Comparative study of the ThinPrep Pap test and conventional cytology results in a Canadian cohort
Bibliographic record
Abstract
OBJECTIVE: To compare the frequency of Pap test results in a prospective series of direct to vial ThinPrep tests to a cohort of conventionally prepared tests. To follow-up all test results for a minimum of 2 years and assess performance based on this outcome. METHODS: All women presenting for either routine screening or colposcopic examination in 2001 were enrolled in the ThinPrep cohort. A similar, population of conventionally prepared tests was extracted from the year 2000 laboratory data. Information on all concurrent and follow-up cervical specimens over the ensuing 2 years was retrieved. RESULTS: The ThinPrep cohort comprised 2288 Pap tests and the conventional, 2211. The frequency of normal [within normal limits (WNL) and benign cellular changes (BCC)] results in the ThinPrep cohort was 6% lower and the frequency of abnormal [> or =atypical squamous cells of undetermined significance (ASCUS)] results was 6.8% higher. Respective ThinPrep and conventional cohort results were 1156 (51%) and 1291 (58%) WNL, 625 (27%) and 561 (25%) BCC, 101 (4%) and 65 (3%) ASCUS, 21 (1%) and 2 (0.1%) atypical glandular cells of undetermined significance, 301 (13%) and 224 (10%) low-grade squamous intraepithelial lesion (LSIL), and 74 (3%) and 40 (2%) high-grade SIL (HSIL) (P < 0.0001). Follow-up was available for nearly 80% of each cohort. LSIL or higher was confirmed in 57.5% (n = 266) of the abnormal ThinPrep and 60.9% (n = 190) of the abnormal conventional tests. The ThinPrep yield of confirmed tests however was almost 50% higher than the conventional test. CONCLUSION: In this population, ThinPrep was superior to the conventional Pap test.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".