Evaluation of the association of area-level socioeconomic deprivation and breast cancer recurrence by oestrogen receptor subtypes in Scotland
Bibliographic record
Abstract
BACKGROUND: Women from socioeconomically deprived areas have lower breast cancer (BC) incidence rates for screen-detected oestrogen receptor (ER) + tumours and higher mortality for select tumour subtypes. We aimed to determine if ipsilateral breast cancer recurrence (IBR) differs by Scottish Index of Multiple Deprivation (SIMD) quintile and tumour subtype in Scotland. METHODS: Patient data for primary invasive BC diagnosed in 2007-2008 in Scotland was analysed. Manual case-note review for 3495 patients from 10 years post-diagnosis was used. To determine the probability of IBR while accounting for the competing risk of death from any cause, cumulative incidence functions stratified by ER subtype and surgery were plotted. Multivariable Cox Proportional Hazards models were used to estimate the association of SIMD accounting for other predictors of IBR. RESULTS: Among 2819 ER + tumours, 423 patients had a recurrence and 438 died. SIMD was related to death (p = 0.018) with the most deprived more likely to have died in the 10-year period (17.7% vs. 12.9%). We found no significant differences by SIMD in prognostic tumour characteristics (grade, TNM stage, treatment, screen-detection) or risk of IBR. Among 676 patients diagnosed with ER- tumours, 105 died and 185 had a recurrence. We found no significant differences in prognostic tumour characteristics by SIMD except screen detection with the most deprived more likely than the least to have their tumours detected from screening (46.9% vs. 28%, p = 0.03). Among patients with ER- tumours, 50% had mastectomy and the most deprived had increased 5-year IBR risk compared to the least deprived (HR 3.03 [1.41-6.53]). CONCLUSIONS: IBR is not a major contributor to mortality differences by SIMD for the majority of BC patients in our study. The lack of inequities in IBR are likely due to standardised treatment protocols and access to healthcare. The association with socioeconomic deprivation and recurrence for ER- tumours requires further study.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".