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Record W4238109377 · doi:10.1093/jnci/djw105

Response

2016· letter· en· W4238109377 on OpenAlexaff
Maureen Trudeau

Bibliographic record

VenueJNCI Journal of the National Cancer Institute · 2016
Typeletter
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsSunnybrook Health Science Centre
Fundersnot available
KeywordsBiologyMedicine

Abstract

fetched live from OpenAlex

We thank Toomey and colleagues from the Royal College of Surgeons of Ireland for submitting their observations related to use of the RNA Disruption Assay (RDA) in the early prediction of pathological complete response (pCR) outcomes in the TCHL (docetaxel, carboplatin, trastuzumab +/- lapatinib) phase II clinical trial (1). Their work supports RDA as a biomarker for pCR in human epidermal growth factor receptor 2 (HER2)–positive breast cancer. They independently show that high RDA scores obtained from core biopsies taken 20 days after the first dose of chemotherapy plus targeted therapy correlate with significantly higher chance of pCR. As well, tumor content from these biopsies was significantly less for the patients who later achieved pCR. In our previous work, we have shown that tumor cellularity at mid-treatment biopsy did not correlate with eventual pCR (2); however, these differences may be due, as Toomey et al. point out, to the rapid response to anti-HER2 therapy in HER2-positive disease compared with other receptor subtypes. In the MA22 National Cancer Institute of Canada Clinical Trials Group phase II trial of combined epirubicin and docetaxel in locally advanced breast cancer (3,4), patients with high tumor RDA scores achieved better long-term disease-free survival regardless of receptor status or whether pCR was achieved. Using RDA, tumors can be divided into three categories—those with high, mid, or low tumor RNA disruption. We hypothesize that those tumors with low disruption are unlikely to respond to the treatment being given. These patients may benefit from an early change in treatment strategy, an idea that warrants further investigation. In unpublished data, RDA scores can be measured in breast cancer early in the first cycle of chemotherapy by fine needle aspiration (FNA), again with correlation of high RDA and pCR. This observation was obtained in a single center, and we are currently carrying out a multicenter trial to confirm the correlation. Although core biopsy material can be used, FNA carried out in the clinic setting may enable widespread use of this simple, inexpensive modality to easily obtain tissue with little morbidity for the patient. In the search for response-guided therapy in primary systemic therapy, RDA warrants further investigation as a potential candidate with both prognostic and predictive benefits. Women with breast cancer will benefit from the knowledge that their treatment is effective and if not will benefit perhaps from a switch in therapy and avoidance of further side effects from ineffective treatment.

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)0.002
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.975
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.019
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0040.002
Scholarly communication0.0040.002
Open science0.0020.002
Research integrity0.0400.029
Insufficient payload (model declined to judge)0.0250.017

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 head0.040
GPT teacher head0.331
Teacher spread0.291 · 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.

Study designNot applicable
Domainnot available
GenreCommentary

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

Citations2
Published2016
Admission routes1
Has abstractno

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