Biometrical Journal最新文献

A New Inverse Probability of Selection Weighted Cox Model to Deal With Outcome-Dependent Sampling in Survival Analysis 生存分析中基于结果相关抽样的一种新的逆选择概率加权Cox模型

IF 1.3 3区生物学

Biometrical Journal Pub Date : 2025-06-11 DOI: 10.1002/bimj.70056

Vera H. Arntzen, Marta Fiocco, Inge M. M. Lakeman, Maartje Nielsen, Mar Rodríguez-Girondo

{"title":"A New Inverse Probability of Selection Weighted Cox Model to Deal With Outcome-Dependent Sampling in Survival Analysis","authors":"Vera H. Arntzen, Marta Fiocco, Inge M. M. Lakeman, Maartje Nielsen, Mar Rodríguez-Girondo","doi":"10.1002/bimj.70056","DOIUrl":"https://doi.org/10.1002/bimj.70056","url":null,"abstract":"<p>Motivated by the study of genetic effect modifiers of cancer, we examined weighting approaches to correct for ascertainment bias in survival analysis. Outcome-dependent sampling is common in genetic epidemiology leading to study samples with too many events in comparison to the population and an overrepresentation of young, affected subjects. A usual approach to correct for ascertainment bias in this setting is to use an inverse probability-weighted Cox model, using weights based on external available population-based age-specific incidence rates of the type of cancer under investigation. However, the current approach is not general enough leading to invalid weights in relevant practical settings if oversampling of cases is not observed in all age groups. Based on the same principle of weighting observations by their inverse probability of selection, we propose a new, more general approach, called the generalized weighted approach. We show the advantage of the new generalized weighted cohort method using simulations and two real data sets. In both applications, the goal is to assess the association between common susceptibility loci identified in genome-wide association studies (GWAS) and cancer (colorectal and breast) using data collected through genetic testing in clinical genetics centers.</p>","PeriodicalId":55360,"journal":{"name":"Biometrical Journal","volume":"67 3","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/bimj.70056","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144264540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Outcomes Truncated by Death in RCTs: A Simulation Study on the Survivor Average Causal Effect 随机对照试验中被死亡截断的结果：幸存者平均因果效应的模拟研究

IF 1.3 3区生物学

Biometrical Journal Pub Date : 2025-06-11 DOI: 10.1002/bimj.70061

Stefanie von Felten, Chiara Vanetta, Christoph M. Rüegger, Sven Wellmann, Leonhard Held

{"title":"Outcomes Truncated by Death in RCTs: A Simulation Study on the Survivor Average Causal Effect","authors":"Stefanie von Felten, Chiara Vanetta, Christoph M. Rüegger, Sven Wellmann, Leonhard Held","doi":"10.1002/bimj.70061","DOIUrl":"https://doi.org/10.1002/bimj.70061","url":null,"abstract":"<div>\u0000 \u0000 <p>Continuous outcome measurements truncated by death present a challenge for the estimation of unbiased treatment effects in randomized controlled trials (RCTs). One way to deal with such situations is to estimate the survivor average causal effect (SACE), but this requires making nontestable assumptions. Motivated by an ongoing RCT in very preterm infants with intraventricular hemorrhage, we performed a simulation study to compare an SACE estimator with complete case analysis (CCA) and analysis after multiple imputation of missing outcomes. We set up nine scenarios combining positive, negative, and no treatment effect on the outcome (cognitive development) and on survival at 2 years of age. Treatment effect estimates from all methods were compared in terms of bias, mean squared error, and coverage with regard to two true treatment effects: the treatment effect on the outcome used in the simulation and the SACE, which was derived by simulation of both potential outcomes per patient. Despite targeting different estimands (principal stratum estimand, hypothetical estimand), the SACE-estimator and multiple imputation gave similar estimates of the treatment effect and efficiently reduced the bias compared to CCA. Also, both methods were relatively robust to omission of one covariate in the analysis, and thus violation of relevant assumptions. Although the SACE is not without controversy, we find it useful if mortality is inherent to the study population. Some degree of violation of the required assumptions is almost certain, but may be acceptable in practice.</p></div>","PeriodicalId":55360,"journal":{"name":"Biometrical Journal","volume":"67 3","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144264541","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Statistical Modeling to Adjust for Time Trends in Adaptive Platform Trials Utilizing Non-Concurrent Controls 利用非并发控制的自适应平台试验中调整时间趋势的统计建模

