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Establishment of RWS guidance reflecting contributions of China to regulatory science J. Biopharm. Stat. (IF 1.1) Pub Date : 2024-03-17 Jun Wang, Jie Chen, Jun Zhao, Ying Wu, Xiaona Xin, Pingyan Chen
China’s accession to the ICH has accelerated the advancement of its regulatory science. To foster innovation and improve the efficiency of pharmaceutical research and development, the China Nationa...
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DOD-Combo: Bayesian dose finding design in combination trials with meta-analytic-predictive prior J. Biopharm. Stat. (IF 1.1) Pub Date : 2024-03-11 Kai Chen, Yunqi Zhao, Meizi Liu, Jianchang Lin, Rachael Liu
Combination therapy, a treatment modality that involves multiple treatment agents, has become imperative for improving treatment effectiveness and addressing resistance in the field of oncology. Ho...
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Modelling alternately recurring events using subject specific hazard estimation approach J. Biopharm. Stat. (IF 1.1) Pub Date : 2024-03-03 Moumita Chatterjee, Sugata Sen Roy, Bhaswati Ganguli
The motivation for this paper is to account for subject specific variations in a Cox proportional hazard model for alternating recurrent events. This is done through two sets of frailty components,...
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A basket trial design based on constrained hierarchical Bayesian model for latent subgroups J. Biopharm. Stat. (IF 1.1) Pub Date : 2024-02-18 Kentaro Takeda, Atsuki Hashimoto, Shufang Liu, Alan Rong
It is well known a basket trial consisting of multiple cancer types has the potential of borrowing strength across the baskets defined by the cancer types, leading to an efficient design in terms o...
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Considerations for master protocols using external controls J. Biopharm. Stat. (IF 1.1) Pub Date : 2024-02-16 Jie Chen, Xiaoyun (Nicole) Li, Chengxing (Cindy) Lu, Sammy Yuan, Godwin Yung, Jingjing Ye, Hong Tian, Jianchang Lin
There has been an increasing use of master protocols in oncology clinical trials because of its efficiency to accelerate cancer drug development and flexibility to accommodate multiple substudies. ...
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[Special issue PRO] Considering endpoints for comparative tolerability of cancer treatments using patient report given the estimand framework J. Biopharm. Stat. (IF 1.1) Pub Date : 2024-02-15 John Devin Peipert, Monique Breslin, Ethan Basch, Melanie Calvert, David Cella, Mary Lou Smith, Gita Thanarajasingam, Jessica Roydhouse
Regulatory agencies are advancing the use of systematic approaches to collect patient experience data, including patient-reported outcomes (PROs), in cancer clinical trials to inform regulatory dec...
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The impact of different data handling strategies in exploratory and confirmatory factor analysis of diary measures: an evaluation using simulated and real-world asthma nighttime symptoms diary data J. Biopharm. Stat. (IF 1.1) Pub Date : 2024-02-14 Gerasimos Dumi, Dara O’Neill, Christina Daskalopoulou, Tom Keeley, Stephanie Rhoten, Dharmraj Sauriyal, Piper Fromy
Daily diaries are an important modality for patient-reported outcome assessment. They typically comprise multiple questions, so understanding their underlying structure is key to appropriate analys...
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Miettinen and Nurminen score statistics revisited J. Biopharm. Stat. (IF 1.1) Pub Date : 2024-02-09 Antonio Martín Andrés, Francisco Gayá Moreno, María Álvarez Hernández, Inmaculada Herranz Tejedor
It is commonly necessary to perform inferences on the difference, ratio, and odds ratio of two proportions p1 and p2 based on two independent samples. For this purpose, the most common asymptotic s...
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Combination MCP-Mod for two-drug combination dose-ranging studies J. Biopharm. Stat. (IF 1.1) Pub Date : 2024-02-09 Yifan Zhou, Abigail Sloan, Sandeep Menon, Ling Wang
Combination therapies with multiple mechanisms of action can offer improved efficacy and/or safety profiles when compared to a single therapy with one mechanism of action. Consequently, the number ...
