Statistics in Medicine最新文献_第4页

Clinically Interpretable Time-To-Event Testing in Randomized Clinical Trials: Milestone Survival Combined With Restricted Mean Survival Time. 随机临床试验中临床可解释的事件发生时间检验：里程碑生存与限制平均生存时间相结合。

IF 2.1 4区医学

Statistics in Medicine Pub Date : 2026-10-01 DOI: 10.1002/sim.70787

Siwen He, Ludovic Trinquart

{"title":"Clinically Interpretable Time-To-Event Testing in Randomized Clinical Trials: Milestone Survival Combined With Restricted Mean Survival Time.","authors":"Siwen He, Ludovic Trinquart","doi":"10.1002/sim.70787","DOIUrl":"10.1002/sim.70787","url":null,"abstract":"The log-rank test and hazard ratio (HR) are widely used to compare survival curves in event-driven randomized clinical trials (RCTs). The optimality of the log-rank test and interpretation of the HR rely on the proportional hazards (PH) assumption, which is frequently violated in oncology due to delayed, waning, or crossing hazards. Although combination procedures built from weighted log-rank tests improve robustness to non-PH, hazard-based summaries remain difficult to interpret clinically. We propose combination tests that integrate two clinically interpretable estimands: the between-group difference in milestone survival probability <math><mrow><mi>S</mi> <mrow><mo>(</mo> <mi>τ</mi> <mo>)</mo></mrow> </mrow> </math> and in restricted mean survival time (RMST) <math><mrow><mi>μ</mi> <mrow><mo>(</mo> <mn>0</mn> <mo>,</mo> <mi>τ</mi> <mo>)</mo></mrow> </mrow> </math> . Using Monte Carlo simulations under a milestone-based design (uniform follow-up to <math><mrow><mi>τ</mi></mrow> </math> ) and supplementary event-driven designs, we compared the proposed combinations with the log-rank and MaxCombo tests across diverse survival patterns, sample sizes, and censoring rates. We evaluated Type I error and power. The milestone combination procedures showed rejection probabilities close to the nominal level under the estimand-null configurations examined and showed competitive to superior power in non-PH settings, including transient effects and crossing hazards. Applications to three oncology RCTs illustrate that, when HRs hover near unity while absolute estimands differ, the milestone combinations can detect benefits at clinically meaningful horizons. These findings support aligning design, estimands, and analysis around a prespecified milestone. Careful selection of <math><mrow><mi>τ</mi></mrow> </math> is essential to balance information and interpretability. Milestone-based combination tests provide a viable, patient-centered alternative or complement to HR-centric methods, particularly when non-PH is anticipated.","PeriodicalId":21879,"journal":{"name":"Statistics in Medicine","volume":"45 23-24","pages":"e70787"},"PeriodicalIF":2.1,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149196532","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

A Path-Based Approach for Detecting and Assessing Inconsistency in Network Meta-Analysis. 基于路径的网络元分析不一致性检测与评估方法。

IF 2.1 4区医学

Statistics in Medicine Pub Date : 2026-10-01 DOI: 10.1002/sim.70752

Noosheen R Tahmasebi, Annabel L Davies, Theodoros Papakonstantinou, Gerta Rücker, Adriani Nikolakopoulou

{"title":"A Path-Based Approach for Detecting and Assessing Inconsistency in Network Meta-Analysis.","authors":"Noosheen R Tahmasebi, Annabel L Davies, Theodoros Papakonstantinou, Gerta Rücker, Adriani Nikolakopoulou","doi":"10.1002/sim.70752","DOIUrl":"10.1002/sim.70752","url":null,"abstract":"Network Meta-Analysis (NMA) is a statistical technique for synthesizing evidence from various sources to compare multiple interventions. NMA relies on integrating both direct evidence from head-to-head comparisons and indirect evidence from different paths that link treatments through common comparators. A key aspect is evaluating consistency between direct and indirect sources. Existing methods to detect inconsistency, although widely used, have limitations. For example, they do not account for differences between indirect sources or cannot estimate inconsistency when direct evidence is absent. In this paper, we introduce a path-based approach that explores all sources of evidence without separating direct and indirect. We introduce a measure based on the square of differences to quantitatively capture inconsistency, and propose a Netpath plot to visualize inconsistencies between various paths. Moreover, it enables the evaluation of inconsistency even for treatment comparisons lacking direct evidence as long as at least two independent paths of evidence are available. We provide an implementation of our path-based method within the netmeta R package. Via application to fictional and real-world examples, we show that our method is able to detect and visualize inconsistency between multiple paths of evidence that would otherwise be masked by considering all indirect sources together. The path-based approach therefore provides a more comprehensive evaluation of inconsistency within a network of treatments.","PeriodicalId":21879,"journal":{"name":"Statistics in Medicine","volume":"45 23-24","pages":"e70752"},"PeriodicalIF":2.1,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13672679/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149196431","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

