Characterization of Human Papillomavirus prevalence and risk factors to guide cervical cancer screening in the North Tongu District, Ghana
Bibliographic record
Abstract
INTRODUCTION: This population-based study aimed to fill the knowledge gap on Human Papillomavirus (HPV) prevalence and associated sociodemographic risk factors of the general population in the North Tongu District, Ghana. These results are needed to guide cervical cancer prevention efforts, as the leading type of female cancers. METHODS: A cross-sectional study including 2002 women in the North Tongu District, Ghana investigated HPV prevalence and associated sociodemographic risk factors. Women were recruited by geographical distribution through the local community-based health system and samples collected using a self-sampling device. For HPV genotyping BSGP5+/6+-PCR with Luminex-MPG readout was used. Multivariate logistic regression analyzed sociodemographic risk factors for HPV positivity. RESULTS: Of 2002 self-collected samples, 1943 were eligible, contained sufficient DNA and provided valid HPV genotyping results. Prevalence of single high risk HPV types was 32.3% and of multiple high risk types 9.7%. The five most common detected HPV types were HPV16 (7.4%; 95%CI: 6.3-8.7), HPV52 (7.2%; 95%CI: 6.1-8.5), HPV35 (4.8%; 95%CI: 3.9-5.8), HPV59 (4.7%; 95%CI: 3.8-5.8), HPV56 (3.9%; 95%CI: 3.1-4.8). Highest prevalence was observed among women aged 18-24 years, while age 25-54 years was inversely associated with high risk HPV positivity in multivariate analysis. Sociodemographic risk factors identified were i) having any sexual partner, ii) more partners increased the odds for high risk HPV positivity, iii) independently from this marital status, in particular not being married. DISCUSSION & CONCLUSION: Most importantly, the high risk HPV prevalence detected from this study is higher than estimates reported for Western Africa. This needs be considered, when deciding on the cervical cancer screening algorithms introduced on a wider scale. Follow-up and triage, depending on the methods chosen, can easily overburden the health system. Self-sampling worked well and provided adequate samples for HPV-based screening. Women with increasing number of sexual partners and not being married were found to have higher odds of being high risk HPV positive, therefore could be a higher prioritized screening target group.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".