The impact of neoadjuvant treatment (NAT) on surgery in early breast cancer (EBC): A real-world data study.
Bibliographic record
Abstract
e12609 Background: NAT is being used with increasing frequency in the multimodal treatment of EBC. Oncologically, NAT provides an opportunity to assess response to early systemic therapy and tailor adjuvant treatment. The surgical objective of NAT is down staging the tumor, which may lead to improved chances of breast conservation surgery; potentially decreasing surgical morbidity. Down staging of axillary disease may also lead to minimizing the need for complete axillary lymph node dissection (ALND) and its associated surgical morbidity. We aimed to describe the potential impact of NAT on surgical de-escalation in the primary breast tumor and axilla in patients (pts) with HER2-positive, node-positive EBC treated in the community setting. Methods: We conducted a retrospective cohort study using a nationwide US electronic health record-derived de-identified database (Flatiron Health). Pts were diagnosed from Jan 1, 2011 to Sep 30, 2021, had reported clinical staging cN≥1, underwent primary breast surgery (index date), and had records indicating initiation of systemic treatment before surgery. Early clinical benefit includes, post-NAT: a) nodal pathologic complete response (pCR; pN=0); b) pCR (absence of residual invasive disease in the breast and axillary lymph nodes at NAT completion, subsequently confirmed at primary surgery); c) down staging (lowered T or N stage). Surgical operations recorded at index date were ALND and sentinel node excision (SNE), mastectomy (MT), and lumpectomy (LT). Results: 174 pts were included. At diagnosis, median age was 55 years, 162 pts (93%) presented with invasive ductal carcinoma, and <5 had bilateral BC. 124 pts (71%) were treated with dual HER2 blockade. As for early clinical benefit, nodal pCR was achieved in 106 pts (61%), pCR in 90 (52%), and down staging in 137 (79%). Types of surgical procedure for the axilla were SNE only for 62 pts (36%), ALND only for 84 (48%), and SNE and ALND for 26 (15%). Surgical procedures for the breast were MT for 118 pts (68%), of which 59 were bilateral, and LT for 55 (32%). Compared with not achieving nodal pCR, achieving nodal pCR was associated with increased odds of SNE only (odds ratio [OR] 2.59 [95% confidence interval (CI) 1.28, 5.53]), decreased odds of ALND (OR 0.47 [95% CI 0.23, 0.93]), increased odds of LT (OR 2.05 [95% CI 1.00, 4.39]), and decreased odds of MT (OR 0.47 [95% CI 0.22, 0.96]). Conclusions: In a real-world population of pts with HER2-positive EBC, NAT use was associated with early clinical benefit, potentially leading to less invasive primary surgery of the breast and axilla. The high use of MT and bilateral MT despite a high pCR rate demonstrates the multiple factors at play behind surgical and pt decision making. These data illustrate how NAT use can benefit pts by de-escalating surgical treatment options. Limitations include the modest sample size and lack of association between early and long-term clinical benefit.
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.
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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".