The role of molecular, clinical and socioeconomic factors in the long-term survival of axillary node negative breast cancer patients
Bibliographic record
Abstract
The overall objective of this study was to investigate factors associated with \nlong-term survival in axillary node negative (ANN) breast cancer patients. Clinical \nand biological factors included stage, histopathologic grade, p53 mutation, Her-2/neu \namplification, estrogen receptor status (ER), progesterone receptor status (PR) and \nvascular invasion. Census derived socioeconomic (SES) indicators included median \nindividual and household income, proportions of university educated individuals, \nhousing type, "incidence" of low income and an indicator of living in an affluent \nneighbourhood. The effects of these measures on breast cancer-specific survival and \ncompeting cause survival were investigated. \nA cohort study examining survival among axillary node negative (ANN) breast \ncancer patients in the greater Toronto area commenced in 1 989. Patients were \nfollowed up until death, lost-to-follow up or study termination in 2004. Data were \ncollected from several sources measuring patient demographics, clinical factors, \ntreatment, recurrence of disease and survival. Census level SES data were collected using census geo-coding of patient addresses' at the time of diagnosis. Additional \nsurvival data were acquired from the Ontario Cancer Registry to enhance and extend \nthe observation period of the study. Survival patterns were examined using KaplanMeier \nand life table procedures. Associations were examined using log-rank and \nWilcoxon tests of univariate significance. Multivariate survival analyses were \nperfonned using Cox proportional hazards models. Analyses were stratified into less \nthan and greater than 5 year survival periods to observe whether known markers of \nshort-tenn survival were also associated with reductions in long-tenn survival among \nbreast cancer patients. \nThe 15 year survival probabilities in this cohort were: for breast cancerspecific \nsurvival 0.88, competing causes survival 0.89 and for overall survival 0.78. \nEstrogen receptor (ER) and progesterone receptor (PR) status (Hazard Ratio (HR) ERIPR- \nversus ER+/PR+, 8.15,95% CI, 4.74, 14.00), p53 mutation (HR, 3.88, 95% CI, \n2.00, 7.53) and Her-2 amplification (HR, 2.66, 95% CI, 1.36, 5.19) were associated \nwith significant reductions in short-tenn breast cancer-specific survival «5 years \nfollowing diagnosis), however, not with long-term survival in univariate analyses. \nStage, histopathologic grade and ERiPR status were the clinicallbiologieal factors that \nwere associated with short-term breast cancer specific survival in multivariate results. \nLiving in an affluent neighbourhood (top quintile of median household income \ncompared to the rest of the population) was associated with the largest significant \nincrease in long-tenn breast cancer-specific survival after adjustment for stage, \nhistopathologic grade and treatment (HR, 0.36, 95% CI, 0.12, 0.89).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".