Pharmaceutical Statistics最新文献_第6页

Comparative Analyses of Bioequivalence Assessment Methods for In Vitro Permeation Test Data. 体外渗透试验数据的生物等效性评估方法比较分析。

IF 1.3 4区医学

Pharmaceutical Statistics Pub Date : 2025-01-01 Epub Date: 2024-08-24 DOI: 10.1002/pst.2434

Sami Leon, Elena Rantou, Jessica Kim, Sungwoo Choi, Nam Hee Choi

{"title":"Comparative Analyses of Bioequivalence Assessment Methods for In Vitro Permeation Test Data.","authors":"Sami Leon, Elena Rantou, Jessica Kim, Sungwoo Choi, Nam Hee Choi","doi":"10.1002/pst.2434","DOIUrl":"10.1002/pst.2434","url":null,"abstract":"For topical, dermatological drug products, an in vitro option to determine bioequivalence (BE) between test and reference products is recommended. In particular, in vitro permeation test (IVPT) data analysis uses a reference-scaled approach for two primary endpoints, cumulative penetration amount (AMT) and maximum flux (J max), which takes the within donor variability into consideration. In 2022, the Food and Drug Administration (FDA) published a draft IVPT guidance that includes statistical analysis methods for both balanced and unbalanced cases of IVPT study data. This work presents a comprehensive evaluation of various methodologies used to estimate critical parameters essential in assessing BE. Specifically, we investigate the performance of the FDA draft IVPT guidance approach alongside alternative empirical and model-based methods utilizing mixed-effects models. Our analyses include both simulated scenarios and real-world studies. In simulated scenarios, empirical formulas consistently demonstrate robustness in approximating the true model, particularly in effectively addressing treatment-donor interactions. Conversely, the effectiveness of model-based approaches heavily relies on precise model selection, which significantly influences their results. The research emphasizes the importance of accurate model selection in model-based BE assessment methodologies. It sheds light on the advantages of empirical formulas, highlighting their reliability compared to model-based approaches and offers valuable implications for BE assessments. Our findings underscore the significance of robust methodologies and provide essential insights to advance their understanding and application in the assessment of BE, employed in IVPT data analysis.","PeriodicalId":19934,"journal":{"name":"Pharmaceutical Statistics","volume":" ","pages":"e2434"},"PeriodicalIF":1.3,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142047000","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

Mixture Experimentation in Pharmaceutical Formulations: A Tutorial. 药物制剂中的混合物实验：教程。

IF 1.3 4区医学

Pharmaceutical Statistics Pub Date : 2025-01-01 Epub Date: 2024-08-05 DOI: 10.1002/pst.2426

Lynne B Hare, Stan Altan, Hans Coppenolle

{"title":"Mixture Experimentation in Pharmaceutical Formulations: A Tutorial.","authors":"Lynne B Hare, Stan Altan, Hans Coppenolle","doi":"10.1002/pst.2426","DOIUrl":"10.1002/pst.2426","url":null,"abstract":"Mixture experimentation is commonly seen in pharmaceutical formulation studies, where the relative proportions of the individual components are modeled for effects on product attributes. The requirement that the sum of the component proportions equals 1 has given rise to the class of designs, known as mixture designs. The first mixture designs were published by Quenouille in 1953 but it took nearly 40 years for the earliest mixture design applications to be published in the pharmaceutical sciences literature by Kettaneh-Wold in 1991 and Waaler in 1992. Since then, the advent of efficient computer algorithms to generate designs has made this class of designs easily accessible to pharmaceutical statisticians, although the use of these designs appears to be an underutilized experimental strategy even today. One goal of this tutorial is to draw the attention of experimental statisticians to this class of designs and their advantages in pursuing formulation studies such as excipient compatibility studies. We present sufficient materials to introduce the novice practitioner to this class of design, associated models, and analysis strategies. An example of a mixture-process variable design is given as a case study.","PeriodicalId":19934,"journal":{"name":"Pharmaceutical Statistics","volume":" ","pages":"e2426"},"PeriodicalIF":1.3,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141894062","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

Balance Index to Determine the Follow-Up Duration of Oncology Trials. 确定肿瘤学试验随访时间的平衡指数。

IF 1.3 4区医学

Pharmaceutical Statistics Pub Date : 2025-01-01 Epub Date: 2024-10-11 DOI: 10.1002/pst.2442

