Abstract
Background
For patients with driver gene-negative non-small cell lung cancer (NSCLC) with brain metastases, chemoimmunotherapy represents the standard treatment. However, the intracranial objective response rate (iORR) remains limited, highlighting the need for effective predictive biomarkers. This study aimed to evaluate the predictive value of systemic inflammatory indices, including the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and lymphocyte-to-monocyte ratio (LMR). These indices were assessed for their ability to predict intracranial response and survival among these patients.
Methods
This dual-center retrospective cohort study enrolled 94 driver gene-negative NSCLC patients with brain metastases receiving first-line chemoimmunotherapy. Optimal cutoff values for NLR, PLR, and LMR for predicting iORR were determined by ROC analysis. Associations with iORR, overall survival (OS), and progression-free survival (PFS) were assessed using logistic and Cox regression.
Results
High NLR (P = 0.001) and high PLR (P = 0.001) were associated with lower iORR, while high LMR predicted higher iORR (P = 0.001), with an AUC of 0.774. In multivariate analysis, LMR was an independent prognostic factor for OS in the overall population (HR = 0.538, P = 0.032). Notably, in the subgroup receiving intracranial radiotherapy (n = 74), LMR retained its independent prognostic significance.
Conclusions
Pretreatment systemic inflammatory indices, particularly LMR, serve as simple and effective predictive biomarkers for intracranial response and long-term survival in driver gene-negative NSCLC patients with brain metastases treated with first-line chemoimmunotherapy. These findings provide a clinical basis for early identification of high-risk patients and may guide individualized treatment strategies.
Keywords: Non-small cell lung cancer, Brain metastases, Platelet-to-lymphocyte ratio, Lymphocyte-to-monocyte ratio, Intracranial objective response rate
Introduction
Lung cancer is a leading cause of cancer incidence and death worldwide, with non-small cell lung cancer (NSCLC) accounting for about 85% of all cases [1, 2]. The majority of patients are diagnosed at a locally advanced or distant metastatic stage [3, 4]. For advanced NSCLC patients who are negative for driver mutations, such as EGFR and ALK wild-type, platinum-based doublet chemotherapy combined with immune checkpoint inhibitors has become the standard first-line treatment [5, 6]. A notable challenge for this patient group is the high occurrence of brain metastases, affecting 20% to 40% of individuals [7]. These metastases are not only a leading cause of neurological deficits and reduced quality of life but also a critical factor in poor prognosis [8, 9].
Although chemoimmunotherapy has improved systemic control, its efficacy within the central nervous system is often suboptimal. The intracranial objective response rate (iORR) remains limited, approximately 40–50% [8, 10]. This indicates that over half of these patients derive limited intracranial benefit from first-line chemoimmunotherapy and are at risk of primary resistance. Once intracranial progression occurs, it severely limits subsequent treatment options and impacts overall survival [11]. Consequently, there is an urgent, unmet clinical need for biomarkers that can accurately and non-invasively identify patients likely to experience poor intracranial response early in their treatment course. Such biomarkers would help identify resistant patient populations and guide the timing of interventions, like the early combination of treatment with brain radiotherapy. In recent years, readily accessible and cost-effective systemic inflammatory indices derived from peripheral blood counts, including the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and lymphocyte-to-monocyte ratio (LMR), have emerged as potential predictors of chemoimmunotherapy outcomes across various solid tumors, including NSCLC [12–14]. These indices are thought to reflect the host’s systemic immune status. A pro-inflammatory, immunosuppressive milieu, characterized by high NLR and PLR, may inhibit cytotoxic T-cell function and promote angiogenesis, thereby compromising anti-tumor immunity [15, 16]. Conversely, a high LMR, indicative of robust lymphocyte counts and low monocyte abundance, may represent a stronger adaptive immune reserve and fewer myeloid-derived suppressor cells, favoring immunotherapy response [17, 18]. However, due to the presence of the blood-brain barrier and the unique characteristics of the intracranial tumor immune microenvironment (TIME), responses to treatment are not always consistent between intracranial and extracranial lesions [19, 20]. This biological compartmentalization raises a critical question: Can peripheral blood biomarkers reliably predict outcomes behind the blood-brain barrier? To date, studies systematically investigating NLR, PLR, and LMR specifically for predicting intracranial response and survival in driver gene-negative NSCLC patients with brain metastases treated with first-line chemoimmunotherapy remain very limited.
Based on this, the present study aims to clearly investigate, via a retrospective cohort analysis, the associations of NLR, PLR, and LMR with iORR and survival outcomes in driver gene-negative NSCLC patients with brain metastases, thereby validating their potential as simple and effective predictive biomarkers to provide a basis for early identification of high-risk patients and formulation of individualized treatment strategies in clinical practice.