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Sample size estimation for recurrent event data using multifrailty and multilevel survival models J. Biopharm. Stat. (IF 1.1) Pub Date : 2024-02-09 Derek Dinart, Carine Bellera, Virginie Rondeau
In epidemiology and clinical research, recurrent events refer to individuals who are likely to experience transient clinical events repeatedly over an observation period. Examples include hospitali...
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Comments on ”Emerging insights and commentaries – MMRM vs LOCF by Naitee Ting” J. Biopharm. Stat. (IF 1.1) Pub Date : 2024-01-14 David Wright, Daniel J. Bratton, Thomas Drury, Oliver N. Keene, Sunita Rehal, Ian R. White
Published in Journal of Biopharmaceutical Statistics (Vol. 34, No. 1, 2024)
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Response to Comment on “Emerging insights and commentaries – MMRM vs LOCF by Naitee Ting” J. Biopharm. Stat. (IF 1.1) Pub Date : 2024-01-14 Naitee Ting
Published in Journal of Biopharmaceutical Statistics (Vol. 34, No. 1, 2024)
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Interval estimation of relative risks for combined unilateral and bilateral correlated data J. Biopharm. Stat. (IF 1.1) Pub Date : 2024-01-09 Kejia Wang, Chang-Xing Ma
Measurements are generally collected as unilateral or bilateral data in clinical trials, epidemiology, or observational studies. For example, in ophthalmology studies, the primary outcome is often ...
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Retraction: A Bayesian joint model for multivariate longitudinal and time-to-event data with application to ALL maintenance studies J. Biopharm. Stat. (IF 1.1) Pub Date : 2024-01-08
Published in Journal of Biopharmaceutical Statistics (Ahead of Print, 2024)
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Interval estimation of common risk difference for stratified unilateral and bilateral data✩ J. Biopharm. Stat. (IF 1.1) Pub Date : 2024-01-05 Shuman Sun, Zhiming Li, Keyi Mou
In clinical trials, unilateral or bilateral data can usually be encountered if a subject contributes one or both of paired organs. For the bilateral data, responses from two paired body parts are c...
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Bayesian phase II adaptive randomization by jointly modeling efficacy and toxicity as time-to-event outcomes J. Biopharm. Stat. (IF 1.1) Pub Date : 2024-01-01 Yu-Mei Chang, Pao-Sheng Shen, Chun-Ying Ho
The main goals of Phase II trials are to identify the therapeutic efficacy of new treatments and continue monitoring all the possible adverse effects. In Phase II trials, it is important to develop...
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Generalized triple outcome decision-making in basket trials J. Biopharm. Stat. (IF 1.1) Pub Date : 2024-01-02 Miao Zang, Rui Liu
Making the go/no-go decision is critical in Phase II (or Ib) clinical trials. The conventional decision-making framework based on a binary hypothesis testing has been gradually replaced by the TODe...
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Directed Acyclic Graph Assisted Method For Estimating Average Treatment Effect J. Biopharm. Stat. (IF 1.1) Pub Date : 2023-12-27 Jingchao Sun, Scott Duncan, Subhadip Pal, Maiying Kong
Observational data, such as electronic clinical records and claims data, can prove invaluable for evaluating the Average Treatment Effect (ATE) and supporting decision-making, provided they are emp...
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Sequential monitoring of cancer immunotherapy trial with random delayed treatment effect J. Biopharm. Stat. (IF 1.1) Pub Date : 2023-12-25 Jianrong Wu, Liang Zhu, Yimei Li
Cancer immunotherapy trials are frequently characterized by a delayed treatment effect that violates the proportional hazards assumption. The log-rank test (LRT) suffers a substantial loss of stati...
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Data-driven monitoring for phase II clinical trial designs based on percentile event time test J. Biopharm. Stat. (IF 1.1) Pub Date : 2023-12-22 Yeonhee Park, Zhanpeng Xu
The goal of phase II clinical trials is to evaluate the therapeutic efficacy of a new drug. Some investigators want to use the time-to-event endpoint as the primary endpoint of the phase II study t...
