Peripheral blood inflammatory biomarkers neutrophil/ lymphocyte ratio, platelet/lymphocyte ratio and systemic immune-inflammation index/albumin ratio predict prognosis and efficacy in non-small cell lung cancer patients receiving immunotherapy and opioids

Abstract

Objective

The study aimed to assess the value of pretreatment peripheral blood neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR) and systemic immune-inflammation index/albumin ratio (SII/ALB) for predicting immunotherapy prognosis and efficacy in Non-small cell lung carcinoma (NSCLC) treated with Immune checkpoint inhibitors (ICIs) and opioids.

Methods

A total of 78 NSCLC patients received ICIs and opioids were retrospectively collected. The optimal cut-off values were determined by receiver operating characteristic curves. The univariate and multivariate analysis investigated the effects of NLR, PLR, and SII/ALB on patients prognosis.

Results

NLR and PLR had predictive value of efficacy. SII/ALB > 17.79 was an independent risk factor for worse outcomes.

Conclusion

PLR and SII/ALB have predictive value of efficacy, but NLR was not. SII/ALB > 17.79 suggests a poor prognosis following immunotherapy in NSCLC patients receiving ICIs and opioids.

Lung cancer remains one of the leading causes of cancer-related mortality worldwide [1]. Non-small cell lung carcinoma (NSCLC) accounts for 85-90% of all lung cancer cases, with a diverse range of treatment options available. Several immune checkpoint inhibitors (ICIs) have been approved for first- and second-line treatment of advanced NSCLC. Compared to traditional chemotherapy, ICIs, whether used as monotherapy or in combination with standard chemotherapy, have demonstrated improved survival rates. However, in clinical practice, while focusing on the tumor itself, it is equally crucial to address the symptoms caused by cancer, particularly cancer-related pain. Approximately 58.2% of patients with advanced lung cancer experience pain, which is one of the most distressing symptoms contributing to depression and anxiety [2]. For patients with moderate to severe cancer pain, the use of opioids is essential. However, studies have shown that opioids may reduce both overall survival (OS) and progression-free survival (PFS) in patients undergoing immunotherapy [3], and may negatively impact the efficacy of ICIs in NSCLC patients [4]. Opioids exhibit a dual role in their effects on immune function: they can directly suppress immune responses, yet they may also indirectly improve immune function by alleviating pain [5], thereby influencing the prognosis and efficacy of immunotherapy [6, 7]. Currently, clinical biomarkers such as programmed death-ligand 1 (PD-L1) expression, tumor mutational burden (TMB), and microsatellite instability (MSI) status [8, 9] are used to predict the efficacy of immunotherapy. However, these biomarkers lack specificity for cancer pain patients, are costly, and require sufficient tumor tissue samples. Therefore, there is an urgent need to identify an economical, convenient, and readily accessible predictive biomarker to address the limitations of existing indicators.

Routine blood tests can provide multiple indicators reflecting the inflammatory status of cancer patients, such as absolute neutrophil count, platelet count, and absolute lymphocyte count, as well as derived ratios including the neutrophil-to-lymphocyte ratio (NLR) [10, 11], platelet-to-lymphocyte ratio (PLR) [12, 13], and systemic immune-inflammation index to albumin ratio (SII/ALB) [14]. These composite indicators reflect the immune, inflammatory, and nutritional status of cancer patients and represent novel prognostic markers for malignancies. Given the significance of peripheral blood inflammatory markers in the context of NSCLC, we explored the predictive value of pretreatment blood inflammatory markers in assessing the efficacy of immunotherapy in NSCLC through retrospective analysis. These findings may assist clinicians in predicting the efficacy of immunotherapy in NSCLC patients and in devising appropriate treatment plans to control disease progression and alleviate symptoms, thereby improving patients’ quality of life. However, there is a lack of reported studies on peripheral blood inflammatory markers in NSCLC patients concurrently receiving opioids and immunotherapy. Therefore, this retrospective study aims to investigate the prognostic value of peripheral blood inflammatory markers in NSCLC patients with cancer pain undergoing ICIs treatment.

Materials & methods

Patients

The medical records of 78 patients with NSCLC cancer pain treated with ICIs at Xuzhou Central Hospital from September 01, 2021 to September 01, 2023 were retrospectively analyzed. The inclusion criteria for patients were as follows: (1) aged ≥ 18 years; (2) with moderate-to-severe cancer pain and a numerical rating scale (NRS) score ≥ 4 points; (3) receiving opioid therapy; (4) patients with blood data within 30 days before the first ICI injection; and (5) having at least one lesion amenable to impact measurement according to the Response Evaluation Criteria in Solid tumors (RECIST) V1.1. The exclusion criteria for patients were as follows: (1) those who could not be followed up continuously; (2) those who had a history of infection within 14 days before immunotherapy; (3) those who did not have blood test results within 1 month before the first ICI treatment; and (4) those who did not have imaging data to evaluate the treatment effect. This study was approved by the Ethics Committee of Xuzhou Central Hospital (XZXY-LK-20230822-0144).

