Implant-based immediate breast reconstruction: failure rate when radiating the tissue expander or the permanent implant—a meta-analysis
Bibliographic record
Abstract
BACKGROUND: Implant-based immediate approach remains to be a first line option for reconstruction of mastectomy defects. When combined with post-mastectomy radiation therapy (PMRT) two different schemas are possible: radiating the temporary tissue expander (TTE) or the permanent implant (PI). The present article intends to be the biggest cohort meta-analysis to the date comparing reconstructive failure (RF) rate in these two scenarios: PMRT to TE compared with PMRT to PI. METHODS: A systematic search of the literature was performed on PUBMED/MEDLINE. The following key words were chosen: Breast Reconstruction AND Implant based AND Immediate. The time limit applied was from January 2008 to January 2019. We selected ten articles (n=1,130) to perform a meta-analysis due to the similarity of their approaches. Secondly, we did a simple literature review in order to identify some variables possibly working as predicting factors for RF. RESULTS: Previous meta-analysis are analysed. Some variables possibly working as risk factors for RF are summarized. We performed a meta-analysis in two scenarios: a fixed-effect model and a random effect model. For the random effect model an OR of 1.85 was obtained (0.96, 3.57; P=0.067). A funnel plot is performed showing no publication bias exists. CONCLUSIONS: There is a tendency towards a higher RF rate when the TTE is irradiated compared with the irradiation of the PI. Further studies trying to elucidate the influence of the suggested risk factors for RF have to be performed to stablish a consensus about the indications and contraindications of this reconstructive modality.
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 | 0.021 | 0.036 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.069 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".