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Record W4399553361 · doi:10.1080/14796694.2024.2342224

Real-world comparative effectiveness and safety of pembrolizumab for PD-L1≥50% metastatic non-small-cell lung cancer

2024· article· en· W4399553361 on OpenAlexaff
Ambica Parmar, Brandon Lu, Jin Luo, Kelvin Chan

Bibliographic record

VenueFuture Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsCanadian Centre for Applied Research in Cancer ControlHealth Sciences CentreCanada Research ChairsUniversity of TorontoCancer Care OntarioSunnybrook Health Science Centre
Fundersnot available
KeywordsPembrolizumabMedicineLung cancerOncologyInternal medicinePD-L1ImmunotherapyCancerIntensive care medicine

Abstract

fetched live from OpenAlex

Background: Despite the demonstrated efficacy of pembrolizumab in KEYNOTE-024, effectiveness and safety in routine practice remain unclear.Methods: The authors identified first-line pembrolizumab or chemotherapy patients from April 2013 to March 2021. The primary outcome was overall survival; the secondary safety outcomes included rates of hospitalization, emergency department visits, specialist visits, and adverse events. Baseline differences were adjusted using propensity score matching (1:1).Results: The matched cohort included 2284 pairs. Median overall survival for pembrolizumab (13.0 months) was significantly longer than for chemotherapy (9.2 months), with a hazard ratio of 0.81 (95% CI: 0.71–0.92). Pembrolizumab patients reported significantly more adverse events and specialist visits, as well as a higher 1-year cumulative incidence of direct hospitalizations.Conclusion: The survival benefit of first-line pembrolizumab persists in the real world, although with increased toxicity and diminished benefit.

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)0.010
metaresearch head score (Gemma)0.026
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 score0.010
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.022
GPT teacher head0.365
Teacher spread0.343 · 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

Citations2
Published2024
Admission routes1
Has abstractyes

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