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MIDAS-2: an enhanced Bayesian platform design for immunotherapy combinations with subgroup efficacy exploration J. Biopharm. Stat. (IF 1.1) Pub Date : 2023-12-22 Liwen Su, Xin Chen, Jingyi Zhang, Fangrong Yan
Although immunotherapy combinations have revolutionised cancer treatment, the rapid screening of effective and optimal therapies from large numbers of candidate combinations, as well as exploring s...
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Bayesian model averaging of longitudinal dose-response models J. Biopharm. Stat. (IF 1.1) Pub Date : 2023-12-17 Richard D. Payne, Pallavi Ray, Mitchell A. Thomann
Selecting a safe and clinically beneficial dose can be difficult in drug development. Dose justification often relies on dose-response modeling where parametric assumptions are made in advance whic...
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Addressing sequential and concurrent treatment regimens in a small n sequential, multiple assignment, randomized trial (snSMART) in the MISTIC study J. Biopharm. Stat. (IF 1.1) Pub Date : 2023-12-14 Yuwei Cheng, Adriana Tremoulet, Jane Burns, Sonia Jain
Multisystem Inflammatory Syndrome in children (MIS-C) is a rare and novel pediatric complication linked to COVID-19 exposure, which was first identified in April 2020. A small n, Sequential, Multip...
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Providing meaningful interpretation of performance outcome measures by co-calibration with patient-reported outcomes through the Rasch model: illustration with multiple sclerosis measures J. Biopharm. Stat. (IF 1.1) Pub Date : 2023-11-26 Antoine Regnault, Juliette Meunier, Anna Ciesluk, Wenting Cheng, Bing Zhu
Performance outcome (PerfO) measures are based on tasks performed by patients in a controlled environment, making their meaningful interpretation challenging to establish. Co-calibrating PerfO and ...
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Adaptive platform trials: the impact of common controls on type one error and power J. Biopharm. Stat. (IF 1.1) Pub Date : 2023-11-21 Quynh Nguyen, Katharina Hees, Benjamin Hofner
Platform trials offer a framework to study multiple interventions in one trial with the opportunity of opening and closing arms. The use of common controls can increase efficiency as compared to in...
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Meaningful within-patient change for clinical outcome assessments: model-based approach versus cumulative distribution functions J. Biopharm. Stat. (IF 1.1) Pub Date : 2023-11-20 Jinma Ren, Andrew G. Bushmakin, Paul R. Cislo, Lucy Abraham, Joseph C. Cappelleri, Robert H. Dworkin, John T. Farrar
The FDA recommends the use of anchor-based methods and empirical cumulative distribution function (eCDF) curves to establish a meaningful within-patient change (MWPC) for a clinical outcome assessm...
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Reflections on estimands for patient-reported outcomes in cancer clinical trials J. Biopharm. Stat. (IF 1.1) Pub Date : 2023-11-19 Rachael Lawrance, Konstantina Skaltsa, Antoine Regnault, Lysbeth Floden
It is common and important to include the patient’s perspective of the impact of treatment on health-related quality of life (HRQoL) outcomes. In this commentary, we focus on applying the new adden...
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Adjusted win ratio using the inverse probability of treatment weighting J. Biopharm. Stat. (IF 1.1) Pub Date : 2023-11-10 Duolao Wang, Sirui Zheng, Ying Cui, Nengjie He, Tao Chen, Bo Huang
The win ratio method has been increasingly applied in the design and analysis of clinical trials. However, the win ratio method is a univariate approach that does not allow for adjusting for baseli...
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A composite semiparametric homogeneity test for the distributions of multigroup interval-bounded longitudinal data J. Biopharm. Stat. (IF 1.1) Pub Date : 2023-11-15 Zhanfeng Wang, Wenmei Li, Hao Ding, Dongsheng Tu
Motivated by comparing the distribution of longitudinal quality of life (QoL) data among different treatment groups from a cancer clinical trial, we propose a semiparametric test statistic for the ...
