Alsadhan Norah, Almaiman Alaa, Pujades-Rodriguez Mar, Brennan Cathy, Shuweihdi Farag, Alhurishi Sultana A, West Robert M
Department of Community Health Sciences, College of Applied Medical Sciences, King Saud University, Riyadh, Saudi Arabia.
Leeds Institute of Health Sciences, School of Medicine, University of Leeds, Leeds, United Kingdom.
Front Oncol. 2022 Nov 30;12:1049486. doi: 10.3389/fonc.2022.1049486. eCollection 2022.
Monitoring cancer trends in a population is essential for tracking the disease's burden, allocating resources, and informing public health policies. This review describes variations in commonly employed methods to estimate colorectal cancer (CRC) incidence trends.
We performed a systematic literature search in four databases to identify population-based studies reporting CRC incidence trends, published between January 2010 and May 2020. We extracted and described data on methods to estimate trends and assess model validity, and the software used.
This review included 145 articles based on studies conducted in five continents. The majority (93%) presented visual summaries of trends combined with absolute, relative, or annual change estimates. Fourteen (10%) articles exclusively calculated the relative change in incidence over a given time interval, presented as the percentage of change in rates. Joinpoint regression analysis was the most commonly used method for assessing incidence trends (= 65, 45%), providing estimates of the annual percentage change (APC) in rates. Nineteen (13%) studies performed Poisson regression and 18 (12%) linear regression analysis. Age-period-cohort modeling- a type of generalized linear models- was conducted in 18 (12%) studies. Thirty-nine (37%) of the studies modeling incidence trends (104, 72%) indicated the method used to evaluate model fitness. The joinpoint program (52%) was the statistical software most commonly used.
This review identified variation in the calculation of CRC incidence trends and inadequate reporting of model fit statistics. Our findings highlight the need for increasing clarity and transparency in reporting methods to facilitate interpretation, reproduction, and comparison with findings from previous studies.
监测人群中的癌症趋势对于追踪疾病负担、分配资源以及为公共卫生政策提供信息至关重要。本综述描述了估计结直肠癌（CRC）发病率趋势的常用方法的差异。
我们在四个数据库中进行了系统的文献检索，以识别2010年1月至2020年5月期间发表的基于人群的报告CRC发病率趋势的研究。我们提取并描述了有关估计趋势的方法、评估模型有效性以及所使用软件的数据。
本综述纳入了基于五大洲开展的研究的145篇文章。大多数（93%）呈现了趋势的可视化总结，并结合了绝对、相对或年度变化估计。14篇（10%）文章专门计算了给定时间间隔内发病率的相对变化，以率的变化百分比表示。Joinpoint回归分析是评估发病率趋势最常用的方法（=65，45%），提供率的年度百分比变化（APC）估计。19项（13%）研究进行了泊松回归，18项（12%）进行了线性回归分析。18项（12%）研究进行了年龄-时期-队列建模——一种广义线性模型。39项（37%）对发病率趋势进行建模的研究（104项，72%）指出了用于评估模型拟合度的方法。Joinpoint程序（52%）是最常用的统计软件。
本综述发现CRC发病率趋势计算存在差异，且模型拟合统计报告不足。我们的研究结果强调，在报告方法时需要提高清晰度和透明度，以促进解释、再现以及与先前研究结果的比较。
