Efficacy comparison of immune treating strategies for NSCLC patients with negative PD-L1 expression
Bibliographic record
Abstract
We intended to compare and grade the proposed immune treating strategies for non-small cell lung cancer (NSCLC) with negative Programmed Cell Death Ligand 1(PD-L1). We compared the efficacy of single immune checkpoint inhibitor (ICI), single ICI plus chemotherapy, and doublet ICIs with chemotherapy alone, as well as single ICI plus radiotherapy with single ICI for negative PD-L1 (<1%) NSCLC patients. Hazard Ratio (HR) and 95% confidence interval (CI) of progression-free survival (PFS) and overall survival (OS) were used as outcomes. We included 23 randomized control trials with 4665 patients. Compared with chemotherapy alone, single ICI, single ICI plus chemotherapy and doublet ICIs all showed a better OS (0.84 [0.71, 0.99] ; 0.77 [0.69, 0.85] ; 0.64 [0.53, 0.77])), while single ICI plus chemotherapy and doublet ICIs showed a better PFS (0.68 [0.61, 0.75] ; 0.69 [0.56, 0.85]). Additionally, single ICI plus radiotherapy obtained a greater pooled PFS (0.49 [0.28–0.87]) than single ICI. Both single ICI plus chemotherapy and doublet ICIs were probably better treatment decisions than chemotherapy alone for negative PD-L1 NSCLC patients. Also, single ICI plus radiotherapy carved out a new strategy.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".