IF 1.3 3区生物学

Biometrical Journal Pub Date : 2025-06-10 DOI: 10.1002/bimj.70059

Pavla Krotka, Martin Posch, Mohamed Gewily, Günter Höglinger, Marta Bofill Roig

{"title":"Statistical Modeling to Adjust for Time Trends in Adaptive Platform Trials Utilizing Non-Concurrent Controls","authors":"Pavla Krotka, Martin Posch, Mohamed Gewily, Günter Höglinger, Marta Bofill Roig","doi":"10.1002/bimj.70059","DOIUrl":"https://doi.org/10.1002/bimj.70059","url":null,"abstract":"<p>Utilizing non-concurrent control (NCC) data in the analysis of late-entering arms in platform trials has recently received considerable attention. While incorporating NCC can lead to increased power and lower sample sizes, it might introduce bias to the effect estimators if temporal drifts are present. Aiming to mitigate this potential bias, we propose various frequentist model-based approaches that leverage the NCC, while adjusting for time. One of the currently available models incorporates time as a categorical fixed effect, separating the trial duration into periods, defined as time intervals bounded by any arm entering or leaving the platform. In this work, we propose two extensions of this model. First, we consider an alternative definition of time by dividing the trial into fixed-length calendar time intervals. Second, we propose alternative model-based time adjustments. Specifically, we investigate adjusting for random effects and employing splines to model time with a polynomial function. We evaluate the performance of the proposed approaches in a simulation study and illustrate their use through a case study. We show that adjusting for time via a spline function controls the type I error in trials with a sufficiently smooth time trend pattern and may lead to power gains compared to the standard fixed effect model. However, the fixed effect model with period adjustment is the most robust model for arbitrary time trends, provided that the trend is equal across all arms. Especially, in trials with sudden changes in the time trend, the period-adjustment model is preferred if NCCs are included.</p>","PeriodicalId":55360,"journal":{"name":"Biometrical Journal","volume":"67 3","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/bimj.70059","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144244560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","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 Bivariate Finite Mixture Random Effects Model for Identifying and Accommodating Outliers in Diagnostic Test Accuracy Meta-Analyses 诊断测试准确性荟萃分析中识别和容纳异常值的二元有限混合随机效应模型

