Prognostic value of platelet to lymphocyte ratio in non-small cell lung cancer: evidence from 3,430 patients

Predictive value of near-term prediction models for severe immune-related adverse events in malignant tumor PD-1 inhibitor therapy

Immune-related adverse events (irAEs) impact outcomes, with most research focusing on early prediction (baseline data), rather than near-term prediction (one cycle before the occurrence of irAEs and the current cycle). We aimed to explore the near-term predictive value of neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), absolute eosinophil count (AEC) for severe irAEs induced by PD-1 inhibitors. Data were collected from tumor patients treated with PD-1 inhibitors. NLR, PLR, and AEC data were obtained from both the previous and the current cycles of irAEs occurrence. A predictive model was developed using elastic net logistic regression Cutoff values were determined using Youden's Index. The predicted results were compared with actual data using Bayesian survival analysis. A total of 138 patients were included, of whom 47 experienced grade 1-2 irAEs and 18 experienced grade 3-5 irAEs. The predictive model identified optimal α and λ through 10-fold cross-validation. The Shapiro-Wilk test, Kruskal-Wallis test and logistic regression showed that only current cycle data were meaningful. The NLR was statistically significant in predicting irAEs in the previous cycle. Both NLR and AEC were significant predictors of irAEs in the current cycle. The model achieved an area under the ROC curve (AUC) of 0.783, with a sensitivity of 77.8% and a specificity of 80.8%. A probability ≥ 0.1345 predicted severe irAEs. The model comprising NLR, AEC, and sex may predict the irAEs classification in the current cycle, offering a near-term predictive advantage over baseline models and potentially extending the duration of immunotherapy for patients.

Associations between peripheral whole blood cell counts derived indexes and cancer prognosis: An umbrella review of meta-analyses of cohort studies

Meta-analyses have reported conflicting data on the whole blood cell count (WBCC) derived indexes (neutrophil-to-lymphocyte ratio [NLR], platelet-to-lymphocyte ratio [PLR], and lymphocyte-to-monocyte ratio [LMR]) and cancer prognosis. However, the strength and quality of this evidence has not been quantified in aggregate. To grade the evidence from published meta-analyses of cohort studies that investigated the associations between NLR, PLR, and LMR and cancer prognosis. A total of 694 associations from 224 articles were included. And 219 (97.8%) articles rated as moderate-to-high quality according to AMSTAR. There were four associations supported by convincing evidence. Meanwhile, 165 and 164 associations were supported by highly suggestive and suggestive evidence, respectively. In this umbrella review, we summarized the existing evidence on the WBCC-derived indexes and cancer prognosis. Due to the direction of effect sizes is not completely consistent between studies, further research is needed to assess causality and provide firm evidence.

Diagnostic accuracy of the neutrophil-to-lymphocyte ratio and the platelet-to-lymphocyte ratio in rheumatoid arthritis: a systematic review and meta-analysis

Existing challenges with the early diagnosis of rheumatoid arthritis (RA) and active disease, mainly by non-rheumatologists, have prompted the search for novel biomarkers. Elevations in indices derived from blood cell counts, e.g., the neutrophil-to-lymphocyte ratio (NLR) and the platelet-to-lymphocyte ratio (PLR), have been reported in RA patients. However, their diagnostic accuracy has not been comprehensively assessed. Therefore, we conducted a systematic review and meta-analysis of studies reporting the sensitivity and specificity of the NLR and PLR, obtained by receiver operating characteristic (ROC) curve analysis, for the presence of RA and active disease. We searched electronic databases from inception to 15 March 2024 and assessed the risk of bias using the JBI Critical Appraisal Checklist (PROSPERO registration number: CRD42024533546). In 15 studies, the NLR exhibited acceptable accuracy for the presence of RA (area under the curve, AUC = 0.76, 95% CI 0.72 to 0.80) and active disease (AUC = 0.70, 95% CI 0.66 to 0.74). The PLR exhibited good accuracy for the presence of RA (AUC = 0.80, 95% CI 0.76 to 0.83). There were insufficient studies to assess the accuracy of the PLR for the presence of active disease. Our systematic review and meta-analysis suggests that the NLR and the PLR are promising biomarkers of RA (NLR and PLR) and active disease (NLR). Further research is required to investigate whether the NLR and PLR can significantly enhance the capacity to diagnose RA and active disease in clinical practice.