Methods
Study design and patient cohort
This study was a dual-center, retrospective cohort study conducted at Ningbo Medical Center Lihuili Hospital and Ninghai First Hospital. By querying the medical record management systems of both institutions, we consecutively enrolled patients with driver gene-negative non-small cell lung cancer and parenchymal brain metastases who visited either hospital between January 2019 and June 2024 and met the following criteria. Inclusion criteria were: (1) histologically or cytologically confirmed NSCLC; (2) brain parenchymal metastases confirmed by cranial MRI; (3) confirmed wild-type status for common driver genes (e.g., EGFR, ALK, ROS1) by ARMS-PCR or next-generation sequencing (NGS); (4) age ≥ 18 years; (5) receipt of platinum-based doublet chemotherapy combined with immune checkpoint inhibitors as first-line systemic therapy. Specifically, patients with adenocarcinoma histology received pemetrexed plus platinum (cisplatin or carboplatin) in combination with a PD-1 inhibitor, while those with non-adenocarcinoma histology received paclitaxel plus platinum combined with a PD-1 inhibitor. The PD-1 inhibitors administered included pembrolizumab, sintilimab, tislelizumab, or camrelizumab, administered per standard dosing schedules. (6) availability of complete blood count results within one week before treatment initiation and serial imaging data suitable for efficacy evaluation. Exclusion criteria were: (1) prior whole-brain radiotherapy (WBRT) or stereotactic radiotherapy (SRT) before initiation of first-line therapy; (2) receipt of brain radiotherapy within 3 cycles after starting chemoimmunotherapy; (3) presence of active autoimmune diseases or long-term use of immunosuppressants; (4) evidence of acute infection within one week before treatment or use of glucocorticoids at a daily dose equivalent to > 10 mg prednisone; (5) incomplete clinical data or loss to follow-up. The study protocol was approved by the Ethics Committee of Ningbo Medical Center Lihuili Hospital, which waived the requirement for informed consent.
Data collection and variable definitions
Patient demographic data, clinicopathological characteristics, and treatment regimens were collected via the electronic medical record system. Systemic inflammatory indices (NLR, PLR, LMR) were calculated based on complete blood count results obtained within one week before treatment initiation. All blood samples were obtained before the initiation of any corticosteroid therapy for brain metastases-related edema. NLR: neutrophil-to-lymphocyte ratio; PLR: platelet-to-lymphocyte ratio; LMR: lymphocyte-to-monocyte ratio. Intracranial radiotherapy was categorized into two timing variables: (1) first-line intracranial radiotherapy, defined as radiotherapy administered after the completion of at least three cycles of first-line chemoimmunotherapy; (2) any intracranial radiotherapy, defined as radiotherapy received at any point during the entire treatment course.
Outcome indicators and definitions
Short-term efficacy assessment included the objective response rate (ORR) for both intracranial and extracranial lesions, evaluated according to RECIST 1.1 criteria. Intracranial efficacy was categorized as intracranial complete response (iCR), intracranial partial response (iPR), intracranial stable disease (iSD), and intracranial progressive disease (iPD). Extracranial efficacy was defined similarly. ORR was defined as the proportion of patients achieving CR plus PR. Survival follow-up was conducted until June 30, 2025. Progression-free survival (PFS) was used to describe the time span from the commencement of treatment to either radiological confirmation of disease progression or death from any cause; intracranial progression-free survival (iPFS) and extracranial progression-free survival (ePFS) were defined accordingly; overall survival (OS) was defined as the time from treatment initiation to death from any cause. For patients lost to follow-up or still alive at the study cutoff date, survival data were censored at the last follow-up date.
Statistical methods
SPSS software version 26.0 was used for all statistical analyses. To evaluate the predictive ability of inflammatory indices for intracranial objective response rate (iORR), we first determined the optimal cutoff values for NLR, PLR, and LMR. This was done using receiver operating characteristic (ROC) curve analysis on the entire cohort of 94 patients, with the cutoff selected to maximize Youden’s index. To address the potential optimism bias associated with deriving and validating cutoff values from the same dataset, we performed internal validation using bootstrap resampling. Patients were dichotomized into high-level and low-level groups based on these cutoff values. Categorical variables were presented as frequencies and percentages, and comparisons between groups were performed using the χ² test or Fisher’s exact test. Survival analysis was conducted using the Kaplan-Meier method, and differences between groups were compared using the log-rank test. To identify independent prognostic factors, we performed multivariate Cox proportional hazards regression analysis. Candidate variables for inclusion in the multivariate model were selected based on clinical relevance and statistical significance in univariate analysis (P < 0.1). The following variables were considered as candidates: age, sex, PD-L1 expression, number of brain metastases, first-line intracranial radiotherapy, NLR, PLR, and LMR. we assessed potential multicollinearity among these inflammatory indices. Variance inflation factors (VIF) were calculated for each index in the multivariate Cox model. A VIF value > 5 was considered indicative of problematic collinearity. All statistical tests were two-sided, and a P value < 0.05 was considered statistically significant.
Results
Patient characteristics
A total of 94 eligible patients with driver gene-negative NSCLC and brain metastases were ultimately included in this study, and their detailed baseline clinicopathological characteristics are summarized in Table 1. The median follow-up time was 34.0 months (95% CI: 31.7–36.3). By the end of follow-up, 67 of the 94 patients (71.3%) had died, and 27 patients (28.7%) were alive. Regarding disease progression, 79 patients (84.0%) experienced intracranial progression, while 15 patients (16.0%) remained free of intracranial recurrence. The median age of patients was 64 years, with a male predominance (68.1%). A notable characteristic is that 78.7% of patients received intracranial radiotherapy during the course of their disease, and 53.2% received it during first-line systemic therapy.
