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Early results of the PASS-01 trial: Pancreatic adenocarcinoma signature stratification for treatment-01.

2024· article· en· W4399452560 on OpenAlexaffabout
Jennifer J. Knox, Elizabeth M. Jaffee, Grainne M. O’Kane, Daniel A. King, Dan Laheru, Kenneth H. Yu, Kimberly Perez, Amber N. Habowski, Robert C. Grant, Sandra E. Fischer, Andrew J. Aguirre, Raymond Woo-Jun Jang, Craig Devoe, Eileen M. O’Reilly, Anna Dodd, Brian M. Wolpin, Xiang Y. Ye, Faiyaz Notta, Steven Gallinger, David A. Tuveson

Bibliographic record

VenueJournal of Clinical Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicPancreatic and Hepatic Oncology Research
Canadian institutionsToronto General HospitalUniversity Health NetworkPrincess Margaret Cancer CentreOntario Institute for Cancer ResearchUniversity of Toronto
FundersStand Up To CancerLustgarten Foundation
KeywordsMedicineAdenocarcinomaOncologyPancreatic cancerRisk stratificationInternal medicineStratification (seeds)Pancreatic ductal adenocarcinomaCancer

Abstract

fetched live from OpenAlex

LBA4004 Background: Over 60% of patients with pancreatic ductal adenocarcinoma (PDAC) present with metastatic disease. Both modified FOLFIRINOX (mFFX) and gemcitabine/nab-paclitaxel (GnP) are first-line options in advanced PDAC, however have not been compared prospectively in North American patients. Moreover, biomarkers to guide selection are lacking. Basal-like and Classical subtypes are prognostic, but their predictive impact is unknown. Patient-derived organoids (PDOs) are now feasible to study for drug pharmacotyping. Expedient molecular profiling with additional PDO drug sensitivities could enable better precision choices in PDAC. Methods: PASS-01 is a multi-center randomized phase II trial evaluating the benefit of 1 st line mFFX vs GnP in de novo metastatic PDAC patients with ECOG PS 0-1, (germline BRCA1/2, PALB2 excluded) who have baseline tumor biopsies (bx) for whole genome/transcriptional sequencing (WGTS) and PDO generation/pharmacotyping with standard and novel drugs. The primary endpoint is the PFS of mFFX vs GnP (received at least 1 dose of assigned chemo, per protocol (PP)), 136 patients needed to reach 80% power to detect a difference in median PFS of 7 vs 5 months between mFFX and GnP at significance level of 0.3 in a 2-sided test. Secondary endpoints include: ORR, SAEs, OS, impact of RNA signatures and GATA6 expression on outcomes. Each patient is discussed at a molecular tumor board immediately following their 1 st 8-week CT with the goal of recommending precision 2nd-line treatment options on progression. Results: This trial accrued 160 pts between 09/20 and 01/24, 45% in Canada, 55% in US with 140 eligible for 1 st line PFS, data lock Mar 1/24 (see table). Median PFS (PP) was 5.1 mo for GnP and 4.0 mo for mFFX (p=0.14). Best response PR/SD for GnP: 29/45% and 24/35% for mFFX. SAEs attributed to the study were 3% GnP, 13% mFFX and 0.7% bx. Median OS (ITT) was 9.7 mo with GnP and 8.4 mo with mFFX, p=0.04. Of 113 patients in the PP analysis with progression, 64 (57%) received 2nd-line treatment (GnP, n= 30, mFFX n=34) Of these, a correlate-guided approach was delivered in 32 (50%), including 21 (66%) receiving chemo and 11 (34%) receiving a targeted or immunotherapy regimen. Correlative studies are underway. Preliminary analysis shows >80% successful whole genomes and >72% RNA signatures. PP patients include 9 % KRAS wild-type and 21% Basal-like PDAC. PDO-drug models have been established in 50%. Conclusions: Upfront multi-omic profiling of PDAC can be successfully incorporated into a multicenter randomized trial. While we have observed PP improved PFS and ITT longer OS favouring GnP in this cohort without gBRCA 1/2 or PALB2m, the benefit of chemo for advanced PDAC patients remains poor, with 43% unable to receive 2 nd line, arguing strongly for the development of 1 st -line biomarker selected strategies. Clinical trial information: NCT04469556 . [Table: see text]

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)0.004
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0060.001

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 head0.214
GPT teacher head0.510
Teacher spread0.296 · 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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Citations21
Published2024
Admission routes2
Has abstractyes

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