Dose Response Modeling in Epidemiologic Cohort Studies

描述（由申请人提供）：本修订提案建立在我目前的工作基础上，在职业队列研究中应用半参数统计方法对具有平滑暴露函数的非线性暴露-响应曲线进行建模（R 01 CA 81345）。在适应惩罚样条生存分析的过程中，我们已经确定了两个需要进一步发展的问题：选择最佳平滑度和诊断统计量的标准，以确定有影响力的观察和测量其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的存在下进行研究。我们建议比较罚款样条的拟合优度和阻力的其他两个常见的平滑：限制三次样条，和局部加权回归平滑称为黄土。在这个修改后的应用程序中，我们建议通过一系列模拟研究中的模型拟合评估来比较这三种平滑方法。将在线性、三次多项式和阈值（断棒）暴露-反应模型下生成数据，假设暴露量呈对数正态分布。在校准了三种方法的平滑度之后，我们将确定最适合真实数据的技术。我们现在还建议开发统计方法来量化影响，并确定半参数模型中具有高杠杆作用的点，特别注意倾斜暴露分布高端的值。我们将计算参数和非参数分量的Cook距离，并制定用于评估统计学显著性的规则以及用于确定平滑参数对受试者删除的敏感性的诊断。新的诊断将开发惩罚样条，然后扩展到限制三次样条和黄土。该模型将被应用于两个癌症死亡率研究的再分析;喉癌，肺癌，前列腺癌和直肠癌的汽车工人暴露于金属加工液（MWF）和肺癌的工人在加州的硅藻土行业暴露于结晶二氧化硅。我们计划将我们的方法学调查的重点放在MWF和二氧化硅，因为我们相信，澄清他们的电导率响应曲线的形状可以作出实质性的贡献，目前的争议，他们在工作场所的控制。

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.