MétaCan
Menu
Back to cohort

Abstract CT094: Durvalumab (D) vs placebo (P) after concurrent chemoradiotherapy (cCRT) in limited-stage small-cell lung cancer (LS-SCLC): Outcomes by PD-L1 expression in ADRIATIC

2025· article· en· W4409822191 on OpenAlexaff
Christine L. Hann, Ying Cheng, David R. Spigel, Byoung Chul Cho, Jian Fang, Yuanbin Chen, Yoshitaka Zenke, Qiming Wang, Reyes Bernabé, John Wen-Cheng Chang, Sema Sezgin Göksu, Lin Wu, Gyeong‐Won Lee, Michael J. Thomas, Y. Ohe, Frank Griesinger, Leah Szadkowski, Hema Gowda, Yashaswi Shrestha, Suresh Senan

Bibliographic record

VenueCancer Research · 2025
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Research Studies
Canadian institutionsAstraZeneca (Canada)
Fundersnot available
KeywordsDurvalumabMedicineOncologyInternal medicineStage (stratigraphy)ChemoradiotherapyPlaceboCancerPathologyImmunotherapyBiology

Abstract

fetched live from OpenAlex

Abstract Background: At the first planned interim analysis of the phase 3 ADRIATIC study (NCT03703297), consolidation D significantly improved the dual primary endpoints of overall survival (OS; HR 0.73; 95% CI 0.57-0.93; p=0.0104) and progression-free survival (PFS; HR 0.76; 95% CI 0.61-0.95; p=0.0161) vs P in patients (pts) with LS-SCLC with no progression after cCRT. Although PD-L1 is not currently a validated immunotherapy biomarker in SCLC (unlike NSCLC) and is generally expressed at low levels in this setting, PD-L1 was evaluated as a potential biomarker in ADRIATIC. Methods: Pts with stage I-III LS-SCLC (stage I/II inoperable), WHO performance status 0/1, and no progression after cCRT, were randomized 1-42 days post cCRT to D (n=264), D + tremelimumab (n=200; arm remains blinded), or P (n=266). The VENTANA PD-L1 (SP263) immunohistochemistry assay was used for central retrospective testing of pre-cCRT tissue samples. OS and PFS were assessed in the PD-L1-evaluable population and in subgroups with PD-L1 expression ≥1% on tumor cells (TC) and/or immune cells (IC) (secondary endpoint) and <1% on TC and IC (data cutoff: Jan 15, 2024). Results: Among 162 (61.4%) and 171 (64.3%) pts in the D and P arms who were evaluable for PD-L1, improvements in OS (HR [D vs P] 0.73 [95% CI 0.53-0.99]) and PFS (HR 0.80 [0.60-1.06]) were of similar magnitude to those in the ITT population. Of the PD-L1-evaluable pts, 51.9% (84/162) in the D arm and 57.3% (98/171) in the P arm had PD-L1 TC or IC ≥1%. D appeared to improve OS and PFS vs P in subgroups with TC or IC ≥1% and with TC and IC <1% (Table), consistent with the ITT population. Conclusions: Among the PD-L1-evaluable population in ADRIATIC, 54.7% (182/333) of pts had PD-L1 TC or IC ≥1%. Consolidation D appeared to improve OS and PFS vs P irrespective of PD-L1 expression based on a cutoff of 1% on TC and/or IC, further supporting consolidation D as the new standard of care in pts with LS-SCLC with no progression after cCRT. Citation Format: Christine Hann, Ying Cheng, David Spigel, Byoung Chul Cho, Jian Fang, Yuanbin Chen, Yoshitaka Zenke, Qiming Wang, Reyes Bernabe, John Wen-Cheng Chang, Sema Sezgin Goksu, Lin Wu, Gyeong-Won Lee, Michael Thomas, Yuichiro Ohe, Frank Griesinger, Leah Szadkowski, Hema Gowda, Yashaswi Shrestha, Suresh Senan. Durvalumab (D) vs placebo (P) after concurrent chemoradiotherapy (cCRT) in limited-stage small-cell lung cancer (LS-SCLC): Outcomes by PD-L1 expression in ADRIATIC [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_2):Abstract nr CT094.

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: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.047
GPT teacher head0.442
Teacher spread0.395 · 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
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueCancer ResearchSame topicLung Cancer Research StudiesFrench-language works237,207