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Record W3122855631 · doi:10.3390/curroncol28010059

Survival Impact of Aggressive Treatment and PD-L1 Expression in Oligometastatic NSCLC

2021· article· en· W3122855631 on OpenAlexaffvenueabout
Camille Gauvin, Vimal Krishnan, Imane Kaci, Danh Tran‐Thanh, Karine Bédard, Roula Albadine, Charles Leduc, Louis Gaboury, Normand Blais, Mustapha Tehfé, Bertrand Routy, Marie Florescu

Bibliographic record

VenueCurrent Oncology · 2021
Typearticle
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsCentre Hospitalier de l’Université de MontréalInstitute for Research in Immunology and CancerUniversité de Montréal
Fundersnot available
KeywordsMedicineInternal medicineOncologyLung cancerImmunotherapyBrain metastasisMetastasisCancer

Abstract

fetched live from OpenAlex

Background: Studies have shown that aggressive treatment of non-small cell lung cancer (NSCLC) with oligometastatic disease improves the overall survival (OS) compared to a palliative approach and some immunotherapy checkpoint inhibitors, such as anti-programmed cell death ligand 1 (PD-L1), anti-programmed cell death protein 1 (PD-1), and T-Lymphocyte-associated antigen 4 (CTLA-4) inhibitors are now part of the standard of care for advanced NSCLC. However, the prognostic impact of PD-L1 expression in the oligometastatic setting remains unknown. Methods: Patients with oligometastatic NSCLC were identified from the patient database of the Centre hospitalier de l’Université de Montréal (CHUM). “Oligometastatic disease” definition chosen is one synchronous metastasis based on the M1b staging of the eight IASLC (The International Association for the Study of Lung Cancer) Classification (within sixth months of diagnosis) or up to three cerebral metastasis based on the methodology of the previous major phase II randomized study of Gomez et al. We compared the OS between patients receiving aggressive treatment at both metastatic and primary sites (Group A) and patients receiving non-aggressive treatment (Group B). Subgroup analysis was performed using tumor PD-L1 expression. Results: Among 643 metastatic NSCLC patients, we identified 67 patients with oligometastasis (10%). Median follow-up was 13.3 months. Twenty-nine patients (43%) received radical treatment at metastatic and primary sites (Group A), and 38 patients (57%) received non-aggressive treatment (Group B). The median OS (mOS) of Group A was significantly longer than for Group B (26 months vs. 5 months, p = 0.0001). Median progression-free survival (mPFS) of Group A was superior than Group B (17.5 months vs. 3.4 months, p = 0.0001). This difference was still significant when controlled for primary tumor staging: stage I (p = 0.316), stage II (p = 0.024), and stage III (p = 0.001). In the cohort of patients who were not treated with PD-L1 inhibitors, PD-L1 expression negatively correlated with mOS. Conclusions: Aggressive treatments of oligometastatic NSCLC significantly improve mOS and mPFS compared to a more palliative approach. PD-L1 expression is a negative prognostic factor which suggests a possible role for immunotherapy in this setting.

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)0.000
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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.099
GPT teacher head0.446
Teacher spread0.347 · 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".

Quick stats

Citations16
Published2021
Admission routes3
Has abstractyes

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