Papanicolaou test utilization and frequency of screening opportunities among women diagnosed with cervical cancer.
Bibliographic record
Abstract
BACKGROUND: Although the importance of Papanicolaou (Pap) smear test screening in reducing the incidence of cervical cancer is well established, in 1994-95 one in 4 women in Manitoba aged 18 to 69 years reported never having had a Pap test or not having had a Pap test in the last 3 years. The objectives of this study were to examine the screening history of women in Manitoba diagnosed with invasive cervical cancer and to explore whether opportunities for screening were missed. METHODS: In this case-control study women aged 18 years and older who resided in Manitoba and were diagnosed with invasive cervical cancer between 1989 and 2001 were each matched by age and area of residence to 5 controls, (N = 4009). Conditional logistic regression analyses were used to examine the association between Pap test utilization and the likelihood of diagnosis with invasive cervical cancer. Generalized linear models using the negative binomial distribution were used to assess the association between cancer status and rates of prior Pap testing and of opportunities to be screened. Logistic generalized estimating equation models were used for the analysis of physician characteristics. RESULTS: Forty-six percent of women in Manitoba diagnosed with invasive cervical cancer and 67% of the control group had received a Pap test in the 5 years before the case's diagnosis. After adjustment for age, income and residence, the rate of Pap testing was significantly higher in the control group (rate ratio [RR] = 1.57, 95% confidence interval [CI] 1.44-1.73). Conversely, when cervical cancer was the outcome, women who had not had Pap tests were more likely to be diagnosed with invasive cervical cancer (odds ratio [OR] = 2.77, 95% CI 2.30-3.30) than women who did have a Pap test. Although women diagnosed with invasive cervical cancer had fewer Pap tests, they had had as many opportunities to be screened as controls (RR = 1.04, 95% CI 0.96-1.12). Compared with urban family physicians, rural family physicians were less likely to provide Pap tests (OR = 0.68, 95% CI 0.58-0.80) and specialists were more likely to provide Pap tests (OR = 1.70, 95% CI 1.30-2.22). CONCLUSIONS: Women who were diagnosed with invasive cervical cancer in the province of Manitoba, Canada, had fewer Pap tests but the same frequency of opportunities to be screened as matched controls. These results reinforce the need to educate women about cervical cancer screening and the importance of receiving Pap tests.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".