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Record W1645070058 · doi:10.1002/cncy.21297

Pooled analysis of the performance of liquid‐based cytology in population‐based cervical cancer screening studies in China

2013· article· en· W1645070058 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCancer Cytopathology · 2013
Typearticle
Languageen
FieldMedicine
TopicCervical Cancer and HPV Research
Canadian institutionsJuravinski Hospital
FundersFogarty International Center
KeywordsMedicineCervical cancerLiquid-based cytologyCytologyCancerChinaCervical cancer screeningGynecologyPopulationChinese populationObstetricsOncologyInternal medicinePathologyEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: Liquid-based cytology (LBC) has been widely used for cervical cancer screening. Despite numerous studies and systematic reviews, to the authors' knowledge few large studies to date have focused on biopsy-confirmed cervical lesions and controversy remains concerning its diagnostic accuracy. The objective of the current study was to assess LBC for detecting biopsy-confirmed cervical intraepithelial neoplasia (CIN) and cancer. METHODS: A pooled analysis of LBC using data from 13 population-based, cross-sectional, cervical cancer screening studies performed in China from 1999 to 2008 was performed. Participants (n = 26,782) received LBC and human papillomavirus testing. Women found to be positive on screening were referred for colposcopy and biopsy. The accuracy of LBC for detecting biopsy-confirmed CIN of type 2 or worse (CIN2+) as well as CIN type 3 or worse (CIN3+) lesions was analyzed. RESULTS: Of 25,830 women included in the analysis, CIN2+ was found in 107 of 2612 with atypical squamous cells (4.1%), 142 of 923 with low-grade squamous intraepithelial neoplasia (15.4%), 512 of 784 with high-grade squamous intraepithelial neoplasia (65.3%), 29 of 30 with squamous cell carcinoma (96.7%), 4 of 27 with atypical glandular cells (14.8%), and 85 of 21,454 with normal cytology results (0.4%). No invasive cancers were found to have atypical squamous cells, atypical glandular cells, or cytologically normal slides. The overall sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of LBC for detecting CIN2+ were 81.0%, 95.4%, 38.3%, 99.3 %, and 94.9%, respectively. Although Hybrid Capture 2 was more sensitive than LBC, the specificity, positive predictive value, and overall accuracy of LBC were higher than those of Hybrid Capture2 at 85.2%, 18.6%, and 85.5%, respectively. CONCLUSIONS: The results of the current study indicate that the performance of LBC can effectively predict the risk of existing CIN2+ and may be a good screening tool for cervical cancer prevention in a developing country.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.054
GPT teacher head0.385
Teacher spread0.332 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it