Department of Preventive Medicine, College of Medicine, The Catholic University of Korea, 222, Banpo-daero, Seocho-gu, Seoul, Republic of Korea, 06591.
Department of Obstetrics and Gynecology, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
BMC Health Serv Res. 2020 Mar 4;20(1):166. doi: 10.1186/s12913-020-5016-y.
The look-back period is needed to define baseline population for estimating incidence. However, short look-back period is known to overestimate incidence of diseases misclassifying prevalent cases to incident cases. The purpose of this study is to evaluate the impact of the various length of look-back period on the observed incidences of uterine leiomyoma, endometriosis and adenomyosis, and to estimate true incidences considering the misclassification errors in the longitudinal administrative data in Korea.
A total of 319,608 women between 15 to 54 years of age in 2002 were selected from Korea National Health Insurance Services (KNHIS) cohort database. In order to minimize misclassification bias incurred when applying various length of look-back period, we used 11 years of claim data to estimate the incidence by equally setting the look-back period to 11 years for each year using prediction model. The association between the year of diagnosis and the number of prevalent cases with the misclassification rates by each look-back period was investigated. Based on the findings, prediction models on the proportion of misclassified incident cases were developed using multiple linear regression.
The proportion of misclassified incident cases of uterine leiomyoma, endometriosis and adenomyosis were 32.8, 10.4 and 13.6% respectively for the one-year look-back period in 2003. These numbers decreased to 6.3% in uterine leiomyoma and - 0.8% in both endometriosis and adenomyosis using all available look-back periods (11 years) in 2013.
This study demonstrates approaches for estimating incidences considering the different proportion of misclassified cases for various length of look-back period. Although the prediction model used for estimation showed strong R-squared values, follow-up studies are required for validation of the study results.
回顾期用于定义估计发病率的基线人群。然而，较短的回顾期已知会高估疾病的发病率，从而将现患病例误诊为新发病例。本研究旨在评估不同长度的回顾期对观察到的子宫肌瘤、子宫内膜异位症和子宫腺肌病发病率的影响，并考虑到韩国纵向行政数据中的误诊错误来估计真实发病率。
从韩国国家健康保险服务（KNHIS）队列数据库中选择了 2002 年年龄在 15 至 54 岁之间的 319,608 名女性。为了最小化应用不同长度回顾期时发生的误诊偏差，我们使用了 11 年的索赔数据，通过为每个年份均等设置 11 年的回顾期，使用预测模型来估计发病率。研究了诊断年份与各回顾期的现患病例数与误诊率之间的关系。基于这些发现，使用多元线性回归开发了用于估计误分类新发病例比例的预测模型。
2003 年一年回顾期时，子宫肌瘤、子宫内膜异位症和子宫腺肌病的误分类新发病例比例分别为 32.8%、10.4%和 13.6%。使用 2013 年所有可用的回顾期（11 年）时，这些数字分别下降到 6.3%的子宫肌瘤和−0.8%的子宫内膜异位症和子宫腺肌病。
本研究展示了考虑不同长度回顾期的不同误分类病例比例来估计发病率的方法。虽然用于估计的预测模型显示出较强的 R 平方值，但需要进一步的随访研究来验证研究结果。