Neutrophil-to-Lymphocyte and Platelet-to-Lymphocyte Ratio: Side by Side with Molecular Mutations in Patients with Non-Small Cell Lung Cancer-The INOLUNG Study

Background and objective: Analysis of inflammatory biomarkers, along with the neutrophil/lymphocyte ratio (NLR) or platelet/lymphocyte ratio (PLR), supports the connection between inflammation and carcinogenesis. Methods: We conducted a retrospective observational study at the Clinical County Hospital Mureș involving patients with lung cancer. The parameters analyzed included histopathological type (NSCLC: squamous cell carcinoma or adenocarcinoma; SCLC), molecular mutations (EGFR, ALK, PD-L1), parameters from the complete blood count, inflammatory parameters, and associated comorbidities. Results: A total of 380 patients were included: 115 patients in the cancer group and 265 patients in the control group. Among patients in the lung cancer group, 88 were diagnosed with NSCLC (44 adenocarcinomas, 44 squamous cell carcinomas) and 27 with SCLC. Both NLR and PLR were significantly higher in cancer patients than in the control group (5.30 versus 2.60, p < 0.001; 217 versus 136, p < 0.001, respectively). NLR and PLR differ between men and women (p = 0.005 and p = 0.056, respectively). C-reactive protein was not correlated with either NLR (p-value: 0.0669) or PLR (p-value: 0.6733) in lung cancer patients. Conclusions: The NLR and PLR values may serve as new predictive biomarkers for the diagnosis of disease in patients with lung cancer, especially those with NSCLC.

A systematic review and meta-analysis of the diagnostic accuracy of the neutrophil-to-lymphocyte ratio and the platelet-to-lymphocyte ratio in systemic lupus erythematosus

The wide range of clinical and serological manifestations in systemic lupus erythematosus (SLE) and the lack of accepted diagnostic criteria warrant the identification of novel, more accurate biomarkers. Hematological indices derived from full blood cell counts, particularly the neutrophil-to-lymphocyte ratio (NLR) and the platelet-to-lymphocyte ratio (PLR), have shown promise in SLE; however, a critical appraisal of their diagnostic accuracy is lacking. We sought to address this issue by conducting a systematic review and meta-analysis of the diagnostic accuracy of the NLR and PLR in SLE. The electronic databases PubMed, Scopus, and Web of Science were systematically searched from inception to 15 March 2024 for studies reporting the sensitivity and specificity of the NLR and PLR, obtained by receiver operating characteristic (ROC) curve analysis, for the presence of SLE, disease severity, organ involvement (lupus nephritis, pericarditis, and pleural disease), and complications (infections). The risk of bias was assessed using the JBI Critical Appraisal Checklist (PROSPERO registration number: CRD42024531446). The NLR exhibited good accuracy for the diagnosis of SLE (eight studies; area under the curve, AUC = 0.81, 95% CI 0.78-0.85) and lupus nephritis (nine studies; AUC = 0.81, 95% CI 0.77-0.84), but not for severe disease (nine studies; AUC = 0.69, 95% CI 0.65-0.73) or infections (six studies; AUC = 0.73, 95% CI 0.69-0.77). The PLR exhibited good accuracy for the diagnosis of severe disease (six studies; AUC = 0.85, 95% CI 0.81-0.87). There were an insufficient number of studies to assess the accuracy of the PLR for the diagnosis of SLE, lupus nephritis, or infections. No study investigated the NLR and PLR in SLE patients with pericarditis or pleural disease. Therefore, the NLR and the PLR have a relatively high diagnostic accuracy for the presence of SLE and lupus nephritis (NLR) and severe disease (PLR). Further studies are warranted to determine whether the NLR and PLR, in combination with clinical evaluation and other serological biomarkers, can enhance the diagnosis and management of SLE.

