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Abstract P2-03-12: Incidence and implications for hormone receptor status change pre- and post- neoadjuvant chemotherapy for locally advanced breast cancer: A retrospective single-center cohort study

2018· article· en· W2791287855 on OpenAlexaffabout
O. Aseyev, L. Simmonds, Menard M. Gertler, Santosh K. Verma

Bibliographic record

VenueCancer Research · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBreast Cancer Treatment Studies
Canadian institutionsNOSM UniversityOttawa HospitalThunder Bay Regional Health Sciences CentreUniversity of Ottawa
Fundersnot available
KeywordsMedicineBreast cancerInternal medicineOncologyChemotherapyCancerIncidence (geometry)Logistic regressionEstrogen receptorHormone receptorStatistical significanceCohort

Abstract

fetched live from OpenAlex

Abstract Background: Hormone receptors (HR) and Human Epidermal Growth Factor Receptor 2 (HER2) status are variables that significantly influence the treatment regimens chosen for each patient (pt). The main objective of this study present was to determine the incidence of HR status change pre- and post- neoadjuvant chemotherapy (NAC) in patients with locally advanced breast cancer (LABC). Methods: A single-centre study was retrospectively conducted at The Ottawa Hospital Cancer Centre looking at a group of 546 pts diagnosed with LABC from 2006-2015. A number of variables were observed including HR and HER2 status, tumor size and grade, regional lymph nodes involvement, presence of DCIS, treatment regimens. 'Positive to Negative' considered pts who were HR and/or HER2 positive pre-NAC and negative post-NAC, 'No Change' represented the pts whose pathology did not change before and after NAC, and 'Negative to Positive' characterized those pts whose HR and/or HER2 pathology was initially negative and became positive post-NAC. Wilcoxon signed-rank test for paired dichotomous variables has been performed in order to estimate statistical significance of changes in status of HR and HER2. To explore possible relationship between HR and HER2 status change and other factors we used Logistic regression method. Results: Of the 386 pts who were examined for Estrogen Receptor (ER) twice, 285 had positive status before surgery, after surgery there were 12 pts (3.11%*) with a 'Positive to Negative' change, 362 pts (93.78%) with no change, and 12 pts who represented a 'Negative to Positive' change. 254 of 378 pts, who had two tests for Progesterone Receptor (PR), had positive results at first time, and 29 (7.67%*) of those represented a 'Positive to Negative' change, there were 337 (89.15%) with no change, and 12 (3.17%) with a 'Negative to Positive' change. From 387 pts who were tested for HER2 before and after surgery, 105 had initially positive status. Of those, 12 (3.10%*) represented a 'Positive to Negative' change, there were 364 (94.06%) with 'No Change' and 11 (2.84%*) with a 'Negative to Positive' change. Logistic regression analysis did not reveal any significant factors that can predict changes in receptors` status. *-Statistically significant changes (p<0.001). The results are comparable with previously published works, which demonstrated changes in IHC status during treatment in metastatic disease (E.Amir, 2011) and a in patients with LABC (Y.Yang, 2013; R.Gahlaut, 2016). Results of comparative meta-analysis will be presented also. Conclusions: Our study shows that a change in HR and HER2 status is common in this population, indicating that close monitoring of biopsy results should be closely compared to surgical pathology specimens to determine a change in biomarkers, and therefore, a potential change in treatment regimen. None of analyzed factors can predict change in status of ER, PR, and HER2 after neoadjuvant treatment. Even though the incidence of change in status is small, the implications for accurate and personalized treatment are important and HR and HER2 testing should be performed as a routine practice on the biopsy and at the time of definitive surgery. Citation Format: Aseyev O, Simmonds L, Gertler M, Verma S. Incidence and implications for hormone receptor status change pre- and post- neoadjuvant chemotherapy for locally advanced breast cancer: A retrospective single-center cohort study [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P2-03-12.

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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)0.001
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 score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.036
GPT teacher head0.377
Teacher spread0.341 · 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".

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Citations0
Published2018
Admission routes2
Has abstractyes

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