IF 1.3 3区生物学

Biometrical Journal Pub Date : 2025-06-09 DOI: 10.1002/bimj.70062

Zelalem F. Negeri

{"title":"A Bivariate Finite Mixture Random Effects Model for Identifying and Accommodating Outliers in Diagnostic Test Accuracy Meta-Analyses","authors":"Zelalem F. Negeri","doi":"10.1002/bimj.70062","DOIUrl":"https://doi.org/10.1002/bimj.70062","url":null,"abstract":"<p>Outlying studies are prevalent in meta-analyses of diagnostic test accuracy studies and may lead to misleading inferences and decision-making unless their negative effect is appropriately dealt with. Statistical methods for detecting and down-weighting the impact of such studies have recently gained the attention of many researchers. However, these methods dichotomize each study in the meta-analysis as outlying or non-outlying and focus on examining the effect of outlying studies on the summary sensitivity and specificity only. We developed and evaluated a robust and flexible random-effects bivariate finite mixture model for meta-analyzing diagnostic test accuracy studies. The proposed model accounts for both the within- and across-study heterogeneity in diagnostic test results, generates the probability that each study in a meta-analysis is outlying instead of dichotomizing the status of the studies, and allows assessing the impact of outlying studies on the pooled sensitivity, pooled specificity, and between-study heterogeneity. Our simulation study and real-life data examples demonstrated that the proposed model was robust to the existence of outlying studies, produced precise point and interval estimates of the pooled sensitivity and specificity, and yielded similar results to the standard models when there were no outliers. Extensive simulations demonstrated relatively better bias and confidence interval width, but comparable root mean squared error and lesser coverage probability of the proposed model. Practitioners can use our proposed model as a stand-alone model to conduct a meta-analysis of diagnostic test accuracy studies or as an alternative sensitivity analysis model when outlying studies are present in a meta-analysis.</p>","PeriodicalId":55360,"journal":{"name":"Biometrical Journal","volume":"67 3","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/bimj.70062","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144244476","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Hazards Constitute Key Quantities for Analyzing, Interpreting and Understanding Time-to-Event Data 危害构成了分析、解释和理解事件发生时间数据的关键量

IF 1.3 3区生物学

Biometrical Journal Pub Date : 2025-06-06 DOI: 10.1002/bimj.70057

Jan Beyersmann, Claudia Schmoor, Martin Schumacher

{"title":"Hazards Constitute Key Quantities for Analyzing, Interpreting and Understanding Time-to-Event Data","authors":"Jan Beyersmann, Claudia Schmoor, Martin Schumacher","doi":"10.1002/bimj.70057","DOIUrl":"https://doi.org/10.1002/bimj.70057","url":null,"abstract":"<p>Censoring makes time-to-event data special and requires customized statistical techniques. Survival and event history analysis therefore builds on hazards as the identifiable quantities in the presence of rather general censoring schemes. The reason is that hazards are conditional quantities, given previous survival, which enables estimation based on the current risk set—those still alive and under observation. But it is precisely their conditional nature that has made hazards subject of critique from a causal perspective: A beneficial treatment will help patients survive longer than had they remained untreated. Hence, in a randomized trial, randomization is broken in later risk sets, which, however, are the basis for statistical inference. We survey this dilemma—after all, mapping analyses of hazards onto probabilities in randomized trials is viewed as still having a causal interpretation—and argue that a causal interpretation is possible taking a functional point of view. We illustrate matters with examples from benefit–risk assessment: Prolonged survival may lead to more adverse events, but this need not imply a worse safety profile of the novel treatment. These examples illustrate that the situation at hand is conveniently parameterized using hazards, that the need to use survival techniques is not always fully appreciated and that censoring not necessarily leads to the question of “what, if no censoring?” The discussion should concentrate on how to correctly interpret causal hazard contrasts and analyses of hazards should routinely be translated onto probabilities.</p>","PeriodicalId":55360,"journal":{"name":"Biometrical Journal","volume":"67 3","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/bimj.70057","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144219931","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Estimating the Optimal Time to Perform a Positron Emission Tomography With Prostate-Specific Membrane Antigen in Prostatectomized Patients, Based on Data From Clinical Practice 基于临床实践的数据估计前列腺切除术患者进行前列腺特异性膜抗原正电子发射断层扫描的最佳时间

