Biometrics最新文献_第3页

Nonparametric Bayesian approach for dynamic borrowing of historical control data. 历史控制数据动态借用的非参数贝叶斯方法。

IF 1.7 4区数学

Biometrics Pub Date : 2025-07-03 DOI: 10.1093/biomtc/ujaf118

Tomohiro Ohigashi, Kazushi Maruo, Takashi Sozu, Masahiko Gosho

{"title":"Nonparametric Bayesian approach for dynamic borrowing of historical control data.","authors":"Tomohiro Ohigashi, Kazushi Maruo, Takashi Sozu, Masahiko Gosho","doi":"10.1093/biomtc/ujaf118","DOIUrl":"https://doi.org/10.1093/biomtc/ujaf118","url":null,"abstract":"When incorporating historical control data into the analysis of current randomized controlled trial data, it is critical to account for differences between the datasets. When the cause of difference is an unmeasured factor and adjustment for only observed covariates is insufficient, it is desirable to use a dynamic borrowing method that reduces the impact of heterogeneous historical controls. We propose a nonparametric Bayesian approach that addresses between-trial heterogeneity and allows borrowing historical controls homogeneous with the current control. Additionally, to emphasize conflict resolution between historical controls and the current control, we introduce a method based on the dependent Dirichlet process (DP) mixture. The proposed methods can be implemented using the same procedure, regardless of whether the outcome data comprise aggregated study-level data or individual participant data. We also develop a novel index of similarity between the historical and current control data, based on the posterior distribution of the parameter of interest. We conduct a simulation study and analyze clinical trial examples to evaluate the performance of the proposed methods compared to existing methods. The proposed method, based on the dependent DP mixture, can accurately borrow from homogeneous historical controls while reducing the impact of heterogeneous historical controls compared to the typical DP mixture. The proposed methods outperform existing methods in scenarios with heterogeneous historical controls, in which the meta-analytic approach is ineffective.","PeriodicalId":8930,"journal":{"name":"Biometrics","volume":"81 3","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144941173","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Correction to: Evaluating the effects of high-throughput structural neuroimaging predictors on whole-brain functional connectome outcomes via network-based matrix-on-vector regression. 修正：通过基于网络的矩阵向量回归评估高通量结构神经成像预测因子对全脑功能连接组结果的影响。

IF 1.7 4区数学

Biometrics Pub Date : 2025-07-03 DOI: 10.1093/biomtc/ujaf111

引用次数: 0

Regression analysis of interval-censored failure time data with change points and a cured subgroup. 具有变化点和修复子群的间隔截尾失效时间数据的回归分析。

IF 1.7 4区数学

Biometrics Pub Date : 2025-07-03 DOI: 10.1093/biomtc/ujaf100

Yichen Lou, Mingyue Du, Xinyuan Song

引用次数: 0

Precision generalized phase I-II designs. 精密广义I-II期设计。

IF 1.7 4区数学

Biometrics Pub Date : 2025-07-03 DOI: 10.1093/biomtc/ujaf043

Saijun Zhao, Peter F Thall, Ying Yuan, Juhee Lee, Pavlos Msaouel, Yong Zang

{"title":"Precision generalized phase I-II designs.","authors":"Saijun Zhao, Peter F Thall, Ying Yuan, Juhee Lee, Pavlos Msaouel, Yong Zang","doi":"10.1093/biomtc/ujaf043","DOIUrl":"10.1093/biomtc/ujaf043","url":null,"abstract":"A new family of precision Bayesian dose optimization designs, PGen I-II, based on early efficacy, early toxicity, and long-term time to treatment failure is proposed. A PGen I-II design refines a Gen I-II design by accounting for patient heterogeneity characterized by subgroups that may be defined by prognostic levels, disease subtypes, or biomarker categories. The design makes subgroup-specific decisions, which may be to drop an unacceptably toxic or inefficacious dose, randomize patients among acceptable doses, or identify a best dose in terms of treatment success defined in terms of time to failure over long-term follow-up. A piecewise exponential distribution for failure time is assumed, including subgroup-specific effects of dose, response, and toxicity. Latent variables are used to adaptively cluster subgroups found to have similar dose-outcome distributions, with the model simplified to borrow strength between subgroups in the same cluster. Guidelines and user-friendly computer software for implementing the design are provided. A simulation study is reported that shows the PGen I-II design is superior to similarly structured designs that either assume patient homogeneity or conduct separate trials within subgroups.","PeriodicalId":8930,"journal":{"name":"Biometrics","volume":"81 3","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12288667/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144706184","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Negative binomial mixed effects location-scale models for intensive longitudinal count-type physical activity data provided by wearable devices. 可穿戴设备提供的密集纵向计数型体力活动数据的负二项混合效应位置尺度模型。

