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Record W4395466551 · doi:10.1001/jamaoncol.2024.0578

Omission of Axillary Dissection Following Nodal Downstaging With Neoadjuvant Chemotherapy

2024· article· en· W4395466551 on OpenAlexaff
Giacomo Montagna, Mary M. Mrdutt, Susie X. Sun, Callie Hlavin, Emilia J. Diego, Stephanie M. Wong, Andrea V. Barrio, Astrid Botty van den Bruele, Neslihan Cabıoğlu, Varadan Sevilimedu, Laura H. Rosenberger, E. Shelley Hwang, Abigail Ingham, Bärbel Papassotiropoulos, Bich Doan Nguyen-Sträuli, Christian Kurzeder, Danilo Díaz Aybar, Denise Vorburger, Dieter Michael Matlac, Edvin Ostapenko, Fabian Riedel, Florian Fitzal, Francesco Meani, Franziska Fick, Jacqueline Sagasser, Hasan Karanlık, Konstantin J. Dedes, László Romics, Maggie Banys‐Paluchowski, Mahmut Müslümanoğlu, María del Rosario Cueva Pérez, Marcelo Chávez Díaz, Martin Heidinger, Mathias K. Fehr, Mattea Reinisch, Mustafa Tükenmez, Nadia Maggi, Nicola Rocco, Nina Ditsch, Oreste ­Gentilini, Régis Resende Paulinelli, Sebastián Solé Zarhi, Sherko Küemmel, S. Bruz̆as, Simona Di Lascio, Tamara K. Parissenti, Tanya L. Hoskin, Uwe Güth, Valentina Ovalle, Christoph Tausch, Henry M. Kuerer, Abigail S. Caudle, Jean-François Boileau, Judy C. Boughey, Thorsten Kühn, Monica Morrow, William P. Weber

Bibliographic record

VenueJAMA Oncology · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBreast Cancer Treatment Studies
Canadian institutionsMcGill UniversityJewish General Hospital
FundersNational Cancer InstituteDipartimento di Scienze Biomediche Avanzate, Università degli Studi di Napoli Federico II
KeywordsMedicineAxillary Lymph Node DissectionBreast cancerSentinel lymph nodeBiopsyAxillaNeoadjuvant therapyRetrospective cohort studyStage (stratigraphy)SurgeryDissection (medical)Lymph nodeRadiologyCancerInternal medicine

Abstract

fetched live from OpenAlex

Importance: Data on oncological outcomes after omission of axillary lymph node dissection (ALND) in patients with breast cancer that downstages from node positive to negative with neoadjuvant chemotherapy are sparse. Additionally, the best axillary surgical staging technique in this scenario is unknown. Objective: To investigate oncological outcomes after sentinel lymph node biopsy (SLNB) with dual-tracer mapping or targeted axillary dissection (TAD), which combines SLNB with localization and retrieval of the clipped lymph node. Design, Setting, and Participants: In this multicenter retrospective cohort study that was conducted at 25 centers in 11 countries, 1144 patients with consecutive stage II to III biopsy-proven node-positive breast cancer were included between April 2013 and December 2020. The cumulative incidence rates of axillary, locoregional, and any invasive (locoregional or distant) recurrence were determined by competing risk analysis. Exposure: Omission of ALND after SLNB or TAD. Main Outcomes and Measures: The primary end points were the 3-year and 5-year rates of any axillary recurrence. Secondary end points included locoregional recurrence, any invasive (locoregional and distant) recurrence, and the number of lymph nodes removed. Results: A total of 1144 patients (median [IQR] age, 50 [41-59] years; 78 [6.8%] Asian, 105 [9.2%] Black, 102 [8.9%] Hispanic, and 816 [71.0%] White individuals; 666 SLNB [58.2%] and 478 TAD [41.8%]) were included. A total of 1060 patients (93%) had N1 disease, 619 (54%) had ERBB2 (formerly HER2)-positive illness, and 758 (66%) had a breast pathologic complete response. TAD patients were more likely to receive nodal radiation therapy (85% vs 78%; P = .01). The clipped node was successfully retrieved in 97% of TAD cases and 86% of SLNB cases (without localization). The mean (SD) number of sentinel lymph nodes retrieved was 3 (2) vs 4 (2) (P < .001), and the mean (SD) number of total lymph nodes removed was 3.95 (1.97) vs 4.44 (2.04) (P < .001) in the TAD and SLNB groups, respectively. The 5-year rates of any axillary, locoregional, and any invasive recurrence in the entire cohort were 1.0% (95% CI, 0.49%-2.0%), 2.7% (95% CI, 1.6%-4.1%), and 10% (95% CI, 8.3%-13%), respectively. The 3-year cumulative incidence of axillary recurrence did not differ between TAD and SLNB (0.5% vs 0.8%; P = .55). Conclusions and Relevance: The results of this cohort study showed that axillary recurrence was rare in this setting and was not significantly lower after TAD vs SLNB. These results support omission of ALND in this population.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.434
Threshold uncertainty score0.398

Codex and Gemma teacher scores by category

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

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 head0.005
GPT teacher head0.279
Teacher spread0.274 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations86
Published2024
Admission routes1
Has abstractyes

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