Effectiveness and safety of camrelizumab combined with pemetrexed-carboplatin in advanced nonsquamous non-small cell lung cancer (NSCLC): a systematic review and meta-analysis
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.035 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".