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Record W4387666168 · doi:10.1371/journal.pone.0290644

Triple combination of HAIC-FO plus tyrosine kinase inhibitors and immune checkpoint inhibitors for advanced hepatocellular carcinoma: A systematic review and meta-analysis

2023· review· en· W4387666168 on OpenAlexaboutno aff
Zhongbao Tan, Jian Zhang, Liandi Xu, Huanjing Wang, Xuequn Mao, Rong Zou, Qingqing Wang, Zhuang Han, Zhen-Hai Di, Daguang Wu

Bibliographic record

VenuePLoS ONE · 2023
Typereview
Languageen
FieldMedicine
TopicHepatocellular Carcinoma Treatment and Prognosis
Canadian institutionsnot available
Fundersnot available
KeywordsHepatocellular carcinomaTyrosine kinaseMeta-analysisMedicineCancer researchOncologyInternal medicineReceptor

Abstract

fetched live from OpenAlex

BACKGROUND: The triple combination of hepatic arterial infusion chemotherapy (HAIC) with fluorouracil, leucovorin, and oxaliplatin (FOLFOX) plus tyrosine kinase inhibitor (TKI) and immune checkpoint inhibitors (ICIs) is expected to have a synergistic anticancer effect in HCC. We conducted this meta-analysis to evaluate the efficacy and safety of the triple combination treatment in advanced HCC patients. METHODS: PubMed, Embase, Cochrane Library, Web of Science databases were systematically searched for relevant studies from the inception of each database to May 10, 2023. All articles focusing the triple combination treatment of HAIC-FO plus TKI and ICIs for advanced HCC were eligible. The meta-analysis was conducted following the PRISMA guidelines. The risk of bias was assessed using the Joanna Briggs Institute (JBI) for case series and Newcastle-Ottawa Scale (NOS) for cohort studies. The primary outcomes were overall survival (OS), progression-free survival (PFS), objective response rate (ORR) and disease control rate (DCR). The secondary results were adverse events. Further meta-analysis of control studies demonstrated the superiority of the triple combination modality to TKI plus ICIs, and TKI alone. RESULTS: Nine articles (four cohort studies and five one-arm studies) involving 777 advanced HCC patients were included in this meta-analysis. In terms of survival analysis, the pooled median PFS was 11 months (95% CI: 10.1-12.0 months) with low heterogeneity (I2 = 0%, p = 0.97). With regard to tumor response, the pooled ORR and DCR was 61.6% (I2=0%, p = 0.71) and 87.9% (I2 = 13%, p = 0.33) with low heterogeneity, respectively. As compared with TKIs plus ICIs, and TKIs alone, the triple combination thrapy was associated with improved median OS (HR=0.51, 95%CI 0.41-0.62) with low heterogeneity across studies (I2 = 0%, p = 0.47), median PFS (HR=0.51, 95%CI 0.41-0.64) with low heterogeneity across studies (I2 = 0%, p = 0.41), ORR (RR = 0.56, 95% CI: 0.42-0.74) with high heterogeneity across studies (I2 = 69%, p = 0.02), and DCR (RR = 0.38, 95%CI 0.27-0.54) with low heterogeneity across studies (I2 = 14%, p = 0.32). The most common 3/4 AEs were elevated ALT and AST, thrombocytopenia, hypertension, nausea and vomiting in this meta-analysis. CONCLUSIONS: The triple combination therapy of HAIC-FO plus TKI and ICIs showed promising efficacy and safety in patients with advanced HCC. REGISTRATION: The protocol was registered with PROSPERO (ID:CRD42023424281).

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)0.021
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 score0.019
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.021
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0190.045
Bibliometrics0.0080.008
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 head0.208
GPT teacher head0.302
Teacher spread0.095 · 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

Citations8
Published2023
Admission routes1
Has abstractyes

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