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Abstract：
Human papillomavirus (HPV) is a common sexually transmitted virus that can cause cervical cancer and other diseases. Dynamic transmission models (DTMs) have been developed to evaluate the health and economic impacts of HPV vaccination. These models typically include many parameters, such as natural history of the disease, transmission, demographic, behavioral, and screening. To ensure the accuracy of DTM projections, it is important to parameterize them with the best available evidence. This study aimed to identify and synthesize data needed to parametrize DTMs on the natural history of HPV infection and related diseases. Parameters describing data of interest were grouped by their anatomical location (genital warts, recurrent respiratory papillomatosis, and cervical, anal, vaginal, vulvar, head and neck, and penile cancers), and natural history (progression, regression, death, cure, recurrence, detection), and were identified through a systematic literature review (SLR) and complementary targeted literature reviews (TLRs). The extracted data were then synthesized by pooling parameter values across publications, and summarized using the range of values across studies reporting each parameter and the median value from the most relevant study. Data were extracted and synthesized from 223 studies identified in the SLR and TLRs. Parameters frequently reported pertained to cervical cancer outcomes, while data for other anatomical locations were less available. The synthesis of the data provides a large volume of parameter values to inform HPV DTMs, such as annual progression rates from cervical intraepithelial neoplasia (CIN) 1 to CIN 2+ (median of highest quality estimate 0.0836), CIN 2 to CIN 3+ (0.0418), carcinoma in situ (CIS) 2 to local cancer+ (0.0396), and regional to distant cancer (0.0474). Our findings suggest that while there is a large body of evidence on cervical cancer, parameter values featured substantial heterogeneity across studies, and further studies are needed to better parametrize the non-cervical components of HPV DTMs.
摘要：
人乳头瘤病毒（HPV）是一种常见的性传播病毒，可引起宫颈癌和其他疾病。已经开发了动态传播模型（DTM）来评估HPV疫苗接种的健康和经济影响。这些模型通常包括许多参数，比如疾病的自然史，传输,人口统计学,行为，和筛选。为确保DTM投影的准确性,重要的是用最好的可用证据对它们进行参数化。这项研究旨在确定和综合参数化对HPV感染和相关疾病的自然史的DTM所需的数据。描述感兴趣数据的参数按其解剖位置(生殖器疣，复发性呼吸道乳头状瘤病，和子宫颈，肛门,阴道,外阴,头部和颈部,和阴茎癌)，和自然史(进展，回归，死亡,治愈,复发,检测)，并通过系统文献综述(SLR)和补充针对性文献综述(TLR)进行鉴定。然后通过在出版物中汇集参数值来合成提取的数据，并使用报告每个参数的研究的值范围和最相关研究的中位数进行总结。从SLR和TLR中鉴定的223项研究中提取和合成数据。经常报告的参数与宫颈癌结果有关，而其他解剖位置的数据较少。数据的合成提供了大量的参数值来通知HPVDTM，例如从宫颈上皮内瘤变（CIN）1到CIN2+的年度进展率（最高质量估计值的中位数为0.0836），CIN2至CIN3+（0.0418），原位癌（CIS）2到局部癌+（0.0396），和区域到远处的癌症（0.0474）。我们的研究结果表明，虽然有大量关于宫颈癌的证据，参数值在研究中具有显著的异质性，需要进一步的研究来更好地参数化HPVDTM的非宫颈成分。
