Exploring the association between post-operative complications, disease-recurrence & mortality in primary operable breast cancer—systematic review & meta-analysis
Bibliographic record
Abstract
Background: Post-operative complications (POCs) affect 36.1% of breast cancer patients. POCs are associated with inferior oncological outcomes in gastro-intestinal, lung, and head and neck cancers. Evidence is less clear in breast cancer. The James Lind Alliance demonstrated the importance of exploring risk factors for disease-recurrence to both patients and clinicians. We reviewed the evidence and performed a meta-analysis to better understand the association between POCs, disease-recurrence and mortality in primary breast cancer. Methods: A PubMed search was conducted on 1st February 2024. Journal titles and abstracts were screened for suitability. Bibliographies of suitable studies were hand-searched for additional eligible studies. Original articles focusing on oncological outcomes after the development of POCs in primary breast cancer were included. Articles analysing risk factors for development of POCs or those assessing in situ or metastatic disease were excluded. Studies were evaluated using the Newcastle-Ottawa Scale. Meta-analysis was performed using a random effects model and presented using Forest plots. Results: Sixteen original studies were included in our review. Two large population studies demonstrate inferior survival in elderly patients who develop major surgical or medical complications, however, neither study accounts for recurrence or cancer-specific survival. Evidence for other comorbidities is lacking. Mastectomy demonstrates increased POC risk and is associated with inferior survival compared to conservation surgery [overall: hazard ratio (HR) 1.32, 95% confidence interval (CI): 1.15–1.51; cancer-specific: HR 1.31, 95% CI: 1.04–1.65]. There is however a paucity of evidence exploring impact of POCs following oncoplastic and/or reconstructive surgery. Meta-analysis demonstrated a significant effect of POCs in increasing the risk of recurrence (HR 1.35, 95% CI: 1.17–1.56, P<0.001), though a high degree of heterogeneity was noted (I2=86%). Variability in ‘wound complication’ definition and associated incidence, as well as the primary outcome reported (locoregional; systemic; any-site recurrence) was noted. Meta-analysis demonstrated a significant impact of POCs on the risk of all-cause mortality (HR 1.27, 95% CI: 1.17–1.39, P<0.001), with no heterogeneity observed (I2=0%). Conclusions: Increased age and mastectomy increase the risk of POC with associated inferior survival. The impact on disease-recurrence remains uncertain. Prospective studies with well-defined criteria are required, alongside studies exploring cellular level changes in primary breast cancer to better understand the underlying mechanism.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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".