Clinical haematological biomarkers: Derived neutrophil-to-lymphocyte ratio (dNLR), platelet-to-lymphocyte ratio (PLR), and prognostic nutritional index (PNI) and their relationship to survival outcomes in non small cell lung cancer (NSCLC) treated with immunotherapy: A multicenter review.
Bibliographic record
Abstract
e20704 Background: Efficient use of immunotherapy in non-small-cell lung cancer (NSCLC) has been limited by the lack of a definitive predictive biomarker. Recently considerable efforts have been invested to develop biomarkers to predict which patients should receive immune checkpoint inhibitors. This retrospective cohort study aimed to determine whether clinical factors and inflammation-based biological markers such as pre-treatment derived neutrophils to lymphocytes (dNLR) ratio, platelets to lymphocytes (PLR) ratio and prognostic nutritional index (PNI) were associated with outcomes in NSCLC patients treated with immunotherapy. Methods: This study was a multicentered, retrospective systematic review. Clinical and electronic records were retrospectively examined from metastatic NSCLC patients treated with immunotherapy from August of 2015 to September 2018 in 2 regional cancer centers and a total of 69 patients were enrolled. NLR ≥5 and PLR ≥260 were defined as elevated and PNI ≤35 was defined as reduced. Results: Approximately, 57% of patients had NLR ≤ 5 and 51% had PLR ≤260. We found utilising univariant analysis, that pretreatment NLR ≤ 5 was independently associated with superior OS (median 12.4 vs. 6.8 months; HR 2.13, 95% CI 1.66-2.6; p = 0.007) and PFS (median 3.55 vs. 2.6 months; HR 1.75, 95% CI 1.18-2.32; p = 0.024). Results were similar when examining PLR ≤260 median OS 13.64 vs. 7.36 months; HR 1.92, 95% CI 1.1-3.5; p = 0.028) The optimal cutoff for PNI was designated to be 35. The majority (87%) had PNI > 35. NSCLC patients with PNI > 35 were found to have significantly higher median OS compared to patients with PNI ≤35 (11.11 vs. 2.4 months; HR 5.36, 95% CI ; p = 0.001). Conclusions: Immunotherapy is considered as an effective new method to treat advanced NSCLC. In this cohort of patients pretreatment NLR < 5,PLR < 260 and PNI > 35 were associated with superior outcomes. It is unclear whether these markers are predictive or prognostic or both.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".