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SP46. Incidental Breast Carcinoma In Reduction Mammoplasty: A Systematic Review

2024· review· en· W4395027548 on OpenAlexaboutno aff
Ronald K. Akiki, Jung Ho Gong, Rachel Sullivan

Bibliographic record

VenuePlastic & Reconstructive Surgery Global Open · 2024
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBreast Cancer Treatment Studies
Canadian institutionsnot available
Fundersnot available
KeywordsReduction MammoplastyMammoplastyBreast reductionBreast carcinomaMedicineReduction (mathematics)CarcinomaGeneral surgeryOncologySurgeryInternal medicineMammaplastyBreast cancerCancerMathematics

Abstract

fetched live from OpenAlex

Purpose: An estimated 534,284 breast reductions were performed worldwide in 2018. Occult histopathological findings of breast cancer in reduction mammoplasty specimens are rare but well documented in the literature. It has been a conventional practice for surgeons to obtain imaging studies prior to the reduction mammoplasty procedure. This practice aims to establish a radiological baseline of the breasts and detect occult pathological lesions before surgical intervention. Recent studies, however, have shown that preoperative imaging leads to an increasing number of false positive results and unnecessary diagnostic workups for the patient.The goal of this study was to conduct a systematic review to summarize the available literature on the incidence of occult breast carcinoma identified in patients undergoing non-oncologic reduction mammoplasty. Methods: A systematic review of all studies on the incidence of breast carcinoma in patients undergoing breast reduction was performed using PRISMA guidelines. Two databases were queried for randomized clinical trials, cohort studies, and retrospective studies. Two reviewers completed screening, data collection, and quality assessment. The Newcastle-Ottawa scale and JBI Critical Appraisal Checklist were used to assess methodological quality. Data extracted included the presence or absence of preoperative screening for breast cancer, sample size, age, pre-operative or intraoperative findings, and study recommendations. Results: A total of 328 articles were identified through a literature search. After the removal of duplicates, a total of 206 studies were screened. A final tally of 20 studies met our inclusion criteria, reporting on the incidence of breast carcinoma in reduction mammoplasty specimens. 18 studies were retrospective and 2 were prospective. All 20 studies used a routine intraoperative histopathologic examination of breast reduction specimens. 12 studies had patients undergo pre-operative imaging prior to reduction, 6 studies had only higher-risk patients undergo preoperative imaging (e.g. higher age, positive family history), and 2 studies had no pre-operative imaging. On histopathological evaluation, the incidence of breast carcinoma ranged from 0% to 1.6%. Most studies (19/20) found no correlation between preoperative imaging and histopathological diagnosis of breast carcinoma. One multicenter study of 5781 patients recommended preoperative imaging to be routinely performed in patients scheduled for non-oncologic reduction mammoplasty. They found a rate of 12.7% radiologically suspect findings, of which 1.3% were biopsy-confirmed malignancies. All studies recommended histopathological evaluation of breast reduction specimens. Conclusion: Our review demonstrates that histopathological evaluation of breast reduction specimens is widely recommended and used despite the small incidence of occult breast carcinoma findings. The current literature remains non-unanimous regarding routine preoperative imaging in patients undergoing reduction mammaplasty. Further studies are needed to confirm the role of preoperative imaging in patients undergoing reduction mammaplasty.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.092
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.026
GPT teacher head0.314
Teacher spread0.288 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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