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Surveillance Mammography following the Treatment of Primary Breast Cancer with Breast Reconstruction: A Systematic Review

2007· review· en· W1979317411 on OpenAlexaff
G Philip Barnsley, Eva Grunfeld, Doug Coyle, Lawrence Paszat

Bibliographic record

VenuePlastic & Reconstructive Surgery · 2007
Typereview
Languageen
FieldMedicine
TopicBreast Implant and Reconstruction
Canadian institutionsInstitute for Clinical Evaluative SciencesSunnybrook Health Science CentreNova Scotia Health AuthorityUniversity of OttawaDalhousie University
FundersNational Cancer Institute
KeywordsMedicineBreast cancerMammographyBreast reconstructionMastectomyCancerGynecologyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Both the prevalence of breast cancer and the number of breast cancer patients seeking breast reconstruction are increasing, highlighting the importance for evidence to direct the clinician in the follow-up of these patients. Current practice guidelines recommend surveillance mammography of the contralateral breast in all breast cancer patients, and of the ipsilateral breast in women treated with breast-conserving surgery. However, there are no guidelines specifically addressing the role of surveillance mammography for women who have undergone mastectomy and breast reconstruction. METHODS: A systematic review was conducted to identify studies specifically addressing the issue of surveillance mammography among women with breast reconstruction following treatment for primary breast cancer. RESULTS: This systematic review identified eight articles, consisting of case reports and case series, that address the issue of surveillance mammography of the ipsilateral breast in women with breast reconstruction. The articles demonstrated that certain local recurrences are able to be detected by surveillance mammography. CONCLUSION: This study has demonstrated the paucity of evidence and highlighted the need for further research to evaluate this issue.

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)0.000
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.603
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0090.003
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.030
GPT teacher head0.280
Teacher spread0.249 · 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

Citations36
Published2007
Admission routes1
Has abstractyes

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