Table 1.
Baseline demographic and clinical characteristics of the study cohort
| Characteristics | Number of patients | % |
|---|---|---|
| Patient number | 94 | 100 |
| Age, years | ||
| Median (range) | 64.18 (43–78) | |
| < 65 | 49 | 52.1 |
| ≥ 65 | 45 | 47.9 |
| Gender | ||
| Female | 30 | 31.9 |
| Male | 64 | 68.1 |
| Drinking | ||
| No | 62 | 66.0 |
| Yes | 32 | 34.0 |
| Smoking | ||
| No | 39 | 41.5 |
| Yes | 55 | 58.5 |
| Histologic subtype | ||
| Adenocarcinoma | 78 | 83.0 |
| Non-adenocarcinoma | 16 | 17.0 |
| PD-L1 | ||
| < 1% | 17 | 18.1 |
| ≥ 1% | 29 | 30.9 |
| Unknown | 48 | 51.0 |
| Number of brain metastases | ||
| 1–5 | 46 | 48.9 |
| > 5 | 48 | 51.1 |
| Metastatic site | ||
| Brain metastasis only | 32 | 34.0 |
| Concomitant metastasis | 62 | 66.0 |
| Intracranial radiotherapy | ||
| No | 20 | 21.3 |
| Yes | 74 | 78.7 |
| First-Line Intracranial radiotherapy | ||
| No | 44 | 46.8 |
| Yes | 50 | 53.2 |
Systemic inflammatory indices predict ORR
To evaluate the predictive ability of inflammatory indices for initial treatment response, we first and foremost analyzed their association with ORR. Using ROC curve analysis, we determined the optimal cutoff values for NLR, PLR, and LMR to predict iORR as 3.962, 151.385, and 2.775, respectively (Fig. 1a-c). The area under the curve (AUC) for NLR, PLR, and LMR was 0.642 (95% CI: 0.529–0.755, P = 0.018), 0.691 (95% CI: 0.583–0.800.583.800, P = 0.001), and 0.774 (95% CI: 0.677–0.871, P = 0.001), respectively, with LMR demonstrating the highest discriminative power. To assess the robustness of these estimates and mitigate potential optimism bias from deriving and validating cutoffs in the same cohort, we performed bootstrap internal validation with 1000 resamples. The bias-corrected AUCs for NLR, PLR, and LMR were 0.646 (95% CI: 0.521–0.749), 0.695 (95% CI: 0.576–0.793), and 0.779 (95% CI: 0.670–0.865), respectively, which were similar to the original AUCs (0.642, 0.691, and 0.774). The analysis revealed that levels of systemic inflammatory indices were significantly associated with iORR. Specifically, high NLR (P = 0.001) and high PLR (P = 0.001) predicted lower iORR; conversely, high LMR was a strong predictor of higher iORR (P = 0.001). Notably, these indices demonstrated consistent predictive value for the extracranial objective response rate (eORR) (all P < 0.05), suggesting that their predictive capacity, while particularly impactful for the intracranial compartment, is reflective of a systemic treatment response. Details are provided in Table 2.
Fig. 1.
a–c Receiver operating characteristic curve of neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and lymphocyte-to-monocyte ratio (LMR) for predicting intracranial objective response
Table 2.
Associations of NLR, PLR and LMR with clinicopathological characteristics
| Characteristics | NLR | PLR | LMR | ||||||
|---|---|---|---|---|---|---|---|---|---|
| ≤ 3.962 | > 3.962 | P-value | ≤ 151.385 | > 151.385 | P-value | ≤ 2.775 | > 2.775 | P-value | |
| Age, years | 0.472 | 0.137 | 0.065 | ||||||
| < 65 | 40 (81.6%) | 9 (18.4%) | 26 (53.1%) | 23 (46.9%) | 19 (38.8%) | 30 (61.2%) | |||
| ≥ 65 | 34 (75.6%) | 11 (24.4%) | 17 (37.8%) | 28 (62.2%) | 26 (57.8%) | 19 (42.2%) | |||
| Gender | 0.739 | 0.571 | 0.777 | ||||||
| Female | 23 (76.7%) | 7 (23.3%) | 15 (50.0%) | 15 (50.0%) | 15 (50.0%) | 15 (50.0%) | |||
| Male | 51 (79.7%) | 13 (20.3%) | 28 (43.8%) | 36 (56.3%) | 30 (46.9%) | 34 (53.1%) | |||
| Drinking | 0.526 | 0.780 | 0.109 | ||||||
| No | 50 (80.6%) | 12 (19.4%) | 29 (46.8%) | 33 (53.2%) | 26 (41.9%) | 36 (58.1%) | |||
| Yes | 24 (75.0%) | 8 (25.0%) | 14 (43.8%) | 18 (56.2%) | 19 (59.4%) | 13 (40.6%) | |||
