<?xml version="1.1" encoding="utf-8"?>
<article xsi:noNamespaceSchemaLocation="http://jats.nlm.nih.gov/publishing/1.1/xsd/JATS-journalpublishing1-mathml3.xsd" dtd-version="1.1" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><front><journal-meta><journal-id journal-id-type="publisher-id">SSSD</journal-id><journal-title-group><journal-title>Scientific and Social Sustainable Development</journal-title></journal-title-group><issn>3066-8964</issn><eissn>3066-8980</eissn><publisher><publisher-name>Art and Design</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.61369/SSSD.2025180011</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title>基于生存优化模型的NIPT 时点选择研究</title><url>https://artdesignp.com/journal/SSSD/1/18/10.61369/SSSD.2025180011</url><author>张辉,肖扬,卜子轩</author><pub-date pub-type="publication-year"><year>2025</year></pub-date><volume>1</volume><issue>18</issue><history><date date-type="pub"><published-time>2025-11-28</published-time></date></history><abstract>高BMI 孕妇NIPT 检测时点选择问题亟待解决。本研究构建AFT 模型与风险优化体系，基于1689例临床数据量化BMI 等指标与检测时点的关联，通过网格搜索法确定7个BMI 分组的最佳检测周数。结果显示，分组策略使总体检测风险降低45.8%，BMI &amp;ge;40组降幅达54.2%，显著提升高BMI 人群筛查时效性。该成果为个性化检测时点选择提供依据，助力产前筛查精准化与资源优化。</abstract><keywords>NIPT,生存分析,加速失效时间模型,风险优化,BMI 分组,时点优化,网格搜索</keywords></article-meta></front><body/><back><ref-list><ref id="B1" content-type="article"><label>1</label><element-citation publication-type="journal"><p>[1] CESARELLI M, ROMANO M, BIFULCO P. Comparison of short term variability indexes in cardiotocographic foetal monitoring[J]. Computers in Biology &amp;amp; Medicine, 2009, 39(2): 106.[2] 王杰, 等. 无创产前筛查中胎儿游离DNA 比例的影响因素分析[J]. 中华医学遗传学杂志, 2018, 35(3): 390&amp;ndash;394.[3] KLEIN J P, MOESCHBERGER M L. Survival Analysis: Techniques for Censored and Truncated Data[M]. 2nd ed. New York: Springer, 2003.[4] AMERICAN COLLEGE OF MEDICAL GENETICS AND GENOMICS. ACMG statement on noninvasive prenatal screening for fetal aneuploidy[J]. Genetics in Medicine, 2016, 18(10): 1056&amp;ndash;1059.[5] 国家卫生计生委办公厅. 胎儿染色体非整倍体无创基因检测技术规范( 试行)[Z]. 2016.[6] THERNEAU T M, GRAMBSCH P M. Modeling Survival Data: Extending the Cox Model[M]. New York: Springer, 2000.[7] HARRELL F E. Regression Modeling Strategies: With Applications to Linear Models, Logistic Regression, and Survival Analysis[M]. New York: Springer, 2001.[8] 刘萧, 李静, 许珂. 基于生存分析的智能电网安全告警事件持续时间预测模型[J]. 计算机应用与软件, 2024, 41(1):328-335.DOI:10.3969/j.issn.1000-386x.2024.01.048.[9] 王能发, 杨哲, 刘自鑫. 基于生存理论的两类博弈模型[J]. 重庆师范大学学报（自然科学版）, 2024, 41(1):1-7.[10] 张娜, 陈文倩, 白雪松, 等. 基于时空优化模型的PM_(2.5) 遥感估测研究[J]. 中国环境科学, 2024(4).</p><pub-id pub-id-type="doi"/></element-citation></ref></ref-list></back></article>
