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Circulating tumour DNA (ctDNA) as a predictor of clinical outcome in non-small cell lung cancer undergoing targeted therapies: A systematic review and meta-analysis.

2023· review· en· W4379338189 on OpenAlexaboutno aff
Farzana Y. Zaman, Ashwin Subramaniam, Zarka Samoon, Walid Zwieky, Surein Arulananda, Muhammad Alamgeer

Bibliographic record

VenueJournal of Clinical Oncology · 2023
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Genomics and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineInternal medicineMeta-analysisOncologyLung cancerHazard ratioPublication biasLiquid biopsyPopulationClinical trialConfidence intervalCancer

Abstract

fetched live from OpenAlex

e21124 Background: Liquid biopsy (LB) analysis using circulating-tumour DNA (ctDNA)/cell-free DNA (cfDNA) is an emerging alternative to tissue profiling in non-small cell lung cancer (NSCLC). LB is used to guide treatment decisions, detect resistance mechanisms, and predicts responses, and therefore outcomes. This systematic review and meta-analysis evaluated the impact of LB quantification on clinical outcomes in molecularly altered advanced NSCLC undergoing targeted therapies. Methods: We searched Embase, MEDLINE, PubMed and Cochrane Database, between 01/01/2000 and 01/08/2022. The primary outcome was progression-free survival (PFS) and overall survival (OS). Secondary outcomes included objective response rate (ORR), sensitivity and specificity of the test. Age stratification was performed based on the mean age of the individual study population. The quality of studies was assessed using the Newcastle-Ottawa Scale (NOS). Results: Twenty-seven studies reporting 2424 patients were included. Eleven studies (n = 1359) reported an association of baseline ctDNA levels, while 16 studies (n = 1649) reported an association of dynamic ctDNA changes to treatment, with clinical outcomes of PFS and/or OS. Baseline ctDNA-negative patients had higher PFS (pooled hazard ratio [pHR] = 2.97; (95%CI: 1.92-4.85; I2= 97.4%), and OS (pHR = 3.49; (95%CI: 1.73-6.95; I2= 84.2%), than ctDNA-positive patients. Egger’s test suggested publication bias (p < 0.001). Early reduction/clearance of ctDNA levels after treatment improved PFS (pHR = 3.78; 95%CI: 1.91-7.38; I2= 98.4%) and OS (pHR = 2.20; 95%CI: 1.49-3.28; I2= 90.6%), compared to those with no reduction/persistence of ctDNA levels. The PFS was comparable for patients stratified by age (age ≤60 years [pHR = 2.92; 95%CI: 1.43-5.93; I2= 98.3 %] vs. age > 60 years [pHR = 3.94; 95%CI: 1.54-10.07; I2= 83.6 %]). The sensitivity analysis based on study quality (NOS) demonstrated improved PFS only for good quality studies (pHR = 3.67; 95%CI: 1.79-7.54; I2= 91.6 %), but not for poor or fair quality studies. Conclusions: This large systematic review, despite heterogeneity, found that baseline negative ctDNA levels, and early reduction in ctDNA following treatment are strong prognostic markers for PFS and OS in patients undergoing targeted therapies for advanced NSCLC. Future randomised clinical trials should incorporate serial ctDNA monitoring to further establish the clinical utility in advanced NSCLC management. Systematic review registration: PROSPERO registration No. CRD42022347791 Keywords: non-small cell lung cancer; NSCLC; liquid biopsy; circulating tumour DNA; ctDNA; progression-free survival; targeted therapies.

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)0.012
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.020
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.029
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0200.034
Bibliometrics0.0060.009
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.002
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 head0.209
GPT teacher head0.496
Teacher spread0.287 · 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 designMeta-analysis
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

Citations0
Published2023
Admission routes1
Has abstractyes

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