Semi-Parametric Survival Methods in Dental Research

牙科研究中的半参数生存方法

• 批准号: 6960441
• 负责人: SUNG-KIANG CHUANG
• 金额: $ 19.09万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-07-15 至 2007-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6960441
• 关键词: clinical research; dental caries; dental implants; dental research; human data; information systems; statistics /biometry

DESCRIPTION (provided by applicant): Datasets composed of time-to-event, within-subject clustered observations are common in patient oriented dental research, and e.g. caries data are recorded from multiple teeth or even multiple surfaces per tooth from each patient. The analysis of data composed of multiple observations per patient is a challenging, yet often overlooked, proposition. Most routinely used statistical analysis procedures require the common assumption that all observations are independent. In the presence of clustered observations, these procedures are usually not directly applicable. To make valid inferences, more sophisticated statistical tools are needed in order to take within cluster correlations into account. The application of sophisticated survival method analyses in patient-oriented dental research is limited. To address this deficiency, Dr. Chuang (principal investigator) is submitting a R03 award to fund his special interests and skills in the quantitative analyses of patient-oriented dental research. This award's broad goal is to facilitate the principal investigator to develop sound and rigorous survival analytic methods with applications in dental research and in the future to function as an independent patient-oriented dental researcher, mentor and clinician. Dr. Chuang's environment is outstanding for implementing patient-oriented research. The department and institution is committed to provide individuals in patient-oriented research methods. The R03 award will provide funding for protected time with at least 35% research effort. The first specific aim of this R03 award is to identify exposures associated with implant failures and complications with a generalized linear transformation model via the marginal approach. The second specific aim is to identify exposures associated with implant failures and complications with a generalized linear transformation model via the frailty approach and to compare and contrast these two different approaches. The principal investigator has chosen this research experience because of its clinical relevance and challenging methodological and analytic issues. The analyses focus on the survival methodological issues of correlated or clustered observations with applications to dental research. The specific analytic issues addressed are generalizable to patient-oriented dental research as many studies using multiple, correlated observations per patient, i.e. probing depths, tooth loss.

描述(由申请人提供)：在面向患者的牙科研究中，由事件发生时间、受试者内的聚集观察组成的数据集是常见的，例如，从每个患者的多颗牙齿甚至每颗牙齿的多个表面记录龋齿数据。对每个患者的多个观察组成的数据的分析是一个具有挑战性的，但经常被忽视的命题。大多数常规使用的统计分析程序都需要一个共同的假设，即所有观测数据都是独立的。在存在成群观测的情况下，这些程序通常不直接适用。为了做出有效的推论，需要更复杂的统计工具，以便考虑到集群内的相关性。复杂的生存方法分析在面向患者的牙科研究中的应用是有限的。为了解决这一不足，庄博士(首席研究员)正在提交R03奖项，以资助他在面向患者的牙科研究定量分析方面的特殊兴趣和技能。该奖项的广泛目标是促进首席研究人员开发合理和严格的生存分析方法，并在牙科研究中应用，并在未来发挥独立的面向患者的牙科研究人员、导师和临床医生的作用。庄博士的环境非常适合实施以患者为中心的研究。科室致力于为个人提供以病人为中心的研究方法。R03奖将为受保护的时间提供至少35%的研究成果。这个R03奖项的第一个具体目标是通过边缘方法确定与种植体失败和并发症相关的暴露，并使用通用的线性转换模型。第二个具体目标是通过Frailty方法用广义线性变换模型识别与种植失败和并发症相关的暴露，并比较和对比这两种方法 不同的方法。首席研究人员之所以选择这项研究经验，是因为它与临床相关，并具有挑战性的方法学和分析问题。这些分析集中在相关或聚集观察的生存方法学问题上，并将其应用于牙科研究。所解决的具体分析问题可以概括为面向患者的牙科研究，因为许多研究使用了每个患者的多个相关观察，例如探测深度、牙齿脱落。