MétaCan
Menu
Back to cohort
Record W2140075859 · doi:10.1016/s1470-2045(13)70158-x

Surrogate endpoints for overall survival in chemotherapy and radiotherapy trials in operable and locally advanced lung cancer: a re-analysis of meta-analyses of individual patients' data

2013· review· en· W2140075859 on OpenAlexaff
Audrey Mauguen, Jean‐Pierre Pignon, Sarah Burdett, Caroline Domerg, David J. Fisher, Rebecca Paulus, Samithra J Mandrekar, Chandra P. Belani, Frances A. Shepherd, Tim Eisen, Herbert Pang, Laurence Collette, William T. Sause, Suzanne E. Dahlberg, Jeffrey Crawford, Mary O’Brien, Steven E. Schild, Mahesh Parmar, Jayne F. Tierney, C. Le Péchoux, Stefan Michiels

Bibliographic record

VenueThe Lancet Oncology · 2013
Typereview
Languageen
FieldMedicine
TopicLung Cancer Diagnosis and Treatment
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMedicineSurrogate endpointRadiation therapyLung cancerClinical endpointInternal medicineOncologyClinical trialChemotherapyRandomized controlled trialMeta-analysisSurvival analysisCancerSurgery

Abstract

fetched live from OpenAlex

BACKGROUND: The gold standard endpoint in clinical trials of chemotherapy and radiotherapy for lung cancer is overall survival. Although reliable and simple to measure, this endpoint takes years to observe. Surrogate endpoints that would enable earlier assessments of treatment effects would be useful. We assessed the correlations between potential surrogate endpoints and overall survival at individual and trial levels. METHODS: We analysed individual patients' data from 15,071 patients involved in 60 randomised clinical trials that were assessed in six meta-analyses. Two meta-analyses were of adjuvant chemotherapy in non-small-cell lung cancer, three were of sequential or concurrent chemotherapy, and one was of modified radiotherapy in locally advanced lung cancer. We investigated disease-free survival (DFS) or progression-free survival (PFS), defined as the time from randomisation to local or distant relapse or death, and locoregional control, defined as the time to the first local event, as potential surrogate endpoints. At the individual level we calculated the squared correlations between distributions of these three endpoints and overall survival, and at the trial level we calculated the squared correlation between treatment effects for endpoints. FINDINGS: In trials of adjuvant chemotherapy, correlations between DFS and overall survival were very good at the individual level (ρ(2)=0.83, 95% CI 0.83-0.83 in trials without radiotherapy, and 0.87, 0.87-0.87 in trials with radiotherapy) and excellent at trial level (R(2)=0.92, 95% CI 0.88-0.95 in trials without radiotherapy and 0.99, 0.98-1.00 in trials with radiotherapy). In studies of locally advanced disease, correlations between PFS and overall survival were very good at the individual level (ρ(2) range 0.77-0.85, dependent on the regimen being assessed) and trial level (R(2) range 0.89-0.97). In studies with data on locoregional control, individual-level correlations were good (ρ(2)=0.71, 95% CI 0.71-0.71 for concurrent chemotherapy and ρ(2)=0.61, 0.61-0.61 for modified vs standard radiotherapy) and trial-level correlations very good (R(2)=0.85, 95% CI 0.77-0.92 for concurrent chemotherapy and R(2)=0.95, 0.91-0.98 for modified vs standard radiotherapy). INTERPRETATION: We found a high level of evidence that DFS is a valid surrogate endpoint for overall survival in studies of adjuvant chemotherapy involving patients with non-small-cell lung cancers, and PFS in those of chemotherapy and radiotherapy for patients with locally advanced lung cancers. Extrapolation to targeted agents, however, is not automatically warranted. FUNDING: Programme Hospitalier de Recherche Clinique, Ligue Nationale Contre le Cancer, British Medical Research Council, Sanofi-Aventis.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.839
Threshold uncertainty score0.859

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0130.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.413
GPT teacher head0.536
Teacher spread0.123 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreReview

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

Citations245
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueThe Lancet OncologySame topicLung Cancer Diagnosis and TreatmentFrench-language works237,207