IF 1.7 4区数学

Biometrics Pub Date : 2025-07-03 DOI: 10.1093/biomtc/ujaf099

Qianheng Ma, Genevieve F Dunton, Donald Hedeker

{"title":"Negative binomial mixed effects location-scale models for intensive longitudinal count-type physical activity data provided by wearable devices.","authors":"Qianheng Ma, Genevieve F Dunton, Donald Hedeker","doi":"10.1093/biomtc/ujaf099","DOIUrl":"10.1093/biomtc/ujaf099","url":null,"abstract":"In recent years, the use of wearable devices, for example, accelerometers, have become increasingly prevalent. Wearable devices enable more accurate real-time tracking of a subject's physical activity (PA) level, such as steps, number of activity bouts, or time in moderate-to-vigorous intensity PA (MVPA), which are important general health markers and can often be represented as counts. These intensive within-subject count data provided by wearable devices, for example, minutes in MVPA summarized per hour across days and even months, allow the possibility for modeling not only the mean PA level, but also the dispersion level for each subject. Especially in the context of daily PA, subjects' dispersion levels are potentially informative in reflecting their exercise patterns: some subjects might exhibit consistent PA across time and can be considered \"less dispersed\" subjects; while others might have a large amount of PA at a particular time point, while being sedentary for most of the day, and can be considered \"more dispersed\" subjects. Thus, we propose a negative binomial mixed effects location-scale model to model these intensive longitudinal PA counts and to account for the heterogeneity in both the mean and dispersion level across subjects. Further, to handle the issue of inflated numbers of zeros in the PA data, we also propose a hurdle/zero-inflated version which additionally includes the modeling of the probability of having $>$0 PA levels.","PeriodicalId":8930,"journal":{"name":"Biometrics","volume":"81 3","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12312402/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144752244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Doubly robust nonparametric estimators of the predictive value of covariates for survival data. 生存数据协变量预测值的双鲁棒非参数估计。

IF 1.4 4区数学

Biometrics Pub Date : 2025-07-03 DOI: 10.1093/biomtc/ujaf084

Torben Martinussen, Mark J van der Laan

引用次数: 0

Inference on age-specific fertility in ecology and evolution. Learning from other disciplines and improving the state of the art. 生态学和进化中年龄生育率的推论。向其他学科学习，提高技术水平。

IF 1.7 4区数学

Biometrics Pub Date : 2025-07-03 DOI: 10.1093/biomtc/ujaf081

Fernando Colchero

{"title":"Inference on age-specific fertility in ecology and evolution. Learning from other disciplines and improving the state of the art.","authors":"Fernando Colchero","doi":"10.1093/biomtc/ujaf081","DOIUrl":"10.1093/biomtc/ujaf081","url":null,"abstract":"Despite the importance of age-specific fertility for ecology and evolution, the methods for modeling and inference have proven considerably limited. However, other disciplines have long focused on exploring and developing a vast number of models. Here, I provide an overview of the different models proposed since the 1940s by formal demographers, statisticians, and social scientists, most of which are unknown to the ecological and evolutionary communities. I describe how these fall into 2 main categories, namely polynomials and those based on probability density functions. I discuss their merits in terms of their overall behavior and how well they represent the different stages of fertility. Despite many alternative models, inference on age-specific fertility has usually been limited to simple least squares. Although this might be sufficient for human data, I hope to demonstrate that inference requires more sophisticated approaches for ecological and evolutionary datasets. To illustrate how inference and model choice can be achieved on different types of typical ecological and evolutionary data, I present the new R package Bayesian Fertility Trajectory Analysis, which I apply to published aggregated data for lions and baboons. I then conduct a simulation study to test its performance on individual-level data. I show that appropriate inference and model selection can be achieved even when a small number of parents are followed.","PeriodicalId":8930,"journal":{"name":"Biometrics","volume":"81 3","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144706183","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Covariance-on-covariance regression. Covariance-on-covariance回归。

