Statistical Methods in Medical Research最新文献_第4页

New clinical trial design borrowing information across patient subgroups based on fusion-penalized regression models. 新的临床试验设计基于融合-惩罚回归模型，借用跨患者亚组的信息。

IF 1.6 3区医学

Statistical Methods in Medical Research Pub Date : 2024-10-01 Epub Date: 2024-08-19 DOI: 10.1177/09622802241267355

Marion Kerioui, Alexia Iasonos, Mithat Gönen, Andrea Arfé

{"title":"New clinical trial design borrowing information across patient subgroups based on fusion-penalized regression models.","authors":"Marion Kerioui, Alexia Iasonos, Mithat Gönen, Andrea Arfé","doi":"10.1177/09622802241267355","DOIUrl":"10.1177/09622802241267355","url":null,"abstract":"In cancer research, basket trials aim to assess the efficacy of a drug using baskets, wherein patients are organized into subgroups according to their tumor type. In this context, using information borrowing strategy may increase the probability of detecting drug efficacy in active baskets, by shrinking together the estimates of the parameters characterizing the drug efficacy in baskets with similar drug activity. Here, we propose to use fusion-penalized logistic regression models to borrow information in the setting of a phase 2 single-arm basket trial with binary outcome. We describe our proposed strategy and assess its performance via a simulation study. We assessed the impact of heterogeneity in drug efficacy, prevalence of each tumor types and implementation of interim analyses on the operating characteristics of our proposed design. We compared our approach with two existing designs, relying on the specification of prior information in a Bayesian framework to borrow information across similar baskets. Notably, our approach performed well when the effect of the drug varied greatly across the baskets. Our approach offers several advantages, including limited implementation efforts and fast computation, which is essential when planning a new trial as such planning requires intensive simulation studies.","PeriodicalId":22038,"journal":{"name":"Statistical Methods in Medical Research","volume":" ","pages":"1718-1730"},"PeriodicalIF":1.6,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142000655","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Joint meta-analysis of two diagnostic tests accounting for within and between studies dependence. 两种诊断测试的联合荟萃分析，考虑了研究内部和研究之间的依赖性。

IF 2.3 3区医学

Statistical Methods in Medical Research Pub Date : 2024-09-11 DOI: 10.1177/09622802241269645

Aristidis K Nikoloulopoulos

{"title":"Joint meta-analysis of two diagnostic tests accounting for within and between studies dependence.","authors":"Aristidis K Nikoloulopoulos","doi":"10.1177/09622802241269645","DOIUrl":"https://doi.org/10.1177/09622802241269645","url":null,"abstract":"There is an extensive literature on methods for meta-analysis of diagnostic test accuracy, but it mainly focuses on a single test. A multinomial generalised linear mixed model was recently proposed for the joint meta-analysis of studies comparing two tests on the same participants in a paired tests design with a gold standard. In this setting, we propose a novel model for joint meta-analysis of studies comparing two diagnostic tests which assumes independent multinomial distributions for the counts of each combination of test results in diseased and non-diseased patients, conditional on the latent vector of probabilities of each combination of test results in diseased and non-diseased patients. For the random effects distribution of the latent proportions, we employ a one-truncated D-vine copula that can provide tail dependence or asymmetry. The proposed model includes the multinomial generalised linear mixed model as a special case, accounts for the within-study dependence induced because the tests are applied to the same participants, allows for between-studies dependence, and can also operate on the original scale of the latent proportions. The latter enables the derivation of summary receiver operating characteristic curves. Our methodology is demonstrated with simulation studies and a meta-analysis of screening for Down's syndrome with two tests: shortened humerus and shortened femur.","PeriodicalId":22038,"journal":{"name":"Statistical Methods in Medical Research","volume":"46 1","pages":"9622802241269645"},"PeriodicalIF":2.3,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142178622","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Common odds ratio test and interval estimation for stratified bilateral and unilateral data 分层双边和单边数据的共同几率检验和区间估计

IF 2.3 3区医学

Statistical Methods in Medical Research Pub Date : 2024-09-11 DOI: 10.1177/09622802241267357

Shuangcheng Hua, Changxing Ma

引用次数: 0

A dependent circular-linear model for multivariate biomechanical data: Ilizarov ring fixator study. 多变量生物力学数据的依赖性圆线性模型：Ilizarov环形固定器研究。

IF 1.6 3区医学

Statistical Methods in Medical Research Pub Date : 2024-09-01 Epub Date: 2024-08-06 DOI: 10.1177/09622802241268654

