Pharmaceutical Statistics最新文献_第8页

PKBOIN-12: A Bayesian Optimal Interval Phase I/II Design Incorporating Pharmacokinetics Outcomes to Find the Optimal Biological Dose. PKBOIN-12：贝叶斯最优间隔 I/II 期设计，纳入药代动力学结果以找到最佳生物剂量。

IF 1.3 4区医学

Pharmaceutical Statistics Pub Date : 2024-10-24 DOI: 10.1002/pst.2444

Hao Sun, Jieqi Tu

{"title":"PKBOIN-12: A Bayesian Optimal Interval Phase I/II Design Incorporating Pharmacokinetics Outcomes to Find the Optimal Biological Dose.","authors":"Hao Sun, Jieqi Tu","doi":"10.1002/pst.2444","DOIUrl":"https://doi.org/10.1002/pst.2444","url":null,"abstract":"Immunotherapies and targeted therapies have gained popularity due to their promising therapeutic effects across multiple treatment areas. The focus of early phase dose-finding clinical trials has shifted from finding the maximum tolerated dose (MTD) to identifying the optimal biological dose (OBD), which aims to balance the toxicity and efficacy outcomes, thus optimizing the risk-benefit trade-off. These trials often collect multiple pharmacokinetics (PK) outcomes to assess drug exposure, which has shown correlations with toxicity and efficacy outcomes but has not been utilized in the current dose-finding designs for OBD selection. Moreover, PK outcomes are usually available within days after initial treatment, much faster than toxicity and efficacy outcomes. To bridge this gap, we introduce the innovative model-assisted PKBOIN-12 design, which enhances BOIN12 by integrating PK information into both the dose-finding algorithm and the final OBD determination process. We further extend PKBOIN-12 to TITE-PKBOIN-12 to address the challenges of late-onset toxicity and efficacy outcomes. Simulation results demonstrate that PKBOIN-12 more effectively identifies the OBD and allocates a greater number of patients to it than BOIN12. Additionally, PKBOIN-12 decreases the probability of selecting inefficacious doses as the OBD by excluding those with low drug exposure. Comprehensive simulation studies and sensitivity analysis confirm the robustness of both PKBOIN-12 and TITE-PKBOIN-12 in various scenarios.","PeriodicalId":19934,"journal":{"name":"Pharmaceutical Statistics","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142505737","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Comparison of Prior Distributions for the Heterogeneity Parameter in a Rare Events Meta-Analysis of a Few Studies. 少数研究的罕见事件 Meta 分析中异质性参数的先验分布比较。

IF 1.3 4区医学

Pharmaceutical Statistics Pub Date : 2024-10-23 DOI: 10.1002/pst.2448

Minghong Yao, Fan Mei, Kang Zou, Ling Li, Xin Sun

{"title":"Comparison of Prior Distributions for the Heterogeneity Parameter in a Rare Events Meta-Analysis of a Few Studies.","authors":"Minghong Yao, Fan Mei, Kang Zou, Ling Li, Xin Sun","doi":"10.1002/pst.2448","DOIUrl":"https://doi.org/10.1002/pst.2448","url":null,"abstract":"Bayesian meta-analysis is a promising approach for rare events meta-analysis. However, the inference of the overall effect in rare events meta-analysis is sensitive to the choice of prior distribution for the heterogeneity parameter. Therefore, it is crucial to assign a convincing prior specification and ensure that it is both plausible and transparent. Various priors for the heterogeneity parameter have been proposed; however, the comparative performance of alternative prior specifications in rare events meta-analysis is poorly understood. Based on a binomial-normal hierarchical model, we conducted a comprehensive simulation study to compare seven heterogeneity prior specifications for binary outcomes, using the odds ratio as the metric. We compared their performance in terms of coverage, median percentage bias, width of the 95% credible interval, and root mean square error (RMSE). We illustrate the results with two recently published rare events meta-analyses of a few studies. The results show that the half-normal prior (with a scale of 0.5), the prior proposed by Turner et al. for the general healthcare setting (without restriction to a specific type of outcome) and for the adverse event setting perform well when the degree of heterogeneity is not relatively high, yielding smaller bias and shorter interval widths with similar coverage and RMSE in most cases compared to other prior specifications. None of the priors performed better when the heterogeneity between-studies were significantly extreme.","PeriodicalId":19934,"journal":{"name":"Pharmaceutical Statistics","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142505736","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

On Some Modeling Issues in Estimating Vaccine Efficacy 关于估算疫苗疗效的一些模型问题

IF 1.5 4区医学

Pharmaceutical Statistics Pub Date : 2024-09-10 DOI: 10.1002/pst.2440

Mauro Gasparini

引用次数: 0

A propensity score-integrated approach for leveraging external data in a randomized controlled trial with time-to-event endpoints. 在随机对照试验中利用外部数据的倾向得分整合方法，以时间为终点。