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Enhancement of Bayesian optimal interval design by accounting for overdose and underdose errors trade-offs J. Biopharm. Stat. (IF 1.1) Pub Date : 2023-11-15 Ryo Sadachi, Hiroyuki Sato, Takeo Fujiwara, Akihiro Hirakawa
Model-assisted designs, a new class of dose-finding designs for determining the maximum tolerated dose (MTD), model only the dose-limiting toxicity (DLT) data observed at the current dose based on ...
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Covariate-adjusted value-guided subgroup identification via boosting J. Biopharm. Stat. (IF 1.1) Pub Date : 2023-11-13 Jinchun Zhang, Pingye Zhang, Junshui Ma, Yue Shentu
It is widely recognized that treatment effects could differ across subgroups of patients. Subgroup analysis, which assesses such heterogeneity, provides valuable information in developing personali...
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Novel 3-arm wait-list controlled trial designs together with mixed-effects analysis improve precision of treatment effect estimators J. Biopharm. Stat. (IF 1.1) Pub Date : 2023-11-06 Xiangmei Ma, Yin Bun Cheung
Clinical trialists have long been searching for approaches to increase statistical power without increasing sample size. Conventional wait-list controlled (WLC) trials are limited to two trial arms...
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Referees for Volume 33 J. Biopharm. Stat. (IF 1.1) Pub Date : 2023-11-01
Published in Journal of Biopharmaceutical Statistics (Vol. 33, No. 6, 2023)
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Multiple test procedures of disease prevalence based on stratified partially validated series in the presence of a gold standard J. Biopharm. Stat. (IF 1.1) Pub Date : 2023-10-19 Shi-Fang Qiu, Xiao-Liang Zhang, Ying-Qiu Qu, Yuan-Quan Han
This paper discusses the problem of disease prevalence in clinical studies, focusing on multiple comparisons based on stratified partially validated series in the presence of a gold standard. Five ...
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Estimation of treatment effects in early-phase randomized clinical trials involving external control data J. Biopharm. Stat. (IF 1.1) Pub Date : 2023-10-12 Heiko Götte, Marietta Kirchner, Johannes Krisam, Arthur Allignol, Armin Schüler, Meinhard Kieser
There are good reasons to perform a randomized controlled trial (RCT) even in early phases of clinical development. However, the low sample sizes in those settings lead to high variability of the t...
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The impact of misclassification errors on the performance of biomarkers based on next-generation sequencing, a simulation study J. Biopharm. Stat. (IF 1.1) Pub Date : 2023-10-11 Dong Wang, Sue-Jane Wang, Samir Lababidi
The development of next-generation sequencing (NGS) opens opportunities for new applications such as liquid biopsy, in which tumor mutation genotypes can be determined by sequencing circulating tum...
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Whole-cage randomization for animal studies with unequal cage or group sizes J. Biopharm. Stat. (IF 1.1) Pub Date : 2023-09-19 Tianhui Zhang, Benjamin Phillips, Natasha Karp, Junmin Wang, Steven Novick
Following good statistical practice, in vivo study investigators allocate animals into two or more treatment groups using a randomization routine to eliminate selection bias and balance known and u...
