time-to-event...
February 2018: Pharmaceutical Statistics
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