Predictors of immune-related adverse events and outcomes in patients with NSCLC treated with immune-checkpoint inhibitors

OBJECTIVE

To identify predictors of immune-related adverse events (IRAEs) in patients with non-small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors (ICIs). Assess associations between outcomes and the development of IRAEs.

METHODS

Retrospective analysis of patients with NSCLC treated with ICIs between 2016 and 2020 in the Pulmonology Department of our hospital. Patients with and without IRAEs were compared. A logistic regression analysis was performed to determine predictors of IRAEs. Progression-free survival (PFS) and overall survival (OS) curves were calculated using the Kaplan-Meier method, and the long-rank test was used to assess survival differences between groups. Univariate and multivariate Cox proportional-hazards regression models were used to identify factors associated with PFS and OS. The value considered statistically significant was p≤0.05.

RESULTS

A total of 184 patients (77.7% men, mean age 66.9±9.5 years) treated with ICIs were analyzed. During follow-up, 49 (26.6%) patients developed IRAEs and 149 (81.0%) died. According to the multivariate logistic regression analysis, treatment with statins (OR:3.15; p = 0.007), previous systemic corticosteroid therapy (OR:3.99; p = 0.001), disease controlled as response to ICI (OR:5.93; p < 0.001) and higher hemoglobin values (OR:1.28; p = 0.040) were independent predictors for the development of IRAEs. Patients who developed IRAEs had significantly longer medians of PFS (41.0 vs 9.0 weeks, p < 0.001) and OS (89.0 vs 28.0 weeks; p < 0.001).

CONCLUSIONS

Patients treated with statins, pre-ICI systemic corticosteroids, higher baseline hemoglobin value and controlled disease as initial response to ICI had a higher risk of developing IRAEs. The development of IRAEs was associated with better outcomes.

Prognostic significance of systemic immune inflammatory index in NSCLC: a meta-analysis

Aim: The aim of this meta-analysis was to investigate the relationship between the baseline systemic immune inflammatory index (SII) and prognosis in patients with NSCLC. Materials & methods: The relation between pretreatment SII and overall survival, disease-free survival, cancer-specific survival, progression-free survival and recurrence-free survival in NSCLC patients was analyzed combined with hazard ratio and 95% CI. Results: The results showed that high SII was significantly correlated with overall survival and progression-free survival of NSCLC patients, but not with disease-free survival, cancer-specific survival and recurrence-free survival. Conclusion: The study suggests that a higher SII has association with worse prognosis in NSCLC patients. PROSPERO registration number: CRD42022336270.

Comparative Analysis of Inflammatory Indexes in Lung Cancer Patients With and Without Brain Metastases

Introduction Lung cancer is the leading cause of oncological deaths worldwide. Various combined inflammatory indexes, such as the systemic immune-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), and platelet-to-lymphocyte ratio (PLR) have shown associations with pretreatment survival prognosis in patients suffering of lung cancer with or without brain metastases. This study aimed to compare the average values of NLR, PLR, LMR, and SII in healthy patients, patients with lung cancer without any other metastases, and patients with lung cancer and brain metastases. Materials and methods In this prospective study, we have divided the patients into three groups: Group 1 included patients diagnosed with lung cancer and one or more brain metastases of lung cancer origin, Group 2 included patients diagnosed with lung cancer without known metastases, and Group 3 was the control group which included healthy subjects. Preoperative complete blood counts were extracted for all included patients and we calculated the values of SII, NLR, PLR, and LMR for each individual patient in each group. The next step was to calculate the average values of SII, NLR, PLR, and LMR for each group of patients and to identify the differences between groups. Results A total number of 228 patients were enrolled in the study. Group 1 included 67 patients with average values of SII = 2020.98, NLR = 7.25, PLR = 199.46, and LMR = 2.97. Group 2 included 88 patients with average values of SII = 1638.01, NLR = 4.58, PLR = 188.42, and LMR = 3.43. Group 3 included 73 subjects with the following average values of the inflammatory indexes: SII = 577.41, NLR = 2.34, PLR = 117.84, and LMR = 3.56. Conclusion We observed statistically significant differences in SII, NLR, and PLR among the three groups of patients, suggesting their potential role as prognostic markers. Furthermore, our analysis revealed significant correlations between inflammatory markers within lung cancer patients, highlighting their involvement in tumor microenvironment modulation. Our findings demonstrate an escalation in SII, NLR, and PLR values as the disease progresses. These parameters of inflammation and immune status are readily and cost-effectively, and repeatedly assessable in routine clinical practice.

