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Effectiveness and safety of camrelizumab combined with pemetrexed-carboplatin in advanced nonsquamous non-small cell lung cancer (NSCLC): a systematic review and meta-analysis

2025· review· W4415371933 on OpenAlexaboutno aff
Intan Dwikarlina, Genta Antariksa, Brenda Kristi, Masaaki Hamada

Bibliographic record

VenueIndonesian Journal of Biomedicine and Clinical Sciences · 2025
Typereview
Language
FieldMedicine
TopicLung Cancer Treatments and Mutations
Canadian institutionsnot available
Fundersnot available
KeywordsLung cancerPemetrexedAdverse effectJadad scaleHazard ratioChemotherapySurvival rateImmunotherapy

Abstract

fetched live from OpenAlex

Lung cancer is the second most common malignancy worldwide, with non-small cell lung cancer (NSCLC) comprising about 80% of cases. Platinum-based chemotherapy with third-generation agents such as pemetrexed-carboplatin remains the first-line treatment for nonsquamous advanced NSCLC; however, survival benefits remain limited and immune evasion persists. Camrelizumab (SHR-1210), a humanized anti-PD-1 monoclonal antibody, enhances antitumor immunity by blocking the PD-1/PD-L1 pathway. This systematic review and meta-analysis evaluated the efficacy of camrelizumab combined with chemotherapy in advanced NSCLC, in accordance with PRISMA guidelines. A comprehensive search was performed in PubMed, EBSCO, Cochrane, ScienceDirect, Wiley, and Google Scholar for English-language publications up to July 2025. Study quality was assessed using the Modified Jadad Score, Newcastle–Ottawa Scale, and JBI Checklist. Statistical analyses were conducted with Review Manager 5.4. The main outcomes included overall survival (OS) and progression-free survival (PFS), expressed as hazard ratios (HRs), and objective response rate (ORR) and disease control rate (DCR), expressed as odds ratios (ORs). Six studies were identified; after excluding duplicates, four trials with a total of 332 patients (stage IIIB–IV adenocarcinoma) were analyzed. Camrelizumab-based regimens significantly improved OS (HR = 0.69; 95% CI: 0.55–0.87; p = 0.002) and PFS (HR = 0.42; 95% CI: 0.28–0.63; p < 0.01) compared with non-camrelizumab regimens. Reported ORR ranged from 40.0% to 58.8%, while DCR was 75.6%–87.7%. Most adverse events were mild (grade ≤2) and manageable. Hematologic toxicities included anemia (OR 4.1; p < 0.00001) and thrombocytopenia (OR 2.59; p < 0.0001), whereas common non-hematologic toxicities included skin reactions (OR 101.42; p < 0.00001), fatigue (OR 16.39; p < 0.00001), and nausea/vomiting (OR 23.56; p < 0.00001). Camrelizumab increases CD8+ T-cell infiltration. In combination with carboplatin and pemetrexed, it shows promising efficacy with a tolerable safety profile in advanced nonsquamous NSCLC. Large-scale trials remain necessary to validate long-term outcomes.

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)0.009
metaresearch head score (Gemma)0.019
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.019
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.019
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0190.035
Bibliometrics0.0050.006
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 head0.028
GPT teacher head0.404
Teacher spread0.376 · 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
Published2025
Admission routes1
Has abstractyes

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