Data collection

The clinical and pathological data of the included patients were collected through electronic medical records. A combination of electronic medical records, internet hospitals, telephone calls, letters and outpatient re-examinations were used to record the diagnosis and treatment, laboratory test and imaging results and survival data. The final follow-up visit was ended on 1 September 2023.A numerical rating scale (NRS) 0–10 was used to rate the pain intensity of the patients.The clinical data included patient information and albumin, neutrophil, lymphocyte, and platelet count from routine blood results within 1 week before NLR, PLR, and SII/ALB are calculated according to the following formulas: NLR: neutrophil count/lymphocyte count; PLR: platelet count/lymphocyte count and SII/ALB: platelet count × neutrophil count/lymphocyte count/albumin.

To evaluate the diagnostic value of the biomarkers, receiver operating characteristic (ROC) curves were used to compare the sensitivity, specificity, optimal cut-off value and area under the curve (AUC) of each tested indicator with the gold standard of ‘evaluating whether the best efficacy is effective’. The Youden index was calculated as follows: sensitivity + specificity-1. When the Youden index was the largest, this value was taken as the optimal cut-off value and the sensitivity and specificity of the index were the best. A cut-off value higher than the optimal cutoff was used for the high subgroup, and a value lower than the optimal cutoff was used for the low subgroup.

The efficacy is evaluated according to the RECIST V1.1 which can be classified as complete response (CR), partial response (PR), stable disease (SD), and disease progression (PD). Objective response rate (ORR) and disease control rate (DCR) were used to assess the post-treatment efficacy: (1) ORR = (CR + PR) / (CR + PR + SD + PD) × 100% and (2) DCR = (CR + PR + SD) / (CR + PR + SD + PD) × 100%.The prognosis was evaluated based on PFS which was defined as the time from the start of immunotherapy to disease progression or death due to any cause.

Statistical analysis

SPSS v. 25.0 software was used for analysis. Comparisons of grouped data were made using the Chi-square (χ²) test. The optimal cut-off values for the NLR, PLR, and SII/ALB were derived from the optimal Youden index through ROC curves.

The Kaplan-Meier method was used to construct survival curves and calculate survival rates. The log-rank test was used to perform single-factor analysis and the Cox proportional hazards regression model was used to perform multivariate analyses. A difference of p < 0.05 was considered to indicate statistical significance.

Results

Determination of the optimal cut-off values of the NLR, PLR, and SII/ALB

The results of the ROC curve analysis showed that the optimal cut-off value of the NLR was 3.985 with an AUC of 0.763. Similarly, the optimal cut-off value of the PLR was 195.005 with an AUC of 0.721. The optimal cut-off value of SII/ALB was 17.79 with an AUC of 0.834. Based on the optimal cut-off values, patients were categorized into a high NLR subgroup and low NLR subgroup, a high PLR subgroup and low PLR subgroup and a high SII/ALB subgroup and low SII/ALB subgroup.(Fig. 1).

Fig. 1

The receiver operating characteristic curves of systemic immune-inflammation-to-albumin, neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio NSCLC patients receiving immunotherapy and opioids

Patient characteristics

According to the inclusion and exclusion criteria, a total of 78 NSCLC patients (27 females, 34.6%; 51 males, 65.4%) treated with ICIs and opioids from September 01, 2021, to September 01, 2023, were enrolled in this study. The relationship between NLR, PLR, and SII/ALB and various clinical characteristics of patients was analyzed using the χ² test. The NLR was significantly correlated with smoking History(P = 0.026), Eastern Cooperative Oncology Group performance status(ECOG PS)(P < 0.001), combined medication with ICIs (P = 0.046), and adverse events (P = 0.032). The PLR was significantly correlated with smoking history (P = 0.020), ECOG PS (P < 0.001), disease stage (P = 0.008), lines of ICI treatment (P = 0.004), combined medication with ICIs (P = 0.003), and adverse events (P < 0.001). The SII/ALB was correlated with histological types (P = 0.025), ECOG PS(P < 0.001), disease stage (P = 0.007), lines of ICI treatment (P = 0.002), combined medication with ICIs (P = 0.002), and adverse events (P < 0.001).(Table 1).