Evaluating Informative Cluster Size in Cluster Randomized Trials. 评价聚类随机试验中的信息聚类大小。

IF 2.1 4区医学

Statistics in Medicine Pub Date : 2026-10-01 DOI: 10.1002/sim.70762

Bryan S Blette, Zhe Chen, Brennan C Kahan, Andrew Forbes, Michael O Harhay, Fan Li

{"title":"Evaluating Informative Cluster Size in Cluster Randomized Trials.","authors":"Bryan S Blette, Zhe Chen, Brennan C Kahan, Andrew Forbes, Michael O Harhay, Fan Li","doi":"10.1002/sim.70762","DOIUrl":"https://doi.org/10.1002/sim.70762","url":null,"abstract":"In cluster randomized trials, the individual-average treatment effect (i-ATE) can be different from the cluster-average treatment effect (c-ATE) when informative cluster size (ICS) is present, that is, when treatment effects or participant outcomes depend on cluster size. In such scenarios, mixed-effects models and generalized estimating equations (GEEs) with exchangeable correlation structure are biased for both the i-ATE and c-ATE estimands, whereas GEEs with an independence correlation structure or analyses of cluster-level summaries are recommended in practice. However, when cluster size is non-informative, mixed-effects models and GEEs with exchangeable correlation structure can provide unbiased estimation and notable efficiency gains over other methods. Thus, hypothesis tests for ICS would be useful to assess this key phenomenon under cluster randomization. In this work, we develop model-based, model-assisted, and randomization-based tests for ICS in cluster randomized trials. We conduct simulation studies to examine the operating characteristics of these tests, show they have appropriate Type I error rate control and meaningful power, and contrast them to existing model-based tests used in the observational study setting. The proposed tests are then applied to data from a recent cluster randomized trial, and practical recommendations for using these tests are discussed.","PeriodicalId":21879,"journal":{"name":"Statistics in Medicine","volume":"45 23-24","pages":"e70762"},"PeriodicalIF":2.1,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149138360","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

A Statistical Perspective on Transformers for Small Longitudinal Cohort Data. 小型纵向队列数据变压器的统计观点。

IF 2.1 4区医学

Statistics in Medicine Pub Date : 2026-10-01 DOI: 10.1002/sim.70744

Kiana Farhadyar, Maren Hackenberg, Kira Ahrens, Charlotte Schenk, Bianca Kollmann, Oliver Tüscher, Klaus Lieb, Michael M Plichta, Andreas Reif, Raffael Kalisch, Martin Wolkewitz, Moritz Hess, Harald Binder

