Human Papillomavirus Vaccine Uptake among Individuals with Systemic Inflammatory Diseases
Bibliographic record
Abstract
OBJECTIVES: The human papillomavirus (HPV) vaccine is safe and efficacious in patients with systemic inflammatory diseases (SID) who have higher rates of persistent HPV infection. We compared HPV vaccine uptake among SID and non-SID patients. METHODS: Using a U.S. insurance claims database (2006-2012), we identified individuals 9-26 years with ≥2 SID diagnosis codes ≥7 days apart with ≥12 months of continuous enrollment prior to the second code (index date). We matched SID patients by age, sex and index date to randomly selected non-SID subjects and selected those with ≥24 months of post-index date continuous follow-up. We also identified a non-SID subcohort with ≥1 diagnosis code for asthma. We defined initiation as ≥1 HPV vaccination claim after 2007, and completion as 3 claims. We used multivariable logistic regression to assess uptake in females 11-26 years comparing SID, non-SID and asthma cohorts, adjusting for demographics, region, comorbidities, and healthcare utilization. RESULTS: We identified 5,642 patients 9-26 years with SID and 20,643 without. The mean age was 18.1 years (SD 4.9). We identified 1,083 patients with asthma; the mean age was 17.2 (SD 5.1). Among females, 20.6% with SID, 23.1% without SID and 22.9% with asthma, received ≥1 HPV vaccine. In our adjusted models, the odds of receipt of ≥1 vaccine was 0.87 times lower in SID (95% CI 0.77-0.98) compared to non-SID and did not differ for 3 vaccines (OR 1.03, 95% CI 0.83-1.26). The odds of initiation and completion were not statistically different between SID and non-SID asthma cohorts. CONCLUSIONS: In this nationwide cohort, HPV vaccine uptake was extremely low. Despite the heightened risk of persistent HPV infection among those with SID, no increase in HPV vaccine uptake was observed. Public health efforts to promote HPV vaccination overall are needed, and may be particularly beneficial for those at higher risk.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| 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) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".