Inhibitors of PD-1 in Non-Small Cell Lung Cancer: A Meta-Analysis of Clinical and Molecular Features
Bibliographic record
Abstract
Objective: PD-1 inhibitors have become an indispensable treatment in Non-Small Cell Lung Cancer (NSCLC), but the potential predictive value of clinical and molecular features need to be clarified. The objective of the study was to study the potency of PD-1 inhibitors in patients with NSCLC in contexts of both clinical and molecular features, and to aid identification of patients for choice of type of PD-1 inhibitor therapy in order to acquire more accurate NSCLC treatment in immunotherapy. Method: PubMed, Google Scholar, Embase Science Direct, the Cochrane library, and major oncology conferences were searched for randomized clinical trials (RCTs) that were published prior to December 2021. RCTs that had PD-1 inhibitor alone or in combination with chemotherapy with non-PD-1 inhibitor for the treatment of NSCLC patients were selected. Two authors independently selected studies, data extraction and bias risk assessment. Basic characteristics of included studies, and also the 95% confidence interval and hazard ratios of the overall patients and subgroups were recorded. The inverse variance weighted method was used to estimate pooled treatment data. Result: A total of eleven RCTs including 5,887 patients were involved. PD-1 inhibitors-based therapy substantially enhanced OS compared with non-PD-1 inhibitor therapy in patients with age group <65 years, 65-74 years, active or previous smokers, without brain metastases, liver metastases, EGFR wild-type patients, individuals in East Asia and U.S./Canada, but not in patients with age group ≥75 years, never smokers, brain metastases, EGFR mutant patients or individuals in Europe. OS was improved in patients with NSCLC who received PD-1 inhibitors regardless of their gender (male or female), histomorphological subtypes (squamous or non-squamous NSCLC), performance status (0 or 1), and PD-L1 tumor proportion score (TPS) (<1%, ≥1%, 1-49%, or ≥50%). An analysis of subgroups revealed that, patients with age group <65 years old, male, non squamous cell carcinoma, PS 1, TPS ≥1%, and TPS ≥50% benefited from pembrolizumab treatment not related with treatment line and treatment regimen. Conclusion: Age group, smoking history, metastasis status/site, EGFR mutation status, and region can be used to predict the potency of PD-1 inhibitors, and to be individualized to choose different types of PD-1 inhibitors, and treatment regimen for NSCLC patients.
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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 | 0.020 | 0.028 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.056 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".