Lei Yang, Feinan Lu

{"title":"Balance Index to Determine the Follow-Up Duration of Oncology Trials.","authors":"Lei Yang, Feinan Lu","doi":"10.1002/pst.2442","DOIUrl":"10.1002/pst.2442","url":null,"abstract":"Several indices were suggested to determine the follow up duration in oncology trials from either maturity or stability perspective, by maximizing time <math> <semantics><mrow><mi>t</mi></mrow> </semantics> </math> such that the index was either greater or less than a pre-defined cutoff value. However, the selection of cutoff value was subjective and usually no commonly agreed cutoff value existed; sometimes one had to resort to simulations. To solve this problem, a new balance index was proposed, which integrated both data stability and data maturity. Its theoretical properties and relationships with other indices were investigated; then its performance was demonstrated through a case study. The highlights of the index are: (1) easy to calculate; (2) free of cutoff value selection; (3) generally consistent with the other indices while sometimes able to shorten the follow-up duration thus more flexible. For the cases where the new balance index cannot be calculated, a modified balance index was also proposed and discussed. For either single arm trial or randomized clinical trial, the two new balance indices can be implemented to widespread situations such as designing a new trial from scratch, or using aggregated trial information to inform the decision-making in the middle of trial conduct.","PeriodicalId":19934,"journal":{"name":"Pharmaceutical Statistics","volume":" ","pages":"e2442"},"PeriodicalIF":1.3,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142400956","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

Potency Assay Variability Estimation in Practice. 实践中的药效测定变异性估算。

IF 1.3 4区医学

Pharmaceutical Statistics Pub Date : 2025-01-01 Epub Date: 2024-07-08 DOI: 10.1002/pst.2408

Hang Li, Tomasz M Witkos, Scott Umlauf, Christopher Thompson

引用次数: 0

Propensity Score Analysis With Baseline and Follow-Up Measurements of the Outcome Variable. 对结果变量进行基线和随访测量的倾向得分分析。

IF 1.3 4区医学

Pharmaceutical Statistics Pub Date : 2025-01-01 Epub Date: 2024-09-05 DOI: 10.1002/pst.2436

Peter C Austin

{"title":"Propensity Score Analysis With Baseline and Follow-Up Measurements of the Outcome Variable.","authors":"Peter C Austin","doi":"10.1002/pst.2436","DOIUrl":"10.1002/pst.2436","url":null,"abstract":"A common feature in cohort studies is when there is a baseline measurement of the continuous follow-up or outcome variable. Common examples include baseline measurements of physiological characteristics such as blood pressure or heart rate in studies where the outcome is post-baseline measurement of the same variable. Methods incorporating the propensity score are increasingly being used to estimate the effects of treatments using observational studies. We examined six methods for incorporating the baseline value of the follow-up variable when using propensity score matching or weighting. These methods differed according to whether the baseline value of the follow-up variable was included or excluded from the propensity score model, whether subsequent regression adjustment was conducted in the matched or weighted sample to adjust for the baseline value of the follow-up variable, and whether the analysis estimated the effect of treatment on the follow-up variable or on the change from baseline. We used Monte Carlo simulations with 750 scenarios. While no analytic method had uniformly superior performance, we provide the following recommendations: first, when using weighting and the ATE is the target estimand, use an augmented inverse probability weighted estimator or include the baseline value of the follow-up variable in the propensity score model and subsequently adjust for the baseline value of the follow-up variable in a regression model. Second, when the ATT is the target estimand, regardless of whether using weighting or matching, analyze change from baseline using a propensity score that excludes the baseline value of the follow-up variable.","PeriodicalId":19934,"journal":{"name":"Pharmaceutical Statistics","volume":" ","pages":"e2436"},"PeriodicalIF":1.3,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11788469/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142140774","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

New Methods for Two-Stage Treatment Switching Estimation.

IF 1.3 4区医学

Pharmaceutical Statistics Pub Date : 2025-01-01 DOI: 10.1002/pst.2462

Dan Jackson, Di Ran, Fanni Zhang, Mario Ouwens, Vitaly Druker, Michael Sweeting, Robert Hettle, Ian R White