IF 16.4 4区医学

Pharmaceutical Statistics Pub Date : 2024-09-01 Epub Date: 2024-03-05 DOI: 10.1002/pst.2377

Wei-Chen Chen, Nelson Lu, Chenguang Wang, Heng Li, Changhong Song, Ram Tiwari, Yunling Xu, Lilly Q Yue

引用次数: 0

Time-to-event estimands and loss to follow-up in oncology in light of the estimands guidance. 根据估算指导，肿瘤学中的时间-事件估算值和随访损失。

IF 16.4 4区医学

Pharmaceutical Statistics Pub Date : 2024-09-01 Epub Date: 2024-03-29 DOI: 10.1002/pst.2386

Jonathan M Siegel, Hans-Jochen Weber, Stefan Englert, Feng Liu, Michelle Casey

{"title":"Time-to-event estimands and loss to follow-up in oncology in light of the estimands guidance.","authors":"Jonathan M Siegel, Hans-Jochen Weber, Stefan Englert, Feng Liu, Michelle Casey","doi":"10.1002/pst.2386","DOIUrl":"10.1002/pst.2386","url":null,"abstract":"Time-to-event estimands are central to many oncology clinical trials. The estimands framework (addendum to the ICH E9 guideline) calls for precisely defining the treatment effect of interest to align with the clinical question of interest and requires predefining the handling of intercurrent events (ICEs) that occur after treatment initiation and \"affect either the interpretation or the existence of the measurements associated with the clinical question of interest.\" We discuss a practical problem in clinical trial design and execution, that is, in some clinical contexts it is not feasible to systematically follow patients to an event of interest. Loss to follow-up in the presence of intercurrent events can affect the meaning and interpretation of the study results. We provide recommendations for trial design, stressing the need for close alignment of the clinical question of interest and study design, impact on data collection, and other practical implications. When patients cannot be systematically followed, compromise may be necessary to select the best available estimand that can be feasibly estimated under the circumstances. We discuss the use of sensitivity and supplementary analyses to examine assumptions of interest.","PeriodicalId":19934,"journal":{"name":"Pharmaceutical Statistics","volume":" ","pages":"709-727"},"PeriodicalIF":16.4,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140326928","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Estimation of the odds ratio from multi-stage randomized trials. 从多阶段随机试验中估算几率比。

IF 16.4 4区医学

Pharmaceutical Statistics Pub Date : 2024-09-01 Epub Date: 2024-03-10 DOI: 10.1002/pst.2378

Shiwei Cao, Sin-Ho Jung

引用次数: 0

Effects of sceptical priors on the performance of adaptive clinical trials with binary outcomes. 怀疑先验对二元结果适应性临床试验绩效的影响。

IF 1.3 4区医学

Pharmaceutical Statistics Pub Date : 2024-09-01 Epub Date: 2024-03-29 DOI: 10.1002/pst.2387

Anders Granholm, Theis Lange, Michael O Harhay, Anders Perner, Morten Hylander Møller, Benjamin Skov Kaas-Hansen

{"title":"Effects of sceptical priors on the performance of adaptive clinical trials with binary outcomes.","authors":"Anders Granholm, Theis Lange, Michael O Harhay, Anders Perner, Morten Hylander Møller, Benjamin Skov Kaas-Hansen","doi":"10.1002/pst.2387","DOIUrl":"10.1002/pst.2387","url":null,"abstract":"It is unclear how sceptical priors impact adaptive trials. We assessed the influence of priors expressing a spectrum of scepticism on the performance of several Bayesian, multi-stage, adaptive clinical trial designs using binary outcomes under different clinical scenarios. Simulations were conducted using fixed stopping rules and stopping rules calibrated to keep type 1 error rates at approximately 5%. We assessed total sample sizes, event rates, event counts, probabilities of conclusiveness and selecting the best arm, root mean squared errors (RMSEs) of the estimated treatment effect in the selected arms, and ideal design percentages (IDPs; which combines arm selection probabilities, power, and consequences of selecting inferior arms), with RMSEs and IDPs estimated in conclusive trials only and after selecting the control arm in inconclusive trials. Using fixed stopping rules, increasingly sceptical priors led to larger sample sizes, more events, higher IDPs in simulations ending in superiority, and lower RMSEs, lower probabilities of conclusiveness/selecting the best arm, and lower IDPs when selecting controls in inconclusive simulations. With calibrated stopping rules, the effects of increased scepticism on sample sizes and event counts were attenuated, and increased scepticism increased the probabilities of conclusiveness/selecting the best arm and IDPs when selecting controls in inconclusive simulations without substantially increasing sample sizes. Results from trial designs with gentle adaptation and non-informative priors resembled those from designs with more aggressive adaptation using weakly-to-moderately sceptical priors. In conclusion, the use of somewhat sceptical priors in adaptive trial designs with binary outcomes seems reasonable when considering multiple performance metrics simultaneously.","PeriodicalId":19934,"journal":{"name":"Pharmaceutical Statistics","volume":" ","pages":"728-741"},"PeriodicalIF":1.3,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11438950/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140326927","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Digital twins and Bayesian dynamic borrowing: Two recent approaches for incorporating historical control data. 数字双胞胎和贝叶斯动态借贷：纳入历史控制数据的两种最新方法。