| Smoking | 0.384 | 0.626 | 0.124 | ||||||
| No | 29 (74.4%) | 10 (25.6%) | 19 (48.7%) | 20 (51.3%) | 15 (38.5%) | 24 (61.5%) | |||
| Yes | 45 (81.8%) | 10 (18.2%) | 24 (43.6%) | 31 (56.4%) | 30 (54.5%) | 25 (45.5%) | |||
| Histologic subtype | 0.082 | 0.201 | 0.199 | ||||||
| Adenocarcinoma | 64 (82.1%) | 14 (17.9%) | 38 (48.7%) | 40 (51.3%) | 35 (44.9%) | 43 (55.1%) | |||
| Non-adenocarcinoma | 10 (62.5%) | 6 (37.5%) | 5 (31.3%) | 11 (68.7%) | 10 (62.5%) | 6 (37.5%) | |||
| PD-L1 | 0.113 | 0.699 | 0.564 | ||||||
| < 1% | 10 (58.8%) | 7 (41.2%) | 7 (41.2%) | 10 (58.8%) | 10 (61.5%) | 7 (38.5%) | |||
| ≥ 1% | 24 (82.8%) | 5 (17.2%) | 12 (41.4%) | 17 (58.6%) | 14 (45.5%) | 15 (54.5%) | |||
| Unknown | 40 (83.3%) | 8 (16.7%) | 24 (50.0%) | 24 (50.0%) | 21 (48.8%) | 27 (51.2%) | |||
| Number of brain metastases | 0.105 | 0.094 | 0.100 | ||||||
| 1–5 | 33 (71.7%) | 13 (28.3%) | 17 (37.5%) | 29 (62.5%) | 26 (56.5%) | 20 (43.5%) | |||
| > 5 | 41 (85.4%) | 7 (14.6%) | 26 (54.3%) | 22 (45.7%) | 19 (39.6%) | 29 (60.4%) | |||
| Metastatic site | 0.667 | 0.874 | 0.767 | ||||||
| Brain metastasis only | 26 (81.3%) | 6 (18.7%) | 15 (46.9%) | 17 (53.1%) | 16 (50.0%) | 16 (50.0%) | |||
| Concomitant metastasis | 48 (77.4%) | 14 (22.6%) | 28 (45.2%) | 34 (54.8%) | 29 (46.8%) | 33 (53.2%) | |||
| Intracranial radiotherapy | 0.759 | 0.349 | 0.772 | ||||||
| No | 15 (75.0%) | 5 (25.0%) | 11 (55.0%) | 9 (45.0%) | 9 (45.0%) | 11 (55.0%) | |||
| Yes | 59 (79.7%) | 15 (20.3%) | 32 (43.2%) | 42 (56.8%) | 36 (48.6%) | 38 (51.4%) | |||
| First-Line Intracranial radiotherapy | 0.183 | 0.377 | 0.103 | ||||||
| No | 32 (72.7%) | 12 (27.3%) | 18 (40.9%) | 26 (59.1%) | 25 (56.8%) | 19 (43.2%) | |||
| Yes | 42 (84.0%) | 8 (16.0%) | 25 (50.0%) | 25 (50.0%) | 20 (40.0%) | 30 (60.0%) | |||
| Intracranial treatment response | 0.001 | 0.001 | 0.001 | ||||||
| ORR | 48 (92.3%) | 4 (7.7%) | 32 (61.5%) | 20 (38.5%) | 14 (26.9%) | 38 (73.1%) | |||
| Non-ORR | 26 (61.9%) | 16 (38.1%) | 11 (26.2%) | 31 (73.8%) | 31 (73.8%) | 11 (26.2%) | |||
| Subgroup: known PD-L1 Expression | 0.002 | 0.108 | 0.003 | ||||||
| ORR | 23 (92.0%) | 2 (8.0%) | 13 (52.0%) | 12 (48.0%) | 8 (32.0%) | 17 (68.0%) | |||
| Non-ORR | 11 (52.4%) | 10 (47.6%) | 6 (28.6%) | 15 (71.4%) | 16 (76.2%) | 5 (23.8%) | |||
| Extracranial treatment response | 0.012 | 0.007 | 0.004 | ||||||
| ORR | 49 (87.5%) | 7 (12.5%) | 32 (57.1%) | 24 (42.9%) | 20 (35.7%) | 36 (64.3%) | |||
| Non-ORR | 25 (65.8%) | 13 (34.2%) | 11 (28.9%) | 27 (71.1%) | 25 (65.8%) | 13 (34.2%) | |||
ORR: objective response rate, patients achieving complete response or partial response;
Non-ORR: stable disease and progressive disease, patients without an objective response
Association between systemic inflammatory indices and survival outcomes
In the univariate analysis of the overall population, the high LMR group demonstrated significantly superior overall survival compared to the low LMR group (median OS: 26.6 months vs. 15.5 months, P = 0.005, Fig. 2a). The low PLR group also showed better OS (median OS: 26.6 months vs. 15.5 months, P = 0.029, Fig. 2b), while NLR was not significantly associated with OS (median OS: 23.5 months vs. 16.2 months, P = 0.236, Fig. 2c). VIF calculated in the multivariate Cox model were 1.333 for NLR, 1.426 for PLR, and 1.446 for LMR, all well below the threshold of 5, indicating no significant multicollinearity. In the multivariate Cox regression analysis, LMR was confirmed as an independent prognostic factor for OS (HR = 0.573, 95% CI: 0.338–0.970, P = 0.038, Table 3), whereas PLR did not demonstrate independent prognostic value (P = 0.216, Table 3).