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CORRECTION J. Biopharm. Stat. (IF 1.1) Pub Date : 2023-09-16
Published in Journal of Biopharmaceutical Statistics (Ahead of Print, 2023)
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Bayesian hierarchical model for dose-finding trial incorporating historical data J. Biopharm. Stat. (IF 1.1) Pub Date : 2023-09-07 Linxi Han, Qiqi Deng, Zhangyi He, Frank Fleischer, Feng Yu
ABSTRACT The Multiple Comparison Procedure and Modelling (MCPMod) approach has been shown to be a powerful statistical technique that can significantly improve the design and analysis of dose-finding studies under model uncertainty. Due to its frequentist nature, however, it is difficult to incorporate information into MCPMod from historical trials on the same drug. BMCPMod, a recently introduced Bayesian
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On variance estimation of target population created by inverse probability weighting J. Biopharm. Stat. (IF 1.1) Pub Date : 2023-08-24 Jinmei Chen, Rui Chen, Yuhao Feng, Ming Tan, Pingyan Chen, Ying Wu
ABSTRACT Inverse probability weighting (IPW) is frequently used to reduce or minimize the observed confounding in observational studies. IPW creates a pseudo-sample by weighting each individual by the inverse of the conditional probability of receiving the treatment level that he/she has actually received. In the pseudo-sample there is no variation among the multiple individuals generated by weighting
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Stochastic curtailment tests for phase II trial with time-to-event outcome using the concept of relative time in the case of non-proportional hazards J. Biopharm. Stat. (IF 1.1) Pub Date : 2023-08-14 Palash Sharma, Milind A. Phadnis
ABSTRACT As part of the drug development process, interim analysis is frequently used to design efficient phase II clinical trials. A stochastic curtailment framework is often deployed wherein a decision to continue or curtail the trial is taken at each interim look based on the likelihood of observing a positive or negative treatment effect if the trial were to continue to its anticipated end. Thus
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Determining the late effect parameter in the Fleming-Harrington test using asymptotic relative efficiency in cancer immunotherapy clinical trials J. Biopharm. Stat. (IF 1.1) Pub Date : 2023-08-10 Yuichiro Kaneko, Satoshi Morita
ABSTRACT The delayed treatment effect, which manifests as a separation of survival curves after a change point, has often been observed in immunotherapy clinical trials. A late effect of this kind may violate the proportional hazards assumption, resulting in the non-negligible loss of statistical power of an ordinary log-rank test when comparing survival curves. The Fleming-Harrington (FH) test, a
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Pediatric needs should be considered early in the clinical development lifecycle J. Biopharm. Stat. (IF 1.1) Pub Date : 2023-08-08 Margaret Gamalo, Jingjing Ye, YounJeong Choi, Rima Izem
Published in Journal of Biopharmaceutical Statistics (Vol. 33, No. 6, 2023)
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Sample size reestimation and Bayesian predictive probability for single-arm clinical trials with a time-to-event endpoint using Weibull distribution with unknown shape parameter J. Biopharm. Stat. (IF 1.1) Pub Date : 2023-08-06 Muhammad Waleed, Jianghua He, Milind A. Phadnis
ABSTRACT This manuscript consists of two topics. Firstly, we explore the utility of internal pilot study (IPS) approach for reestimating sample size at an interim stage when a reliable estimate of the nuisance shape parameter of the Weibull distribution for modeling survival data is unavailable during the planning phase of a study. Although IPS approach can help rescue the study power, it is noted
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Adaptive Multiple Comparison Sequential Design (AMCSD) for clinical trials J. Biopharm. Stat. (IF 1.1) Pub Date : 2023-08-01 Ping Gao, Yingqiu Li
ABSTRACT We propose an adaptive sequential testing procedure for clinical trials that test the efficacy of multiple treatment options, such as dose/regimen, different drugs, sub-populations, endpoints, or a mixture of them in one trial. At any interim analyses, sample size re-estimation can be conducted, and any option can be dropped for lack of efficacy or unsatisfactory safety profile. Inference
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Special Issue PRO-Analysis of Clinically Meaningful Change on Patient-Reported Outcomes: Renewed Insights About Covariate Adjustment J. Biopharm. Stat. (IF 1.1) Pub Date : 2023-08-01 Joseph C. Cappelleri, Paul R. Cislo
