MétaCan
Menu
Back to cohort
Record W3047425187 · doi:10.1093/noajnl/vdaa073.048

60. IDEAL TREATMENT REGIMEN FOR PATIENTS WITH ≥1 BRAIN METASTASIS FROM PRIMARY NON-SMALL-CELL LUNG CANCER – A SYSTEMATIC REVIEW AND NETWORK META-ANALYSIS

2020· review· en· W3047425187 on OpenAlexaff
Karanbir Brar, Yosef Ellenbogen, Behnam Sadeghirad, Jiawen Deng, Winston Hou, Xiaoqin Wang, Shervin Taslimi, Alireza Mansouri

Bibliographic record

VenueNeuro-Oncology Advances · 2020
Typereview
Languageen
FieldMedicine
TopicLung Cancer Treatments and Mutations
Canadian institutionsMcMaster UniversityUniversity of Toronto
Fundersnot available
KeywordsMedicineInternal medicineMeta-analysisLung cancerOncologyRandomized controlled trialBrain metastasisnon-small cell lung cancer (NSCLC)RegimenCancerMetastasis

Abstract

fetched live from OpenAlex

Abstract BACKGROUND Brain metastases (BM) are common in non-small cell lung cancer (NSCLC). The aim of this study was to assess the comparative effectiveness of treatments for BM from NSCLC. METHODS We searched MEDLINE, EMBASE, Web of Science, ClinicalTrials.gov, CENTRAL and references of key studies for randomized controlled trials (RCTs) published until October 2018. We also searched the Chinese databases Wanfang Data, Wanfang Med Online, China National Knowledge Infrastructure, and Chongqing VIP Information for RCTs published until September 2019. Trials including > 10 patients were selected. The primary outcomes were overall survival (OS) and intracranial progression-free survival (PFS). We used a frequentist random-effects model for network meta-analysis and assessed the certainty of evidence using the GRADE approach. RESULTS Among 8798 abstracts, 106 RCTs (9452 patients) met inclusion criteria. Median sample size was 67 (range 25–554). All trials included adult patients with histologically proven NSCLC and >1 BM proven on CT/MRI. Of trials that reported performance status (e.g. ECOG or KPS, n=67), 63/67 excluded patients with non-favorable performance status. Interventions assessed included surgery, WBRT, SRS, targeted therapies (i.e. EGFR/ALK inhibitors), and chemotherapy. Compared to WBRT alone, several interventions demonstrated a statistically significant increase in median OS, including non-targeted chemotherapy + surgery (MD: 415.3 days, 95% CI: 31.3–799.4), WBRT + EGFRi (MD: 200.2 days, 95% CI:146.3–254.1), and EGFRi alone (MD: 169.7 days, 95% CI: 49.7–289.7). Among all interventions, only WBRT + EGFRi showed a significant improvement in median PFS (MD: 108.0 days, 95%CI: 48.5–167.5). CONCLUSIONS Our preliminary analyses indicate an OS and PFS benefit on the addition of EGFR inhibitors to WBRT for the treatment of BMs from NSCLC. Further analyses of hazard ratios for OS/PFS are underway, and subgroup analyses are planned. These data support the growing role of targeted therapies in the treatment of BMs, particularly in susceptible mutant tumours.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.566
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0130.002
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 head0.039
GPT teacher head0.376
Teacher spread0.337 · 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.

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
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueNeuro-Oncology AdvancesSame topicLung Cancer Treatments and MutationsFrench-language works237,207