The value of lung function assessment and Testin expression detection in clinicopathological features and prognosis of NSCLC patients

OBJECTIVE

The aim of this study is to investigate the clinical value and potential prognostic significance of lung function assessment and Testin expression in non-small cell lung cancer (NSCLC) patients.

METHODS

The NSCLC patients were classified into three groups according to lung function: group of normal lung function, group of PRISm (preserved ratio impaired spirometry) (FEV1, forced expiratory volume during the first second < 80% predicted and FEV1/FVC (forced vital capacity) ≥ 70%) and group of COPD (chronic obstructive pulmonary disease) (FEV1/FVC < 70%). The pre-operational clinicopathological characteristics of these patients were recorded and the markers of systemic inflammatory response, including neutrophil to lymphocyte ratio (NLR), lymphocyte to monocyte ratio (LMR), platelet to lymphocyte ratio (PLR) and eosinophils (EOS), were compared between three groups. The expression of Testin in NSCLC samples was detected by IHC and we further explored the correlation between Testin expression and clinicopathological characteristics and prognosis of NSCLC patients. Finally, Cox regression analysis was conducted to study the prognostic factors of NSCLC patients.

RESULTS

Of the 158 NSCLC patients, percentages of normal lung function, PRISm and COPD were 41.4%, 22.8% and 36.1%, respectively. Patients with tumor in the left lung were more likely to have pulmonary dysfunction (PRISm and COPD) than the right lung. The markers of systemic inflammatory response showed differences to various degree in the three groups and NSCLC patients with PRISm or COPD presented more unfavorable prognosis than patients with normal function. The expression of Testin correlated with lymph node metastasis, TNM stage and tumor invasion of NSCLC patients. Moreover, patients with low Testin expression exhibited poorer disease-free survival and overall survival than those with high Testin expression. In Cox regression analysis, we found that PRISm, COPD and Testin expression served as prognostic factors in NSCLC patients.

CONCLUSIONS

The presence of COPD or PRISm influenced systemic inflammatory response and prognosis of NSCLC patients. Testin expression correlated with clinicopathological features and could be potentially used as a prognostic marker in NSCLC.

Prognostic Nutritional Index Predicts Efficacy and Immune-Related Adverse Events of First-Line Chemoimmunotherapy in Patients with Extensive-Stage Small-Cell Lung Cancer

Background

Currently, there is a lack of well-established markers to predict the efficacy of chemoimmunotherapy in small-cell lung cancer (SCLC). Neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), advanced lung cancer inflammation index (ALI) and prognostic nutritional index (PNI) are associated with prognosis in several tumors, whereas their predictive role in SCLC remains unclear.

Methods

A retrospective study was conducted at Sun Yat-sen University Cancer Center, involving extensive-stage SCLC (ES-SCLC) patients who received first-line chemoimmunotherapy between January 2020 and December 2021. Peripheral blood biomarkers were extracted from medical records and their correlation with prognosis and immune-related adverse events (IRAEs) was analyzed.