Table 1 Clinic and pathologic features of 78 NSCLC patients receiving immunotherapy and opioids

Efficacy evaluation

The Chi-square test was used to assess the associations between the NLR, PLR, SII/ALB and the ORR, DCR of immunotherapy for NSCLC patients treated with ICIs and opioids. The results showed that patients in the low SII/ALB subgroup had a better ORR (35.14%; p = 0.007) and a better DCR (72.97%; p = 0.003) and that patients in the low PLR subgroup had a better DCR (65.31%; p = 0.019) (Table 2).

Table 2 Relationship of NLR, PLR, AndSII/ALB with ORR and DCR of immunotherapy in NSCLC receiving ICIs and opioids

Survival curve

The Kaplan-Meier method was used to plot survival curves and calculate survival rates was assessed using the log-rank test. The Kaplan-Meier survival curve demonstrated that an increased NLR, PLR, and SII/ALB were associated with decreased PFS. The low NLR(11.45 vs. 5.76 months, HR = 0.1367; 95% CI: 0.0674–0.2773, P < 0.001), PLR(13.1 vs. 5.21 months, HR = 0.073; 95% CI: 0.0345–0.1546, P < 0.001), and SII/ALB(13.1 vs. 5.7 months, HR = 0.0812; 95% CI: 0.0415–0.1591, P < 0.001) group had longer PFS after opioid treatment than the high group.(Fig. 2).

Fig. 2

Kaplan–Meier estimates of progression free survival according to SII/ALB (A), NLR (B), PLR (C)

Univariate and multivariable Cox regression analysis models

The univariate Cox regression analysis results revealed that patients with a NRS score of 7–10 (p = 0.004), stage IV disease (p = 0.025), and a high SII/ALB ratio (p < 0.001) had significantly shorter PFS times, indicating that these indices were associated with poor PFS prognosis after immunotherapy in NSCLC patients treated with ICIs and opioids.

Multivariate Cox proportional hazards model analysis revealed that a NRS score of 7–10 (p = 0.007), stage IV disease (p < 0.001), and a high SII/ALB ratio (p < 0.001) were found to be independent risk factors for poor PFS in NSCLC patients treated with ICIs and opioids.(Table 3).

Table 3 Univariate and multivariate Cox proportional hazard regression model survival analysis of SII/ALB, NLR, PLR for PFS

Discussion

To the best of our knowledge, this is the first study to investigate the prognostic value of hematological markers in predicting outcomes for NSCLC patients with cancer pain undergoing ICI therapy. While most previous research has primarily focused on the efficacy of immunotherapy itself, there has been limited attention on NSCLC patients experiencing cancer pain. This study offers an initial exploration into the potential of hematological markers as predictive tools for guiding immunotherapy in this specific patient population. Our findings demonstrate that pre-treatment levels of NLR, PLR, and SII/ALB are significantly associated with both prognosis and treatment efficacy in NSCLC patients with cancer pain receiving ICI therapy.

This retrospective study enrolled in 78 NSCLC patients who received ICIs and opioids. First, the peripheral blood inflammatory markers NLR, PLR and SII/ALB had predictive value for the efficacy of immunotherapy in NSCLC patients receiving opioids and the AUC of the SII/ALB was 0.834 which was better than that of the NLR or PLR. Second, the high NLR, PLR, and SII/ALB groups exhibited significantly higher proportions of patients with ECOG PS ≥ 2 and Grade > 2 adverse events, indicating poorer overall health status in these groups. Third, according to the optimal cut-off value patients with NSCLC receiving opioids in the SII/ALB-low subgroup (SII/ALB ≤ 17.79) had a better ORR and DCR after immunotherapy (35.14 and 72.97%; p < 0.05). Fourth, univariate and multivariate Cox proportional hazards model analysis showed that NRS scores 7–10, stage IV, and SII/ALB>17.79 were independent risk factors for poor PFS from immunotherapy in NSCLC patients treated with opioids.

NSCLC patients with a NRS score of 7–10 exhibit poorer prognoses compared to those with an NRS score of 4–6. This correlation is likely due to the fact that higher NRS scores reflect more severe cancer pain, which is associated with elevated levels of pro-inflammatory cytokines such as IL-1, IL-6, and TNF-α. These cytokines are closely linked to the onset and prognosis of cancer pain in these patients [15]. Furthermore, baseline cancer pain has been identified as a negative prognostic factor in lung cancer patients undergoing immunotherapy [16]. Notably, the development of breakthrough pain in patients with baseline cancer pain is associated with even worse survival outcomes. Additionally, the clinical stage of the disease plays a critical role in prognosis; later stages, particularly stage IV, are linked to poorer outcomes [17]. Advanced-stage cancers generally exhibit a diminished response to immunotherapy, likely due to the secretion of immune-suppressive cytokines, such as TGF-β and IL-10, which drive systemic inflammation and immune suppression [18], thereby weakening the body’s immune response against tumor cells.