{"title":"A Statistical Perspective on Transformers for Small Longitudinal Cohort Data.","authors":"Kiana Farhadyar, Maren Hackenberg, Kira Ahrens, Charlotte Schenk, Bianca Kollmann, Oliver Tüscher, Klaus Lieb, Michael M Plichta, Andreas Reif, Raffael Kalisch, Martin Wolkewitz, Moritz Hess, Harald Binder","doi":"10.1002/sim.70744","DOIUrl":"10.1002/sim.70744","url":null,"abstract":"Modeling of longitudinal cohort data typically involves complex temporal dependencies between multiple variables. There, the transformer architecture, which has been highly successful in language and vision applications, allows us to account for the fact that the most recently observed time points in an individual's history may not always be the most important for the immediate future. This is achieved by assigning attention weights to observations of an individual based on a transformation of their values. One reason why these ideas have not yet been fully leveraged for longitudinal cohort data is that typically, large datasets are required. Therefore, we present a simplified transformer architecture that retains the core attention mechanism while reducing the number of parameters to be estimated, to be more suitable for small datasets with few time points. Guided by a statistical perspective on transformers, we use an autoregressive model as a starting point and incorporate attention as a kernel-based operation with temporal decay, where aggregation of multiple transformer heads, that is, different candidate weighting schemes, is expressed as accumulating evidence on different types of underlying characteristics of individuals. This also enables a permutation-based statistical testing procedure for identifying contextual patterns. In simulation studies, including a controlled simulation on real clinical predictor data, the approach is shown to recover contextual dependencies even with a small number of individuals and time points. In an application to data from a resilience study, we identify temporal patterns in the dynamics of stress and mental health. This indicates that properly adapted transformers can not only achieve competitive predictive performance, but also uncover complex context dependencies in small data settings.","PeriodicalId":21879,"journal":{"name":"Statistics in Medicine","volume":"45 23-24","pages":"e70744"},"PeriodicalIF":2.1,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13600780/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149031409","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

Gated Spatial Hidden Markov Models for Classification in Histological Samples, With Application to Muscle Fiber-Typing. 组织样本分类的门控空间隐马尔可夫模型及其在肌纤维分型中的应用。

IF 2.1 4区医学

Statistics in Medicine Pub Date : 2026-10-01 DOI: 10.1002/sim.70781

Tilman M Davies

引用次数: 0

Taking Into Account the Susceptible Window for Exposures in Cox Proportional Hazards Model: A Way Using Splines to Model the Lag-Risk Relationship. 考虑Cox比例风险模型中暴露的敏感窗口：一种用样条曲线模拟滞后风险关系的方法。

IF 2.1 4区医学

Statistics in Medicine Pub Date : 2026-10-01 DOI: 10.1002/sim.70755

Fuyu Guo, Zihan Qian, Wenyi Wang, Fenglei Wang, Bernard Rosner, Molin Wang

{"title":"Taking Into Account the Susceptible Window for Exposures in Cox Proportional Hazards Model: A Way Using Splines to Model the Lag-Risk Relationship.","authors":"Fuyu Guo, Zihan Qian, Wenyi Wang, Fenglei Wang, Bernard Rosner, Molin Wang","doi":"10.1002/sim.70755","DOIUrl":"10.1002/sim.70755","url":null,"abstract":"External exposures take time to accumulate and affect human health, leading to a time lag between initial exposure and the manifestation of clinical signs. Susceptible time window analysis aims to describe the relationship between the time since exposure and its effects. To obtain unbiased estimates in susceptible time window analysis, researchers may need to adjust for exposures measured at different times simultaneously. Conventional Cox proportional hazards models often fail in this regard due to the strong multicollinearity between lagged exposure terms. In addition to estimation challenges, missing data in historical exposures present another obstacle for long-term analysis. To address these challenges, we first impose flexible parametric models on the effects across historical exposures by assuming that they follow restricted cubic splines. Based on our proposed restricted cubic spline model, we develop two model selection algorithms to help researchers determine the optimal knot locations in the splines. Additionally, we propose using multiple imputations to handle the missing exposure data. We conducted simulation studies to evaluate the performance of the restricted cubic spline models and the imputation algorithms in various realistic settings. The results show that our model demonstrates strong performance, offering great flexibility and robustness to misspecified maximum length of effect. Compared to the complete-person-time analysis, our multiple imputation algorithm exhibits significantly lower variance, with only a slight increase in bias. Finally, as an illustrative example, we apply our proposed models to analyze the effect of folate consumption on colorectal cancer incidence in the Nurses' Health Study from 1976 to 2016.","PeriodicalId":21879,"journal":{"name":"Statistics in Medicine","volume":"45 23-24","pages":"e70755"},"PeriodicalIF":2.1,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149138387","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