Fig. 2.
a–c Overall survival curves for lymphocyte-to-monocyte ratio (LMR), platelet-to-lymphocyte ratio (PLR), and neutrophil-to-lymphocyte ratio (NLR) in the entire cohort
Table 3.
Multivariable Cox regression analysis of factors associated with overall survival in the entire cohort
| Prognostic factors | Overall survival | ||
|---|---|---|---|
| HR | 95% CI | P-value | |
|
PLR (≤ 151.385 vs. > 151.385) |
1.400 | 0.822–2.385 | 0.216 |
|
LMR (≤ 2.775 vs.> 2.775) |
0.573 | 0.338–0.970 | 0.038 |
Sensitivity analysis in patients with known PD-L1 expression
Given that 51.0% of patients had unknown PD-L1 status, we conducted a sensitivity analysis in the subgroup with documented PD-L1 expression (n = 46). In this cohort, high NLR remained significantly associated with lower iORR (P = 0.002), and high LMR maintained its significant association with higher iORR (P = 0.003). However, PLR was no longer significantly associated with iORR (P = 0.108), despite its significance in the full cohort. For overall survival, although the high LMR group showed a numerically longer median OS (34.3 vs. 17.5 months), the difference did not reach statistical significance in univariate analysis (HR = 0.498, 95% CI: 0.227–1.091, P = 0.075, Fig. 3a). In contrast, NLR and PLR showed no significant association with OS (P = 0.295 and P = 0.255, Fig. 3b-c).
Fig. 3.
a–c Overall survival curves for lymphocyte-to-monocyte ratio (LMR), neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR) in the subgroup of patients with known PD-L1 expression
Intracranial radiotherapy and exploratory subgroup analysis
We confirmed that receiving intracranial radiotherapy during first-line therapy significantly prolonged iPFS (median: 13.2 months vs. 8.0 months, P = 0.008, Fig. 4), though it did not translate into a significant OS benefit (P = 0.168, Fig. 5a). Additionally, receipt of intracranial radiotherapy at any time during the entire treatment course was not associated with OS (P = 0.929, Fig. 5b). Analyses of other relevant clinical characteristics are presented in Table 4.
Fig. 4.
Kaplan-Meier curves for intracranial progression-free survival by whether patients received first-line intracranial radiotherapy
Fig. 5.
a, b Overall survival curves for patients received first-line intracranial radiotherapy and any intracranial radiotherapy
Table 4.
Univariate analysis of factors associated with intracranial progression-free survival, extracranial progression-free survival, and overall survival
| Prognostic factors | Intracranial progression-free survival | Extracranial progression-free survival | Overall survival | ||||||
|---|---|---|---|---|---|---|---|---|---|
| HR | 95% CI | P-value | HR | 95% CI | P-value | HR | 95% CI | P-value | |
| Age, years | |||||||||
| < 65 | 1 | 1 | 1 | ||||||
| ≥ 65 | 1.488 | 0.949–2.332 | 0.083 | 1.266 | 0.816–1.964 | 0.292 | 1.446 | 0.891–2.346 | 0.136 |
| Gender | |||||||||
| Female | 1 | 1 | 1 | ||||||
| Male | 0.634 | 0.395–1.018 | 0.059 | 0.673 | 0.420–1.077 | 0.098 | 0.671 | 0.408–1.103 | 0.115 |
| Drinking | |||||||||
| No | 1 | 1 | 1 | ||||||
| Yes | 1.002 | 0.625–1.606 | 0.993 | 0.975 | 0.615–1.546 | 0.915 | 1.003 | 0.601–1.674 | 0.992 |
| Smoking | |||||||||
| No | 1 | 1 | 1 | ||||||
| Yes | 1.064 | 0.673–1.681 | 0.792 | 0.913 | 0.583–1.430 | 0.692 | 1.144 | 0.692–1.889 | 0.600 |
| Histologic subtype | |||||||||
| Adenocarcinoma | 1 | 1 | 1 | ||||||
| Non-adenocarcinoma | 1.651 | 0.936–2.914 | 0.084 | 1.526 | 0.875–2.660 | 0.136 | 1.502 | 0.801–2.818 | 0.205 |
| PD-L1 | |||||||||
| < 1% | 1 | 1 | 1 | ||||||
| ≥ 1% | 0.892 | 0.459–1.736 | 0.737 | 0.775 | 0.401–1.495 | 0.447 | 1.190 | 0.548–2.584 | 0.659 |
| Number of brain metastases | |||||||||
| 1–5 | 1 | 1 | 1 | ||||||
