Case-cohort sampling is a commonly used and efficient method for studying large cohorts. In many situations, some covariates are easily measured on all cohort subjects, and surrogate measurements of the expensive cova...Case-cohort sampling is a commonly used and efficient method for studying large cohorts. In many situations, some covariates are easily measured on all cohort subjects, and surrogate measurements of the expensive covariates also may be observed. In this paper, to make full use of the covariate data collected outside the case-cohort sample, we propose＇a class of weighted estimators with general time-varying weights for the additive hazards model, and the estimators are shown to be consistent and asymptotically normal. We also identify the estimator within this class that maximizes efficiency, and simulation studies show that the efficiency gains of the proposed estimator over the existing ones can be substantial in practical situations. A real example is provided.展开更多
Case-cohort design usually requires the disease rate to be low in large cohort study,although it has been extensively used in practice.However,the disease with high rate is frequently observed in many clinical studies...Case-cohort design usually requires the disease rate to be low in large cohort study,although it has been extensively used in practice.However,the disease with high rate is frequently observed in many clinical studies.Under such circumstances,it is desirable to consider a generalized case-cohort design,where only a fraction of cases are sampled.In this article,we propose the inference procedure for the additive hazards regression under the generalized case-cohort sampling.Asymptotic properties of the proposed estimators for the regression coefcients are established.To demonstrate the efectiveness of the generalized case-cohort sampling,we compare it with simple random sampling in terms of asymptotic relative efciency.Furthermore,we derive the optimal allocation of the subsamples for the proposed design.The fnite sample performance of the proposed method is evaluated through simulation studies.展开更多
Case-cohort design is an efficient and economical design to study risk factors for diseases with expensive measurements, especially when the disease rate is low. When several diseases are of interest, multiple case-co...Case-cohort design is an efficient and economical design to study risk factors for diseases with expensive measurements, especially when the disease rate is low. When several diseases are of interest, multiple case-cohort design studies may be conducted using the same subcohort. To study the association between risk factors and each disease occurrence or death, we consider a general additive-multiplicative hazards model for case-cohort designs with multiple disease outcomes. We present an estimation procedure for the regression parameters of the additive-multiplicative hazards model, and show that the proposed estimator is consistent and asymptotically normal. Large sample approximation works well in finite sample studies in simulation. Finally, we apply the proposed method to a real data example for illustration.展开更多
Generalized case-cohort design has been proved to be a cost-effective way to enhance the efficiency of large epidemiological cohort. In this article, we propose an inference procedure for estimating the unknown parame...Generalized case-cohort design has been proved to be a cost-effective way to enhance the efficiency of large epidemiological cohort. In this article, we propose an inference procedure for estimating the unknown parameters in Cox＇s proportional hazards model in generalized case-cohort design and establish an optimal sample size allocation to achieve the maximum power at a given budget. The finite sample performance of the proposed method is evaluated through simulation studies. The proposed method is applied to a real data set from the National Wilm＇s Tumor Study Group.展开更多
