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Adjunctive statistical standardization of quantitated adjuvant ER and PgR in CCTG MA.27.

2024· article· en· W4399121921 on OpenAlexaff
Judy‐Anne W. Chapman, Jane Bayani, Sandip Sengupta, John MS Battlett, Tammy Piper, Mary Anne Quintayo, Shakeel Virk, Paul E. Goss, James N. Ingle, Matthew J. Ellis, George W. Sledge, G. Thomas Budd, Manuela Rabaglio, Vered Stearns, Edith A. Perez, Karen A. Gelmon, Timothy J. Whelan, L. E. Shepherd, Bingshu E. Chen, Karen J. Taylor

Bibliographic record

VenueJournal of Clinical Oncology · 2024
Typearticle
Languageen
FieldEngineering
TopicNon-Destructive Testing Techniques
Canadian institutionsMcMaster UniversityBC Cancer AgencyOntario Institute for Cancer ResearchQueen's University
Fundersnot available
KeywordsMedicineAdjuvantInternal medicineOncologyCancer research

Abstract

fetched live from OpenAlex

567 Background: We proposed adjunctive statistical standardization of quantitated ER and PgR to improve inter-laboratory comparability of biomarker results and therapeutic management of breast cancer. Methods: We utilized CCTG MA.27 (NCT00066573), an adjuvant phase III trial of exemestane versus anastrozole in postmenopausal women with ER+ and/or PgR+ tumours. IHC ER and PgR HSCORE and % positivity (%+) were centrally assessed by machine image quantitation, and each statistically standardized to mean of 0, standard deviation of 1 following Box-Cox variance stabilization transformations of square for ER; for PgR, 1.) natural logarithm (0.1 added to 0 HSCOREs and 0 %+), 2.) square root. The primary endpoint was STEEP distant disease-free survival (DDFS) at the longest trial follow-up of median 4.1 years; a secondary endpoint was event-free survival (EFS). Survival was described with Kaplan-Meier plots and tested with the univariate Wilcoxon (Peto-Prentice) test statistic. We examined cut-points at standard deviations about mean of 0 (<-1; (-1,0]; (0,1]; >1) and explored single cut-points. Cox multivariate regressions were adjusted for age, T and N stage, grade, lymphovascular invasion, treatment, and baseline patient demographics; 2-sided Wald tests had nominal significance if p<0.05. Results: Of the 7576 women accrued, 3048 women had machine-quantitated image analysis results: 2900 (95%) for ER; 2726 (89%) for PgR. Statistically standardized HSCORE and %+ units differentiated both univariate DDFS and EFS; DDFS was significantly different by ER levels (p<0.001) and PgR levels (p<0.001). In multivariable assessments, ER HSCORE and %+ were not significantly associated (p=0.52-0.88) with the DDFS primary endpoint in models with PgR, while higher PgR HSCORE and %+ had significantly better DDFS (p=.001, in all instances) in models with ER. Conclusions: DDFS was superior for patients with higher ER and PgR standardized units compared with those with HSCOREs and %+ <-1. The adjunctive statistical standardization of ER and PgR performed here is similar to that mandated for clinical practice by the World Health Organization for BMD. [Table: see text]

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.347
Threshold uncertainty score0.400

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.080
GPT teacher head0.446
Teacher spread0.367 · 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
Published2024
Admission routes1
Has abstractyes

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