Results

A total of 114 patients were included. Patients with a low PLR, high ALI and high PNI had prolonged progression-free survival (PFS) compared to those with a high PLR, low ALI and low PNI. Patients with a low NLR, low PLR, high ALI and high PNI had prolonged overall survival (OS) compared to those with a high NLR, high PLR, low ALI and low PNI. Cox regression model showed that PNI was an independent risk factor for both PFS and OS. ROC curve showed that PNI outperforms NLR, PLR and ALI in predicting both PFS and OS. The PNI-based nomogram demonstrated strong predictive capability for both PFS and OS. In addition, there was a significant correlation between PNI and IRAEs.

Conclusion

A high baseline PNI might be associated with improved prognosis and the occurrence of IRAEs in ES-SCLC patients treated with first-line chemoimmunotherapy.

Evaluating the predictive significance of systemic immune-inflammatory index and tumor markers in lung cancer patients with bone metastases

Objective

This study aims to develop a predictive model for identifying lung cancer patients at elevated risk for bone metastases, utilizing the Unified Immunoinflammatory Index and various tumor markers. This model is expected to facilitate timely and effective therapeutic interventions, especially in the context of the growing significance of immunotherapy for lung cancer treatment.

Methods

A retrospective analysis was conducted on 324 lung cancer patients treated between January 2019 and January 2021. After meeting the inclusion criteria, 241 patients were selected, with 56 exhibiting bone metastases. The cohort was divided into a training group (169 patients) and a validation group (72 patients) at a 7:3 ratio. Lasso regression was employed to identify critical variables, followed by logistic regression to construct a Nomogram model for predicting bone metastases. The model's validity was ascertained through internal and external evaluations using the Concordance Index (C-index) and Receiver Operating Characteristic (ROC) curve.

Results

The study identified several factors influencing bone metastasis in lung cancer, such as the Systemic Immune-Inflammatory Index (SII), Carcinoembryonic Antigen (CEA), Neuron Specific Enolase (NSE), Cyfra21-1, and Neutrophil-to-Lymphocyte Ratio (NLR). These factors were incorporated into the Nomogram model, demonstrating high validation accuracy with C-index scores of 0.936 for internal and 0.924 for external validation.

Conclusion

The research successfully developed an intuitive and accurate Nomogram prediction model utilizing clinical indicators to predict the risk of bone metastases in lung cancer patients. This tool can be instrumental in aiding clinicians in developing personalized treatment plans, thereby optimizing patient outcomes in lung cancer care.

Sixth-Week Immune-Nutritional-Inflammatory Biomarkers: Can They Predict Clinical Outcomes in Patients with Advanced Non-Small Cell Lung Cancer Treated with Immune Checkpoint Inhibitors?

BACKGROUND

We investigated the relationships between inflammatory markers such as the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), Lung Immune Prognostic Index (LIPI), and modified Glasgow prognostic score (mGPS) to determine whether they could predict treatment response to pembrolizumab or nivolumab (immunotherapy) 6 weeks after the start of treatment (post-treatment).

METHODS

We included all patients with lung cancer treated with immunotherapy. We examined the biomarker trends and explored their associations with progression-free survival (PFS), overall survival (OS), and response rate (RR) at 6 weeks.

RESULTS

Eighty-three patients were enrolled in the study. The presence of liver metastasis, low post-treatment NLR (<5), low post-treatment PLR (<170), intermediate post-treatment LIPI, and immune-related adverse events were significantly associated with the response. The multivariate analysis revealed that high post-treatment NLRs ≥ 5 (p = 0.004) and PLRs ≥ 170 (p ≤ 0.001) were independent prognostic factors of shorter OS. A good LIPI status was associated with better PFS (p = 0.020) and OS (p = 0.065). Post-treatment mGPS (0-2) was significantly associated with improved PFS (p = 0.009) and OS (p = 0.064).

CONCLUSIONS

Post-treatment NLR, PLR, LIPI, and mGPS are associated with worse OS and recurrence. These findings should be independently and prospectively validated in further studies.

