Accepting the Universal Truths of Cervical Human Papillomavirus Epidemiology in Pursuit of the Remaining Mysteries
Bibliographic record
Abstract
In this issue, Sauvaget et al.1 present one of the largest cross-sectional studies ever performed on the epidemiologic determinants of cervical human papillomavirus (HPV) infection. In the HPV testing arm of the landmark Indian cervical cancer screening trial,2 they found that in the middle-aged population of >27,000 women HPV prevalence increased with low education level, manual occupation, early age at first sexual intercourse, widowhood, and older age. The authors point out that their huge interview, coding, keying, and analysis effort mainly corroborated known, expected epidemiologic associations. Cervical HPV epidemiology is uniform in many respects worldwide. As a result of 30 years of concordant cross-sectional studies of the determinants of HPV prevalence, by aggregation, a set of strong “prior beliefs” has formed, from which a single discrepant article could not easily dislodge us. In fact, the large and well-performed study by Sauvaget et al. led us to consider whether there are topics in global HPV epidemiology that are sufficiently established to forego further active examination. First and foremost, we think it is proven that HPV is a common, easily transmitted sexually transmitted infection. Sauvaget et al. did not measure sexual partner history directly, but any variable linked to having sex, such as young age and number of sexual partners, increases risk of infection.3 For example, being unmarried (including widowhood, adjusted for age) is usually a risk factor because of the implication of more recent partners, including partners who are sexually active with other women, etc. Similarly, depending on regional social/sexual practices, low education and early age at first intercourse can plausibly be linked to higher risk of acquisition. Apart from sociologic analyses, as etiologists, we do not need to question the sexual correlates of HPV infection. As an example of another thoroughly studied topic, not addressed by Sauvaget et al., the major established cofactors for cancer risk among HPV infected women, all of moderate strength, are smoking, long-term oral contraceptive use, and multiparity.4–6 Given the firm results of large pooling projects, 7–9 it is difficult to perceive what new conventional epidemiology studies of these cofactors will add. As another example, the same dozen, evolutionarily related carcinogenic types cause cervical cancer throughout the world (now and going back in time).10–12 These are the types pooled in the assay used by Sauvaget et al.; the most important of the types are included in the pending 9-type HPV vaccine (reference available at: http://www.merck.com). Apart from the continued methodical pooling projects conducted by international groups affiliated with IARC and ICO, we believe that there are more interesting questions than HPV types in cervical cancer, which can be addressed by local groups (such as the variation in age curves discussed later). Thus, in the absence of accompanying novel findings, it might no longer be sufficiently novel to report another population in which HPV16 accounts for approximately half of cancers with relatively smaller contributions of the other known carcinogenic types. To confirm our admittedly personal impression that the topics aforementioned are well accepted and, therefore, less interesting to HPV researchers, we informally examined the abstracts presented at the last 5 International Papillomavirus Workshops (Vancouver in 2005, Prague in 2006, Beijing in 2007, Malmo in 2009, and Montreal in 2010). In the Workshops, oral presentations are given to the topics considered to be of heightened interest to the researchers. Increasingly in sequential meetings, we found that very few oral presentations addressed determinants of HPV infection, the conventional cofactors for cancer among HPV-infected women, or the types of HPV found in invasive cancers (except for the extremely large pooling projects conducted by IARC and ICO). Almost all of the global epidemiologic studies of these topics were presented as posters, signifying lower priority among HPV researchers. In contrast, there are many remaining vibrant questions in global HPV epidemiology. As a novel part of their presentation, Sauvaget et al. explored one such enduring mystery, that is, their finding of increasing HPV prevalence at older ages. HPV age-prevalence curves vary substantially by region for unknown reasons.13 HPV prevalence is the basis of using HPV testing in cervical cancer screening; understanding the varying age-specific prevalence patterns guide how we design our programs. Sauvaget et al. found a rise in HPV prevalence over the age of 50 years that is observed in countries with U-shaped prevalence curves. Because this was a screening project, they did not study young women among whom one would expect the highest, initial peak of sexually transmitted HPV incidence and prevalence. As the authors state, the secondary peak at older ages could result from immune senescence and reappearance of HPV infections originally acquired at young ages. But, in some settings, there could be continued acquisition linked to patterns of sexual behavior at older ages. Questionnaire studies stratified by age remain very interesting; perhaps they can help in explaining age-specific prevalence patterns (although the questions asked by Sauvaget et al. did not explain the upturn in HPV prevalence.). If we suspect that the determinant of the upturn is immune senescence, it would be extremely helpful to have easily obtainable measures of immunity to HPV, especially cell-mediated immunity for keeping infections under control.14 The immunoepidemiology of HPV is a largely unexplored and important phenomenon which could vary worldwide. Such assays are not yet validated. Some of the remaining important questions about HPV epidemiology require prospective or even longitudinal, repeated measures designs that are admittedly much difficult to achieve than cross-sectional surveys. For example, sexual transmission studies that address specific practices, mechanisms, and efficiency of transmission are difficult to perform and still very much needed. And, returning to the issue of HPV prevalence at older ages, it is still fundamental and unclear how frequently HPV infection reappears after initial clearance15 contributing to the U-shaped prevalence curves. If HPV does reappear, the subsequent risk of precancer and cancer is poorly understood. Our work in progress (A. C. Rodriguez, unpublished data, 2011) suggests that very few cases of cancer arise from reappearing HPV infections, but confirmation is certainly required in multiple geographical regions. As a final selected example of “novel” topics, aspects of HPV epidemiology that address translation of natural history understanding into assays, vaccines, and preventive programs remain extremely topical and interesting. Although the International Papillomavirus Workshop was fundamentally mechanistic and etiologic 20 years ago, its center has shifted; it is now a global translational research meeting. We expect that other HPV researchers might have their own views of what global epidemiology topics are now most interesting as we move forward. We are expressly not criticizing the fine effort by Sauvaget et al. We are raising for public discussion the proposition that we can accept certain universal truths about HPV (e.g., its fundamental nature as a typically benign sexually transmitted infection), and can encourage each other, when the opportunity and resources permit, to pursue the remaining mysteries.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".