IF 1.3 3区生物学

Biometrical Journal Pub Date : 2025-05-22 DOI: 10.1002/bimj.70058

Martina Amongero, Gianluca Mastrantonio, Stefano De Luca, Mauro Gasparini

{"title":"Estimating the Optimal Time to Perform a Positron Emission Tomography With Prostate-Specific Membrane Antigen in Prostatectomized Patients, Based on Data From Clinical Practice","authors":"Martina Amongero, Gianluca Mastrantonio, Stefano De Luca, Mauro Gasparini","doi":"10.1002/bimj.70058","DOIUrl":"https://doi.org/10.1002/bimj.70058","url":null,"abstract":"<p>Prostatectomized patients are at risk of resurgence, and for this reason, during a follow-up period, they are monitored for prostate-specific antigen (PSA) growth, an indicator of tumor progression. The presence of tumors can be evaluated with an expensive exam, called positron emission tomography with prostate-specific membrane antigen (PET-PSMA). To justify the high cost of the PET-PSMA and, at the same time, to contain the risk for the patient, this exam should be recommended only when the evidence of tumor progression is strong. With the aim of estimating the optimal time to recommend the exam based on the patient's history and collected data, we build a hierarchical Bayesian model that describes, jointly, the PSA growth curve and the probability of a positive PET-PSMA. With our proposal, we process all past and present information about the patients PSA measurement and PET-PSMA results, in order to give an informed estimate of the optimal time, improving current practice.</p>","PeriodicalId":55360,"journal":{"name":"Biometrical Journal","volume":"67 3","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/bimj.70058","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144108956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Issue Information: Biometrical Journal 3'25 期刊信息：bioometic Journal 3'25

IF 1.3 3区生物学

Biometrical Journal Pub Date : 2025-05-12 DOI: 10.1002/bimj.70060

引用次数: 0

Semi-Markov Multistate Modeling Approaches for Multicohort Event History Data 多队列事件历史数据的半马尔可夫多状态建模方法

IF 1.3 3区生物学

Biometrical Journal Pub Date : 2025-05-08 DOI: 10.1002/bimj.70051

Xavier Piulachs, Klaus Langohr, Mireia Besalú, Natàlia Pallarès, Jordi Carratalà, Cristian Tebé, Guadalupe Gómez Melis

{"title":"Semi-Markov Multistate Modeling Approaches for Multicohort Event History Data","authors":"Xavier Piulachs, Klaus Langohr, Mireia Besalú, Natàlia Pallarès, Jordi Carratalà, Cristian Tebé, Guadalupe Gómez Melis","doi":"10.1002/bimj.70051","DOIUrl":"https://doi.org/10.1002/bimj.70051","url":null,"abstract":"<div>\u0000 \u0000 <p>Two Cox-based multistate modeling approaches are compared for modeling a complex multicohort event history process. The first approach incorporates cohort information as a fixed covariate, thereby providing a direct estimation of the cohort-specific effects. The second approach includes the cohort as a stratum variable, which offers an extra flexibility in estimating the transition probabilities. Additionally, both approaches may include possible interaction terms between the cohort and a given prognostic predictor. Furthermore, the Markov property conditional on observed prognostic covariates is assessed using a global score test. Whenever departures from the Markovian assumption are revealed for a given transition, the time of entry into the current state is incorporated as a fixed covariate, yielding a semi-Markov process. The two proposed methods are applied to a three-wave dataset of COVID-19-hospitalized adults in the southern Barcelona metropolitan area (Spain), and the corresponding performance is discussed. While both semi-Markovian approaches are shown to be useful, the preferred one will depend on the focus of the inference. To summarize, the cohort–covariate approach enables an insightful discussion on the behavior of the cohort effects, whereas the stratum–cohort approach provides flexibility to estimate transition-specific underlying risks according to the different cohorts.</p></div>","PeriodicalId":55360,"journal":{"name":"Biometrical Journal","volume":"67 3","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143919341","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

How Should Parallel Cluster Randomized Trials With a Baseline Period be Analyzed?—A Survey of Estimands and Common Estimators 有基线期的平行群随机试验应该如何分析？-估价及一般估价员概览

