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Record W2909180257 · doi:10.1177/1533033818821104

Intraoperative Assessment of Sentinel Lymph Nodes in Breast Cancer Patients Post-Neoadjuvant Therapy

2019· article· en· W2909180257 on OpenAlexaff
W. Douglas Wong, Illana Rubenchik, Sharon Nofech‐Mozes, Elzbieta Slodkowska, Carlos Parra‐Herran, Wedad Hanna, Fang‐I Lu

Bibliographic record

VenueTechnology in Cancer Research & Treatment · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBreast Cancer Treatment Studies
Canadian institutionsHealth Sciences CentreSunnybrook Health Science CentreNorth York General HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineBreast cancerNeoadjuvant therapyLymphSentinel lymph nodeCancerOncologyRadiologyInternal medicinePathology

Abstract

fetched live from OpenAlex

BACKGROUND: Shift toward minimizing axillary lymph node dissection in patients with breast cancer post neoadjuvant therapy has led to the assessment of sentinel lymph nodes by frozen section intraoperatively to determine the need for axillary lymph node dissection. However, few studies have examined the accuracy of sentinel lymph node frozen section after neoadjuvant therapy. Our objective is to compare the accuracy of sentinel lymph node frozen section in patients with breast cancer with and without neoadjuvant therapy and to identify features that may influence accuracy. DESIGN: We identified 161 sentinel lymph node frozen section from 77 neoadjuvant therapy patients and 255 sentinel lymph node frozen section from 88 non-neoadjuvant therapy patients diagnosed between 2010 and 2016 in 2 institutions. The frozen section diagnoses were compared to the final diagnoses, and clinicopathologic data were analyzed. RESULTS: The sensitivity, specificity, and accuracy of frozen section analysis were comparable between neoadjuvant therapy patients and non-neoadjuvant therapy patients (71.9% vs 50%, 100% vs 100%, and 88.3% vs 81.8%). Nine (11.7%) of 77 neoadjuvant therapy patients had discordant results, most often due to undersampling (tumor absent on frozen section slide). Four of these patients subsequently underwent axillary lymph node dissection. Discordant results (all false negatives) were significantly more likely in neoadjuvant therapy patients with Estrogen Receptor-positive/HER2-negative status, and in sentinel lymph node with pN1mic and pN0i+ deposits; age, preneoadjuvant therapy lymph node status, histotype, nuclear grade, tumor size, and response to neoadjuvant therapy showed no significant differences. For non-neoadjuvant therapy cases, large tumor size, lobular histotype, and sentinel lymph node with pN1mic and pN0i+ were associated with false-negative frozen section assessment. CONCLUSION: Sentinel lymph node frozen section diagnosis post-neoadjuvant therapy has comparable sensitivity, specificity, and accuracy to the sentinel lymph node frozen section diagnosis in the non-neoadjuvant therapy setting.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.389
Teacher spread0.366 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations11
Published2019
Admission routes1
Has abstractyes

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