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Conventional Oral Systemic Chemotherapy for Postoperative Hepatocellular Carcinoma

2014· article· en· W2074394581 on OpenAlexvenueno aff
Jian‐Hong Zhong

Bibliographic record

VenueJournal of cancer research updates · 2014
Typearticle
Languageen
FieldMedicine
TopicHepatocellular Carcinoma Treatment and Prognosis
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineInternal medicineAdjuvantHepatocellular carcinomaMeta-analysisCochrane LibrarySorafenibRandomized controlled trialClinical trialAdverse effectOdds ratioConfidence intervalOncologyAdjuvant therapyIncidence (geometry)ChemotherapySurgery

Abstract

fetched live from OpenAlex

Background:The findings of randomized clinical trials (RCTs) about the efficacy of adjuvant conventional oral systemic chemotherapy (COSC) for patients with hepatocellular carcinoma (HCC) after curative hepatic resection (HR) are contradictory. Therefore, a systematic review of clinical trials is needed to evaluate the clinical efficacy of adjuvant COSC. Methods:Sources such as MEDLINE, EMBASE and the Cochrane Library were systematically searched.All clinical trials comparing curative HR with HR plus COSC for HCC were identified. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated. Results:Five RCTs and one non-RCT involving a total of 461 patients were included. No treatment-related deaths were reported in the including trials. The adverse effects of COSC were generally mild. However, included studies and meta-analysis showed that adjuvant COSC did not demonstrate statistically significant improvement for the 1-, 3-, and 5-year overall survival. For the 1-, 3-, and 5-year tumor recurrence and recurrence-free survival rates, adjuvant COSC also did not show statistically significant less incidence. Conclusion:Adjuvant COSC provides no survival benefits for HCC patients after curative HR. Considering the efficacy of sorafenib for advanced HCC and the results of this systematic review, no more trials should be carried out to explore the efficacy of adjuvant COSC.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.872
Threshold uncertainty score0.468

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.108
GPT teacher head0.378
Teacher spread0.270 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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