MétaCan
Menu
Back to cohort

Perioperative immunochemotherapy (mDCF + avelumab) in locally advanced gastro-esophageal adenocarcinoma: A phase II trial.

2023· article· en· W4379282230 on OpenAlexaff
Thierry Alcindor, Pierre Fiset, Touhid Opu, Mehrnoush Dehghani, Nicholas Bertos, Carmen Mueller, Jonathan Cools‐Lartigue, Marc Hickeson, Victoria Marcus, Sophie Camilleri‐Broët, Alan Spatz, Gertruda Evaristo, Mina Farag, Giovanni Artho, Arielle Elkrief, Ramy Saleh, Veena Sangwan, Lorenzo Ferri

Bibliographic record

VenueJournal of Clinical Oncology · 2023
Typearticle
Languageen
FieldMedicine
TopicGastric Cancer Management and Outcomes
Canadian institutionsMcGill UniversityMcGill University Health Centre
Fundersnot available
KeywordsMedicineInternal medicineAdenocarcinomaDocetaxelPerioperativeGastroenterologyClinical endpointChemotherapyEsophageal cancerSurgeryCancerOncologyClinical trial

Abstract

fetched live from OpenAlex

4055 Background: Perioperative chemotherapy improves cure rate in locally advanced gastro-esophageal adenocarcinoma (GEA). Immune checkpoint inhibitors have activity in GEA. This trial is testing the hypothesis that the addition of avelumab, an anti-PD-L1 antibody, to perioperative mDCF chemotherapy, will increase the pathologic complete response (pCR) rate, a potential surrogate for overall survival, in comparison with a historical pCR rate of 7%. Methods: Single-arm phase II study (NCT03288350) of avelumab + chemotherapy (modified docetaxel/cisplatin/5-FU or mDCF) given every 2 weeks x 4 cycles before and after surgery. Planned sample size of 50 operated patients. The hypothesis cannot be refuted if ≥6 patients show pCR, the primary endpoint. Inclusion criteria: histologically proven GEA, locally advanced disease (cT3-4 and/or N+), adequate organ function, WHO performance status 0-1. Exclusion criteria: other histology, metastatic stage, use of immunosuppressants, serious autoimmune disease, intake >10 mg prednisone/d. Adverse effects prospectively recorded per NCI CTCAE guidelines. Pathological response and tumor regression grade (TRG) determined by CAP criteria: 0=complete;1=near complete; 2=moderate; 3 = poor/no response. Data presented as median (range), KM determined survival. Results: Study accrual completed August 2022: 51 patients enrolled, 45 M/6 F, age 64 (18-79), ECOG 0 (35) and 1 (16). One patient withdrew consent after 2 treatment cycles and is excluded from efficacy analysis. Tumor anatomic site: Esophagus =19(38%)/gastroesophageal junction 21(42%)/subcardia stomach 10(20%). Staging: cT3 (88%), cT4 (6%), N+ (62%). Histology: all adenocarcinoma; dMMR 9/50 in 18%; CPS<1, 1-5, 6-10, >10 in 0%/33%/27%/40% of tumors tested. All 4 pre-operative cycles administered to 48/50 (96%); 36/50 received ≥2 adjuvant treatment cycles and 23/50 (46%) received all 8 cycles. Grade 3-4 toxicity events from neoadjuvant therapy affected: GI tract (diarrhea 4%); respiratory system (pneumonia 4%); endocrine system (adrenal insufficiency 2%). Other common side effects (grades 1-2, incidence > 15%) were: fatigue, diarrhea, skin rash/pruritus. Post-operative mortality at 30 and 90 days was 0/50 (0%) and 1/50 (2%). R0 resection was achieved in 48/50 (96%); a median of 36 (13-78) lymph nodes were resected. Pathological response was TRG 0/1/2/3 in 7/2/16/25 with pCR seen in 7 (14%), meeting the primary endpoint. Major pathologic response (TRG 0 and 1) was seen in 9 (18%), but without correlation with CPS or dMMR biomarker status. At 37.5 (9-71) months follow up, overall survival at 1, 2, and 3 years is 93.6%, 75.7%, and 69.2%. MPR showed a trend to improved survival ( p = 0.06). Conclusions: The neoadjuvant combination of avelumab with chemotherapy (mDCF) shows promising safety and efficacy in gastroesophageal adenocarcinoma, without obvious correlation to known biomarkers. Clinical trial information: NCT03288350 .

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.102
GPT teacher head0.479
Teacher spread0.378 · 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 designNon-randomized trial
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".

Quick stats

Citations3
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Clinical OncologySame topicGastric Cancer Management and OutcomesFrench-language works237,207