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Record W2046584623 · doi:10.1148/radiol.12102348

A Review of Interval Breast Cancers Diagnosed among Participants of the Nova Scotia Breast Screening Program

2012· review· en· W2046584623 on OpenAlexaffabout
Jennifer Payne, Judy Caines, Julie Gallant, T. Foley

Bibliographic record

VenueRadiology · 2012
Typereview
Languageen
FieldMedicine
TopicGlobal Cancer Incidence and Screening
Canadian institutionsQueen Elizabeth II Health Sciences CentreGreenfield Research (Canada)Dalhousie University
Fundersnot available
KeywordsMedicineNova scotiaConfidence intervalBreast cancerCancerGynecologyPediatricsInternal medicine

Abstract

fetched live from OpenAlex

PURPOSE: To conduct a radiologic review of interval breast cancer cases to determine rates of true interval and missed cancers in Nova Scotia, Canada. MATERIALS AND METHODS: This quality assurance project was exempt from institutional review board approval. Interval cancer cases were identified among women aged 40-69 years who were participants in the Nova Scotia Breast Screening Program from 1991 to 2004. For each case, the index negative screening mammogram was reviewed blindly by three radiologists from a pool of experienced radiologists. Cases were identified as those with normal or abnormal findings, the latter being a case that required further investigation. True interval cases were identified as cases in which a minimum of two radiologists reviewed the findings as normal. True interval and missed cancer rates were calculated separately for women according to age group and screening interval (for ages 40-49 years, a 1-year interval; for ages 50-69 years, a 1-year and a 2-year interval). RESULTS: The rate of missed cancers per 1000 women screened was one-half of the true interval rate among women screened annually (for ages 40-49 years, 0.45 vs 0.93; for ages 50-69 years, 1.08 vs 2.22). Among women aged 50-69 years who were screened biennially, the rate of missed cancers per 1000 women screened was one-third of the true interval rate (0.90 vs 3.15). Similarly, the rate of missed cancers per 10,000 screening examinations was one-half of the true interval rate among those 40-49 years old (1.95 vs 3.99) and one-third of the true interval rate among those 50-69 years old (3.34 vs 10.44). CONCLUSION: In screening programs, true interval cancer rates should be differentiated from missed cancer rates as part of ongoing quality assurance.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.893
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.181
GPT teacher head0.422
Teacher spread0.241 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

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".

Quick stats

Citations18
Published2012
Admission routes2
Has abstractyes

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