Statistics in Biosciences最新文献_第10页

Designing HIV Vaccine Efficacy Trials in the Context of Highly Effective Non-vaccine Prevention Modalities. 在高度有效的非疫苗预防模式背景下设计艾滋病疫苗疗效试验。

IF 0.8

Statistics in Biosciences Pub Date : 2020-12-01 Epub Date: 2020-10-22 DOI: 10.1007/s12561-020-09292-1

Holly Janes, Yifan Zhu, Elizabeth R Brown

{"title":"Designing HIV Vaccine Efficacy Trials in the Context of Highly Effective Non-vaccine Prevention Modalities.","authors":"Holly Janes, Yifan Zhu, Elizabeth R Brown","doi":"10.1007/s12561-020-09292-1","DOIUrl":"10.1007/s12561-020-09292-1","url":null,"abstract":"The evolving HIV prevention landscape poses challenges to the statistical design of future trials of candidate HIV vaccines. Study designs must address the anticipated reduction in HIV incidence due to adding new prevention modalities to the standard prevention package provided to trial participants, and must also accommodate individual choices of participants with regard to the use of these modalities. We explore four potential trial designs that address these challenges, with a focus on accommodating the newest addition to the prevention package-antiretroviral-based oral pre-exposure prophylaxis (PrEP). The designs differ with respect to how individuals who take up oral PrEP at screening are handled. An All-Comers Design enrolls and randomizes all eligible individuals, a Decliners Design enrolls and randomizes only those who decline PrEP at screening, and Single and Multi-Stage Run-In Designs enroll all but randomize only those who decline PrEP or show inadequate adherence to PrEP after one or multiple run-in periods. We compare these designs with respect to required sample sizes, study duration, and resource requirements, using a simulation model that incorporates data on HIV risk and PrEP uptake and adherence among men who have sex with men (MSM) in the Americas. We advocate considering Run-In Designs for some future contexts, and identify their advantages and tradeoffs relative to the other designs. The design concepts apply beyond HIV vaccines to other prevention modalities being developed with the aim to achieve further reductions in HIV incidence.","PeriodicalId":45094,"journal":{"name":"Statistics in Biosciences","volume":"12 3","pages":"468-494"},"PeriodicalIF":0.8,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10022814/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9155515","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A New Algorithm for Convex Biclustering and Its Extension to the Compositional Data 一种新的凸双聚类算法及其在合成数据中的推广

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Statistics in Biosciences Pub Date : 2020-11-24 DOI: 10.1007/s12561-022-09356-4

Binhuan Wang, Lanqiu Yao, Jiyuan Hu, Huilin Li

引用次数: 0

An Application of the Cure Model to a Cardiovascular Clinical Trial 治愈模型在心血管疾病临床试验中的应用

IF 1

Statistics in Biosciences Pub Date : 2020-11-12 DOI: 10.1007/s12561-020-09297-w

V. Sevilimedu, Shuangge Ma, P. Hartigan, T. Kyriakides

引用次数: 1

An Approach to Analyze Longitudinal Zero-Inflated Microbiome Count Data Using Two-Stage Mixed Effects Models 用两阶段混合效应模型分析纵向零膨胀微生物组计数数据的方法

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Statistics in Biosciences Pub Date : 2020-10-01 DOI: 10.1007/s12561-020-09295-y

Jian Wang, C. Reyes-Gibby, S. Shete

引用次数: 3

Can the Concept Be Proven? 这个概念可以被证明吗?

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Statistics in Biosciences Pub Date : 2020-09-07 DOI: 10.1007/s12561-020-09290-3

Ying-Ying Zhang, Naitee Ting

引用次数: 0

Survival Modeling of Suicide Risk with Rare and Uncertain Diagnoses 罕见和不确定诊断的自杀风险生存模型

IF 1

Statistics in Biosciences Pub Date : 2020-09-05 DOI: 10.1007/s12561-023-09374-w

Wenjie Wang, Chongliang Luo, R. Aseltine, Fei Wang, Jun Yan, Kun Chen

引用次数: 0

Correction to: A Simulation Study of Statistical Approaches to Data Analysis in the Stepped Wedge Design 修正:阶梯式楔形设计中数据分析统计方法的模拟研究

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Statistics in Biosciences Pub Date : 2020-08-17 DOI: 10.1007/s12561-020-09289-w