The case-cohort design is widely used in large epidemiological studms and prevention trials for cost reduction. In such a design, covariates are assembled only for a subcohort which is a random subset of the entire co...The case-cohort design is widely used in large epidemiological studms and prevention trials for cost reduction. In such a design, covariates are assembled only for a subcohort which is a random subset of the entire cohort and any additional cases outside the subcohort. In this paper, we discuss the case-cohort analysis with a class of general additive-multiplicative hazard models which includes the commonly used Cox model and additive hazard model as special cases. Two sampling schemes for the subcohort, Bernoulli sampling with arbitrary selection probabilities and stratified simple random sampling with fixed subcohort sizes, are discussed. In each setting, an estimating function is constructed to estimate the regression parameters. The resulting estimator is shown to be consistent and asymptotically normally distributed. The limiting variance-covariance matrix can be consistently estimated by the case-cohort data. A simulation study is conducted to assess the finite sample performances of the proposed method and a real example is provided.展开更多
Case-cohort study designs are widely used to reduce the cost of large cohort studies. When several diseases are of interest, we can use the same subcohort. In this paper, we will study the casecohort design of margina...Case-cohort study designs are widely used to reduce the cost of large cohort studies. When several diseases are of interest, we can use the same subcohort. In this paper, we will study the casecohort design of marginal additive hazards model for multiple outcomes by a more efficient version. Instead of analyzing each disease separately, ignoring the additional exposure measurements collected on subjects with other diseases, we propose a new weighted estimating equation approach to improve the efficiency by utilizing as much information collected as possible. The consistency and asymptotic normality of the resulting estimator are established. Simulation studies are conducted to examine the finite sample performance of the proposed estimator, which confirm the efficiency gains.展开更多
背景支气管肺发育不良(BPD)是早产儿最常见的严重肺部疾病,是多种因素对未成熟肺的损伤,识别BPD的危险因素对制定预防策略至关重要。目前BPD的危险因素尚存争议,且国内外鲜有系统评价。目的系统分析早产儿BPD的危险因素。方法计算机检...背景支气管肺发育不良(BPD)是早产儿最常见的严重肺部疾病,是多种因素对未成熟肺的损伤,识别BPD的危险因素对制定预防策略至关重要。目前BPD的危险因素尚存争议,且国内外鲜有系统评价。目的系统分析早产儿BPD的危险因素。方法计算机检索中国知网(CNKI)、万方数据知识服务平台(Wanfang Data)、中国生物医学文献数据库(CBM)、维普网(VIP)、PubMed、EmBase、Web of Science和Cochrane Library中有关早产儿BPD危险因素的文献,检索时限为建库至2021年10月。采用RevMan 5.3软件进行Meta分析。结果共纳入23篇文献,BPD早产儿累计33508例,各文献纽尔卡斯-渥太华量表(NOS)评分总体质量较高。Meta分析结果显示,母亲合并绒毛膜羊膜炎〔比值比(OR)=1.46,95%CI(1.18,1.80),P=0.0006〕、母亲合并妊娠期高血压〔OR=1.26,95%CI(1.15,1.37),P<0.00001〕、母亲合并胎膜早破〔OR=1.18,95%CI(1.10,1.26),P<0.00001〕、早产儿小于胎龄儿(SGA)〔OR=2.64,95%CI(1.85,3.77),P<0.00001〕、早产儿产房气管插管〔OR=2.50,95%CI(1.39,4.50),P=0.002〕、早产儿5 min Apgar评分<7分〔OR=2.47,95%CI(1.36,4.47),P=0.003〕、男性早产儿〔OR=1.49,95%CI(1.43,1.55),P<0.00001〕、早产儿机械通气〔OR=1.59,95%CI(1.28,1.96),P<0.0001〕、早产儿机械通气>7 d〔OR=7.99,95%CI(4.47,14.29),P<0.00001〕、早产儿使用肺表面活性物质〔OR=3.46,95%CI(1.96,6.11),P<0.0001〕、早产儿使用类固醇〔OR=2.42,95%CI(1.93,3.03),P<0.00001〕、早产儿呼吸窘迫综合征(RDS)〔OR=3.40,95%CI(2.01,5.75),P<0.00001〕、早产儿动脉导管未闭(PDA)〔OR=1.96,95%CI(1.38,2.79),P=0.0002〕、早产儿败血症〔OR=1.82,95%CI(1.36,2.44),P<0.0001〕、早产儿坏死性小肠结肠炎(NEC)〔OR=1.62,95%CI(1.18,2.22),P=0.003〕是早产儿发生BPD的危险因素。早产儿出生体质量高〔OR=0.79,95%CI(0.76,0.83),P<0.00001〕、早产儿胎龄高〔OR=0.80,95%CI(0.73,0.87),P<0.00001〕是早产儿发生BPD的保护因素。漏斗图结合Begg's检验和Egger's检验显示无发表偏倚(P>0.05)。结论当前证据表明,母亲合并绒毛膜羊膜炎、妊娠期高血压、胎膜早破及早产儿SGA、产房气管插管、5 min Apgar评分<7分、男性、机械通气、机械通气>7 d、使用肺表面活性物质、使用类固醇、RDS、PDA、败血症、NEC是早产儿BPD发生的危险因素,高出生体质量、高胎龄是早产儿发生BPD的保护因素,医护人员应及时识别并处理相关危险因素,预防早产儿BPD的发生。展开更多