IF 1.3 3区生物学

Biometrical Journal Pub Date : 2025-04-29 DOI: 10.1002/bimj.70052

Kenneth Menglin Lee, Fan Li

{"title":"How Should Parallel Cluster Randomized Trials With a Baseline Period be Analyzed?—A Survey of Estimands and Common Estimators","authors":"Kenneth Menglin Lee, Fan Li","doi":"10.1002/bimj.70052","DOIUrl":"https://doi.org/10.1002/bimj.70052","url":null,"abstract":"<p>The parallel cluster randomized trial with baseline (PB-CRT) is a common variant of the standard parallel cluster randomized trial (P-CRT). We define two natural estimands in the context of PB-CRTs with informative cluster sizes, the individual-average treatment effect (iATE) and cluster-average treatment effect (cATE), to address individual and cluster-level hypotheses. In this work, we theoretically derive the convergence of the unweighted and inverse cluster-period size weighted (i) independence estimating equation (IEE), (ii) fixed-effects (FE) model, (iii) exchangeable mixed-effects (EME) model, and (iv) nested-exchangeable mixed-effects (NEME) model treatment effect estimators in a PB-CRT with informative cluster sizes and continuous outcomes. Overall, we theoretically show that the unweighted and weighted IEE and FE models yield consistent estimators for the iATE and cATE estimands. Although mixed-effects models yield inconsistent estimators to these two natural estimands under informative cluster sizes, we empirically demonstrate that the EME model is surprisingly robust to bias. This is in sharp contrast to the corresponding analyses in P-CRTs and the NEME model in PB-CRTs when informative cluster sizes are present, carrying implications for practice. We report a simulation study and conclude with a re-analysis of a PB-CRT examining the effects of community youth teams on improving mental health among adolescent girls in rural eastern India.</p>","PeriodicalId":55360,"journal":{"name":"Biometrical Journal","volume":"67 3","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/bimj.70052","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143889149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Bayesian Inference of Phenotypic Plasticity of Cancer Cells Based on Dynamic Model for Temporal Cell Proportion Data 基于时间细胞比例数据动态模型的癌细胞表型可塑性贝叶斯推断

IF 1.3 3区生物学

Biometrical Journal Pub Date : 2025-04-29 DOI: 10.1002/bimj.70055

Shuli Chen, Yuman Wang, Da Zhou, Jie Hu

{"title":"Bayesian Inference of Phenotypic Plasticity of Cancer Cells Based on Dynamic Model for Temporal Cell Proportion Data","authors":"Shuli Chen, Yuman Wang,  Da Zhou, Jie Hu","doi":"10.1002/bimj.70055","DOIUrl":"https://doi.org/10.1002/bimj.70055","url":null,"abstract":"<div>\u0000 \u0000 <p>Mounting evidence underscores the prevalent hierarchical organization of cancer tissues. At the foundation of this hierarchy reside cancer stem cells, a subset of cells endowed with the pivotal role of engendering the entire cancer tissue through cell differentiation. In recent times, substantial attention has been directed toward the phenomenon of cancer cell plasticity, where the dynamic interconversion between cancer stem cells and nonstem cancer cells has garnered significant interest. Since the task of detecting cancer cell plasticity from empirical data remains a formidable challenge, we propose a Bayesian statistical framework designed to infer phenotypic plasticity within cancer cells, utilizing temporal data on cancer stem cell proportions. Our approach is grounded in a stochastic model, adept at capturing the dynamic behaviors of cells. Leveraging Bayesian analysis, we scrutinize the moment equation governing cancer stem cell proportions, derived from the Kolmogorov forward equation of our stochastic model. Our methodology introduces an improved Euler method for parameter estimation within nonlinear ordinary differential equation models, also extending insights to compositional data. Extensive simulations robustly validate the efficacy of our proposed method. To further corroborate our findings, we apply our approach to analyze published data from SW620 colon cancer cell lines. Our results harmonize with in situ experiments, thereby reinforcing the utility of our method in discerning and quantifying phenotypic plasticity within cancer cells.</p></div>","PeriodicalId":55360,"journal":{"name":"Biometrical Journal","volume":"67 3","pages":""},"PeriodicalIF":1.3,"publicationDate":"2025-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143884019","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0