Early Detection, Prevention and Infections Branch, International Agency for Research on Cancer (IARC/WHO), Lyon, France.
Elife. 2023 May 25;12:e81752. doi: 10.7554/eLife.81752.
Local cervical cancer epidemiological data essential to project the context-specific impact of cervical cancer preventive measures are often missing. We developed a framework, hereafter named Footprinting, to approximate missing data on sexual behaviour, human papillomavirus (HPV) prevalence, or cervical cancer incidence, and applied it to an Indian case study. With our framework, we (1) identified clusters of Indian states with similar cervical cancer incidence patterns, (2) classified states without incidence data to the identified clusters based on similarity in sexual behaviour, (3) approximated missing cervical cancer incidence and HPV prevalence data based on available data within each cluster. Two main patterns of cervical cancer incidence, characterized by high and low incidence, were identified. Based on the patterns in the sexual behaviour data, all Indian states with missing data on cervical cancer incidence were classified to the low-incidence cluster. Finally, missing data on cervical cancer incidence and HPV prevalence were approximated based on the mean of the available data within each cluster. With the Footprinting framework, we approximated missing cervical cancer epidemiological data and made context-specific impact projections for cervical cancer preventive measures, to assist public health decisions on cervical cancer prevention in India and other countries.
本地宫颈癌流行病学数据对于预测宫颈癌预防措施的具体影响至关重要，但往往缺失。我们开发了一种名为“足迹”（Footprinting）的框架，用于近似估算性行为、人乳头瘤病毒（HPV）流行率或宫颈癌发病率等缺失数据，并将其应用于印度的案例研究。通过我们的框架，我们：(1) 确定了具有相似宫颈癌发病模式的印度邦聚类；(2) 根据性行为的相似性，将无发病数据的邦分类到已识别的聚类中；(3) 根据每个聚类内的现有数据，近似估算缺失的宫颈癌发病率和 HPV 流行率数据。确定了两种主要的宫颈癌发病率模式，其特征是发病率高和低。根据性行为数据中的模式，所有宫颈癌发病率缺失的印度邦都被归类为低发病率聚类。最后，根据每个聚类内可用数据的平均值，估算了宫颈癌发病率和 HPV 流行率的缺失数据。通过足迹框架，我们近似估算了缺失的宫颈癌流行病学数据，并对宫颈癌预防措施的具体影响进行了预测，以协助印度和其他国家在宫颈癌预防方面的公共卫生决策。