| > 5 | 1.285 | 0.819–2.016 | 0.275 | 1.340 | 0.862–2.083 | 0.193 | 1.231 | 0.757–2.004 | 0.402 |
| Metastatic site | |||||||||
| Brain metastasis only | 1 | 1 | 1 | ||||||
| Concomitant metastasis | 1.064 | 0.662–1.710 | 0.799 | 1.297 | 0.806–2.088 | 0.284 | 1.071 | 0.632–1.815 | 0.799 |
| Intracranial radiotherapy | |||||||||
| No | 1 | 1 | 1 | ||||||
| Yes | 0.888 | 0.503–1.569 | 0.682 | 1.235 | 0.704–2.168 | 0.462 | 0.973 | 0.528–1.793 | 0.929 |
| First-Line Intracranial radiotherapy | |||||||||
| No | 1 | 1 | 1 | ||||||
| Yes | 0.538 | 0.337–0.860 | 0.010 | 0.815 | 0.521–1.277 | 0.372 | 0.705 | 0.427–1.164 | 0.172 |
| NLR | |||||||||
| ≤ 3.962 | 1 | 1 | 1 | ||||||
| > 3.962 | 0.991 | 0.563–1.746 | 0.976 | 1.125 | 0.656–1.929 | 0.670 | 1.417 | 0.793–2.533 | 0.239 |
| PLR | |||||||||
| ≤ 151.385 | 1 | 1 | 1 | ||||||
| > 151.385 | 1.159 | 0.740–1.816 | 0.519 | 0.943 | 0.606–1.465 | 0.793 | 1.720 | 1.051–2.815 | 0.031 |
| LMR | |||||||||
| ≤ 2.775 | 1 | 1 | 1 | ||||||
| > 2.775 | 0.855 | 0.547–1.336 | 0.492 | 0.803 | 0.514–1.254 | 0.335 | 0.506 | 0.310–0.824 | 0.006 |
Given that radiotherapy is a key modality for managing brain metastases, we performed an exploratory analysis to investigate whether the predictive value of inflammatory indices was maintained in the subgroup of patients who received intracranial radiotherapy (n = 74). In this subgroup (Table 5), the survival advantages of PLR and LMR remained robust. The low PLR group demonstrated a significantly superior median OS compared to the high PLR group (27.9 months vs. 14.0 months, P = 0.003, Fig. 6a). Similarly, the high LMR group showed a significantly better median OS than the low LMR group (26.8 months vs. 13.6 months, P = 0.001, Fig. 6b). Additionally, the younger age group exhibited a trend toward better median OS (27.9 months vs. 13.9 months, P = 0.059, Fig. 6c). To ensure that the observed survival benefits associated with inflammatory indices were not merely reflections of radiotherapy timing, we included first-line radiotherapy as a covariate in multivariate Cox models. Multivariate analysis further confirmed that within this subgroup, only LMR remained an independent prognostic factor for OS (HR = 0.523, 95% CI: 0.290–0.941, P = 0.031), whereas neither age, PLR, nor the timing of first-line intracranial radiotherapy demonstrated independent prognostic value for OS in the final model (Table 6).
Table 5.
Univariate analysis of factors associated with overall survival in patients who received intracranial radiotherapy
| Prognostic factors | Overall survival | ||
|---|---|---|---|
| HR | 95% CI | P-value | |
| Age, years | |||
| < 65 | 1 | ||
| ≥ 65 | 1.692 | 0.981–2.919 | 0.059 |
| Gender | |||
| Female | 1 | ||
| Male | 0.771 | 0.440–1.350 | 0.363 |
| Drinking | |||
| No | 1 | ||
| Yes | 1.152 | 0.646–2.054 | 0.632 |
| Smoking | |||
| No | 1 | ||
| Yes | 1.471 | 0.814–2.655 | 0.201 |
| Histologic subtype | |||
| Adenocarcinoma | 1 | ||
| Non-adenocarcinoma | 1.783 | 0.861–3.691 | 0.119 |
| PD-L1 | |||
| < 1% | 1 | ||
| ≥ 1% | 1.016 | 0.452–2.284 | 0.969 |
| Number of brain metastases | |||
| 1–5 | 1 | ||
| > 5 | 0.870 | 0.506–1.494 | 0.612 |
| Metastatic site | |||
| Brain metastasis only | 1 | ||
| Concomitant metastasis | 1.098 | 0.609–1.981 | 0.755 |
| First-Line Intracranial radiotherapy | |||
| No | 1 | ||
| Yes | 0.617 | 0.341–1.114 | 0.109 |
| NLR | |||
| ≤ 3.962 | 1 | ||
| > 3.962 | 1.570 | 0.819–3.011 | 0.174 |
| PLR | |||
| ≤ 151.385 | 1 | ||
| > 151.385 | 2.288 | 1.303–4.017 | 0.004 |
| LMR | |||
| ≤ 2.775 | 1 | ||
| > 2.775 | 0.420 | 0.242–0.727 | 0.002 |
Fig. 6.
a–c Kaplan-Meier curves for overall survival stratified by platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), and age in the subgroup of patients who received intracranial radiotherapy
Table 6.
