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Record W3114129790 · doi:10.3747/co.27.6583

A Systematic Review and Network Meta-Analysis of Second-Line Therapy in Hepatocellular Carcinoma

2020· review· en· W3114129790 on OpenAlexaffvenue
Seanthel Delos Santos, Suji Udayakumar, Anthony Nguyen, Y.J. Ko, Scott Berry, Mark Doherty, Kelvin Chan

Bibliographic record

VenueCurrent Oncology · 2020
Typereview
Languageen
FieldMedicine
TopicHepatocellular Carcinoma Treatment and Prognosis
Canadian institutionsCanadian Centre for Applied Research in Cancer ControlHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsRegorafenibSorafenibMedicineHazard ratioPlaceboInternal medicineCabozantinibHepatocellular carcinomaConfidence intervalOncologyMeta-analysisRandomized controlled trialSubgroup analysisCancerColorectal cancerPathologyAlternative medicine

Abstract

fetched live from OpenAlex

Background: In patients with advanced hepatocellular carcinoma (hcc) following sorafenib failure, it is unclear which treatment is most efficacious, as treatments in the second-line setting have not been directly compared and no standard therapy exists. This systematic review and network meta-analysis (nma) aimed to compare the clinical benefits and toxicities of these treatments. Methods: A systematic review of randomized controlled trials (rcts) was conducted to identify phase iii rcts in advanced hcc following sorafenib failure. Baseline characteristics and outcomes of placebo were examined for heterogeneity. Primary outcomes of interest were extracted for results, including overall survival (os), progression-free survival (pfs), objective response rate (orr), grade 3/4 toxicities, and subgroups. An nma was conducted to compare both drugs through the intermediate placebo. Comparisons were expressed as hazard ratios (hrs) for os and pfs, and as risk difference (rd) for orr and toxicities. Subgroup analyses for os and pfs were also performed. Results: Two rcts were identified (1280 patients) and compared through an indirect network; celestial (cabozantinib vs. placebo) and resorce (regorafenib vs. placebo). Baseline characteristics of patients in both trials were similar. Both trials also had similar placebo outcomes. Cabozantinib, compared with regorafenib, showed similar os [hazard ratio (hr): 1.21; 95% confidence interval (ci): 0.90 to 1.62], pfs (hr: 1.02; 95% ci: 0.78 to 1.34) and orr (-3.0%; 95% ci: -7.6% to 1.7%). Both treatments showed similar toxicities, but there were marginally higher risks of grade 3/4 hand-foot syndrome (5%; 95% ci: 0.1% to 9.8%), diarrhea (4.8%; 95% ci: 1.1% to 8.5%), and anorexia (4.4%; 95% ci: 0.8% to 8.0%) for cabozantinib. Subgroup results for os and pfs were consistent with overall results. Conclusions: Overall, this nma determined that cabozantinib and regorafenib have similar clinical benefits and toxicities for second-line hcc.

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)0.027
metaresearch head score (Gemma)0.058
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 score0.027
Threshold uncertainty score0.145

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.058
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0180.040
Bibliometrics0.0090.009
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
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 head0.429
GPT teacher head0.421
Teacher spread0.008 · 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

Citations9
Published2020
Admission routes2
Has abstractyes

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