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Docetaxel-based triplet neoadjuvant therapy for esophageal adenocarcinoma: A comprehensive analysis of outcomes spanning over a decade.

2023· article· en· W4317863022 on OpenAlexaff
James Tankel, Nabeel Ahmed, Thierry Alcindor, Jamil Asselah, Petr Kavan, Frédéric Lemay, Dominique A. Frechette, Shelly Sud, L. Lee, Sara Najmeh, Jonathan Spicer, Jonathan Cools‐Lartigue, Carmen Mueller, Lorenzo Ferri

Bibliographic record

VenueJournal of Clinical Oncology · 2023
Typearticle
Languageen
FieldMedicine
TopicEsophageal Cancer Research and Treatment
Canadian institutionsCentre Intégré de Santé et de Services Sociaux des LaurentidesJewish General HospitalCentre Hospitalier Universitaire de SherbrookeMcGill University Health CentreCentre intégré de santé et de services sociaux de Chaudière-AppalachesMcGill University
Fundersnot available
KeywordsDocetaxelMedicineNeoadjuvant therapyOxaliplatinEsophageal cancerInternal medicineRegimenOncologyTaxaneEsophagectomyChemotherapyAdenocarcinomaCancerGastroenterologyColorectal cancer

Abstract

fetched live from OpenAlex

332 Background: Docetaxel-based therapy is currently the most effective neoadjuvant regimen for locally advanced gastroesophageal adenocarcinoma. However, prior trials were primarily designed to target gastric cancer. As survival associated with taxane-based chemotherapy in esophageal adenocarcinoma (EAC) is less well described, we sought to review our experience with docetaxel based therapy as a neoadjuvant approach for EAC. Methods: A single centre retrospective review of a prospectively maintained upper GI cancer surgical database was performed (2008-2021). Patients with EAC undergoing curative intent neoadjuvant therapy with two similar docetaxel-based regimens (DCF - Docetaxel/Cisplatin/5FU or FLOT - 5FU, Leucovorin, Oxaliplatin, and Docetaxel) followed by en-bloc resection were included. Gastric/EGJ type III tumors were excluded. Clinicopathological data and overall survival (OS) were recorded and stratified by chemotherapy type (DCF vs FLOT). Data are presented as median (+/-SD). Mann-Whitney U tests for continuous or Fischer exact test for categorical variables determined significance. Kaplan-Meier curves compared OS. Results: 225 EAC patients were identified: Age 64.2 (±10.3) and tumor location was Esophageal/EGJ I/EGJ II (106/33/86). Clinical stage was cT3-4 in 201/225 (89.3%) and most were cN+ (200/225: 88.9%). There were 121 (53.7%) treated with neoadjuvant DCF whilst 104 (46.3%) received FLOT. All pre-op cycles were completed in 181 (80.4%) and did not differ between DCF and FLOT (81.8% vs 78.8% - NS). Operative procedure included Ivor Lewis in 188 (83.5%), left thoraco-abdominal esophagectomy in 20 (8.8%), and McKeown in 17 (7.5%) and also did not differ between DCF and FLOT. In terms of pathologic outcomes, the median lymph node yield was 35 (±16) of which 3.6±5.8 were positive). There was no difference when comparing between regimens. There were 134 (59.6%) patients ypN1-3 (DCF=76(62.8%) vs FLOT=58(55.8%)- NS). An R0 resection was achieved in 210 (93%) patients (DCF=92.6% vs FLOT=94.2%- NS). Complete pathological response (no residual cancer) was found in 21 patients (9.3%) (DCF=14(11.6%) vs FLOT=7(6.7%) – NS). At follow up of 41(±36) months (DCF= 52±41 vs FLOT=27±23 - p<0.001) OS (KM curve Fig 1) at 1, 3 and 5 years for the entire cohort was 91.4%, 62.8%, and 55.7%, with no difference between DCF (92.3%/68.8%/59.5%) and FLOT (89.8%/54.5%/51.7% - NS). Conclusions: This retrospective review, the largest yet reported, demonstrates that these similar docetaxel-based neoadjuvant chemotherapy regimens are highly effective for patients with locally advanced esophageal adenocarcinoma.

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)0.001
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
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 head0.235
GPT teacher head0.537
Teacher spread0.302 · 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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Citations0
Published2023
Admission routes1
Has abstractyes

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