Multivariable analysis of factors associated with overall survival in patients who received intracranial radiotherapy
| Prognostic factors | Overall survival | ||
|---|---|---|---|
| HR | 95% CI | P-value | |
|
Age, years (< 65 vs.≥ 65) |
1.619 | 0.932–2.810 | 0.087 |
|
First-Line Intracranial radiotherapy (< No vs.≥ Yes) |
0.726 | 0.395–1.332 | 0.300 |
|
PLR (≤ 151.385 vs. > 151.385) |
1.810 | 0.990–3.311 | 0.054 |
|
LMR (≤ 2.775 vs.> 2.775) |
0.548 | 0.302–0.995 | 0.048 |
Discussion
This dual-center retrospective study provides the first systematic evidence for the utility of pretreatment inflammatory indices in driver gene-negative NSCLC with brain metastases by demonstrating that these markers (NLR, PLR, LMR) are strongly associated with iORR to first-line chemoimmunotherapy, an association that was strongest for LMR. This finding provides an easily accessible solution to the clinical dilemma of high intracranial primary resistance rates and the lack of effective predictive tools in this population. A key discovery of this research is the notable correlation between pretreatment NLR, PLR, and LMR and iORR. This not only supports the widely recognized concept that systemic inflammatory status is a key host factor influencing immunotherapy response [21, 22], but more importantly, it successfully extends this theoretical framework to the “intracranial” compartment, a special and therapeutically challenging anatomical site. A critical question is how peripheral blood indices can predict response behind the blood-brain barrier (BBB). These findings suggest that peripheral immune status may reflect, at least in part, the intracranial immune environment, possibly through neuro-immune crosstalk. Systemic inflammation has been associated with modulation of BBB integrity and immune cell trafficking, which may influence the brain metastatic niche [23–25]. Our results indicate that peripheral blood immune status can reflect intracranial immune activity to a considerable extent. This finding deepens our understanding of the connection between the systemic and local aspects of TIME and provides a new, highly cost-effective direction for the application of the “liquid biopsy” concept in neuro-oncology.
In the survival analysis, LMR demonstrated robust and independent prognostic value across different cohorts. In the entire study cohort, a high LMR was associated with a nearly doubled median OS and remained significant in multivariate analysis (HR = 0.573, P = 0.038). Notably, this prognostic consistency of LMR was further validated in the subgroup receiving intracranial radiotherapy (n = 74), where a high LMR was also associated with significantly prolonged median OS and remained an independent predictor after adjusting for other factors (HR = 0.523, P = 0.031). These findings align with previous studies that have highlighted LMR as a key prognostic marker in advanced NSCLC [12, 26, 27]. We propose that the stable predictive ability of LMR across different treatment contexts stems from its dual capacity to reflect a favorable systemic immune phenotype: it indicates robust lymphocyte-mediated adaptive anti-tumor immunity alongside a lower burden of pro-tumor monocytes and myeloid-derived suppressor cells. This balanced immune state may reflect a systemic environment conducive to both initial intracranial disease control and sustained long-term anti-tumor activity. Consequently, LMR exhibits reliable prognostic discrimination in diverse clinical settings, regardless of whether local radiotherapy is combined with systemic therapy.
Notably, although PLR showed a significant association with OS in univariate analysis, it was not an independent prognostic factor in the overall multivariate model (P = 0.216). This contrasts with some studies in NSCLC without brain metastases [28], suggesting that in the context of established brain metastases, dominant prognostic drivers (e.g., intracranial disease progression) or altered host-tumor dynamics may diminish the independent contribution of PLR to OS. In this clinical setting, its value may be more prominent as a predictor of early treatment response rather than long-term survival.
Exploratory, hypothesis-generating analysis of the radiotherapy subgroup provided deeper insight. Given the post-hoc nature of this analysis, the findings should be interpreted cautiously and regarded as preliminary evidence to guide future research rather than as definitive conclusions. A noteworthy observation is the context-dependent shift in the prognostic significance of PLR: while it showed no independent predictive value in the overall population (P = 0.216), its P-value approached the threshold of statistical significance in the multivariate analysis of patients who received intracranial radiotherapy (P = 0.053). This shift suggests that radiotherapy may alter the strength of the association between PLR and patient prognosis. The local inflammatory response, vascular endothelial injury, and platelet activation induced by radiotherapy could amplify the weight of systemic inflammatory status (reflected by a high PLR) on outcomes. Furthermore, radiotherapy-induced remodeling of the tumor microenvironment and its interaction with systemic immunity may render the inflammatory and coagulation pathways represented by PLR more biologically relevant in the post-radiotherapy phase. Although the P-value did not reach significance, this trend indicates that PLR may retain prognostic relevance in specific treatment contexts—particularly when combined with radiotherapy—warranting further validation in larger or more homogeneous radiotherapy cohorts.