PROComb: A Practical and Robust Design With Randomization to Optimize Dose Combinations in Drug Combination Trials. PROComb：一种实用且稳健的随机化设计，以优化药物联合试验中的剂量组合。

IF 2.1 4区医学

Statistics in Medicine Pub Date : 2026-10-01 DOI: 10.1002/sim.70743

Yingjie Qiu, Mingyue Li

{"title":"PROComb: A Practical and Robust Design With Randomization to Optimize Dose Combinations in Drug Combination Trials.","authors":"Yingjie Qiu, Mingyue Li","doi":"10.1002/sim.70743","DOIUrl":"10.1002/sim.70743","url":null,"abstract":"The US Food and Drug Administration's Project Optimus has initiated a paradigm shift in oncology drug development from \"more is better\" to \"less is more.\" Methodological development for combination therapy trials remains limited due to their complex dose-combination space and the need to integrate multi-source data, including toxicity, clinical efficacy, and biological antitumor outcomes such as pharmacodynamic (PD) activity. We propose PROComb, a practical and robust design with randomization to optimize dose combinations, to address these challenges with minimal assumptions and to facilitate practical implementation. In the first stage, the complex dose-combination space is efficiently explored through the integration of multi-source data and the inherent relationships among different dose-outcomes. Patients are adaptively assigned to dose combinations to establish a therapeutic dose space (TDS), defined as the set of doses with acceptable toxicity and promising efficacy. A recommended Stage II dose set (RS2D) is constructed at the end of Stage I. In the second stage, patients are randomized to RS2D combinations for further monitoring, screening and identification of the optimal biologic dose combination (OBDC). Three PROComb versions are developed to mitigate potential between-stage drift. Simulation studies demonstrate that PROComb achieves favorable operating characteristics compared with conventional model-based and model-assisted designs.","PeriodicalId":21879,"journal":{"name":"Statistics in Medicine","volume":"45 23-24","pages":"e70743"},"PeriodicalIF":2.1,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149025945","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

Group-Specific Nonlinear Mixed Effects Models for Longitudinal Data With Realignment of Time. 具有时间调整的纵向数据群特定非线性混合效应模型。

IF 2.1 4区医学

Statistics in Medicine Pub Date : 2026-10-01 DOI: 10.1002/sim.70759

Ziyue Liu, Sujuan Gao

{"title":"Group-Specific Nonlinear Mixed Effects Models for Longitudinal Data With Realignment of Time.","authors":"Ziyue Liu, Sujuan Gao","doi":"10.1002/sim.70759","DOIUrl":"10.1002/sim.70759","url":null,"abstract":"We propose group-specific nonlinear mixed effects models for longitudinal data whose indexing time is right-aligned to specific events, modeled as the time preceding those events. These models are motivated by dementia cohort studies that examine nonlinear trajectories of longitudinal cognitive test scores in late life, with separate trajectories for individuals with and without dementia in the period leading up to death. The model framework includes three sub-models: one for group membership, which represents dementia status in our motivating data, one for time to the indexing events, and one for the longitudinal outcome. Group membership is modeled using logistic regression or random forest. Conditional on group memberships, time to indexing events is modeled using accelerated failure time (AFT) models. Given both group membership and time to the indexing event, longitudinal data are modeled using nonlinear mixed effects models. By modeling and integrating out the time to indexing events, individuals whose indexing events have not been observed can be incorporated into the models. Stochastic approximation expectation maximization (SAEM) algorithms are adopted to maximize the likelihood for parameter estimation. In addition to modeling group-specific longitudinal trajectories aligned to the index time, the proposed models can also be used to predict group memberships or improve the prediction of time to the indexing events. Simulation studies are conducted to evaluate finite sample performance. An application to data from a dementia study is used for illustration.","PeriodicalId":21879,"journal":{"name":"Statistics in Medicine","volume":"45 23-24","pages":"e70759"},"PeriodicalIF":2.1,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13628699/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149115100","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

High-Dimensional Mediation Analysis With Network Mediators: Applications to Pediatric Acute Lymphoblastic Leukemia. 网络介质的高维中介分析：在儿童急性淋巴细胞白血病中的应用。

