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利用 CRC-AIM 微观模拟模型估计基于粪便的结直肠癌筛查比较效果的差异依从性影响。

Estimating the impact of differential adherence on the comparative effectiveness of stool-based colorectal cancer screening using the CRC-AIM microsimulation model.

机构信息

EmpiriQA, LLC, Long Grove, IL, United States of America.

Exact Sciences Corporation, Madison, WI, United States of America.

出版信息

PLoS One. 2020 Dec 29;15(12):e0244431. doi: 10.1371/journal.pone.0244431. eCollection 2020.


DOI:10.1371/journal.pone.0244431
PMID:33373409
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7771985/
Abstract

BACKGROUND: Real-world adherence to colorectal cancer (CRC) screening strategies is imperfect. The CRC-AIM microsimulation model was used to estimate the impact of imperfect adherence on the relative benefits and burdens of guideline-endorsed, stool-based screening strategies. METHODS: Predicted outcomes of multi-target stool DNA (mt-sDNA), fecal immunochemical tests (FIT), and high-sensitivity guaiac-based fecal occult blood tests (HSgFOBT) were simulated for 40-year-olds free of diagnosed CRC. For robustness, imperfect adherence was incorporated in multiple ways and with extensive sensitivity analysis. Analysis 1 assumed adherence from 0%-100%, in 10% increments. Analysis 2 longitudinally applied real-world first-round differential adherence rates (base-case imperfect rates = 40% annual FIT vs 34% annual HSgFOBT vs 70% triennial mt-sDNA). Analysis 3 randomly assigned individuals to receive 1, 5, or 9 lifetime (9 = 100% adherence) mt-sDNA tests and 1, 5, or 9 to 26 (26 = 100% adherence) FIT tests. Outcomes are reported per 1000 individuals compared with no screening. RESULTS: Each screening strategy decreased CRC incidence and mortality versus no screening. In individuals screened between ages 50-75 and adherence ranging from 10%a-100%, the life-years gained (LYG) for triennial mt-sDNA ranged from 133.1-300.0, for annual FIT from 96.3-318.1, and for annual HSgFOBT from 99.8-320.6. At base-case imperfect adherence rates, mt-sDNA resulted in 19.1% more LYG versus FIT, 25.4% more LYG versus HSgFOBT, and generally had preferable efficiency ratios while offering the most LYG. Completion of at least 21 FIT tests is needed to reach approximately the same LYG achieved with 9 mt-sDNA tests. CONCLUSIONS: Adherence assumptions affect the conclusions of CRC screening microsimulations that are used to inform CRC screening guidelines. LYG from FIT and HSgFOBT are more sensitive to changes in adherence assumptions than mt-sDNA because they require more tests be completed for equivalent benefit. At imperfect adherence rates, mt-sDNA provides more LYG than FIT or HSgFOBT at an acceptable tradeoff in screening burden.

摘要

背景:结直肠癌(CRC)筛查策略在实际应用中的依从性并不完美。CRC-AIM 微观模拟模型用于估计指南认可的基于粪便的筛查策略的相对益处和负担因不完美依从性而产生的影响。

方法:对无诊断 CRC 的 40 岁人群进行多靶标粪便 DNA(mt-sDNA)、粪便免疫化学检测(FIT)和高灵敏度愈创木脂粪便潜血检测(HSgFOBT)的预测结果进行模拟。为了稳健性,以多种方式纳入了不完美依从性,并进行了广泛的敏感性分析。分析 1 假设依从性在 0%-100%之间,每次增加 10%。分析 2 纵向应用真实世界首轮差异依从率(基础不完美率=40%年度 FIT 与 34%年度 HsgFOBT 与 70%三年一次 mt-sDNA)。分析 3 随机分配个体接受 1、5 或 9 次终生(9=100%依从性)mt-sDNA 检测和 1、5 或 26 次(26=100%依从性)FIT 检测。与不筛查相比,每 1000 人报告一次筛查结果。

结果:与不筛查相比,每种筛查策略均降低了结直肠癌的发病率和死亡率。在年龄在 50-75 岁之间且依从性在 10%-100%之间的个体中,mt-sDNA 每 1000 人每年的生命年获益(LYG)范围为 133.1-300.0,FIT 为 96.3-318.1,HSgFOBT 为 99.8-320.6。在基础不完美依从率下,mt-sDNA 与 FIT 相比,LYG 增加了 19.1%,与 HsgFOBT 相比,LYG 增加了 25.4%,并且一般具有更好的效率比,同时提供了更多的 LYG。需要完成至少 21 次 FIT 检测才能达到与 9 次 mt-sDNA 检测大致相同的 LYG。

结论:CRC 筛查微观模拟中依从性假设的影响会影响用于为 CRC 筛查指南提供信息的 CRC 筛查模拟。由于需要完成更多的检测才能获得同等的益处,因此 FIT 和 HsgFOBT 的 LYG 比 mt-sDNA 更敏感于依从性假设的变化。在不完美的依从率下,mt-sDNA 提供的 LYG 比 FIT 或 HsgFOBT 多,同时在筛查负担方面具有可接受的折衷。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b913/7771985/a18415303393/pone.0244431.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b913/7771985/7d9ac02684a2/pone.0244431.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b913/7771985/8f09e1affaec/pone.0244431.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b913/7771985/7936306a03bf/pone.0244431.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b913/7771985/a18415303393/pone.0244431.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b913/7771985/7d9ac02684a2/pone.0244431.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b913/7771985/8f09e1affaec/pone.0244431.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b913/7771985/7936306a03bf/pone.0244431.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b913/7771985/a18415303393/pone.0244431.g004.jpg

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