Predictors of Immunotherapy Efficacy in Metastatic Non-Small Cell Lung Cancer: Lung Immune Prognostic Index and Immune-Related Toxicity
Bibliographic record
Abstract
Background: Immune checkpoint inhibitors (ICIs) have been proposed as the standard first-line and subsequent treatment for metastatic non-small cell lung cancer (NSCLC). This study analyzed whether patients with good lung immune prognostic index (LIPI) have a better response to ICIs and the relationship between immune-related adverse events (irAEs) and response in clinical practice. Methods: This was an observational, retrospective, single-center study. Patients with stage IV NSCLC between 2016 and 2021 were included in the study. Toxicity was assessed according to The Common Terminology Criteria for Adverse Events. Response assessment was performed according to RECIST 2.0 and immuno-related criteria. Descriptive and survival analyses were conducted. Degree of toxicity and response to treatment (based on treatment and histology) were assessed. LIPI and response were assessed. LIPI included dNLR (absolute neutrophil count/(white blood cell count - absolute neutrophil count)) ≥ 3 and lactate dehydrogenase (LDH) greater than the upper limit of normal. Patients were stratified into good (G), intermediate (I), and poor (P) prognostic groups. Results: A total of 168 patients were included (130 men and 38 women, mean age 64.3 years). ICI use in the first- or second-line treatment was 65% and 35%, respectively. Fifteen (9%) patients showed complete response (CR), 50 (30%) showed partial response (PR), 39 (22%) had stable disease (SD), 45 (28%) had progressive disease (PD), and 19 (11%) were not evaluated (NE). Patients with good prognostic LIPI (dNLR < 3 and normal LDH levels) showed a better response. Progression-free survival (PFS) was 19 months in G, 6 months in I, and 2 months in P. Overall survival (OS) was 27 months in G, 8 months in I, and 3 months in P. One hundred fourteen patients died (56% G, 76% I, 93% P). Patients with adenocarcinoma were 116 (77 with irAEs G1-4 (13 CR, 31 PR, 21 SD, eight PD, and four NE)), and without were 39 (three PR, six SD, 21 PD, and nine NE). Fifty-two patients had squamous carcinoma (27 with irAEs G1-4 (two CR, 12 PR, nine SD, and four PD)), and 25 did not (four PR, three SD, 12 PD, and six NE)). IrAEs appearance was observed in longer PFS (19 vs. 2 months) and OS (27 vs. 4 months; P < 0.0001). Conclusions: LIPI was a positive predictor of response to ICI. The presence of irAEs is associated with a better immune response. In contrast, the absence of toxicity predicted a worse prognosis.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".