Priyanka Nagar, Andriette Bekker, Mohammad Arashi, Cor-Jacques Kat, Annette-Christi Barnard

{"title":"A dependent circular-linear model for multivariate biomechanical data: Ilizarov ring fixator study.","authors":"Priyanka Nagar, Andriette Bekker, Mohammad Arashi, Cor-Jacques Kat, Annette-Christi Barnard","doi":"10.1177/09622802241268654","DOIUrl":"10.1177/09622802241268654","url":null,"abstract":"Biomechanical and orthopaedic studies frequently encounter complex datasets that encompass both circular and linear variables. In most cases (i) the circular and linear variables are considered in isolation with dependency between variables neglected and (ii) the cyclicity of the circular variables is disregarded resulting in erroneous decision making. Given the inherent characteristics of circular variables, it is imperative to adopt methods that integrate directional statistics to achieve precise modelling. This paper is motivated by the modelling of biomechanical data, that is, the fracture displacements, that is used as a measure in external fixator comparisons. We focus on a dataset, based on an Ilizarov ring fixator, comprising of six variables. A modelling framework applicable to the six-dimensional joint distribution of circular-linear data based on vine copulas is proposed. The pair-copula decomposition concept of vine copulas represents the dependence structure as a combination of circular-linear, circular-circular and linear-linear pairs modelled by their respective copulas. This framework allows us to assess the dependencies in the joint distribution as well as account for the cyclicity of the circular variables. Thus, a new approach for accurate modelling of mechanical behaviour for Ilizarov ring fixators and other data of this nature is imparted.","PeriodicalId":22038,"journal":{"name":"Statistical Methods in Medical Research","volume":" ","pages":"1660-1672"},"PeriodicalIF":1.6,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11497752/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141894363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Estimation and inference on the partial volume under the receiver operating characteristic surface. 接收器工作特征表面下部分体积的估计和推断。

IF 1.6 3区医学

Statistical Methods in Medical Research Pub Date : 2024-09-01 Epub Date: 2024-08-08 DOI: 10.1177/09622802241267356

Kate J Young, Leonidas E Bantis

{"title":"Estimation and inference on the partial volume under the receiver operating characteristic surface.","authors":"Kate J Young, Leonidas E Bantis","doi":"10.1177/09622802241267356","DOIUrl":"10.1177/09622802241267356","url":null,"abstract":"measures of biomarker accuracy that employ the receiver operating characteristic surface have been proposed for biomarkers that classify patients into one of three groups: healthy, benign, or aggressive disease. The volume under the receiver operating characteristic surface summarizes the overall discriminatory ability of a biomarker in such configurations, but includes cutoffs associated with clinically irrelevant true classification rates. Due to the lethal nature of pancreatic cancer, cutoffs associated with a low true classification rate for identifying patients with pancreatic cancer may be undesirable and not appropriate for use in a clinical setting. In this project, we study the properties of a more focused criterion, the partial volume under the receiver operating characteristic surface, that summarizes the diagnostic accuracy of a marker in the three-class setting for regions restricted to only those of clinical interest. We propose methods for estimation and inference on the partial volume under the receiver operating characteristic surface under parametric and non-parametric frameworks and apply these methods to the evaluation of potential biomarkers for the diagnosis of pancreatic cancer.","PeriodicalId":22038,"journal":{"name":"Statistical Methods in Medical Research","volume":" ","pages":"1577-1594"},"PeriodicalIF":1.6,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141907756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Multivariate Poisson cokriging: A geostatistical model for health count data. 多变量泊松 cokriging：健康计数数据的地质统计模型

IF 1.6 3区医学

Statistical Methods in Medical Research Pub Date : 2024-09-01 Epub Date: 2024-08-14 DOI: 10.1177/09622802241268488