{"title":"New Methods for Two-Stage Treatment Switching Estimation.","authors":"Dan Jackson, Di Ran, Fanni Zhang, Mario Ouwens, Vitaly Druker, Michael Sweeting, Robert Hettle, Ian R White","doi":"10.1002/pst.2462","DOIUrl":"10.1002/pst.2462","url":null,"abstract":"Treatment switching is common in randomized trials of oncology treatments. For example, control group patients may receive the experimental treatment as a subsequent therapy. One possible estimand is the effect of trial treatment if this type of switching had instead not occurred. Two-stage estimation is an established approach for estimating this estimand. We argue that other estimands of interest instead describe the effect of trial treatments if the proportion of patients who switched was different. We give precise definitions of such estimands. By motivating estimands using real-world data, decision-making in universal health care systems is facilitated. Focusing on estimation, we show that an alternative choice of secondary baseline, the time of first subsequent treatment, is easily defined, and widely applicable, and makes alternative estimands amenable to two-stage estimation. We develop methodology using propensity scores, to adjust for confounding at a secondary baseline, and a new quantile matching technique that can be used to implement any parametric form of the post-secondary baseline survival model. Our methodology was motivated by a recent immuno-oncology trial where a substantial proportion of control group patients subsequently received a form of immunotherapy.","PeriodicalId":19934,"journal":{"name":"Pharmaceutical Statistics","volume":"24 1","pages":"e2462"},"PeriodicalIF":1.3,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11794985/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143189758","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

Covariate adjustment and estimation of difference in proportions in randomized clinical trials. 随机临床试验中的协变量调整和比例差异估算。

IF 1.3 4区医学

Pharmaceutical Statistics Pub Date : 2024-11-01 Epub Date: 2024-05-19 DOI: 10.1002/pst.2397

Jialuo Liu, Dong Xi

{"title":"Covariate adjustment and estimation of difference in proportions in randomized clinical trials.","authors":"Jialuo Liu, Dong Xi","doi":"10.1002/pst.2397","DOIUrl":"10.1002/pst.2397","url":null,"abstract":"Difference in proportions is frequently used to measure treatment effect for binary outcomes in randomized clinical trials. The estimation of difference in proportions can be assisted by adjusting for prognostic baseline covariates to enhance precision and bolster statistical power. Standardization or g-computation is a widely used method for covariate adjustment in estimating unconditional difference in proportions, because of its robustness to model misspecification. Various inference methods have been proposed to quantify the uncertainty and confidence intervals based on large-sample theories. However, their performances under small sample sizes and model misspecification have not been comprehensively evaluated. We propose an alternative approach to estimate the unconditional variance of the standardization estimator based on the robust sandwich estimator to further enhance the finite sample performance. Extensive simulations are provided to demonstrate the performances of the proposed method, spanning a wide range of sample sizes, randomization ratios, and model specification. We apply the proposed method in a real data example to illustrate the practical utility.","PeriodicalId":19934,"journal":{"name":"Pharmaceutical Statistics","volume":" ","pages":"884-905"},"PeriodicalIF":1.3,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141065823","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 Treatment Policy Estimands for Continuous Outcomes Using Off-Treatment Sequential Multiple Imputation. 使用非治疗序列多重估算法估算连续结果的治疗政策估计值。

IF 1.3 4区医学

Pharmaceutical Statistics Pub Date : 2024-11-01 Epub Date: 2024-08-04 DOI: 10.1002/pst.2411

Thomas Drury, Juan J Abellan, Nicky Best, Ian R White

{"title":"Estimation of Treatment Policy Estimands for Continuous Outcomes Using Off-Treatment Sequential Multiple Imputation.","authors":"Thomas Drury, Juan J Abellan, Nicky Best, Ian R White","doi":"10.1002/pst.2411","DOIUrl":"10.1002/pst.2411","url":null,"abstract":"The estimands framework outlined in ICH E9 (R1) describes the components needed to precisely define the effects to be estimated in clinical trials, which includes how post-baseline 'intercurrent' events (IEs) are to be handled. In late-stage clinical trials, it is common to handle IEs like 'treatment discontinuation' using the treatment policy strategy and target the treatment effect on outcomes regardless of treatment discontinuation. For continuous repeated measures, this type of effect is often estimated using all observed data before and after discontinuation using either a mixed model for repeated measures (MMRM) or multiple imputation (MI) to handle any missing data. In basic form, both these estimation methods ignore treatment discontinuation in the analysis and therefore may be biased if there are differences in patient outcomes after treatment discontinuation compared with patients still assigned to treatment, and missing data being more common for patients who have discontinued treatment. We therefore propose and evaluate a set of MI models that can accommodate differences between outcomes before and after treatment discontinuation. The models are evaluated in the context of planning a Phase 3 trial for a respiratory disease. We show that analyses ignoring treatment discontinuation can introduce substantial bias and can sometimes underestimate variability. We also show that some of the MI models proposed can successfully correct the bias, but inevitably lead to increases in variance. We conclude that some of the proposed MI models are preferable to the traditional analysis ignoring treatment discontinuation, but the precise choice of MI model will likely depend on the trial design, disease of interest and amount of observed and missing data following treatment discontinuation.","PeriodicalId":19934,"journal":{"name":"Pharmaceutical Statistics","volume":" ","pages":"1144-1155"},"PeriodicalIF":1.3,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11602932/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141889907","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

