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Record W2120065707 · doi:10.1093/jnci/dji239

Role of Detection Method in Predicting Breast Cancer Survival: Analysis of Randomized Screening Trials

2005· review· en· W2120065707 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJNCI Journal of the National Cancer Institute · 2005
Typereview
Languageen
FieldMedicine
TopicGlobal Cancer Incidence and Screening
Canadian institutionsUniversity of Toronto
FundersNational Cancer Institute
KeywordsMedicineBreast cancerOncologyHazard ratioInternal medicineStage (stratigraphy)MammographyProportional hazards modelConfidence intervalCancerBreast diseaseGynecology

Abstract

fetched live from OpenAlex

BACKGROUND: Screening mammography detects breast cancers earlier than those detected symptomatically, and so mammographically detected breast cancers tend to have better prognoses. The so-called stage shift that results from screen detection is subject to lead-time and length biases, and so earlier detection may not translate into longer survival. We used data from three large breast cancer screening trials--Health Insurance Plan (HIP) of New York and two Canadian National Breast Cancer Screening Studies (CNBSS)--to investigate survival benefits of breast cancer screening beyond stage shift. We also address whether method of detection is an independent prognostic factor in breast cancer. METHODS: The HIP trial randomly assigned approximately 62,000 women to screening and control groups. The two CNBSS trial cohorts CNBSS-1 and CNBSS-2 included a total of 44,970 women in the screening group and 44,961 in the control group. After adjusting for stage and other tumor characteristics in a Cox proportional hazards model, survival distributions were compared by method of breast cancer detection with both univariate and multivariable analyses. All P values are two-sided. RESULTS: Breast cancers detected by screening mammography had a shift in stage distribution to earlier stages (for HIP, P < .001; for CNBSS-1, P = .03; and for CNBSS-2, P < .001). After adjusting for tumor size, lymph node status, and disease stage in a Cox proportional hazards model, method of detection was a statistically significant independent predictor of disease-specific survival. Patients with interval cancers had a 53% (95% confidence interval [CI] = 17% to 100%) greater hazard of death from breast cancer than patients with screen-detected cancers, and patients with cancer in the control groups had a 36% (95% CI = 10% to 68%) greater hazard of death than patients with screen-detected cancer. CONCLUSION: There was an apparent survival benefit beyond stage shift for patients with screen-detected breast cancers compared with patients with breast cancers detected otherwise. Method of detection appears to be an important prognostic factor, even after adjusting for known tumor characteristics. This finding suggests that clinical trialists should routinely collect information about method of detection.

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)0.014
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.933
Threshold uncertainty score0.861

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0070.004
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.295
GPT teacher head0.512
Teacher spread0.216 · 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