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Phase 1/2 randomized, open-label, multicenter, Simon two-stage study of pelareorep combined with modified FOLFIRINOX +/- atezolizumab in patients with metastatic pancreatic ductal adenocarcinoma.

2024· article· en· W4400272924 on OpenAlexaff
Dirk Arnold, Houra Loghmani, Karol Cheetham, Richard Trauger, Thomas C. Heineman

Bibliographic record

VenueJournal of Clinical Oncology · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Research and Treatments
Canadian institutionsOncolytics Biotech (Canada)
Fundersnot available
KeywordsMedicineFOLFIRINOXAtezolizumabPancreatic ductal adenocarcinomaOncologyInternal medicineOpen labelStage (stratigraphy)Pancreatic cancerRandomized controlled trialOxaliplatinCancerNivolumabColorectal cancerImmunotherapy

Abstract

fetched live from OpenAlex

TPS4203 Background: Immune therapies benefit only the small subset of metastatic pancreatic ductal adenocarcinoma (mPDAC) patients who have microsatellite instability-high (MSI-H) tumors (approximately 1%). Most PDAC tumors are microsatellite stable (MSS) and have an immunologically “cold” phenotype with fewer genetic mutations, reduced immune cell infiltration, and downregulated immune checkpoint proteins. These attributes make most mPDAC tumors resistant to conventional immunotherapy including checkpoint inhibitors. Pelareorep is a naturally occurring, non-genetically modified reovirus that selectively infects cancer cells following intravenous administration. Upon infection, pelareorep’s double-stranded RNA genome stimulates a pro-inflammatory response that primes tumors for immunologic killing. This includes increased T cell infiltration into tumors, expansion of tumor-infiltrating lymphocyte clones, increased PD-L1 expression, and stimulation of tumor-directed innate and adaptive immune responses. Pelareorep combined with chemotherapy, checkpoint inhibitors, or both has shown promising efficacy in several malignancies, including mPDAC. This study is designed to evaluate pelareorep plus modified FOLFIRINOX with or without the PD-L1 inhibitor atezolizumab as first-line therapy in patients with mPDAC. Methods: This trial represents a new cohort within the ongoing GOBLET signal finding platform study in gastrointestinal cancers. This is a phase 1/2 randomized, open-label study that uses a screened selection design within a Simon two-stage approach. Eligible patients must be 18 years or older and have newly diagnosed, radiologically evaluable mPDAC with no prior chemotherapy and an ECOG performance status of 0 or 1. Patients are randomized 1:1 to receive either pelareorep + mFOLFIRINOX orpelareorep + mFOLFIRINOX + atezolizumab. The first stage enrolls 15 evaluable patients into each arm. If pre-specified efficacy criteria are met in Stage 1, one or both arms may be expanded to Stage 2 and enroll 17 additional evaluable patients per arm. The first 3-6 patients enrolled into both arms comprise a safety run-in that must be successfully concluded prior to enrolling additional patients. The treatment period consists of 4-week treatment cycles. The primary objectives are 1) safety and tolerability of pelareorep + mFOLFIRINOX with or without atezolizumab and 2) efficacy based on objective response rate per RECIST v1.1. Secondary objectives include duration of response, progression-free survival, and overall survival. In addition, tumor and blood samples are being collected to evaluate the immunological effects of treatment and to explore potential biomarkers of response. Clinical trial information: Eudra-CT: 2020-003996-16.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0070.002

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 head0.088
GPT teacher head0.464
Teacher spread0.376 · 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 designRandomized 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

Citations2
Published2024
Admission routes1
Has abstractyes

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