Suppr超能文献

德克萨斯州城市的结直肠癌发病率、不平等现象和预防重点:使用“surveil”软件包进行监测研究。

Colorectal Cancer Incidence, Inequalities, and Prevention Priorities in Urban Texas: Surveillance Study With the "surveil" Software Package.

机构信息

Department of Population and Data Sciences, University of Texas Southwestern Medical Center, Dallas, TX, United States.

Department of Geospatial Information Sciences, The University of Texas at Dallas, Dallas, TX, United States.

出版信息

JMIR Public Health Surveill. 2022 Aug 16;8(8):e34589. doi: 10.2196/34589.

Abstract

BACKGROUND

Monitoring disease incidence rates over time with population surveillance data is fundamental to public health research and practice. Bayesian disease monitoring methods provide advantages over conventional methods including greater flexibility in model specification and the ability to conduct formal inference on model-derived quantities of interest. However, software platforms for Bayesian inference are often inaccessible to nonspecialists.

OBJECTIVE

To increase the accessibility of Bayesian methods among health surveillance researchers, we introduce a Bayesian methodology and open source software package, surveil, for time-series modeling of disease incidence and mortality. Given case count and population-at-risk data, the software enables health researchers to draw inferences about underlying risk and derivative quantities including age-standardized rates, annual and cumulative percent change, and measures of inequality.

METHODS

We specify a Poisson likelihood for case counts and model trends in log-risk using the first-difference (random-walk) prior. Models in the surveil R package were built using the Stan modeling language. We demonstrate the methodology and software by analyzing age-standardized colorectal cancer (CRC) incidence rates by race and ethnicity for non-Latino Black (Black), non-Latino White (White), and Hispanic/Latino (of any race) adults aged 50-79 years in Texas's 4 largest metropolitan statistical areas between 1999 and 2018.

RESULTS

Our analysis revealed a cumulative decline of 31% (95% CI -37% to -25%) in CRC risk among Black adults, 17% (95% CI -23% to -11%) for Latino adults, and 35% (95% CI -38% to -31%) for White adults from 1999 to 2018. None of the 3 observed groups experienced significant incidence reduction in the final 4 years of the study (2015-2018). The Black-White rate difference (per 100,000) was 44 (95% CI 30-57) in 1999 and 35 (95% CI 28-43) in 2018. Cumulatively, the Black-White gap accounts for 3983 CRC cases (95% CI 3746-4219) or 31% (95% CI 29%-32%) of total CRC incidence among Black adults in this period.

CONCLUSIONS

Stalled progress on CRC prevention and excess CRC risk among Black residents warrant special attention as cancer prevention and control priorities in urban Texas. Our methodology and software can help the public and health agencies monitor health inequalities and evaluate progress toward disease prevention goals. Advantages of the methodology over current common practice include the following: (1) the absence of piecewise linearity constraints on the model space, and (2) formal inference can be undertaken on any model-derived quantities of interest using Bayesian methods.

摘要

背景

利用人群监测数据监测疾病发病率随时间的变化,是公共卫生研究和实践的基础。贝叶斯疾病监测方法相对于传统方法具有优势,包括在模型规范方面具有更大的灵活性,以及能够对模型衍生的感兴趣的数量进行正式推断。然而,贝叶斯推理的软件平台通常对非专业人员来说是无法访问的。

目的

为了提高健康监测研究人员对贝叶斯方法的可及性,我们引入了一种贝叶斯方法和开源软件包 surveil,用于疾病发病率和死亡率的时间序列建模。给定病例计数和高危人群数据,该软件使健康研究人员能够对潜在风险和衍生数量进行推断,包括年龄标准化率、年度和累计百分比变化,以及不平等衡量标准。

方法

我们为病例计数指定了泊松似然,并使用一阶差分(随机游走)先验来对对数风险的趋势进行建模。surveil R 包中的模型是使用 Stan 建模语言构建的。我们通过分析 1999 年至 2018 年期间德克萨斯州四个最大的大都市统计区中 50-79 岁的非拉丁裔黑人(黑人)、非拉丁裔白人(白人)和西班牙裔/拉丁裔(任何种族)成年人的年龄标准化结直肠癌(CRC)发病率,展示了该方法和软件的应用。

结果

我们的分析显示,1999 年至 2018 年间,黑人成年人的 CRC 风险下降了 31%(95%CI-37%至-25%),拉丁裔成年人的风险下降了 17%(95%CI-23%至-11%),白人成年人的风险下降了 35%(95%CI-38%至-31%)。在研究的最后四年(2015-2018 年),这三个观察到的群体中没有一个经历了显著的发病率下降。1999 年,黑人和白人之间的发病率差异(每 10 万人)为 44(95%CI 30-57),而 2018 年为 35(95%CI 28-43)。累计起来,黑人和白人之间的差距占这段时间内黑人成年人 CRC 总发病率的 3983 例(95%CI 3746-4219)或 31%(95%CI 29%-32%)。

结论

CRC 预防方面的进展停滞不前,以及黑人居民的 CRC 风险过高,这在德克萨斯州的城市中需要特别关注,作为癌症预防和控制的优先事项。我们的方法和软件可以帮助公众和卫生机构监测健康不平等现象,并评估预防疾病目标的进展。与当前常见做法相比,该方法的优势包括以下几点:(1)模型空间不存在分段线性性约束,(2)可以使用贝叶斯方法对任何模型衍生的感兴趣的数量进行正式推断。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2938/9428771/e2b9742fd9cd/publichealth_v8i8e34589_fig1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验