Immune-Related Adverse Events, Biomarkers of Systemic Inflammation, and Survival Outcomes in Patients Receiving Pembrolizumab for Non-Small-Cell Lung Cancer

BACKGROUND

Pembrolizumab monotherapy for non-small-cell lung cancer (NSCLC) expressing PD-L1 ≥ 50% doubles five-year survival rates compared to chemotherapy. However, immune-related adverse events (irAEs) can cause severe, long-term toxicity necessitating high-dose steroids and/or treatment cessation. Interestingly, patients experiencing irAEs demonstrate better survival outcomes. Biomarkers of systemic inflammation, including the Scottish Inflammatory Prognostic Score (SIPS), also predict survival in this patient group. This study examines the relationship between inflammatory status, irAEs, and survival outcomes in NSCLC.

METHODS

A retrospective analysis was conducted on patients with NSCLC expressing PD-L1 ≥ 50% receiving first-line pembrolizumab monotherapy at a large cancer centre in Scotland. Regression analyses were conducted to examine the relationship between SIPS, irAEs, and survival.

RESULTS

83/262 eligible patients (32%) experienced an irAE. Dermatological, endocrine, gastrointestinal, and hepatic, but not pulmonary, irAEs were associated with prolonged PFS and OS (p <= 0.011). Mild irAEs were associated with better PFS and OS in all patients, including on time-dependent analyses (HR0.61 [95% CI 0.41-0.90], p = 0.014 and HR0.41 [95% CI 0.26-0.63], p < 0.001, respectively). SIPS predicted PFS (HR 1.60 [95% CI 1.34-1.90], p < 0.001) and OS (HR 1.69 [95% CI 1.41-2.02], p < 0.001). SIPS predicted the occurrence of any irAE in all patients (p = 0.011), but not on 24-week landmark analyses (p = 0.174). The occurrence of irAEs predicted favourable outcomes regardless of the baseline inflammatory status (p = 0.015).

CONCLUSION

The occurrence of certain irAEs is associated with a survival benefit in patients with NSCLC expressing PD-L1 ≥ 50% receiving pembrolizumab. We find that the association between low levels of systemic inflammation and the risk of irAEs is confounded by their independent prognostic value.

Predictive Value of Modified Glasgow Prognostic Score and Persistent Inflammation among Patients with Non-Small Cell Lung Cancer Treated with Durvalumab Consolidation after Chemoradiotherapy: A Multicenter Retrospective Study

BACKGROUND

Durvalumab consolidation after chemoradiotherapy (CRT) is a standard treatment for locally advanced non-small cell lung cancer (NSCLC). However, studies on immunological and nutritional markers to predict progression-free survival (PFS) and overall survival (OS) are inadequate. Systemic inflammation causes cancer cachexia and negatively affects immunotherapy efficacy, which also reflects survival outcomes.

PATIENTS AND METHODS

We retrospectively investigated 126 patients from seven institutes in Japan.

RESULTS

The modified Glasgow Prognostic Score (mGPS) values, before and after CRT, were the essential predictors among the evaluated indices. A systemic inflammation-based prognostic risk classification was created by combining mGPS values before CRT, and C-reactive protein (CRP) levels after CRT, to distinguish tumor-derived inflammation from CRT-induced inflammation. Patients were classified into high-risk (n = 31) and low-risk (n = 95) groups, and the high-risk group had a significantly shorter median PFS of 7.2 months and an OS of 19.6 months compared with the low-risk group. The hazard ratios for PFS and OS were 2.47 (95% confidence interval [CI]: 1.46-4.19, p < 0.001) and 3.62 (95% CI: 1.79-7.33, p < 0.001), respectively. This association was also observed in the subgroup with programmed cell death ligand 1 expression of ≥50%, but not in the <50% subgroup. Furthermore, durvalumab discontinuation was observed more frequently in the high-risk group than in the low-risk group.

