ArticleBMC cancer2026
Characteristics and hematological indicators predictors of immunotherapy response in advanced non-small cell lung cancer.
Article in BMC cancer, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Baseline Neutrophil-to-Lymphocyte Ratio and Two-Year Incident Distant Metastasis in Stage I-III Lung Cancer: A Single-Center Retrospective Cohort Study.Journal of clinical medicine · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
objectiveImmune checkpoint inhibitors (ICIs) have significantly improved the treatment outcomes for advanced non-small cell lung cancer (NSCLC), but patient benefits vary individually. Therefore, identifying biomarkers to predict the efficacy and prognosis of immunotherapy is crucial. Hematological markers such as the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), albumin-bilirubin (ALBI) score, and lactate dehydrogenase (LDH) levels may correlate with tumor prognosis. This study aimed to evaluate the prognostic value of these hematological and clinical markers in advanced NSCLC patients treated with ICIs, providing a basis for individualized treatment strategies.
methodsThis retrospective study included NSCLC patients treated with ICIs at the Tumor Centers of Renmin Hospital of Wuhan University and Macheng City People's Hospital between January 2021 and December 2023. Clinical data such as gender, age, ECOG PS score, clinical stage, and treatment details were collected. Patients were stratified based on NLR, PLR, LDH, and ALBI scores. ROC curve analysis assessed the predictive capacity of these markers for mortality risk. Chi-square tests, logistic regression, Kaplan-Meier survival analysis, and log-rank tests were used to analyze short-term efficacy, immune-related adverse events (irAEs), progression-free survival (PFS), and overall survival (OS). Cox regression identified independent prognostic factors for PFS and OS.
resultsA total of 198 advanced NSCLC patients (median follow-up: 28.1 months) were included. Median PFS (mPFS) and OS (mOS) were 7.7 months (95% CI: 6.9 ~ 8.5) and 20.1 months (95% CI: 18.2 ~ 21.9), respectively. ROC analysis demonstrated significant predictive value for baseline NLR, PLR, ALBI, and LDH in mortality risk (AUC: 0.804, 0.694, 0.684, 0.726, respectively). Efficacy analysis revealed PD-L1 positivity (OR = 0.361, 95% CI: 0.161 ~ 0.808, P = 0.013) and ALBI < -2.68 (OR = 2.524, 95% CI: 1.148-5.552, P = 0.021) as independent predictors of objective response rate (ORR: 25.8%), while camrelizumab significantly reduced response rates (OR = 0.157, P = 0.006). Baseline NLR, PLR, ALBI, and LDH significantly stratified PFS (P < 0.05): low NLR (8.7 vs. 7.1 months, P = 0.001), low PLR (7.9 vs. 7.4 months, P = 0.007), low ALBI (8.1 vs. 7.0 months, P = 0.028), and low LDH (9.5 vs. 7.1 months; 46.3% risk reduction, P < 0.001). In the adenocarcinoma subgroup, LDH remained an independent prognostic factor (9.5 vs. 6.8 months, P = 0.032). For squamous cell carcinoma, low NLR (9.1 vs. 7.1 months, P = 0.002), low PLR (10.2 vs. 7.4 months, P = 0.002), low ALBI (8.7 vs. 7.1 months, P = 0.022), and low LDH (9.1 vs. 7.5 months, P = 0.002) were significant. Baseline markers also predicted OS: low NLR (21.4 vs. 17.5 months, P < 0.001), low PLR (20.4 vs. 17.7 months, P = 0.009), and low LDH (21.4 months; 42.5% risk reduction, P < 0.001). Subtype analysis showed adenocarcinoma benefited from low NLR (21.4 vs. 16.5 months, P = 0.013) and low LDH (20.1 vs. 17.5 months, P = 0.021), while squamous carcinoma relied on low NLR (21.4 vs. 16.8 months, P = 0.008), low PLR (21.8 vs. 20.1 months, P = 0.024), low ALBI (21.4 vs. 18.2 months, P = 0.047), and low LDH (24.6 vs. 19.8 months, P = 0.001). Multivariate Cox analysis identified radiotherapy, NLR, and LDH as independent predictors of PFS: Radiotherapy reduced risk by 37.5% (HR = 0.625, P = 0.004); NLR ≥ 3.72 (HR = 1.642) and LDH ≥ 226.5 U/L (HR = 1.821) increased risk by 64.2% and 82.1% (P < 0.05). For OS, adenocarcinoma (HR = 0.361) and squamous carcinoma (HR = 0.350) reduced mortality risk by 63.9% and 65.0% (P < 0.05), while NLR ≥ 3.72 (HR = 1.536), and LDH ≥ 226.5 U/L (HR = 1.728) increased risk by 53.6% and 72.8% (P < 0.05). LDH ≥ 226.5 U/L (HR = 2.372) stained highest risk in squamous carcinoma (P < 0.05).
conclusionsBaseline hematological markers (NLR, PLR, ALBI, LDH) are valuable predictors of efficacy and prognosis in advanced NSCLC patients undergoing immunotherapy. Their prognostic roles vary by pathological subtype: squamous carcinoma relies more on inflammatory markers, while adenocarcinoma emphasizes metabolic markers and genetic mutations. This study provides a hematological biomarker-based stratification framework for individualized immunotherapy decisions in advanced NSCLC, offering critical guidance for optimizing treatment and prognosis management.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.