背景新型冠状病毒肺炎(COVID-19)在全球范围蔓延,严重影响人类健康和生活。有研究报道COVID-19可导致血栓性疾病,而脑卒中与血栓事件密切相关。目的评估COVID-19对脑卒中患者病死率的影响,并对其可能机制进行探讨,从而为合并COVID-19的...背景新型冠状病毒肺炎(COVID-19)在全球范围蔓延,严重影响人类健康和生活。有研究报道COVID-19可导致血栓性疾病,而脑卒中与血栓事件密切相关。目的评估COVID-19对脑卒中患者病死率的影响,并对其可能机制进行探讨,从而为合并COVID-19的脑卒中患者的科学防治提供可靠的临床理论依据。方法计算机检索PubMed、EmBase、Web of Science、Cochrane Library、中国知网及万方数据知识服务平台等数据库,收集关于COVID-19对脑卒中患者病死率影响的队列研究或病例对照研究,检索时间为2019年12月至2022年1月。2名研究人员独立进行文献筛选、资料提取,采用纽卡斯尔-渥太华量表(NOS)对文献质量进行评估。采用Meta分析评价COVID-19对脑卒中患者病死率的影响,采用漏斗图评价文献发表偏倚。结果共纳入18篇文献,12篇文献质量为高质量,6篇文献质量为中等质量。Meta分析结果显示,合并COVID-19的脑卒中患者病死率、凝血酶原时间(PT)、D-二聚体水平、美国国立卫生研究院卒中量表(NIHSS)评分高于未合并COVID-19的脑卒中患者〔RR=4.16,95%CI(2.82,6.13),P<0.00001;MD=0.78,95%CI(0.35,1.20),P=0.0003;MD=1.34,95%CI(0.83,1.84),P<0.00001;MD=6.66,95%CI(4.54,8.79),P<0.00001〕,年龄低于未合并COVID-19的脑卒中患者〔MD=-2.04,95%CI(-3.48,-0.61),P=0.005〕。合并COVID-19的脑卒中患者和未合并COVID-19的脑卒中患者活化部分凝血活酶时间(APTT)比较,差异无统计学意义〔MD=2.51,95%CI(-2.69,7.71),P=0.34〕。对合并COVID-19脑卒中患者的病死率绘制漏斗图,结果显示两侧基本对称分布。结论COVID-19可增加脑卒中患者病死率,PT、D-二聚体等凝血系统指标的改变可能在其中发挥重要的作用,其预后与年龄、入院时NIHSS评分等相关。展开更多
基金partly supported by the National Natural Science Foundation of China Grants(No.11231010,11171330 and 11101314)Key Laboratory of RCSDS,CAS(No.2008DP173182)and BCMIIS
文摘Case-cohort sampling is a commonly used and efficient method for studying large cohorts. In many situations, some covariates are easily measured on all cohort subjects, and surrogate measurements of the expensive covariates also may be observed. In this paper, to make full use of the covariate data collected outside the case-cohort sample, we propose＇a class of weighted estimators with general time-varying weights for the additive hazards model, and the estimators are shown to be consistent and asymptotically normal. We also identify the estimator within this class that maximizes efficiency, and simulation studies show that the efficiency gains of the proposed estimator over the existing ones can be substantial in practical situations. A real example is provided.
基金supported by the Fundamental Research Fund for the Central Universitiessupported by National Natural Science Foundation of China(Grant No.11301545)supported by National Natural Science Foundation of China(Grant No.11171263)
文摘Case-cohort design usually requires the disease rate to be low in large cohort study,although it has been extensively used in practice.However,the disease with high rate is frequently observed in many clinical studies.Under such circumstances,it is desirable to consider a generalized case-cohort design,where only a fraction of cases are sampled.In this article,we propose the inference procedure for the additive hazards regression under the generalized case-cohort sampling.Asymptotic properties of the proposed estimators for the regression coefcients are established.To demonstrate the efectiveness of the generalized case-cohort sampling,we compare it with simple random sampling in terms of asymptotic relative efciency.Furthermore,we derive the optimal allocation of the subsamples for the proposed design.The fnite sample performance of the proposed method is evaluated through simulation studies.