CONCLUSION

Combining pre-CRT mGPS values with post-CRT CRP levels in patients with locally advanced NSCLC helps to predict the PFS and OS of durvalumab consolidation after CRT.

Immunotherapy for early-stage non-small cell lung cancer: A system review

With the addition of immunotherapy, lung cancer, one of the most common cancers with high mortality rates, has broadened the treatment landscape. Immune checkpoint inhibitors have demonstrated significant efficacy in the treatment of non-small cell lung cancer (NSCLC) and are now used as the first-line therapy for metastatic disease, consolidation therapy after radiotherapy for unresectable locally advanced disease, and adjuvant therapy after surgical resection and chemotherapy for resectable disease. The use of adjuvant and neoadjuvant immunotherapy in patients with early-stage NSCLC, however, is still debatable. We will address several aspects, namely the initial efficacy of monotherapy, the efficacy of combination chemotherapy, immunotherapy-related biomarkers, adverse effects, ongoing randomized controlled trials, and current issues and future directions for immunotherapy in early-stage NSCLC will be discussed here.

Pretreatment lymphocyte-to-monocyte ratio as a prognostic factor and influence on dose-effect in fractionated stereotactic radiotherapy for oligometastatic brain metastases in non-small cell lung cancer patients

Background

Studies on the prognostic factors for patients with brain oligo-metastasis treated with fractionated stereotactic radiotherapy (FSRT) usually focus on the size of metastatic tumor and radiation dose. Some inflammatory indicators have predictive value in non-small cell lung cancer (NSCLC) with brain metastasis receiving stereotactic radiotherapy. However, the prognostic value of inflammatory indicators in NSCLC patients with brain oligo-metastasis treated with FSRT, and their effect on radiotherapy dose is unknown.

Methods

A total of 95 advanced NSCLC patients with brain oligo-metastasis who had undergone FSRT treatment at Ningbo Medical Center Lihuili Hospital between January 2015 and April 2022 were enrolled into the study. Neutrophil to lymphocyte ratio (NLR), platelet lymphocyte ratio (PLR), lymphocyte to monocyte ratio (LMR), tumor diameter and biologically effective dose (BED10) were analyzed using Chi-square test. Univariate and multivariate Cox regressions were used to identify predictors of survival.

Results

Tumor diameter (< 2 cm), BED10 (≥ 48Gy) and LMR (≥ 4) were found to be independently associated with good intracranial local control survival (i-LCS) through multivariate analysis. The median i-LCS was longer in patients with 2 independent risk factors (tumor diameter ≥ 2 and LMR < 4) administered with BED10 > 53.6Gy compared with patients administered with BED10 ≤ 53.6Gy (20.7 months vs 12.0 months, P = 0.042). LMR ≥ 4 (P = 0.019) and positivity for driver gene mutations (P = 0.011) were independently associated with better overall survival (OS).

Conclusions

LMR is an independent prognostic factor of i-LCS and OS in NSCLC patients with brain oligo-metastasis treated with FSRT. Patients with tumor diameter ≥ 2 and LMR < 4 should be treated with BED10 greater than 53.6Gy.

Soluble biomarkers to predict clinical outcomes in non-small cell lung cancer treated by immune checkpoints inhibitors

Lung cancer remains the first cause of cancer-related death despite many therapeutic innovations, including immune checkpoint inhibitors (ICI). ICI are now well used in daily practice at late metastatic stages and locally advanced stages after a chemo-radiation. ICI are also emerging in the peri-operative context. However, all patients do not benefit from ICI and even suffer from additional immune side effects. A current challenge remains to identify patients eligible for ICI and benefiting from these drugs. Currently, the prediction of ICI response is only supported by Programmed death-ligand 1 (PD-L1) tumor expression with perfectible results and limitations inherent to tumor-biopsy specimen analysis. Here, we reviewed alternative markers based on liquid biopsy and focused on the most promising biomarkers to modify clinical practice, including non-tumoral blood cell count such as absolute neutrophil counts, platelet to lymphocyte ratio, neutrophil to lymphocyte ratio, and derived neutrophil to lymphocyte ratio. We also discussed soluble-derived immune checkpoint-related products such as sPD-L1, circulating tumor cells (detection, count, and marker expression), and circulating tumor DNA-related products. Finally, we explored perspectives for liquid biopsies in the immune landscape and discussed how they could be implemented into lung cancer management with a potential biological-driven decision.