Yuqi Ren, James P. Hughes, P. Heagerty

引用次数: 1

Competing Risks Model with Short-Term and Long-Term Covariate Effects for Cancer Studies 癌症研究中具有短期和长期协变量效应的竞争风险模型

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Statistics in Biosciences Pub Date : 2020-07-21 DOI: 10.1007/s12561-020-09288-x

G. Diao, A. Vidyashankar, S. Zohar, S. Katsahian

引用次数: 0

A curve free Bayesian decision-theoretic design for phase Ia/Ib trials considering both safety and efficacy outcomes. 考虑安全性和有效性结果的Ia/Ib期试验无曲线贝叶斯决策理论设计。

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Statistics in Biosciences Pub Date : 2020-07-01 Epub Date: 2020-03-26 DOI: 10.1007/s12561-020-09272-5

Shenghua Fan, Bee Leng Lee, Ying Lu

{"title":"A curve free Bayesian decision-theoretic design for phase Ia/Ib trials considering both safety and efficacy outcomes.","authors":"Shenghua Fan, Bee Leng Lee, Ying Lu","doi":"10.1007/s12561-020-09272-5","DOIUrl":"https://doi.org/10.1007/s12561-020-09272-5","url":null,"abstract":"A curve-free, Bayesian decision-theoretic two-stage design is proposed to select biological efficacious doses (BEDs) for phase Ia/Ib trials in which both toxicity and efficacy signals are observed. No parametric models are assumed to govern the dose-toxicity, dose-efficacy, and toxicity-efficacy relationships. We assume that the dose-toxicity curve is monotonic non-decreasing and the dose-efficacy curve is unimodal. In the phase Ia stage, a Bayesian model on the toxicity rates is used to locate the maximum tolerated dose. In the phase Ib stage, we model the dose-efficacy curve using a step function while continuing to monitor the toxicity rates. Furthermore, a measure of the goodness of fit of a candidate step function is proposed, and the interval of BEDs associated with the best fitting step function is recommended. At the end of phase Ib, if some doses are recommended as BEDs, a cohort of confirmation is recruited and assigned at these doses to improve the precision of estimates at these doses. Extensive simulation studies show that the proposed design has desirable operating characteristics across different shapes of the underlying true toxicity and efficacy curves.","PeriodicalId":45094,"journal":{"name":"Statistics in Biosciences","volume":"12 2","pages":"146-166"},"PeriodicalIF":1.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s12561-020-09272-5","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"25557996","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Flexible Phase I-II design for partially ordered regimens with application to therapeutic cancer vaccines. 灵活的I-II期设计，部分有序方案应用于治疗性癌症疫苗。

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Statistics in Biosciences Pub Date : 2020-07-01 Epub Date: 2019-06-04 DOI: 10.1007/s12561-019-09245-3

Nolan A Wages, Craig L Slingluff

{"title":"Flexible Phase I-II design for partially ordered regimens with application to therapeutic cancer vaccines.","authors":"Nolan A Wages, Craig L Slingluff","doi":"10.1007/s12561-019-09245-3","DOIUrl":"https://doi.org/10.1007/s12561-019-09245-3","url":null,"abstract":"Existing methodology for the design of Phase I-II studies has been intended to search for the optimal regimen, based on a trade-off between toxicity and efficacy, from a set of regimens comprised of doses of a new agent. The underlying assumptions guiding allocation are that the dose-toxicity curve is monotonically increasing, and that the dose-efficacy curve either plateaus or decreases beyond an intermediate dose. This article considers the problem of designing Phase I-II studies that violate these assumptions for both outcomes. The motivating application studies regimens that are not defined by doses of a new agent, but rather a peptide vaccine plus novel adjuvants for the treatment of melanoma. All doses of each adjuvant are fixed, and the regimens vary by the number and selection of adjuvants. This structure produces regimen-toxicity curves that are partially ordered, and regimen-efficacy curves that may deviate from a plateau or unimodal shape. Application of a Bayesian model-based design is described in determining the optimal biologic regimen, based on bivariate binary measures of toxicity and biologic activity. A simulation study of the design's operating characteristics is conducted, and its versatility in handling other Phase I-II problems is discussed.","PeriodicalId":45094,"journal":{"name":"Statistics in Biosciences","volume":"12 2","pages":"104-123"},"PeriodicalIF":1.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s12561-019-09245-3","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38060011","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3