ABSTRACT Determining clinically meaningful change (CMC) in a patient-reported (PRO) measure is central to its existence in gauging how patients feel and function, especially for evaluating a treatment effect. Anchor-based approaches are recommended to estimate a CMC threshold on a PRO measure. Determination of CMC involves linking changes or differences in the target PRO measure to that in an external
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Simulating survival data when one subgroup lacks information J. Biopharm. Stat. (IF 1.1) Pub Date : 2023-07-26 Yiqi Zhao, Ping Yan, Xinfeng Yang
ABSTRACT In this paper, we aim to show the process of simulating survival data when the distribution of the overall population and one subgroup (called “positive subgroup”) as well as the proportion of the subgroup is known, while the distribution of the other subgroup (called “negative subgroup”) is unknown. We propose a combination method which generates survival data of the positive subgroup and
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Incorporating patient-reported outcomes in dose-finding clinical trials with continuous patient enrollment J. Biopharm. Stat. (IF 1.1) Pub Date : 2023-07-26 Anaïs Andrillon, Lucie Biard, Shing M. Lee
ABSTRACT Dose-finding clinical trials in oncology estimate the maximum tolerated dose (MTD), based on toxicity obtained from the clinician’s perspective. While the collection of patient-reported outcomes (PROs) has been advocated to better inform treatment tolerability, there is a lack of guidance and methods on how to use PROs for dose assignments and recommendations. The PRO continual reassessment
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Direct estimation of volume under the ROC surface with verification bias J. Biopharm. Stat. (IF 1.1) Pub Date : 2023-07-20 Shuangfei Shi, Gengsheng Qin
ABSTRACT In practice, the receiver operating characteristic (ROC) curve of a diagnostic test is widely used to show the performance of the test for discriminating two-class events. The area under the ROC curve (AUC) is proposed as an index for the assessment of the diagnostic accuracy of the test under consideration. Due to ethical and cost considerations associated with application of gold standard
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A Bayesian phase I–II clinical trial design to find the biological optimal dose on drug combination J. Biopharm. Stat. (IF 1.1) Pub Date : 2023-07-17 Ziqing Wang, Jingyi Zhang, Tian Xia, Ruyue He, Fangrong Yan
ABSTRACT In recent years, combined therapy shows expected treatment effect as they increase dose intensity, work on multiple targets and benefit more patients for antitumor treatment. However, dose -finding designs for combined therapy face a number of challenges. Therefore, under the framework of phase I–II, we propose a two-stage dose -finding design to identify the biologically optimal dose combination
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A new type of generalized information criterion for regularization parameter selection in penalized regression with application to treatment process data J. Biopharm. Stat. (IF 1.1) Pub Date : 2023-07-17 Amir Hossein Ghatari, Mina Aminghafari
ABSTRACT We propose a new approach to select the regularization parameter using a new version of the generalized information criterion ( GICGIC ) in the subject of penalized regression. We prove the identifiability of bridge regression model as a prerequisite of statistical modeling. Then, we propose asymptotically efficient generalized information criterion ( AGIC ) and prove that it has asymptotic
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Group sequential multi-arm multi-stage survival trial design with treatment selection J. Biopharm. Stat. (IF 1.1) Pub Date : 2023-07-16 Jianrong Wu, Yimei Li
ABSTRACT Multi-arm trials are increasingly of interest because for many diseases; there are multiple experimental treatments available for testing efficacy. Several novel multi-arm multi-stage (MAMS) clinical trial designs have been proposed. However, a major hurdle to adopting the group sequential MAMS routinely is the computational effort of obtaining stopping boundaries. For example, the method
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Two-stage response adaptive randomization designs for multi-arm trials with binary outcome J. Biopharm. Stat. (IF 1.1) Pub Date : 2023-07-15 Xinlin Lu, Guogen Shan
ABSTRACT In recent years, adaptive randomization methods have gained significant popularity in clinical research and trial design due to their ability to provide both efficiency and flexibility in adjusting the statistical procedures of ongoing clinical trials. For a study to compare multiple treatments, a multi-arm two-stage design could be utilized to select the best treatment from the first stage
