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模拟早发性癌症动力学以研究潜在风险、检测及人群筛查影响的变化。

MODELING EARLY-ONSET CANCER KINETICS TO STUDY CHANGES IN UNDERLYING RISK, DETECTION, AND IMPACT OF POPULATION SCREENING.

作者信息

Mirzaei Navid Mohammad, Hur Chin, Terry Mary Beth, Dalerba Piero, Yang Wan

机构信息

Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York, USA.

Department of Medicine, Columbia University Irving Medical Center, New York, New York, USA.

出版信息

medRxiv. 2024 Dec 8:2024.12.05.24318584. doi: 10.1101/2024.12.05.24318584.

Abstract

Recent studies have reported increases in early-onset cancer cases (diagnosed under age 50) and call into question whether the increase is related to earlier diagnosis from other medical tests and reflected by decreasing tumor-size-at-diagnosis (apparent effects) or actual increases in underlying cancer risk (true effects), or both. The classic Multi-Stage Clonal Expansion (MSCE) model assumes cancer detection at the emergence of the first malignant cell, although later modifications have included lag-times or stochasticity in detection to more realistically represent tumor detection requiring a certain size threshold. Here, we introduce an approach to explicitly incorporate tumor-size-at-diagnosis in the MSCE framework and account for improvements in cancer detection over time to distinguish between apparent and true increases in early-onset cancer incidence. We demonstrate that our model is structurally identifiable and provides better parameter estimation than the classic model. Applying this model to colorectal, female breast, and thyroid cancers, we examine changes in cancer risk while accounting for detection improvements over time in three representative birth cohorts (1950-1954, 1965-1969, and 1980-1984). Our analyses suggest accelerated carcinogenic events and shorter mean sojourn times in more recent cohorts. We further use this model to examine the screening impact on the incidence of breast and colorectal cancers, both having established screening protocols. Our results align with well-documented differences in screening effects between these two cancers. These findings underscore the importance of accounting for tumor-size-at-diagnosis in cancer modeling and support true increases in early-onset cancer risk in recent years for breast, colorectal, and thyroid cancer.

摘要

近期研究报告了早发性癌症病例(50岁以下确诊)有所增加,这引发了一个问题:这种增加是否与其他医学检查更早的诊断有关,是由诊断时肿瘤尺寸减小(表观效应)反映出来,还是潜在癌症风险的实际增加(真实效应)导致的,亦或是两者兼而有之。经典的多阶段克隆扩增(MSCE)模型假定在首个恶性细胞出现时就能检测到癌症,不过后来的修正包括了检测中的延迟时间或随机性,以便更现实地表示需要一定大小阈值才能检测到肿瘤。在此,我们引入一种方法,在MSCE框架中明确纳入诊断时的肿瘤大小,并考虑随着时间推移癌症检测的改善情况,以区分早发性癌症发病率的表观增加和真实增加。我们证明我们的模型在结构上是可识别的,并且比经典模型能提供更好的参数估计。将此模型应用于结直肠癌、女性乳腺癌和甲状腺癌,我们在考虑三个代表性出生队列(1950 - 1954年、1965 - 1969年和1980 - 1984年)随时间推移检测改善情况的同时,研究癌症风险的变化。我们的分析表明,在更近的队列中致癌事件加速,平均停留时间缩短。我们进一步使用此模型来研究筛查对乳腺癌和结直肠癌发病率的影响,这两种癌症都有既定的筛查方案。我们的结果与这两种癌症筛查效果方面有充分记录的差异一致。这些发现强调了在癌症建模中考虑诊断时肿瘤大小的重要性,并支持近年来乳腺癌、结直肠癌和甲状腺癌早发性癌症风险的真实增加。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2d40/12234089/4379f1c834b4/nihpp-2024.12.05.24318584v2-f0001.jpg

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