基金partly supported by the Natural Science Research Project of Universities of Anhui Province(No.KJ2016B026)partly supported by the National Natural Science Foundation of China Grants(No.11301355)the Technology Foundation for Selected Overseas Chinese Scholar,Ministry of Personnel of Beijing,China
文摘Case-cohort design is an efficient and economical design to study risk factors for diseases with expensive measurements, especially when the disease rate is low. When several diseases are of interest, multiple case-cohort design studies may be conducted using the same subcohort. To study the association between risk factors and each disease occurrence or death, we consider a general additive-multiplicative hazards model for case-cohort designs with multiple disease outcomes. We present an estimation procedure for the regression parameters of the additive-multiplicative hazards model, and show that the proposed estimator is consistent and asymptotically normal. Large sample approximation works well in finite sample studies in simulation. Finally, we apply the proposed method to a real data example for illustration.
基金Supported in part by the Central Universities under Grant No.31541311216,2042014kf0256the National Natural Science Foundation of China under Grant No.11171263,11301545,61371126 and 11401443
文摘Generalized case-cohort design has been proved to be a cost-effective way to enhance the efficiency of large epidemiological cohort. In this article, we propose an inference procedure for estimating the unknown parameters in Cox＇s proportional hazards model in generalized case-cohort design and establish an optimal sample size allocation to achieve the maximum power at a given budget. The finite sample performance of the proposed method is evaluated through simulation studies. The proposed method is applied to a real data set from the National Wilm＇s Tumor Study Group.
基金supported by the National Natural Science Foundation of China(11101091)the Specialized Research Fund for the Doctoral Program of Higher Education of China(20110071120023)supported by the National Natural Science Foundation of China(10971033)
文摘The case-cohort design is widely used in large epidemiological studms and prevention trials for cost reduction. In such a design, covariates are assembled only for a subcohort which is a random subset of the entire cohort and any additional cases outside the subcohort. In this paper, we discuss the case-cohort analysis with a class of general additive-multiplicative hazard models which includes the commonly used Cox model and additive hazard model as special cases. Two sampling schemes for the subcohort, Bernoulli sampling with arbitrary selection probabilities and stratified simple random sampling with fixed subcohort sizes, are discussed. In each setting, an estimating function is constructed to estimate the regression parameters. The resulting estimator is shown to be consistent and asymptotically normally distributed. The limiting variance-covariance matrix can be consistently estimated by the case-cohort data. A simulation study is conducted to assess the finite sample performances of the proposed method and a real example is provided.
基金supported by Graduate Innovation Foundation of Shanghai University of Finance and Economics,China(Grant No.CXJJ2014-453)the second author is supported by National Natural Science Foundation of China(Grant No.11301355)+1 种基金the Technology Foundation for Selected Overseas Chinese Scholar,Ministry of Personnel of BeijingChina
文摘Case-cohort study designs are widely used to reduce the cost of large cohort studies. When several diseases are of interest, we can use the same subcohort. In this paper, we will study the casecohort design of marginal additive hazards model for multiple outcomes by a more efficient version. Instead of analyzing each disease separately, ignoring the additional exposure measurements collected on subjects with other diseases, we propose a new weighted estimating equation approach to improve the efficiency by utilizing as much information collected as possible. The consistency and asymptotic normality of the resulting estimator are established. Simulation studies are conducted to examine the finite sample performance of the proposed estimator, which confirm the efficiency gains.