IF 2.1 4区医学

Statistics in Medicine Pub Date : 2026-10-01 DOI: 10.1002/sim.70756

Jade Xiaoqing Wang, Zhao-Hua Lu, Wilburn E Reddick, Heather M Conklin, John O Glass, Lisa Jacola, Arzu Onar-Thomas, Sima Jeha, Cheng Cheng, Xiang Zhou, Yimei Li

{"title":"High-Dimensional Mediation Analysis With Network Mediators: Applications to Pediatric Acute Lymphoblastic Leukemia.","authors":"Jade Xiaoqing Wang, Zhao-Hua Lu, Wilburn E Reddick, Heather M Conklin, John O Glass, Lisa Jacola, Arzu Onar-Thomas, Sima Jeha, Cheng Cheng, Xiang Zhou, Yimei Li","doi":"10.1002/sim.70756","DOIUrl":"10.1002/sim.70756","url":null,"abstract":"Acute lymphoblastic leukemia (ALL) is the most common childhood cancer, with survivors frequently experiencing long-term neurocognitive morbidities. Here, we utilize the TOTXVI clinical trial data to elucidate the mechanisms underlying treatment-related neurocognitive side effects in pediatric ALL patients by incorporating brain connectivity network data. To enable such analysis, we propose a high-dimensional mediation analysis method with a novel network mediation structural shrinkage (NMSS) prior, which is particularly suited for analyzing high-dimensional brain structural connectivity network data that serve as mediators. Our method is capable of addressing the structural dependencies of brain connectivity networks including sparsity, effective degrees of nodes, and modularity, yielding accurate estimates of the high-dimensional coefficients and mediation effects. We demonstrate the effectiveness and superiority of the proposed NMSS method through simulation studies and apply it to the TOTXVI data, revealing significant mediation effects of brain connectivity on visual processing speed directed by IT intensity. The findings shed light on the potential of targeted interventions to mitigate neurocognitive deficits in pediatric ALL survivors.","PeriodicalId":21879,"journal":{"name":"Statistics in Medicine","volume":"45 23-24","pages":"e70756"},"PeriodicalIF":2.1,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149115103","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

Joint Analysis for Multivariate Longitudinal and Event Time Data With a Change Point Anchored at Interval-Censored Event Time. 变化点锚定于间隔截后事件时间的多元纵向和事件时间数据的联合分析。

IF 2.1 4区医学

Statistics in Medicine Pub Date : 2026-10-01 DOI: 10.1002/sim.70765

Yue Zhan, Cheng Zheng, Ying Zhang

{"title":"Joint Analysis for Multivariate Longitudinal and Event Time Data With a Change Point Anchored at Interval-Censored Event Time.","authors":"Yue Zhan, Cheng Zheng, Ying Zhang","doi":"10.1002/sim.70765","DOIUrl":"10.1002/sim.70765","url":null,"abstract":"Huntington's disease (HD) is an autosomal dominant neurodegenerative disorder characterized by motor dysfunction, psychiatric disturbances, and cognitive decline. The onset of HD is marked by severe motor impairment, which may be predicted by prior cognitive decline and, in turn, exacerbate cognitive deficits. Clinical data, however, are often collected at discrete time points, so the timing of disease onset is subject to interval censoring. To address the challenges posed by such data, we develop a joint model for multivariate longitudinal biomarkers with a change point anchored at an interval-censored event time. The model simultaneously assesses the effects of longitudinal biomarkers on the event time and the changes in biomarker trajectories following the event. We conduct a comprehensive simulation study to demonstrate the finite-sample performance of the proposed method for statistical inference based on the asymptotic normality theorem. Finally, we apply the method to PREDICT-HD, a multisite observational cohort study of prodromal HD individuals, to ascertain how cognitive impairment and motor dysfunction interact during disease progression.","PeriodicalId":21879,"journal":{"name":"Statistics in Medicine","volume":"45 23-24","pages":"e70765"},"PeriodicalIF":2.1,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13652669/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149148307","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