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Record W2150557592 · doi:10.1200/jop.2011.000413

Improving Work-Up of the Abnormal Mammogram Through Organized Assessment: Results From the Ontario Breast Screening Program

2012· article· en· W2150557592 on OpenAlexafffundabout
May Lynn Quan, Rene Shumak, Vicky Majpruz, Claire M.D. Holloway, Frances P. O’Malley, Anna M. Chiarelli

Bibliographic record

VenueJournal of Oncology Practice · 2012
Typearticle
Languageen
FieldMedicine
TopicGlobal Cancer Incidence and Screening
Canadian institutionsFoothills Medical CentreHealth Sciences CentreUniversity of TorontoCancer Care OntarioSunnybrook Health Science CentreSt. Michael's Hospital
FundersCancer Care Ontario
KeywordsMedicineMammographyMedical physicsMEDLINEWork (physics)Medical educationFamily medicineBreast cancerData scienceInternal medicineCancer

Abstract

fetched live from OpenAlex

PURPOSE: Women with an abnormal screening mammogram should ideally undergo an organized assessment to attain a timely diagnosis. This study evaluated outcomes of women undergoing work-up after abnormal mammogram through a formal breast assessment affiliate (BAA) program with explicit care pathways compared with usual care (UC) using developed quality indicators for screening mammography programs. METHODS: Between January 1 and December 31, 2007, a total of 320,635 women underwent a screening mammogram through the Ontario Breast Screening Program (OBSP), of whom 25,543 had an abnormal result requiring further assessment. Established indicators assessing timeliness, appropriateness of follow-up, and biopsy rates were compared between women who were assessed through either a BAA or UC using χ(2) analysis. RESULTS: Work-up of the abnormal mammogram for patients screened through a BAA resulted in a greater proportion of women attaining a definitive diagnosis within the recommended time interval when a histologic diagnosis was required. In addition, use of other quality measures including specimen radiography for both core biopsies and surgical specimens and preoperative core needle biopsy was greater in BAA facilities. CONCLUSION: These findings support future efforts to increase the number of BAAs within the OBSP, because the pathways and reporting methods associated with them result in improvements in our ability to provide timely and appropriate care for women requiring work-up of an abnormal mammogram.

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)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.374
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.002
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 head0.082
GPT teacher head0.400
Teacher spread0.318 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations20
Published2012
Admission routes3
Has abstractyes

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