The prognostic value of the SII/ALB is better than that of the NLR and PLR in NSCLC patients with cancer pain receiving ICIs. However, relevant clinical studies using peripheral blood inflammatory markers to predict and assess the predictive value of three different peripheral blood inflammatory markers for efficacy and prognosis in NSCLC patients treated with ICIs and opioids not been reported. The results of univariate and multivariate survival analyses showed that the SII/ALB>17.79 was an independent risk factor affecting the prognosis of NSCLC patients treated with ICIs and opioids. These findings suggest a potential interplay between systemic inflammation, nutritional status, and immune function, collectively influencing tumor progression and clinical outcomes. Inflammation may exacerbate malnutrition by enhancing catabolic processes and impairing nutrient absorption, while malnutrition, in turn, can amplify inflammatory responses [19]. In the context of malignancy, excessive levels of pro-inflammatory cytokines synergistically impair hepatic albumin synthesis [20].Collectively, these mechanisms highlight the close relationship between albumin levels and systemic inflammation.

In tumor-associated acute inflammation, neutrophils, the most abundant leukocytes, are often the first immune cells to infiltrate inflammatory sites, demonstrating robust homing capabilities toward tumor regions [21]. Platelets, on the other hand, support cancer stem cell survival [22] and protect tumor cells from the cytotoxic effects of chemotherapeutic agents [23]. Through direct interactions with cancer cells and mediation of epithelial-mesenchymal transition (EMT), platelets further promote cancer cell adhesion, proliferation, and invasion, exacerbating tumor aggressiveness [24].

The difference between high and low PD-L1 expression on the prognosis of NSCLC patients treated with ICIs and opioids was not statistically significant in this retrospective study. Possible reasons for this situation include tumor patient heterogeneity, the objectivity of PD-L1 testing, and differences in the disease states of the included populations [25]. Because the current PD-L1 expression cannot comprehensively and accurately predict the efficacy and prognosis of immunotherapy for NSCLC treated with ICIs and opioids, we conducted this retrospective study with the expectation that screening for other metrics would help us predict the efficacy and prognosis of immunotherapy for NSCLC patients receiving opioids.

In summary, the clinical outcomes of NSCLC patients with cancer pain receiving ICIs are influenced by a combination of factors, including tumor burden, systemic inflammatory status, and nutritional and immune conditions. Therefore, a comprehensive assessment of these factors is essential to accurately predict patient prognosis, identify high-risk populations, and develop tailored treatment strategies aimed at optimizing outcomes and prolonging survival.

In this study, we preliminarily identified that a high SII/ALB ratio is associated with poor prognosis and diminished immunotherapy response, suggesting its potential as a prognostic biomarker for NSCLC patients with cancer pain undergoing ICIs treatment. However, this study has several limitations. First, the use of ROC curve-derived cut-off values for PFS remains controversial, as there is currently no standardized approach. Larger-scale studies are needed to establish consensus on optimal thresholds. Second, this study did not dynamically monitor longitudinal changes in NLR, PLR, SII/ALB levels, or NRS pain scores, thereby limiting the ability to fully assess the impact of these changes on prognosis. Finally, the single-center, retrospective design with a relatively small sample size may introduce selection bias, potentially limiting the generalizability of the findings. Future large-scale, multicenter prospective studies are warranted to validate these results and further elucidate the prognostic significance of these biomarkers, thereby enhancing the robustness and clinical applicability of the finding.

Conclusion

The study confirmed the predictive value of peripheral blood inflammatory markers for the efficacy of immunotherapy in NSCLC patients treated with ICIs and opioids and suggested that the SII/ALB > 17.79 was an independent risk factor for poor prognosis after immunotherapy in NSCLC patients treated with ICIs and opioids. In this study, we assessed the prognostic value of peripheral blood inflammatory markers for immunotherapy efficacy in NSCLC patients with ICIs and opioids and screened the best peripheral blood inflammatory marker predictors and the best cut-off values through comparative analysis of different peripheral blood inflammatory markers, thereby providing a new and effective reference and evaluation index for evaluating the efficacy and outcomes of immunotherapy in NSCLC patients treated with ICIs and opioids.