Incidence and outcome of interval breast cancer among women participating in the provincial population based screening program in Manitoba, Canada.
Bibliographic record
Abstract
6595 Background: The province of Manitoba, Canada has an organized population based biennial mammographic screening program. Here we report outcomes of women diagnosed with Interval Cancers (IC), defined as cancer diagnosed within 24 months of a normal screening mammogram and before the next screening mammogram, compared to Screen Detected (SD) cancers. Methods: The Manitoba Cancer Registry was used to obtain data about tumor and host characteristics and cause-specific mortality for women 52 to 64 years of age diagnosed with invasive breast cancer from January 2004 to December 2010. Lead time bias in SD cancers was adjusted based on Duffy's correction factor. Competing risk analysis was used to examine the risk of death by cancer detection method. To examine the relationship between breast cancer detection type and personal and tumour characteristics, we performed multinomial logistic regression analysis with age, area-level income quintile, tumour grade, hormone receptor, and HER2 receptor as independent variables. Results: There were 5,884 women diagnosed with invasive breast cancer during the study period of which 1,338 were SD, 362 were IC, and the remainder were diagnosed outside the screening program or were non-compliant to screening. IC were more likely than SD cancers to be high grade [Odds Ratio (OR) 3.8, 95% Confidence Interval (CI): 2.1-6.8], and ER negative [OR 1.7, 95% CI: 1.02-3.12]. At data cut-off date of June 30, 2012, risk of death from breast cancer was significantly higher for IC compared to SD cancers [Hazard Ratio (HR) 4.18, 95% CI: 1.97-8.87)], for sojorn time (period when tumour is asymptomatic but screen detectable) of 2 years adjusting for area-level average income quintile and age. Sensitivity analyses with sojourn times of 1, 3, and 4 years showed similar results. Risk of non-breast cancer death was not increased with IC compared to SD cancers (HR 1.33, 95% CI: 0.43-4.15). Conclusions: Among women who participated in a systematic population-based screening program, IC occurred frequently; breast cancer-related death for IC was 4-times that of SD cancers. These results highlight the discordance between the principles underpinning population based breast cancer screening and natural history of these more lethal breast cancers.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".