IF 16.4 4区医学

Pharmaceutical Statistics Pub Date : 2024-09-01 Epub Date: 2024-03-04 DOI: 10.1002/pst.2376

Carl-Fredrik Burman, Erik Hermansson, David Bock, Stefan Franzén, David Svensson

{"title":"Digital twins and Bayesian dynamic borrowing: Two recent approaches for incorporating historical control data.","authors":"Carl-Fredrik Burman, Erik Hermansson, David Bock, Stefan Franzén, David Svensson","doi":"10.1002/pst.2376","DOIUrl":"10.1002/pst.2376","url":null,"abstract":"Recent years have seen an increasing interest in incorporating external control data for designing and evaluating randomized clinical trials (RCT). This may decrease costs and shorten inclusion times by reducing sample sizes. For small populations, with limited recruitment, this can be especially important. Bayesian dynamic borrowing (BDB) has been a popular choice as it claims to protect against potential prior data conflict. Digital twins (DT) has recently been proposed as another method to utilize historical data. DT, also known as PROCOVA™, is based on constructing a prognostic score from historical control data, typically using machine learning. This score is included in a pre-specified ANCOVA as the primary analysis of the RCT. The promise of this idea is power increase while guaranteeing strong type 1 error control. In this paper, we apply analytic derivations and simulations to analyze and discuss examples of these two approaches. We conclude that BDB and DT, although similar in scope, have fundamental differences which need be considered in the specific application. The inflation of the type 1 error is a serious issue for BDB, while more evidence is needed of a tangible value of DT for real RCTs.","PeriodicalId":19934,"journal":{"name":"Pharmaceutical Statistics","volume":" ","pages":"611-629"},"PeriodicalIF":16.4,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140028706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Simulation-based sample size calculations of marginal proportional means models for recurrent events with competing risks. 基于边际比例均值模型的模拟样本量计算，适用于具有竞争风险的复发性事件。

IF 16.4 4区医学

Pharmaceutical Statistics Pub Date : 2024-09-01 Epub Date: 2024-03-20 DOI: 10.1002/pst.2382

Julie Funch Furberg, Per Kragh Andersen, Thomas Scheike, Henrik Ravn

{"title":"Simulation-based sample size calculations of marginal proportional means models for recurrent events with competing risks.","authors":"Julie Funch Furberg, Per Kragh Andersen, Thomas Scheike, Henrik Ravn","doi":"10.1002/pst.2382","DOIUrl":"10.1002/pst.2382","url":null,"abstract":"In randomised controlled trials, the outcome of interest could be recurrent events, such as hospitalisations for heart failure. If mortality rates are non-negligible, both recurrent events and competing terminal events need to be addressed when formulating the estimand and statistical analysis is no longer trivial. In order to design future trials with primary recurrent event endpoints with competing risks, it is necessary to be able to perform power calculations to determine sample sizes. This paper introduces a simulation-based approach for power estimation based on a proportional means model for recurrent events and a proportional hazards model for terminal events. The simulation procedure is presented along with a discussion of what the user needs to specify to use the approach. The method is flexible and based on marginal quantities which are easy to specify. However, the method introduces a lack of a certain type of dependence. This is explored in a sensitivity analysis which suggests that the power is robust in spite of that. Data from a randomised controlled trial, LEADER, is used as the basis for generating data for a future trial. Finally, potential power gains of recurrent event methods as opposed to first event methods are discussed.","PeriodicalId":19934,"journal":{"name":"Pharmaceutical Statistics","volume":" ","pages":"687-708"},"PeriodicalIF":16.4,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140175941","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimal sample size allocation for two-arm superiority and non-inferiority trials with binary endpoints. 二元终点的双臂优效和非优效试验的最佳样本量分配。

IF 16.4 4区医学

Pharmaceutical Statistics Pub Date : 2024-09-01 Epub Date: 2024-03-12 DOI: 10.1002/pst.2375

Marietta Kirchner, Stefanie Schüpke, Meinhard Kieser

引用次数: 0