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Abstract P6-09-20: Clinical utility of PgR with various cutpoints using 3 commercial assays relative to 15yr survival

2017· article· en· W2591741565 on OpenAlexaffabout
EN Kornaga, Xiaobin Feng, DG Morris, A. M. Magliocco, AC Klimowicz

Bibliographic record

VenueCancer Research · 2017
Typearticle
Languageen
FieldMedicine
TopicAdvanced Breast Cancer Therapies
Canadian institutionsBC Cancer AgencyUniversity of British ColumbiaAlberta Health Services
Fundersnot available
KeywordsTamoxifenMedicineBreast cancerOncologyCohortInternal medicineCancerImmunohistochemistryHormonal therapyEstrogen receptorAdjuvant therapyEstrogenGynecology

Abstract

fetched live from OpenAlex

Abstract Introduction: Hormone receptors ER and PgR are routinely assessed by pathologists using immunohistochemical (IHC) assays to guide treatment decisions. Patients who are hormone receptor positive are offered hormonal therapy, such as tamoxifen, which improves survival. Although both ER and PgR are evaluated, ER is primarily utilized for patient management as the clinical utility of PgR has not been clearly established according to CAP/ASCO guidelines. Notably, a meta-analysis by the Early Breast Cancer Trialists' Collaborative Group reported that PgR status was not significantly predictive of response to adjuvant tamoxifen, suggesting that PgR may not have a role in breast cancer management. More recently, the level of PgR expression has been hypothesized to be important in predicting response to endocrine therapy, where high PgR levels are more indicative of estrogen-dependent tumors, and thus more sensitive to hormonal treatment. In this study, we evaluate PgR expression using the current cut-point (Allred>2), as well as an optimized cut-point (Allred>5 to identify PgR high tumors), with regards to 15yr disease-free survival (DFS) and disease-specific overall survival (DSOS) using three commercially available ready-to-use (RTU) IHC assays from Dako, Leica and Ventana in an ER+ cohort. Methods: The Calgary tamoxifen breast cancer cohort (Calgary cohort) is a TMA series that includes 532 patients diagnosed with primary breast cancer (1985-2000) who received tamoxifen treatment regardless of hormone receptor status. All RTU assays followed vendor recommended protocols. Specific details regarding the cohort and IHC assays have been previously described (Kornaga et al. Mod Path 2016). All analyses were performed using Stata 12, and multivariate models were adjusted for age, grade, size, lymph node and HER2 status. ER status was defined by the corresponding vendor specific IHC assay. Results: Multivariate models looking at DFS are presented in Table 1. None of the assays were significant when the clinical cut-point was used; however, when the optimized cut-point was investigated, all assays found high expression of PgR was significantly associated with improved DFS. Table 2 presents the multivariate models looking at DSOS. Similarly, PgR was not found to be associated with improved DSOS using the current cut-point. When the optimized cut-point was examined, Dako and Leica assays were significantly associated with improved DSOS: The Ventana assay did not reach significance. Table 1 PgR15YR DFS CutpointHR95% CIp-valueDako>20.830.40-1.730.624Dako>50.560.35-0.910.020Leica>21.130.45-2.830.792Leica>50.520.30-0.890.017Ventana>20.730.32-1.670.460Ventana>50.570.34-0.970.037 Table 2 PgR15YR DSOS CutpointHR95% CIp-valueDako>20.740.33-1.650.464Dako>50.550.32-0.950.031Leica>20.880.35-2.220.780Leica>50.440.24-0.790.006Ventana>20.590.25-1.370.218Ventana>50.630.35-1.150.134 Conclusions: High PgR expression (Allred>5) is associated with improved 15yr DFS and DSOS in a tamoxifen-treated cohort, where PgR positivity defined using current guidelines is not associated with improved DFS or DSOS. Additionally, differences were noted between the vendor RTU assays with regards to DSOS. Citation Format: Kornaga EN, Paterson AHG, Feng X, Morris DG, Magliocco AM, Klimowicz AC. Clinical utility of PgR with various cutpoints using 3 commercial assays relative to 15yr survival [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P6-09-20.

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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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.245
Threshold uncertainty score0.743

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.346
GPT teacher head0.553
Teacher spread0.206 · 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 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
Published2017
Admission routes2
Has abstractyes

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