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Circulating tumor DNA detection after neoadjuvant chemotherapy and prediction of distant relapse free survival, local recurrence, and distant recurrence in triple-negative breast cancer in the TRICIA study.

2024· article· en· W4400523166 on OpenAlexaff
Adriana Aguilar, Talia Roseshter, Anna Klemantovich, Luca Cavallone, Josiane Lafleur, Cathy Lan, Oluwadara Elebute, Sarah Jenna, Suzan McNamara, Jean-François Boileau, Manuela Pelmus, Rossanna C. Pezo, Muriel Brackstone, Terry L. Ng, Mark Basik

Bibliographic record

VenueJournal of Clinical Oncology · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Genomics and Diagnostics
Canadian institutionsOttawa HospitalSunnybrook Health Science CentreHealth Sciences CentreMcGill UniversityLondon Health Sciences CentreJewish General Hospital
Fundersnot available
KeywordsMedicineTriple-negative breast cancerBreast cancerChemotherapyOncologyInternal medicineDistant metastasisTriple negativeNeoadjuvant therapyComplete responseCancerRadiologyMetastasis

Abstract

fetched live from OpenAlex

610 Background: Patients with triple negative breast cancer who have a residual tumor at surgery (non-pCR) following neoadjuvant chemotherapy (NAC) have a very poor prognosis. Additional adjuvant capecitabine improves relapse-free survival (RFS) by 15%. There is a need for biomarkers to identify patients who may not require adjuvant capecitabine. The TRICIA trial (NCT04874064) accrued non-pCR TNBC patients for ctDNA measurements at pre-operative (T1), post-operative (T2), 3-month (T3) and 6-month (T4) time points using hospital-based tumor-specific personalized assays. Methods: Whole exome sequencing was performed on FFPE TNBC residual tumors or biopsies to select 5 variants/patient for Digital droplet PCR (ddPCR) assays. Patients with ≥1 detectable mutation were considered ctDNA positive. ctDNA detection was correlated with Relapse Free Survival (RFS), local recurrence, distal recurrence, overall survival (OS) and residual cancer burden (RCB) score. Results: 79 patients were recruited with a median follow-up of 32.9 months post-surgery. 32 of 79 patients relapsed and the median RFS for these patients was 8.7 months. The RCB score distribution was: 17 RCB1, 41 RCB2 and 21 RCB3. Of the 4 time points, ctDNA detection at T1 is the strongest prognostic factor for both RFS (HR=0.19, p<0.0001, 95% CI= 0.09 – 0.40) and OS (HR=0.19, p=0.0007, 95% CI= 0.08 – 0.5). 21/22 (95%) patients without detectable ctDNA at T1 did not have distant disease relapse, whereas 66% with detectable ctDNA (27/41) developed either local and/or distant disease relapse. The post-operative (T2) time point was not prognostic whereas the post-capecitabine time point (T4) was weakly prognostic. All 14 RCB3 patients that relapsed and had T1 plasma had detectable ctDNA at T1 while none of the 5 RCB3 patients without relapse had detectable ctDNA at T1. The one RCB1 patient with detectable ctDNA also relapsed. 53 patients received adjuvant capecitabine. ctDNA at T1 remained the strongest prognostic factor associated with RFS (HR=0.16, p<0.0001, 95% CI=0.06-0.4), with none of the ctDNA negative patients showing distant relapse. ctDNA clearance after Xeloda was not associated with prognosis. CtDNA was detectable at T1 in 3 of 4 patients who eventually developed local recurrence with a median lead time of 10 months. Detectable ctDNA was observed in 96% of patients (27/28) with distant recurrence and the median time from ctDNA appearance to recurrence was 9.1 months. Conclusions: A hospital-based tumor bespoke assay provides very strong prognostic information when performed after NAC and before surgery. Local and distant recurrence can both be predicted with a lead time of 9-10 months from the appearance of detectable ctDNA. These results validate the use of a hospital-based tumor bespoke platform for clinical testing. Clinical trial information: NCT04874064 .

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 score0.005

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 communication0.0010.000
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 head0.030
GPT teacher head0.363
Teacher spread0.333 · 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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Citations1
Published2024
Admission routes1
Has abstractyes

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