Epidemiologic natural history and clinical management of Human Papillomavirus (HPV) Disease: a critical and systematic review of the literature in the development of an HPV dynamic transmission model

Abstract

Background: Natural history models of human papillomavirus (HPV) infection and disease have been used in a number of policy evaluations of technologies to prevent and screen for HPV disease (e.g., cervical cancer, anogenital warts), sometimes with wide variation in values for epidemiologic and clinical inputs. The objectives of this study are to: (1) Provide an updated critical and systematic review of the evidence base to support epidemiologic and clinical modeling of key HPV disease-related parameters in the context of an HPV multi-type disease transmission model which we have applied within a U.S. population context; (2) Identify areas where additional studies are particularly needed.

Methods: Consistent with our and other prior HPV natural history models, the literature review was confined to cervical disease and genital warts. Between October 2005 and January 2006, data were gathered from the published English language medical literature through a search of the PubMed database and references were examined from prior HPV natural history models and review papers. Study design and data quality from individual studies were compared and analyses meeting pre-defined criteria were selected.

Results: Published data meeting review eligibility criteria were most plentiful for natural history parameters relating to the progression and regression of cervical intraepithelial neoplasia (CIN) without HPV typing, and data concerning the natural history of HPV disease due to specific HPV types were often lacking. Epidemiologic evidence to support age-dependency in the risk of progression and regression of HPV disease was found to be weak, and an alternative hypothesis concerning the time-dependence of transition rates is explored. No data were found on the duration of immunity following HPV infection. In the area of clinical management, data were observed to be lacking on the proportion of clinically manifest anogenital warts that are treated and the proportion of cervical cancer cases that become symptomatic by stage.

Conclusion: Knowledge of the natural history of HPV disease has been considerably enhanced over the past two decades, through the publication of an increasing number of relevant studies. However, considerable opportunity remains for advancing our understanding of HPV natural history and the quality of associated models, particularly with respect to examining HPV age- and type-specific outcomes, and acquired immunity following infection.

Figure 1

Overview of epidemiologic structure of multi-HPV type model. HPV infection may progress to either genital warts or cervical disease, with regression possible for HPV infection, CIN grades 1–3 and genital warts. Only cervical cancer confers an added risk of mortality, as depicted in the figure. However, in the full model (not shown for simplicity) all individuals face an underlying age and sex-specific mortality rate due to non-cervical cancer-related causes. CIN = Cervical Intraepithelial Neoplasia; HPV = Human Papillomavirus.

Figure 2

Overview of clinical structure of multi-HPV typemodel. HPV infection may progress to either genital warts or cervical disease, with regression possible for HPV infection, CIN grades 1–3 and genital warts. Treated genital warts, CIN and cervical cancer may result in disease eradication with elimination of HPV infection, disease eradication with persistent HPV infection, or failure to eradicate disease or HPV infection. Once CIN is detected, women are followed with annual Pap screening. Women in all health states are also subject to an age-specific rate of hysterectomy for benign conditions (not shown for simplicity). CIN = Cervical Intraepithelial Neoplasia; HPV = Human Papillomavirus.

Figure 3

Annual Proportion of An Incident Cohort Progressing Under An Exponential Distribution. In this example, an incident cohort at year 0 progresses to a subsequent health state at an annual rate of 0.078, corresponding to a constant annual risk of 7.5%. This results in 7.5% (1*.075) of the original cohort progressing in year 1. By the start of year 10, 49.6% of the original cohort remains in the initial health state, and only 3.7% (.496*.075) progress during year 10. Regardless of the value for risk chosen, the absolute proportion progressing will be highest during year 1 and decline steadily with time. For simplicity, mortality and disease regression are not modeled here.

Figure 4

Illustration of Normally Distributed Progression Over Time In An Incident Cohort. In this example, an identical average annual rate (0.078) and risk (7.5%) of progression over a 25 year period has been modeled as in figure 3. However, through a transformation, the absolute risk of progression over time has now been rendered normally distributed (with standard deviation of 6) with the largest proportion of individuals now progressing near year 13 rather than year 1.

Figure 5

Incidence of CIN 2/3 Detected Through Screening and Cervical Cancer Incidence Prior to Screening. Rates are per 100,000 women undergoing routine cytologic screening for CIN 2/3, and per 100,000 women for cervical cancer. The peak incidence of invasive cervical cancer is observed approximately 25–30 years later than for CIN 2/3. Sources: CIN 2/3 incidence among screened women (Kaiser Permanente Northwest Health Plan, Portland, Oregon, 1998–2002) [73], Cervical cancer incidence among unscreened women (Connecticut, 1940–1944) [73].