The effect of neoadjuvant chemotherapy on short-term outcomes in breast surgery: A propensity score adjusted analysis of NSQIP data.
Bibliographic record
Abstract
115 Background: Neoadjuvant chemotherapy (NAC) is increasingly used in the treatment of breast cancer. The primary objective of this study was to determine whether administration of NAC increased the proportion of overall 30-day post-operative complications among patients undergoing surgery for invasive breast cancer. Methods: An analysis of the American College of Surgeons, National Surgical Quality Improvement Program (ACS-NSQIP) participant user files from 2005-2012 was performed. Patients undergoing surgery for invasive breast cancer were included; those with high-risk comorbidities or concurrent surgery were excluded. The primary outcome was a composite of overall 30-day post-operative complications. A propensity score was calculated and a propensity score adjusted multivariable logistic regression model was used to determine the independent effect of NAC on overall 30-day complications. Results: In the study period67,685 patients having surgery for invasive breast cancer were identified; of those, 3,624 (5.5%) received NAC. The rate of NAC use within this cohort increased from 5.5% to 10.2%. Patients who received NAC were: younger and had fewer medical comorbidities, but, were more likely to receive neoadjuvant radiation and undergo bilateral surgery. On unadjusted analysis, patients receiving NAC had significantly more post-operative complications than those not receiving NAC (4.9% vs. 3.7%, p = 0.0003) mainly due to infection and bleeding. However, after adjusting for confounders by propensity score adjusted multivariable regression, there was no longer a significant difference in overall 30-day post-operative complications between those receiving NAC versus not (odds ratio 1.16 [95%CI: 0.98, 1.36]). Conclusions: This is the largest study to examine the effect of NAC on post-operative complications in patients undergoing surgery for invasive breast cancer. The receipt of NAC does not impart a significantly increased risk of post-operative complications in this patient population.
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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".