Dose Response Modeling in Epidemiologic Cohort Studies

流行病学队列研究中的剂量反应模型

• 批准号: 6892164
• 负责人: Ellen Aura Eisen
• 金额: $ 25.97万
• 依托单位: HARVARD SCHOOL OF PUBLIC HEALTH
• 依托单位国家: 美国
• 财政年份: 1999
• 资助国家: 美国
• 起止时间: 1999-08-01 至 2008-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6892164
• 关键词: cancer risk; clinical research; computer simulation; environment related neoplasm /cancer; environmental exposure; human data; human mortality; industry; larynx neoplasms; lung neoplasms; mathematical model; metal working fluid; method development; model design /development; neoplasm /cancer epidemiology; occupational disease /disorder; occupational hazard; prostate neoplasms; rectum neoplasms; silicates; statistics /biometry

DESCRIPTION (provided by applicant): This revised proposal builds on my current work applying semiparametric statistical methods to model nonlinear exposure-response curves with smooth functions of exposure in occupational cohort studies (R01 CA81345). In the course of adapting penalized splines for survival analysis, we have identified two issues that need further development: criteria for choosing the optimal amount of smoothness and diagnostic statistics to identify influential observations and measure their influence on the fitted values of the curve. These issues will be examined in the presence of right skewed distributions typical of workplace exposures. We propose to compare the goodness of fit and resistance of penalized splines to that of two other common smoothers: restricted cubic splines, and a locally weighted regression smoother called loess. In this revised application, we propose to compare the three smoothing methods by evaluating model fit in a series of simulation studies. Data will be generated under linear, cubic polynomial, and threshold (broken stick) exposure-response models, assuming exposure has a lognormal distribution. We will identify the technique with the best fit to the true data, after calibrating the amount of smoothness across the three methods. We also now propose to develop statistical methods to quantify influence and identify points with high leverage in semiparametric models, with particular attention to values at the high end of the skewed exposure distribution. We will compute Cook's distance for parametric and nonparametric components and develop rules for assessing statistical significance as well as diagnostics for determining the sensitivity of the smoothing parameter to subject deletion. The new diagnostics will be developed for penalized splines and then extended to restricted cubic splines and loess. The models will be applied to the re-analyses of two cancer mortality studies; larynx, lung, prostate and rectal cancer in autoworkers exposed to metalworking fluids (MWF) and lung cancer in workers in California's diatomaceous earth industry exposed to crystalline silica. We plan to focus our methodologic investigations on MWF and silica because we believe that clarifying the shapes of their exposure-response curves can make a substantial contribution to current controversies over their control in the workplace.

描述(申请人提供)：本修订建议建立在我目前工作的基础上，应用半参数统计方法在职业队列研究中建立具有平滑暴露函数的非线性暴露-反应曲线模型(R01 CA81345)。在采用惩罚样条法进行生存分析的过程中，我们发现了两个需要进一步发展的问题：选择最佳光滑量的标准和诊断统计量，以识别有影响的观测并衡量它们对曲线拟合值的影响。这些问题将在工作场所暴露的典型右偏分布存在的情况下进行审查。我们建议将惩罚样条法与其他两种常见光滑器的拟合优度和阻力进行比较：受限三次样条法和称为黄土的局部加权回归光滑器。在这个修订的应用中，我们建议通过在一系列模拟研究中评估模型拟合来比较三种平滑方法。数据将在线性、三次多项式和阈值(折断棒)暴露-反应模型下生成，假设暴露具有对数正态分布。在校准了三种方法的平滑度后，我们将确定与真实数据最匹配的技术。我们现在还建议开发统计方法来量化影响并识别半参数模型中具有高杠杆率的点，特别注意偏斜暴露分布的高端的值。我们将计算参数和非参数分量的库克距离，并开发用于评估统计显著性的规则以及用于确定平滑参数对主题删除的敏感度的诊断。新的诊断方法将被开发用于惩罚样条法，然后扩展到限制三次样条法和黄土。这些模型将被用于对两项癌症死亡率研究的重新分析：接触金属加工液(MWF)的汽车工人的喉癌、肺癌、前列腺癌和直肠癌，以及接触结晶二氧化硅的加州硅藻土行业工人的肺癌。我们计划将我们的方法学研究重点放在MWF和二氧化硅上，因为我们相信，澄清它们的暴露-反应曲线的形状可以对目前关于它们在工作场所的控制的争议做出重大贡献。