De-Implementation of Axillary Staging and Radiotherapy in Low-Risk Breast Cancer Patients Aged 70–79 Years from Six Italian Cancer Institutes
Bibliographic record
Abstract
In women aged ≥70 with low-risk breast cancer (BrC), some major international guidelines recommend against sentinel lymph node biopsy (for example, those from the Society of Surgical Oncology, U.S.) and post-lumpectomy radiotherapy (for example, those from the National Comprehensive Cancer Network, U.S.). We assessed the frequency of both procedures in six National Cancer Institutes (IRCCSs) in the North, the Centre, and the South of Italy. Data on tumour characteristics and treatment were obtained from each centre. Patients aged 70-79 years diagnosed with a pT1-pT2, clinically axillary lymph node-negative, oestrogen and/or progesterone receptor-positive, and human epidermal growth factor receptor 2-negative BrC between 2015 and 2020 were eligible for the study. Factors associated with the omission of the two procedures were evaluated using binary penalised logistic regression models. Axillary staging was omitted in 33/1000 (3.3%) women. After simultaneous adjustment for the centre of treatment and all other key variables, axillary staging was omitted more often in 2015-2016 vs. 2017-2020 (odds ratio (OR): 2.7; 95% CI: 1.0-7.5), in women aged 75-79 vs. 70-74 years (OR: 2.3; 95% CI: 1.1-4.9), and in those who had mastectomy vs. breast-conserving surgery (OR: 3.3; 95% CI: 1.2-9.0). The higher the histological grade was, the less frequent were the omissions (OR for grade 3 vs. grade 1: 0.2; 95% CI: 0.0-0.7). Post-lumpectomy radiotherapy was omitted in 56/651 (8.6%) women with no significant association with age, period, tumour stage, and tumour grade. In conclusion, the omission of axillary staging and post-lumpectomy radiotherapy in low-risk older BrC patients was rare in the Italian IRCCSs. Although women included in the study cannot be considered a nationally representative sample of BrC patients in Italy, our findings can serve as a baseline to monitor the impact of future guidelines. To do that, the recording and storage of hospital-based information should be improved.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".