University Hospital of Old Age Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland.
Institute of Social and Preventive Medicine (ISPM), University of Bern, Bern, Switzerland.
Sci Rep. 2023 Apr 19;13(1):6406. doi: 10.1038/s41598-023-32867-z.
Effective clinical decision procedures must balance multiple competing objectives such as time-to-decision, acquisition costs, and accuracy. We describe and evaluate POSEIDON, a data-driven method for PrOspective SEquentIal DiagnOsis with Neutral zones to individualize clinical classifications. We evaluated the framework with an application in which the algorithm sequentially proposes to include cognitive, imaging, or molecular markers if a sufficiently more accurate prognosis of clinical decline to manifest Alzheimer's disease is expected. Over a wide range of cost parameter data-driven tuning lead to quantitatively lower total cost compared to ad hoc fixed sets of measurements. The classification accuracy based on all longitudinal data from participants that was acquired over 4.8 years on average was 0.89. The sequential algorithm selected 14 percent of available measurements and concluded after an average follow-up time of 0.74 years at the expense of 0.05 lower accuracy. Sequential classifiers were competitive from a multi-objective perspective since they could dominate fixed sets of measurements by making fewer errors using less resources. Nevertheless, the trade-off of competing objectives depends on inherently subjective prescribed cost parameters. Thus, despite the effectiveness of the method, the implementation into consequential clinical applications will remain controversial and evolve around the choice of cost parameters.
有效的临床决策程序必须平衡多个相互竞争的目标，如决策时间、获取成本和准确性。我们描述并评估了 POSEIDON，这是一种用于前瞻性序列诊断的基于数据的方法，具有中性区，可实现临床分类的个体化。我们通过一个应用程序评估了该框架，该程序通过算法连续提出包括认知、成像或分子标志物，如果预期对临床下降表现出阿尔茨海默病的预后有足够更准确的话。在广泛的成本参数数据驱动调优范围内，与固定的测量集相比，总费用定量降低。基于参与者在 4.8 年的平均时间内获得的所有纵向数据的分类准确性为 0.89。顺序算法选择了可用测量值的 14%，在平均随访时间为 0.74 年的情况下，以 0.05 的精度降低为代价得出结论。由于顺序分类器通过使用更少的资源犯更少的错误，因此从多目标的角度来看具有竞争力，因此可以通过固定的测量集进行竞争。然而，竞争目标的权衡取决于固有的主观规定的成本参数。因此，尽管该方法有效，但在 consequential 临床应用中的实施仍存在争议，并将围绕成本参数的选择展开。
