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Record W2970862661 · doi:10.1093/jncics/pkz063

PTHrP, A Biomarker for CNS Metastasis in Triple-Negative Breast Cancer and Selection for Adjuvant Chemotherapy in Node-Negative Disease

2019· article· en· W2970862661 on OpenAlexafffund
Gloria Assaker, Anne Camirand, Bassam Abdulkarim, Atilla Ömeroğlu, Jean Deschênes, Kurian Joseph, Abu Shadat Mohammod Noman, Agnihotram V Ramana Kumar, Richard Kremer, Siham Sabri

Bibliographic record

VenueJNCI Cancer Spectrum · 2019
Typearticle
Languageen
FieldMedicine
TopicBone health and treatments
Canadian institutionsMcGill UniversityUniversity of AlbertaMcGill University Health Centre
FundersFondation de l'Hôpital Général de MontréalJewish General HospitalUniversity of ChittagongAlberta Cancer FoundationMcGill University Health CentreAmerican Association for Cancer ResearchMcGill UniversityU.S. Department of Defense
KeywordsMedicineBreast cancerOncologyTriple-negative breast cancerInternal medicineHazard ratioProportional hazards modelBiomarkerTrastuzumabCancerMetastasisUnivariate analysisConfidence intervalMultivariate analysisBiology

Abstract

fetched live from OpenAlex

Abstract Background Triple-negative breast cancer (TNBC) is characterized by poor prognosis and lack of targeted therapies and biomarkers to guide decisions on adjuvant chemotherapy. Parathyroid hormone-related protein (PTHrP) is frequently overexpressed in breast cancer and involved in proliferation and metastasis, two hallmarks of poor prognosis for node-negative breast cancer. We investigated the prognostic value of PTHrP with respect to organ-specific metastasis and nodal status in TNBC. Methods We assessed PTHrP expression using immunohistochemistry in a clinically annotated tissue microarray for a population-based study of 314 patients newly diagnosed with TNBC, then analyzed its correlation to progression and survival using Kaplan-Meier and Cox regression analyses. The Cancer Genome Atlas (TCGA) validation analysis was performed through Bioconductor. All statistical tests were two-sided. Results PTHrP overexpression (160 of 290 scorable cases, 55.2%) was statistically significantly associated in univariate analysis with decreased overall survival (OS) in our cohort (P = .0055) and The Cancer Genome Atlas (P = .0018) and decreased central nervous system (CNS)-progression-free survival (P = .0029). In multivariate analysis, PTHrP was a statistically significant independent prognostic factor for CNS-progression-free survival in TNBC (hazard ratio [HR] = 5.014, 95% confidence interval [CI] = 1.421 to 17.692, P = .0122) and for OS selectively in node-negative TNBC (HR = 2.423, 95% CI = 1.129 to 5.197, P = .0231). Strikingly, PTHrP emerged as the only statistically significant prognostic factor (HR = 2.576, 95% CI = 1.019 to 6.513, P = .0456) for OS of low-clinical risk node-negative patients who did not receive adjuvant chemotherapy. Conclusions PTHrP is a novel independent prognostic factor for CNS metastasis and adjuvant chemotherapy selection of low-clinical risk node-negative TNBC. Its predictive value needs to be prospectively assessed in clinical trials.

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)0.002
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 score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
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)0.0010.000

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 head0.021
GPT teacher head0.338
Teacher spread0.316 · 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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Citations20
Published2019
Admission routes2
Has abstractyes

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