Department of Health Policy and Management, Center for Health Decision Science, Harvard School of Public Health, Boston, MA 02115, USA.
Int J Cancer. 2013 Apr 15;132(8):1895-900. doi: 10.1002/ijc.27835. Epub 2012 Oct 11.
Knowledge of a country's cervical cancer (CC) burden is critical to informing decisions about resource allocation to combat the disease; however, many countries lack cancer registries to provide such data. We developed a prognostic model to estimate CC incidence rates in countries without cancer registries, leveraging information on human papilloma virus (HPV) prevalence, screening, and other country-level factors. We used multivariate linear regression models to identify predictors of CC incidence in 40 countries. We extracted age-specific HPV prevalence (10-year age groups) by country from a meta-analysis in women with normal cytology (N = 40) and matched to most recent CC incidence rates from Cancer Incidence in Five Continents when available (N = 36), or Globocan 2008 (N = 4). We evaluated country-level behavioral, economic, and public health indicators. CC incidence was significantly associated with age-specific HPV prevalence in women aged 35-64 (adjusted R-squared 0.41) ("base model"). Adding geographic region to the base model increased the adjusted R-squared to 0.77, but the further addition of screening was not statistically significant. Similarly, country-level macro-indicators did not improve predictive validity. Age-specific HPV prevalence at older ages was found to be a better predictor of CC incidence than prevalence in women under 35. However, HPV prevalence could not explain the entire CC burden as many factors modify women's risk of progression to cancer. Geographic region seemed to serve as a proxy for these country-level indicators. Our analysis supports the assertion that conducting a population-based HPV survey targeting women over age 35 can be valuable in approximating the CC risk in a given country.
了解一个国家的宫颈癌（CC）负担对于决定资源分配以抗击该疾病至关重要；然而，许多国家缺乏癌症登记系统来提供此类数据。我们开发了一种预后模型，利用人乳头瘤病毒（HPV）流行率、筛查和其他国家层面因素的信息，来估计没有癌症登记系统的国家的 CC 发病率。我们使用多元线性回归模型来确定 40 个国家 CC 发病率的预测因素。我们从正常细胞学（N=40）的女性中进行的荟萃分析中提取了每个国家特定年龄的 HPV 流行率（10 年年龄组），并与最近的 CC 发病率进行了匹配，当有癌症发病率在五大洲时（N=36），或 Globocan 2008（N=4）。我们评估了国家层面的行为、经济和公共卫生指标。CC 发病率与 35-64 岁女性特定年龄的 HPV 流行率显著相关（调整后的 R 平方为 0.41）（“基础模型”）。将地理区域添加到基础模型中，将调整后的 R 平方增加到 0.77，但进一步添加筛查在统计学上并不显著。同样，国家层面的宏观指标并没有提高预测的有效性。在年龄较大的女性中发现特定年龄的 HPV 流行率比 35 岁以下女性的流行率更能预测 CC 发病率。然而，HPV 流行率不能解释整个 CC 负担，因为许多因素会改变女性向癌症进展的风险。地理区域似乎是这些国家层面指标的替代物。我们的分析支持这样的观点，即针对 35 岁以上女性进行基于人群的 HPV 调查可以有效地估算特定国家的 CC 风险。