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Statistical Considerations and Software for Designing Sequential, Multiple Assignment, Randomized Trials (SMART) with a Survival Final Endpoint J. Biopharm. Stat. (IF 1.1) Pub Date : 2023-07-11 Sasha Kravets, Amy S. Ruppert, Sawyer B. Jacobson, Jennifer G. Le-Rademacher, Sumithra J. Mandrekar
ABSTRACT Sequential, multiple assignment, randomized trial (SMART) designs are appropriate for comparing adaptive treatment interventions, in which intermediate outcomes (called tailoring variables) guide subsequent treatment decisions for individual patients. Within a SMART design, patients may be re-randomized to subsequent treatments following the outcomes of their intermediate assessments. In this
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Using Bayesian hierarchical models for controlled post hoc subgroup analysis of clinical trials: application to smoking cessation treatment in American Indians and Alaska Natives J. Biopharm. Stat. (IF 1.1) Pub Date : 2023-07-07 Elena Shergina, Kimber P. Richter, Christine Makosky Daley, Babalola Faseru, Won S. Choi, Byron J. Gajewski
ABSTRACT Clinical trials powered to detect subgroup effects provide the most reliable data on heterogeneity of treatment effect among different subpopulations. However, pre-specified subgroup analysis is not always practical and post hoc analysis results should be examined cautiously. Bayesian hierarchical modelling provides grounds for defining a controlled post hoc analysis plan that is developed
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Statistical considerations for some issues in clinical bridging studies evaluating companion diagnostic devices J. Biopharm. Stat. (IF 1.1) Pub Date : 2023-06-18 Changhong Song, Xiaoqin Xiong, Sunghee Kim, Zhiheng Xu, Dandan Xu, Bipasa Biswas
ABSTRACT An in vitro diagnostic device (IVD) that is essential for the safe and effective use of a corresponding therapeutic product is commonly referred to as companion diagnostic device. Clinical trials using companion diagnostic devices (tests) together with therapies can yield the information necessary to address whether both products are safe and effective. A clinical trial ideally assesses safety
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Generalized exponentiated unit Gompertz distribution for modeling arthritic pain relief times data: classical approach to statistical inference J. Biopharm. Stat. (IF 1.1) Pub Date : 2023-05-29 Tabassum Naz Sindhu, Anum Shafiq, Zawar Huassian
ABSTRACT Arthritis is the tenderness and swelling of one or more of the joints. Arthritis therapies are directed mainly at reducing symptoms and improving quality of life. In this article, we introduced a novel four parametric model known as generalized exponentiated unit Gompertz (GEUG) for modeling a clinical trial data which represent the relief or relaxing times of arthritic patients receiving
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Dissecting the restricted mean time in favor of treatment J. Biopharm. Stat. (IF 1.1) Pub Date : 2023-05-24 Lu Mao, Tuo Wang
The restricted mean time in favor (RMT-IF) summarizes the treatment effect on a hierarchical composite endpoint with mortality at the top. Its crude decomposition into “stage-wise effects,” i.e., t...
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Applying latent profile analysis to identify adolescents and young adults with chronic conditions at risk for poor health-related quality of life J. Biopharm. Stat. (IF 1.1) Pub Date : 2023-05-14 Suwei Wang, Cara J. Arizmendi, Dandan Chen, Li Lin, Dan V. Blalock, I-Chan Huang, David Thissen, Darren A. DeWalt, Wei Pan, Bryce B. Reeve
ABSTRACT The impact of chronic diseases on health-related quality of life (HRQOL) in adolescents and young adults (AYAs) is understudied. Latent profile analysis (LPA) can identify profiles of AYAs based on their HRQOL scores reflecting physical, mental, and social well-being. This paper will (1) demonstrate how to use LPA to identify profiles of AYAs based on their scores on multiple HRQOL indicators;
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scRAA: the development of a robust and automatic annotation procedure for single-cell RNA sequencing data J. Biopharm. Stat. (IF 1.1) Pub Date : 2023-05-10 Dongyan Yan, Zhe Sun, Jiyuan Fang, Shanshan Cao, Wenjie Wang, Xinyue Chang, Sarkhan Badirli, Haoda Fu, Yushi Liu
ABSTRACT A critical task in single-cell RNA sequencing (scRNA-Seq) data analysis is to identify cell types from heterogeneous tissues. While the majority of classification methods demonstrated high performance in scRNA-Seq annotation problems, a robust and accurate solution is desired to generate reliable outcomes for downstream analyses, for instance, marker genes identification, differentially expressed