An Evolutionary Algorithm to Personalize Stool-Based Colorectal Cancer Screening.
An Evolutionary Algorithm to Personalize Stool-Based Colorectal Cancer Screening.
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DOI：
10.3389/fphys.2021.718276
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发表时间：
2021
影响因子：
4
通讯作者：
Meester RGS
中科院分区：
文献类型：
--
作者：
van Duuren LA;Ozik J;Spliet R;Collier NT;Lansdorp-Vogelaar I;Meester RGS
粪便免疫化学检测（FIT）是一种成熟的结直肠癌（CRC）筛查方法。测量的fit浓度与当前和未来的CRC风险相关，可用于个性化筛查。然而，个性化筛查的评估在计算上具有挑战性。在本研究中，提出了一种广泛适用的算法来有效优化个性化筛查策略，该策略根据年龄和fit病史规定筛查间隔和fit截止时间。我们提出了一个个性化筛选政策的数学框架和一个双目标进化算法，该算法识别成本最小和健康效益最大的政策。该算法与已建立的微观模拟模型（MISCAN-Colon）相结合，在没有限制性马尔可夫假设的情况下，准确估计所生成政策的成本和收益。通过三个实验验证了该算法的性能。在实验1中，一个相对较小的基准问题，最优策略是已知的。该算法接近最大可行效益，相对差值为0.007%。实验2优化了间隔和截止时间，实验3只优化了截止时间。两个实验的最优策略都是未知的。与最近为USPSTF评估的政策相比，个性化筛查在不增加成本的情况下，分别将实验2和实验3的健康效益提高了14%和4.3%。生成的策略具有与当前筛选建议一致的几个特征。本文提出的方法是灵活的，能够优化个性化筛选策略评估与计算密集，但已建立的仿真模型。它可用于为结直肠癌或其他疾病的筛查政策提供信息。对于儿童权利公约而言，需要更多地讨论一项政策需要表现出哪些特征才能使其适合在实践中实施。
Fecal immunochemical testing (FIT) is an established method for colorectal cancer (CRC) screening. Measured FIT-concentrations are associated with both present and future risk of CRC, and may be used for personalized screening. However, evaluation of personalized screening is computationally challenging. In this study, a broadly applicable algorithm is presented to efficiently optimize personalized screening policies that prescribe screening intervals and FIT-cutoffs, based on age and FIT-history. We present a mathematical framework for personalized screening policies and a bi-objective evolutionary algorithm that identifies policies with minimal costs and maximal health benefits. The algorithm is combined with an established microsimulation model (MISCAN-Colon), to accurately estimate the costs and benefits of generated policies, without restrictive Markov assumptions. The performance of the algorithm is demonstrated in three experiments. In Experiment 1, a relatively small benchmark problem, the optimal policies were known. The algorithm approached the maximum feasible benefits with a relative difference of 0.007%. Experiment 2 optimized both intervals and cutoffs, Experiment 3 optimized cutoffs only. Optimal policies in both experiments are unknown. Compared to policies recently evaluated for the USPSTF, personalized screening increased health benefits up to 14 and 4.3%, for Experiments 2 and 3, respectively, without adding costs. Generated policies have several features concordant with current screening recommendations. The method presented in this paper is flexible and capable of optimizing personalized screening policies evaluated with computationally-intensive but established simulation models. It can be used to inform screening policies for CRC or other diseases. For CRC, more debate is needed on what features a policy needs to exhibit to make it suitable for implementation in practice.
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影响因子：
6.2
作者：
Meester RGS;Peterse EFP;Knudsen AB;de Weerdt AC;Chen JC;Lietz AP;Dwyer A;Ahnen DJ;Siegel RL;Smith RA;Zauber AG;Lansdorp-Vogelaar I
通讯作者：
Lansdorp-Vogelaar I
影响因子：
2.7
作者：
Maillart, Lisa M.;Ivy, Julie Simmons;Diehl, Kathleen
通讯作者：
Diehl, Kathleen
影响因子：
29.4
作者：
Grobbee, Esmee J.;Schreuders, Eline H.;Kuipers, Ernst J.
通讯作者：
Kuipers, Ernst J.
DOI：
10.1007/978-3-319-47766-4_7
发表时间：
2017-01-01
期刊：
MARKOV DECISION PROCESSES IN PRACTICE
影响因子：
--
作者：
Otten, J. W. M.;Witteveen, A.;IJzerman, M. J.
通讯作者：
IJzerman, M. J.
影响因子：
14.3
作者：
Deb, K;Pratap, A;Meyarivan, T
通讯作者：
Meyarivan, T