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首页> 外文期刊>Journal of the Royal Statistical Society >A joint model of persistent human papilloma virus infection and cervical cancer risk: implications for cervical cancer screening
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A joint model of persistent human papilloma virus infection and cervical cancer risk: implications for cervical cancer screening

机译:持续性人类乳头瘤病毒感染与宫颈癌风险的联合模型:对宫颈癌筛查的意义

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New cervical cancer screening guidelines in the USA and many European countries recommend that women are tested for human papilloma virus (HPV). To inform decisions about screening intervals, we calculate the increase in precancer or cancer risk per year of continued HPV infection. However, both time to onset of precancer or cancer and time to HPV clearance are interval censored, and onset of precancer or cancer strongly informatively censors HPV clearance. We analyse these bivariate informatively interval-censored data by developing a novel joint model for time to clearance of HPV and time to precancer or cancer by using shared random effects, where the estimated mean duration of each woman's HPV infection is a covariate in the submodel for time to precancer or cancer. The model was fitted to data on 9553 HPV positive and negative women undergoing cervical cancer screening at Kaiser Permanente Northern California: data that were pivotal to the development of US screening guidelines. We compare the implications for screening intervals of this joint model with those from population-average marginal models of precancer or cancer risk. In particular, after 2 years the marginal population-average precancer or cancer risk was 5%, suggesting a 2-year interval to control population-average risk at 5%. In contrast, the joint model reveals that almost all women exceeding 5% individual risk in 2 years also exceeded 5% in 1 year, suggesting that a 1-year interval is better to control individual risk at 5%. The example suggests that sophisticated risk models that can predict individual risk may have implications that are different from those of population-average risk models that are currently used for informing medical guideline development.
机译:美国和许多欧洲国家/地区的新宫颈癌筛查指南建议对妇女进行人类乳头瘤病毒(HPV)测试。为了告知有关筛查间隔的决定,我们计算了持续HPV感染每年增加的癌前或癌症风险。但是,癌前期或癌症发作的时间和HPV清除时间都是间隔检查的,癌前期或癌症的发作强烈地检查了HPV的清除。我们使用共享的随机效应,通过开发新型的清除HPV的时间以及清除HPV的时间以及癌前或癌症时间的新型联合模型,分析了这些具有双变量信息的区间检查数据,其中,每个女性HPV感染的估计平均持续时间是该子模型中的协变量癌症或癌症的时间到了。该模型适用于在北加州凯撒永久医疗中心接受宫颈癌筛查的9553名HPV阳性和阴性妇女的数据:这些数据对美国筛查指南的制定至关重要。我们比较了这种联合模型的筛查间隔与癌症前期或癌症风险人群平均边际模型的筛查间隔的影响。特别是,在2年后,边缘人群的平均癌症前期风险或癌症风险为5%,建议每2年间隔将人群平均风险控制在5%。相反,联合模型显示,几乎所有在2年内超过5%个人风险的女性在1年内也超过了5%,这表明以1年为间隔将个体风险控制在5%更好。该示例表明,可以预测个体风险的复杂风险模型可能具有与当前用于指导医学指南制定的人群平均风险模型不同的含义。

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