David Payares-Garcia, Frank Osei, Jorge Mateu, Alfred Stein

{"title":"Multivariate Poisson cokriging: A geostatistical model for health count data.","authors":"David Payares-Garcia, Frank Osei, Jorge Mateu, Alfred Stein","doi":"10.1177/09622802241268488","DOIUrl":"10.1177/09622802241268488","url":null,"abstract":"Multivariate disease mapping is important for public health research, as it provides insights into spatial patterns of health outcomes. Geostatistical methods that are widely used for mapping spatially correlated health data encounter challenges when dealing with spatial count data. These include heterogeneity, zero-inflated distributions and unreliable estimation, and lead to difficulties when estimating spatial dependence and poor predictions. Variability in population sizes further complicates risk estimation from the counts. This study introduces multivariate Poisson cokriging for predicting and filtering out disease risk. Pairwise correlations between the target variable and multiple ancillary variables are included. By means of a simulation experiment and an application to human immunodeficiency virus incidence and sexually transmitted diseases data in Pennsylvania, we demonstrate accurate disease risk estimation that captures fine-scale variation. This method is compared with ordinary Poisson kriging in prediction and smoothing. Results of the simulation study show a reduction in the mean square prediction error when utilizing auxiliary correlated variables, with mean square prediction error values decreasing by up to 50%. This gain is further evident in the real data analysis, where Poisson cokriging yields a 74% drop in mean square prediction error relative to Poisson kriging, underscoring the value of incorporating secondary information. The findings of this work stress on the potential of Poisson cokriging in disease mapping and surveillance, offering richer risk predictions, better representation of spatial interdependencies, and identification of high-risk and low-risk areas.","PeriodicalId":22038,"journal":{"name":"Statistical Methods in Medical Research","volume":" ","pages":"1637-1659"},"PeriodicalIF":1.6,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11500483/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141976656","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

A general consonance principle for closure tests based on p-values. 基于 p 值的闭合检验的一般一致性原则。

IF 1.6 3区医学

Statistical Methods in Medical Research Pub Date : 2024-09-01 DOI: 10.1177/09622802241269624

Sonja Zehetmayer, Franz Koenig, Martin Posch

{"title":"<ArticleTitle xmlns:ns0=\"http://www.w3.org/1998/Math/MathML\">A general consonance principle for closure tests based on <ns0:math><ns0:mi>p</ns0:mi></ns0:math>-values.","authors":"Sonja Zehetmayer, Franz Koenig, Martin Posch","doi":"10.1177/09622802241269624","DOIUrl":"https://doi.org/10.1177/09622802241269624","url":null,"abstract":"The closure principle is a powerful approach to constructing efficient testing procedures controlling the familywise error rate in the strong sense. For small numbers of hypotheses and the setting of independent elementary <math><mi>p</mi></math>-values we consider closed tests where each intersection hypothesis is tested with a <math><mi>p</mi></math>-value combination test. Examples of such combination tests are the Fisher combination test, the Stouffer test, the Omnibus test, the truncated test, or the Wilson test. Some of these tests, such as the Fisher combination, the Stouffer, or the Omnibus test, are not consonant and rejection of the global null hypothesis does not always lead to rejection of at least one elementary null hypothesis. We develop a general principle to uniformly improve closed tests based on <math><mi>p</mi></math>-value combination tests by modifying the rejection regions such that the new procedure becomes consonant. For the Fisher combination test and the Stouffer test, we show by simulations that this improvement can lead to a substantial increase in power.","PeriodicalId":22038,"journal":{"name":"Statistical Methods in Medical Research","volume":"33 9","pages":"1595-1609"},"PeriodicalIF":1.6,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142508327","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Improving estimation efficiency of case-cohort studies with interval-censored failure time data. 利用区间失效时间数据提高病例队列研究的估算效率。

IF 1.6 3区医学

Statistical Methods in Medical Research Pub Date : 2024-09-01 Epub Date: 2024-08-06 DOI: 10.1177/09622802241268601

Qingning Zhou, Kin Yau Wong

{"title":"Improving estimation efficiency of case-cohort studies with interval-censored failure time data.","authors":"Qingning Zhou, Kin Yau Wong","doi":"10.1177/09622802241268601","DOIUrl":"10.1177/09622802241268601","url":null,"abstract":"The case-cohort design is a commonly used cost-effective sampling strategy for large cohort studies, where some covariates are expensive to measure or obtain. In this paper, we consider regression analysis under a case-cohort study with interval-censored failure time data, where the failure time is only known to fall within an interval instead of being exactly observed. A common approach to analyzing data from a case-cohort study is the inverse probability weighting approach, where only subjects in the case-cohort sample are used in estimation, and the subjects are weighted based on the probability of inclusion into the case-cohort sample. This approach, though consistent, is generally inefficient as it does not incorporate information outside the case-cohort sample. To improve efficiency, we first develop a sieve maximum weighted likelihood estimator under the Cox model based on the case-cohort sample and then propose a procedure to update this estimator by using information in the full cohort. We show that the update estimator is consistent, asymptotically normal, and at least as efficient as the original estimator. The proposed method can flexibly incorporate auxiliary variables to improve estimation efficiency. A weighted bootstrap procedure is employed for variance estimation. Simulation results indicate that the proposed method works well in practical situations. An application to a Phase 3 HIV vaccine efficacy trial is provided for illustration.","PeriodicalId":22038,"journal":{"name":"Statistical Methods in Medical Research","volume":" ","pages":"1673-1685"},"PeriodicalIF":1.6,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141894364","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Sample size calculation for mixture cure model with restricted mean survival time as a primary endpoint. 以受限平均存活时间为主要终点的混合治愈模型的样本量计算。

