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Record W2010130357 · doi:10.3389/fonc.2014.00386

Prospective Validation Obtained in a Similar Group of Patients and with Similar High Throughput Biological Tests Failed to Confirm Signatures for Prediction of Response to Chemotherapy and Survival in Advanced NSCLC: A Prospective Study from the European Lung Cancer Working Party

2015· article· en· W2010130357 on OpenAlexaff
Thierry Berghmans, Lieveke Ameye, Jean‐Jacques Lafitte, Benoît Colinet, Alexis B. Cortot, Ingrid CsToth, Stéphane Holbrechts, Jacques Lecomte, C. Mascaux, Anne‐Pascale Meert, Marianne Paesmans, Michel Richez, Arnaud Scherpereel, Christian Tulippe, Luc Willems, Tiffany Dernies, Nathalie Leclercq, Jean‐Paul Sculier

Bibliographic record

VenueFrontiers in Oncology · 2015
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Treatments and Mutations
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsVinorelbineOncologyMedicineInternal medicineLung cancerCisplatinSurvival analysisChemotherapy

Abstract

fetched live from OpenAlex

AIM: Cisplatin doublets are standard 1st line treatment for advanced non-small cell lung cancer (NSCLC), without accurate predictor for response and survival, but important toxicity. Our aims were to identify predictive (for response) and prognostic (for survival) biological signatures in patients with NSCLC using messenger RNAs (mRNA) and miRNA expression. METHODS: Patients with pathologically proven untreated NSCLC, receiving 1st line cisplatin-vinorelbine and with an assessable lesion were eligible. A bronchial biopsy was lysed into Tripure Isolation Reagent on ice, snap frozen, and stored at -80°C. mRNA expression was analyzed using microarrays Agilent Technologies. miRNA expression was assessed using TaqMan Low Density Arrays (756 human miR panel, Applied Biosystems). Validation was performed by RT-PCR on the selected genes. Survival was measured from the registration date and response assessed by WHO criteria. RESULTS: Biopsies for transcriptomic analyses were obtained from 60 consecutive patients. No statistically significant differences were observed according to the main clinical characteristics, response rate (43 vs. 41%) or survival (median 25 vs. 29 months) between derivation and validation sets. In the derivation set (n = 38 patients), two mRNA and one miRNA predictive signatures for response were obtained. One mRNA and one miRNA prognostic signatures were derived from the first set, allowing an adequate distinction of patients with good and poor overall and progression-free survivals. None of these signatures could be validated in the validation set (n = 22 patients). CONCLUSION: In this prospective study with advanced NSCLC treated with cisplatin-vinorelbine, we were able to derive with high throughput techniques predictive and prognostic signatures based on transcriptomic analyses. However, these results could not be reproduced in an independent validation set. The role of miRNA and mRNA as predictive or prognostic factors remains a research topic and the use of high throughput technology in that context questionable. The ClinicalTrials.gov study identifier is NCT00864266 (www.clinicaltrials.gov).

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.355

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.018
GPT teacher head0.331
Teacher spread0.313 · 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 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

Citations10
Published2015
Admission routes1
Has abstractyes

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