Abstract:
Human papillomavirus (HPV) is the cause of almost all cases of cervical cancer, a disease that kills some 340,000 women per year. The timeline from initial infection with HPV to the onset of invasive cervical cancer spans decades, and observational studies of this process are limited to settings in which treatment of precancerous lesions was withheld or inadequate. Such studies have been critical for understanding the natural history of HPV. Modeling can shed additional insight on the natural history of HPV, especially across geographical settings with varying prevalence of factors known to affect the host-side immune response to HPV, such as HIV and tobacco use. In this study, we create models for the 30 most populous countries in Sub-Saharan Africa, each with country-specific demographic, and behavioral inputs. We found that it was not possible to fit the data if we assumed that the natural history parameters were exactly identical for all countries, even after accounting for demographic and behavioral differences, but that we could achieve a good fit with the addition of a single immunocompetence parameter for each country. Our results indicate that variation in host immune responses may play a role in explaining the differences in the burden of cervical cancer between countries, which in turn implies a greater need for more geographically diverse data collection to understand the natural history of HPV.
摘要:
人乳头瘤病毒(HPV)是几乎所有宫颈癌病例的原因,一种每年杀死约34万妇女的疾病。从最初感染HPV到侵袭性宫颈癌发作的时间表跨越了几十年,对这一过程的观察性研究仅限于对癌前病变的治疗被拒绝或不充分的环境。这些研究对于了解HPV的自然史至关重要。建模可以提供有关HPV自然史的更多见解,特别是在地理环境中,已知影响宿主对HPV的免疫反应的因素的患病率不同,如艾滋病毒和烟草使用。在这项研究中,我们为撒哈拉以南非洲30个人口最多的国家创建模型,每个都有特定国家的人口,和行为输入。我们发现,如果我们假设所有国家的自然史参数完全相同,就不可能拟合数据,即使在考虑了人口和行为差异之后,但是我们可以通过为每个国家添加单个免疫能力参数来实现良好的匹配。我们的结果表明,宿主免疫反应的变化可能在解释国家之间宫颈癌负担的差异方面发挥作用。这反过来意味着更需要更多的地理上不同的数据收集,以了解HPV的自然史。