IF 1.6 3区医学

Statistical Methods in Medical Research Pub Date : 2024-09-01 Epub Date: 2024-08-06 DOI: 10.1177/09622802241265501

Zhaojin Li, Xiang Geng, Yawen Hou, Zheng Chen

{"title":"Sample size calculation for mixture cure model with restricted mean survival time as a primary endpoint.","authors":"Zhaojin Li, Xiang Geng, Yawen Hou, Zheng Chen","doi":"10.1177/09622802241265501","DOIUrl":"10.1177/09622802241265501","url":null,"abstract":"It is not uncommon for a substantial proportion of patients to be cured (or survive long-term) in clinical trials with time-to-event endpoints, such as the endometrial cancer trial. When designing a clinical trial, a mixture cure model should be used to fully consider the cure fraction. Previously, mixture cure model sample size calculations were based on the proportional hazards assumption of latency distribution between groups, and the log-rank test was used for deriving sample size formulas. In real studies, the latency distributions of the two groups often do not satisfy the proportional hazards assumptions. This article has derived a sample size calculation formula for a mixture cure model with restricted mean survival time as the primary endpoint, and did simulation and example studies. The restricted mean survival time test is not subject to proportional hazards assumptions, and the difference in treatment effect obtained can be quantified as the number of years (or months) increased or decreased in survival time, making it very convenient for clinical patient-physician communication. The simulation results showed that the sample sizes estimated by the restricted mean survival time test for the mixture cure model were accurate regardless of whether the proportional hazards assumptions were satisfied and were smaller than the sample sizes estimated by the log-rank test in most cases for the scenarios in which the proportional hazards assumptions were violated.","PeriodicalId":22038,"journal":{"name":"Statistical Methods in Medical Research","volume":" ","pages":"1546-1558"},"PeriodicalIF":1.6,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141898272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Accounting for regression to the mean under the bivariate t-distribution. 双变量 t 分布下的均值回归核算。

IF 1.6 3区医学

Statistical Methods in Medical Research Pub Date : 2024-09-01 Epub Date: 2024-08-08 DOI: 10.1177/09622802241267808

Muhammad Umair, Manzoor Khan, Jake Olivier

{"title":"<ArticleTitle xmlns:ns0=\"http://www.w3.org/1998/Math/MathML\">Accounting for regression to the mean under the bivariate <ns0:math><ns0:mi>t</ns0:mi></ns0:math>-distribution.","authors":"Muhammad Umair, Manzoor Khan, Jake Olivier","doi":"10.1177/09622802241267808","DOIUrl":"10.1177/09622802241267808","url":null,"abstract":"Regression to the mean occurs when an unusual observation is followed by a more typical outcome closer to the population mean. In pre- and post-intervention studies, treatment is administered to subjects with initial measurements located in the tail of a distribution, and a paired sample <math><mi>t</mi></math>-test can be utilized to assess the effectiveness of the intervention. The observed change in the pre-post means is the sum of regression to the mean and treatment effects, and ignoring regression to the mean could lead to erroneous conclusions about the effectiveness of the treatment effect. In this study, formulae for regression to the mean are derived, and maximum likelihood estimation is employed to numerically estimate the regression to the mean effect when the test statistic follows the bivariate <math><mi>t</mi></math>-distribution based on a baseline criterion or a cut-off point. The pre-post degrees of freedom could be equal but also unequal such as when there is missing data. Additionally, we illustrate how regression to the mean is influenced by cut-off points, mixing angles which are related to correlation, and degrees of freedom. A simulation study is conducted to assess the statistical properties of unbiasedness, consistency, and asymptotic normality of the regression to the mean estimator. Moreover, the proposed methods are compared with an existing one assuming bivariate normality. The <math><mi>p</mi></math>-values are compared when regression to the mean is either ignored or accounted for to gauge the statistical significance of the paired <math><mi>t</mi></math>-test. The proposed method is applied to real data concerning schizophrenia patients, and the observed conditional mean difference called the total effect is decomposed into the regression to the mean and treatment effects.","PeriodicalId":22038,"journal":{"name":"Statistical Methods in Medical Research","volume":" ","pages":"1624-1636"},"PeriodicalIF":1.6,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141907755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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