In this radiotherapy subgroup, although both low PLR and high LMR were associated with significantly better OS in univariate analysis, only LMR retained independent prognostic significance in multivariate analysis. These results indicate that the favorable survival signal associated with LMR is more fundamental and not merely a surrogate for other factors such as PLR or age. The biological perturbation induced by radiotherapy—including local inflammation and antigen release [29–32]—likely creates a critical juncture at which a pre-existing, robust adaptive immune foundation, reflected by a high LMR, becomes paramount for achieving long-term survival benefit. In the sensitivity analysis restricted to patients with known PD-L1 expression (n = 46), we observed that NLR and LMR remained significantly associated with iORR (P = 0.002 and P = 0.003, respectively), reinforcing their potential as robust predictors of intracranial response, even after accounting for PD-L1 status. However, PLR lost its significant association with iORR in this subgroup (P = 0.108), suggesting that its predictive value may be more susceptible to confounding by PD-L1 expression or to the reduced statistical power in smaller cohorts. This discrepancy highlights the need for cautious interpretation of PLR-based predictions in patients with known PD-L1 status and calls for further investigation into the interplay between platelet-related inflammation and PD-L1-driven immune evasion. Regarding overall survival, although patients with high LMR exhibited a numerically longer median OS (34.3 vs. 17.5 months), the difference did not reach statistical significance in univariate analysis (P = 0.075). This trend, while not definitive, aligns with the independent prognostic role of LMR observed in the full cohort and in the radiotherapy subgroup. The lack of significance may be attributed to the reduced sample size and consequent loss of statistical power, rather than a true absence of effect. In contrast, NLR and PLR showed no meaningful association with OS in this subgroup (both P > 0.2), consistent with their limited role in predicting long-term survival beyond initial treatment response. Collectively, these findings suggest that while NLR and LMR consistently predict intracranial response regardless of PD-L1 data availability, their prognostic value for survival may be attenuated in smaller, selected populations. Future prospective studies with comprehensive PD-L1 annotation are warranted to validate these observations and to clarify whether the integration of inflammatory indices with PD-L1 expression can refine risk stratification in this challenging patient population. Notably, the presence of liver metastases has been reported to attenuate the efficacy of immune checkpoint inhibitors in NSCLC [33]. Although our cohort included patients with various metastatic sites, the relatively small sample size precluded a detailed subgroup analysis based on liver metastasis status; this remains an important consideration for future investigations.
Beyond the inflammatory indices evaluated in this study, several other systemic inflammation-based scores have been implicated as prognostic markers in NSCLC, including the Glasgow Prognostic Score (GPS), systemic inflammation response index (SIRI), prognostic nutritional index (PNI), and serum lactate dehydrogenase (LDH) levels [34]. Although these markers were not available in our retrospective cohort due to the absence of routine collection of certain parameters (e.g., C-reactive protein) and the retrospective design, their potential utility in the context of driver gene-negative NSCLC with brain metastases warrants discussion. In particular, the interplay between systemic inflammation, nutritional status, and tumor metabolism may provide complementary insights beyond those offered by NLR, PLR, and LMR alone. For instance, combining LMR with PNI could potentially refine risk stratification by capturing both immune competence and nutritional reserve [35]. Future prospective studies should consider integrating a broader panel of inflammatory and nutritional markers to develop more comprehensive predictive models.
We acknowledge several limitations of this study. The retrospective, dual-center design and moderate sample size may introduce selection bias and limit the statistical power of subgroup analyses. The measurement of inflammatory indices at a single time point, along with heterogeneity in radiotherapy timing and technique, are additional constraints. Future prospective, multi-center studies with larger cohorts are warranted to validate our findings, explore dynamic changes in these indices, incorporate standardized performance status assessments, and develop integrated predictive models.
Despite these limitations, our findings hold immediate clinical relevance. Pretreatment assessment of NLR, PLR, and LMR provides a simple, cost-effective tool for early risk stratification. Patients with an unfavorable inflammatory profile (high NLR/PLR, low LMR) may benefit from more vigilant intracranial monitoring or earlier consideration of multidisciplinary interventions, such as upfront integration of radiotherapy. Conversely, a favorable profile, particularly a high LMR, may reinforce confidence in ongoing systemic therapy.
Conclusion
This study provides the first systematic evidence supporting the predictive utility of pretreatment peripheral blood inflammatory indices in driver gene-negative NSCLC with brain metastases. We demonstrated that NLR, PLR, and LMR are significantly associated with iORR to first-line chemoimmunotherapy, an association that was strongest for LMR. Furthermore, LMR emerged as an independent prognostic factor for overall survival, consistently across the overall cohort and in the radiotherapy subgroup. These findings suggest that peripheral immune-inflammatory status reflects intracranial treatment response and long-term prognosis despite the blood–brain barrier.
Author contributions
Jinxian He and Yang Zhou contributed to the conception and design of the study. Mengqiu Tang and Tian Chen wrote the article. Peijin Wang and Shiwei Li contributed to acquisition and analysis of the data. Jinxian He and Yang Zhou participated in revising of the article. All authors reviewed the manuscript.
Funding
This work was supported by the National Natural Science Foundation of China (12575364), the Natural Science Foundation of Ningbo (2023J031), the Zhejiang Medical and Health Science and Technology Plan Project (2025KY1302) and the Huili Medical and Health Science and Technology Plan Project (2025ZDY001).
Data availability
The data used to support the findings of this study are available from the corresponding author upon request.
Declarations
Ethics approval and consent to participate
This study was conducted in accordance with the principles of the Declaration of Helsinki. The Ethics Committee of Ningbo Medical Center Lihuili Hospital approved the study protocol (approval number: KY2025SL411-01). As this was a retrospective review, patient names and other identifying information were anonymized or maintained confidentially.
Consent for publication
All authors have read this manuscript and agree to publish.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Mengqiu Tang and Tian Chen are co-first authors.
Contributor Information
Jinxian He, Email: hejinxian@163.com.
Yang Zhou, Email: zhouyang610@163.com.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data used to support the findings of this study are available from the corresponding author upon request.