Investigating Stability in Subgroup Identification for Stratified Medicine. 研究分层医疗亚组识别的稳定性。

IF 1.3 4区医学

Pharmaceutical Statistics Pub Date : 2024-11-01 Epub Date: 2024-06-25 DOI: 10.1002/pst.2409

G M Hair, T Jemielita, S Mt-Isa, P M Schnell, R Baumgartner

{"title":"Investigating Stability in Subgroup Identification for Stratified Medicine.","authors":"G M Hair, T Jemielita, S Mt-Isa, P M Schnell, R Baumgartner","doi":"10.1002/pst.2409","DOIUrl":"10.1002/pst.2409","url":null,"abstract":"Subgroup analysis may be used to investigate treatment effect heterogeneity among subsets of the study population defined by baseline characteristics. Several methodologies have been proposed in recent years and with these, statistical issues such as multiplicity, complexity, and selection bias have been widely discussed. Some methods adjust for one or more of these issues; however, few of them discuss or consider the stability of the subgroup assignments. We propose exploring the stability of subgroups as a sensitivity analysis step for stratified medicine to assess the robustness of the identified subgroups besides identifying possible factors that may drive this instability. After applying Bayesian credible subgroups, a nonparametric bootstrap can be used to assess stability at subgroup-level and patient-level. Our findings illustrate that when the treatment effect is small or not so evident, patients are more likely to switch to different subgroups (jumpers) across bootstrap resamples. In contrast, when the treatment effect is large or extremely convincing, patients generally remain in the same subgroup. While the proposed subgroup stability method is illustrated through Bayesian credible subgroups method on time-to-event data, this general approach can be used with other subgroup identification methods and endpoints.","PeriodicalId":19934,"journal":{"name":"Pharmaceutical Statistics","volume":" ","pages":"945-958"},"PeriodicalIF":1.3,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141458676","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

Futility Interim Analysis Based on Probability of Success Using a Surrogate Endpoint. 基于使用替代终点的成功概率的无用性中期分析。

IF 1.3 4区医学

Pharmaceutical Statistics Pub Date : 2024-11-01 Epub Date: 2024-07-02 DOI: 10.1002/pst.2410

Ronan Fougeray, Loïck Vidot, Marco Ratta, Zhaoyang Teng, Donia Skanji, Gaëlle Saint-Hilary

{"title":"Futility Interim Analysis Based on Probability of Success Using a Surrogate Endpoint.","authors":"Ronan Fougeray, Loïck Vidot, Marco Ratta, Zhaoyang Teng, Donia Skanji, Gaëlle Saint-Hilary","doi":"10.1002/pst.2410","DOIUrl":"10.1002/pst.2410","url":null,"abstract":"In clinical trials with time-to-event data, the evaluation of treatment efficacy can be a long and complex process, especially when considering long-term primary endpoints. Using surrogate endpoints to correlate the primary endpoint has become a common practice to accelerate decision-making. Moreover, the ethical need to minimize sample size and the practical need to optimize available resources have encouraged the scientific community to develop methodologies that leverage historical data. Relying on the general theory of group sequential design and using a Bayesian framework, the methodology described in this paper exploits a documented historical relationship between a clinical \"final\" endpoint and a surrogate endpoint to build an informative prior for the primary endpoint, using surrogate data from an early interim analysis of the clinical trial. The predictive probability of success of the trial is then used to define a futility-stopping rule. The methodology demonstrates substantial enhancements in trial operating characteristics when there is a good agreement between current and historical data. Furthermore, incorporating a robust approach that combines the surrogate prior with a vague component mitigates the impact of the minor prior-data conflicts while maintaining acceptable performance even in the presence of significant prior-data conflicts. The proposed methodology was applied to design a Phase III clinical trial in metastatic colorectal cancer, with overall survival as the primary endpoint and progression-free survival as the surrogate endpoint.","PeriodicalId":19934,"journal":{"name":"Pharmaceutical Statistics","volume":" ","pages":"971-983"},"PeriodicalIF":1.3,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141492960","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