IF 1.7 4区数学

Biometrics Pub Date : 2025-07-03 DOI: 10.1093/biomtc/ujaf097

Yi Zhao, Yize Zhao

引用次数: 0

Bayesian inference for copy number intra-tumoral heterogeneity from single-cell RNA-sequencing data. 单细胞rna测序数据对拷贝数肿瘤内异质性的贝叶斯推断。

IF 1.7 4区数学

Biometrics Pub Date : 2025-07-03 DOI: 10.1093/biomtc/ujaf115

PuXue Qiao, Chun Fung Kwok, Guoqi Qian, Davis J McCarthy

{"title":"Bayesian inference for copy number intra-tumoral heterogeneity from single-cell RNA-sequencing data.","authors":"PuXue Qiao, Chun Fung Kwok, Guoqi Qian, Davis J McCarthy","doi":"10.1093/biomtc/ujaf115","DOIUrl":"https://doi.org/10.1093/biomtc/ujaf115","url":null,"abstract":"Copy number alterations (CNA) are important drivers and markers of clonal structures within tumors. Understanding these structures at single-cell resolution is crucial to advancing cancer treatments. The objective is to cluster single cells into clones and identify CNA events in each clone. Early attempts often sacrifice the intrinsic link between cell clustering and clonal CNA detection for simplicity and rely heavily on human input for critical parameters such as the number of clones. Here, we develop a Bayesian model to utilize single-cell RNA sequencing (scRNA-seq) data for automatic analysis of intra-tumoral clonal structure concerning CNAs, without reliance on prior knowledge. The model clusters cells into sub-tumoral clones, identifies the number of clones, and simultaneously infers the clonal CNA profiles. It synergistically incorporates input from gene expression and germline single-nucleotide polymorphisms. A Gibbs sampling algorithm has been implemented and is available as an R package Chloris. We demonstrate that our new method compares strongly against existing software tools in terms of both cell clustering and CNA profile identification accuracy. Application to human metastatic melanoma and anaplastic thyroid tumor data demonstrates accurate clustering of tumor and non-tumor cells and reveals clonal CNA profiles that highlight functional gene expression differences between clones from the same tumor.","PeriodicalId":8930,"journal":{"name":"Biometrics","volume":"81 3","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144940997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Revisiting optimal allocations for binary responses: insights from considering type-I error rate control. 重新审视二元响应的最优分配：从考虑i型错误率控制的见解。

IF 1.7 4区数学

Biometrics Pub Date : 2025-07-03 DOI: 10.1093/biomtc/ujaf114

Lukas Pin, Sofía S Villar, William F Rosenberger

{"title":"Revisiting optimal allocations for binary responses: insights from considering type-I error rate control.","authors":"Lukas Pin, Sofía S Villar, William F Rosenberger","doi":"10.1093/biomtc/ujaf114","DOIUrl":"https://doi.org/10.1093/biomtc/ujaf114","url":null,"abstract":"This work revisits optimal response-adaptive designs from a type-I error rate perspective, highlighting when and how much these allocations exacerbate type-I error rate inflation-an issue previously undocumented. We explore a range of approaches from the literature that can be applied to reduce type-I error rate inflation. However, we found that all of these approaches fail to give a robust solution to the problem. To address this, we derive 2 optimal allocation proportions, incorporating the more robust score test (instead of the Wald test) with finite sample estimators (instead of the unknown true values) in the formulation of the optimization problem. One proportion optimizes statistical power, and the other minimizes the total number of failures in a trial while maintaining a fixed variance level. Through simulations based on an early phase and a confirmatory trial, we provide crucial practical insight into how these new optimal proportion designs can offer substantial patient outcomes advantages while controlling type-I error rate. While we focused on binary outcomes, the framework offers valuable insights that naturally extend to other outcome types, multi-armed trials, and alternative measures of interest.","PeriodicalId":8930,"journal":{"name":"Biometrics","volume":"81 3","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144941151","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0