文摘背景支气管肺发育不良(BPD)是早产儿最常见的严重肺部疾病,是多种因素对未成熟肺的损伤,识别BPD的危险因素对制定预防策略至关重要。目前BPD的危险因素尚存争议,且国内外鲜有系统评价。目的系统分析早产儿BPD的危险因素。方法计算机检索中国知网(CNKI)、万方数据知识服务平台(Wanfang Data)、中国生物医学文献数据库(CBM)、维普网(VIP)、PubMed、EmBase、Web of Science和Cochrane Library中有关早产儿BPD危险因素的文献,检索时限为建库至2021年10月。采用RevMan 5.3软件进行Meta分析。结果共纳入23篇文献,BPD早产儿累计33508例,各文献纽尔卡斯-渥太华量表(NOS)评分总体质量较高。Meta分析结果显示,母亲合并绒毛膜羊膜炎〔比值比(OR)=1.46,95%CI(1.18,1.80),P=0.0006〕、母亲合并妊娠期高血压〔OR=1.26,95%CI(1.15,1.37),P<0.00001〕、母亲合并胎膜早破〔OR=1.18,95%CI(1.10,1.26),P<0.00001〕、早产儿小于胎龄儿(SGA)〔OR=2.64,95%CI(1.85,3.77),P<0.00001〕、早产儿产房气管插管〔OR=2.50,95%CI(1.39,4.50),P=0.002〕、早产儿5 min Apgar评分<7分〔OR=2.47,95%CI(1.36,4.47),P=0.003〕、男性早产儿〔OR=1.49,95%CI(1.43,1.55),P<0.00001〕、早产儿机械通气〔OR=1.59,95%CI(1.28,1.96),P<0.0001〕、早产儿机械通气>7 d〔OR=7.99,95%CI(4.47,14.29),P<0.00001〕、早产儿使用肺表面活性物质〔OR=3.46,95%CI(1.96,6.11),P<0.0001〕、早产儿使用类固醇〔OR=2.42,95%CI(1.93,3.03),P<0.00001〕、早产儿呼吸窘迫综合征(RDS)〔OR=3.40,95%CI(2.01,5.75),P<0.00001〕、早产儿动脉导管未闭(PDA)〔OR=1.96,95%CI(1.38,2.79),P=0.0002〕、早产儿败血症〔OR=1.82,95%CI(1.36,2.44),P<0.0001〕、早产儿坏死性小肠结肠炎(NEC)〔OR=1.62,95%CI(1.18,2.22),P=0.003〕是早产儿发生BPD的危险因素。早产儿出生体质量高〔OR=0.79,95%CI(0.76,0.83),P<0.00001〕、早产儿胎龄高〔OR=0.80,95%CI(0.73,0.87),P<0.00001〕是早产儿发生BPD的保护因素。漏斗图结合Begg's检验和Egger's检验显示无发表偏倚(P>0.05)。结论当前证据表明,母亲合并绒毛膜羊膜炎、妊娠期高血压、胎膜早破及早产儿SGA、产房气管插管、5 min Apgar评分<7分、男性、机械通气、机械通气>7 d、使用肺表面活性物质、使用类固醇、RDS、PDA、败血症、NEC是早产儿BPD发生的危险因素,高出生体质量、高胎龄是早产儿发生BPD的保护因素,医护人员应及时识别并处理相关危险因素,预防早产儿BPD的发生。
文摘背景新型冠状病毒肺炎(COVID-19)在全球范围蔓延,严重影响人类健康和生活。有研究报道COVID-19可导致血栓性疾病,而脑卒中与血栓事件密切相关。目的评估COVID-19对脑卒中患者病死率的影响,并对其可能机制进行探讨,从而为合并COVID-19的脑卒中患者的科学防治提供可靠的临床理论依据。方法计算机检索PubMed、EmBase、Web of Science、Cochrane Library、中国知网及万方数据知识服务平台等数据库,收集关于COVID-19对脑卒中患者病死率影响的队列研究或病例对照研究,检索时间为2019年12月至2022年1月。2名研究人员独立进行文献筛选、资料提取,采用纽卡斯尔-渥太华量表(NOS)对文献质量进行评估。采用Meta分析评价COVID-19对脑卒中患者病死率的影响,采用漏斗图评价文献发表偏倚。结果共纳入18篇文献,12篇文献质量为高质量,6篇文献质量为中等质量。Meta分析结果显示,合并COVID-19的脑卒中患者病死率、凝血酶原时间(PT)、D-二聚体水平、美国国立卫生研究院卒中量表(NIHSS)评分高于未合并COVID-19的脑卒中患者〔RR=4.16,95%CI(2.82,6.13),P<0.00001;MD=0.78,95%CI(0.35,1.20),P=0.0003;MD=1.34,95%CI(0.83,1.84),P<0.00001;MD=6.66,95%CI(4.54,8.79),P<0.00001〕,年龄低于未合并COVID-19的脑卒中患者〔MD=-2.04,95%CI(-3.48,-0.61),P=0.005〕。合并COVID-19的脑卒中患者和未合并COVID-19的脑卒中患者活化部分凝血活酶时间(APTT)比较,差异无统计学意义〔MD=2.51,95%CI(-2.69,7.71),P=0.34〕。对合并COVID-19脑卒中患者的病死率绘制漏斗图,结果显示两侧基本对称分布。结论COVID-19可增加脑卒中患者病死率,PT、D-二聚体等凝血系统指标的改变可能在其中发挥重要的作用,其预后与年龄、入院时NIHSS评分等相关。
