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首页> 外文期刊>Statistical methods in medical research >Flexible and structured survival model for a simultaneous estimation of non-linear and non-proportional effects and complex interactions between continuous variables: Performance of this multidimensional penalized spline approach in net survival trend analysis
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Flexible and structured survival model for a simultaneous estimation of non-linear and non-proportional effects and complex interactions between continuous variables: Performance of this multidimensional penalized spline approach in net survival trend analysis

机译：用于同时估计非线性和非比例效应和连续变量之间的复杂相互作用的柔性和结构化生存模型：这种多维惩罚曲线方法在净生存趋势分析中的性能

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摘要

Cancer survival trend analyses are essential to describe accurately the way medical practices impact patients' survival according to the year of diagnosis. To this end, survival models should be able to account simultaneously for non-linear and non-proportional effects and for complex interactions between continuous variables. However, in the statistical literature, there is no consensus yet on how to build such models that should be flexible but still provide smooth estimates of survival. In this article, we tackle this challenge by smoothing the complex hypersurface (time since diagnosis, age at diagnosis, year of diagnosis, and mortality hazard) using a multidimensional penalized spline built from the tensor product of the marginal bases of time, age, and year. Considering this penalized survival model as a Poisson model, we assess the performance of this approach in estimating the net survival with a comprehensive simulation study that reflects simple and complex realistic survival trends. The bias was generally small and the root mean squared error was good and often similar to that of the true model that generated the data. This parametric approach offers many advantages and interesting prospects (such as forecasting) that make it an attractive and efficient tool for survival trend analyses.
机译：癌症生存趋势分析对于准确描述医疗措施影响患者的诊断年份的生存至关重要。为此，生存模型应该能够同时考虑非线性和非比例效应以及连续变量之间的复杂相互作用。然而，在统计文献中，目前还没有达成共识，但如何建立应该是灵活的这种模型，但仍提供生存的顺利估算。在本文中，我们通过使用来自边际时间，年龄的张量产物的张量产物和年。考虑到这一惩罚的生存模式作为泊松模型，我们评估了这种方法在估计净生存时的表现，以综合模拟研究反映了简单且复杂的现实生存趋势。偏差通常很小，根均方误差良好，并且通常类似于产生数据的真实模型的误差。该参数方法提供了许多优点和有趣的前景（如预测），使其成为生存趋势分析的有吸引力和有效的工具。

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