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联合脆弱性Copula模型在分析宫颈癌女性复发时间和死亡时间中的应用

Application of the Joint Frailty Copula Model for Analyzing Time to Relapse and Time to Death of Women with Cervical Cancer.

作者信息

Shewa Gari Firomsa, Fenta Biru Tashome, Endale Gurmu Selamawit

机构信息

Department of Statistics, Assosa University, Assosa, Ethiopia.

出版信息

Int J Womens Health. 2023 Aug 8;15:1295-1304. doi: 10.2147/IJWH.S414946. eCollection 2023.

DOI:10.2147/IJWH.S414946
PMID:37576182
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10423001/
Abstract

BACKGROUND

Worldwide, there were 12.7 million new cervical cancer cases, of which 5.6 million took place in industrialized nations and 7.1 million in underdeveloped nations. In eastern, western, middle, and southern Africa, it is the main cancer-related cause of death in female patients. In Ethiopia, cancer was responsible for roughly 5.8% of all fatalities. This study makes use of sophisticated statistical models that take into account population heterogeneity in terms of frailty and dependence between two endpoints in terms of copulas.

METHODS

Based on hospital registry data, this retrospective study intends to examine the time to relapse and time to death of cervical cancer. This study analyzes 907 cervical cancer-positive women from various parts of Ethiopia. The copula model was used to link time to relapse and time to death of women with cervical cancer. Shared frailty model was used to incorporate unexplained heterogeneity for women with cervical cancer patients.

RESULTS

Of the 907 cervical cancer patients, 275 (30.32%) experienced a relapse, 353 (38.92%) died, and 554 (61.08%) were censored. Age, smoking status, family planning, HIV status, family history, abortion, and stage are the most reliable predictors of both time to relapse and time to death of cervical cancer patients. The estimate of the copula parameter (θ = 1.476, 95% CI: 1.082, 1.870) shows moderate amount of dependence between time to relapse and time to death (Kendall's rank correlation (τ) = 0.425). The estimate of the variability (heterogeneity) parameter in the population of clusters (region) is η = 0.495, 95% CI: 0.101, 0.889.

CONCLUSION

Age, smoking status, family planning, HIV status, family history, abortion, and more advanced stage significantly increase the risk of relapse and death of female cervical patients. There was a significant association between the time to relapse and the time to die for women with cervical cancer. There was a significant heterogeneity effect in the Tikur Anbessa Specialized Hospital.

摘要

背景

全球范围内,每年有1270万例新发宫颈癌病例,其中560万例发生在工业化国家,710万例发生在欠发达国家。在东非、西非、中非和南非,宫颈癌是女性患者主要的癌症相关死因。在埃塞俄比亚,癌症约占所有死亡人数的5.8%。本研究使用了复杂的统计模型,该模型考虑了脆弱性方面的人群异质性以及基于copula函数的两个终点之间的依赖性。

方法

基于医院登记数据,这项回顾性研究旨在考察宫颈癌患者的复发时间和死亡时间。本研究分析了来自埃塞俄比亚各地的907名宫颈癌阳性女性。使用copula模型来关联宫颈癌女性患者的复发时间和死亡时间。使用共享脆弱模型纳入宫颈癌患者群体中无法解释的异质性。

结果

在907名宫颈癌患者中,275例(30.32%)复发,353例(38.92%)死亡,554例(61.08%)被截尾。年龄、吸烟状况、计划生育、艾滋病毒感染状况、家族史、流产和分期是宫颈癌患者复发时间和死亡时间最可靠的预测因素。copula参数估计值(θ = 1.476,95%可信区间:1.082,1.870)显示复发时间和死亡时间之间存在中等程度的依赖性(肯德尔等级相关性(τ) = 0.425)。聚类(地区)人群中变异性(异质性)参数估计值为η = 0.495,95%可信区间:0.101,0.889。

结论

年龄、吸烟状况、计划生育、艾滋病毒感染状况、家族史、流产以及更晚期别显著增加了女性宫颈癌患者复发和死亡的风险。宫颈癌女性患者的复发时间和死亡时间之间存在显著关联。提库尔·安贝萨专科医院存在显著的异质性效应。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be77/10423001/52e0898cd328/IJWH-15-1295-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be77/10423001/52e0898cd328/IJWH-15-1295-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be77/10423001/52e0898cd328/IJWH-15-1295-g0001.jpg

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本文引用的文献

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Global estimates of incidence and mortality of cervical cancer in 2020: a baseline analysis of the WHO Global Cervical Cancer Elimination Initiative.2020 年全球宫颈癌发病率和死亡率估计:世卫组织全球消除宫颈癌倡议的基线分析。
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Time to Kidneys Failure Modeling in the Patients at Adama Hospital Medical College: Application of Copula Model.阿达玛医院医学院患者肾衰竭模型构建的时间:Copula 模型的应用。
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Bivariate Survival Copula Analysis of Glaucoma Patients during Blindness: Glaucoma Cases at Alert Hospital in Addis Ababa City of Ethiopia.
青光眼患者失明期间的双变量生存 Copula 分析:埃塞俄比亚亚的斯亚贝巴市 Alert 医院的青光眼病例。
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Cancer Med. 2019 Aug;8(10):4906-4917. doi: 10.1002/cam4.2352. Epub 2019 Jul 2.
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PLoS One. 2019 May 10;14(5):e0216522. doi: 10.1371/journal.pone.0216522. eCollection 2019.
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