Platelet to lymphocyte ratio was a risk factor in Perthes disease

The study was aimed to determine the relationship between PLR (platelet to lymphocyte ratio) and the lateral pillar classification of Perthes disease, and to provide an alternative index for clinical diagnosis. In addition, the association of the PLR with the necrosis stage of Perthes disease was also explored. This was a retrospective study. 74 children with Perthes disease and 60 children in the healthy control group without femoral head necrosis in our hospital from 2012 to 2021 were collected. The general data and clinical parameters were collected from the hospital information system. The modified herring lateral pillar classification was collected for the fragmentation stage case group and the PLR, NLR (neutrophil to lymphocyte ratio), LMR (lymphocyte to monocyte ratio) and PNR (platelet to neutrophil ratio) were calculated. The cases were divided into four groups, herring A and B were group I, herring B/C and C were group II, the healthy control group was group III, and the necrosis stage was group IV. The hematological indexes (NLR, PLR, LMR, PNR) of children at different stages were statistically analyzed. Group I consisted of 36 patients, with an average age of 7.4 ± 2.0 years (3-11 years). Group II consisted of 23 patients, with an average age of 7.4 ± 1.9 years (4-12 years). Group III consisted of 60 patients, with a mean age of 7.4 ± 2.7 years (4-13 years). Group IV consisted of 15 patients, with an average age of 6.4 ± 1.7 years (3-10 years). The average values of PLR in groups I, II, III and IV were 131.98 ± 47.44, 122.19 ± 37.88, 102.46 ± 30.68 and 128.90 ± 28.11, respectively. It's worth noting that there was statistically significant difference among groups I, II and III (P = 0.003). The optimal threshold of PLR was 130.25, the sensitivity was 45.8% and the specificity was 85%. PLR was also significantly different between groups III and group IV. PLR was higher in Herring A and B classifications than in Herring B/C and C classifications. PLR had certain diagnostic value in both the necrosis stage and fragmentation stage as a risk factor.

A biomarker predicting unfavorable prognosis in malignant pleural mesothelioma: systemic immune–inflammation index

Aim: Malignant pleural mesothelioma (MPM) is an extremely mortal condition. Only a few prognostic biomarkers have been described for MPM. Our study looked into the association between patient survival and the Systemic Immune Inflammation Index (SII). Material and Method: A total of 158 patients who were admitted to our hospital between January 2013 and December 2022, and had a histopathologically confirmed diagnosis of MPM were included in the study. Before treatment, hematological parameters and SII were determined. A Spearman's correlation analysis was performed to analyze the correlation of mean survival with hematological parameters. Results: The study involved 158 patients in all. 70 patients had a history of smoking, the median age was 63 years, the mean survival time was 15.3 months, and 57.6% of the participants were men. The epithelioid type (84.2%) was the most prevalent histological subtype, and 29 patients had stage 4 illnesses. Of the participants, 84% had received chemotherapy, and 22% had received radiotherapy before. Among the 39 patients who had surgery, 5 had an extrapleural pneumonectomy. SII mean±sd was (1427.2±1207.3). The patients with stage 4 disease had significantly shorter survival (p=0.001). The patients who had surgery survived significantly longer (p=0.01). Hemoglobin (Hb) (r:0.21, p:0.01) and Hematocrit (Hct) (r:0.18, p:0.03) values showed weak positive correlations with mean survival. It was evident that mean survival got shorter as SII (r:-0.17, p:0.04) and neutrophil-lymphocyte ratio (NLR) (r:-0.19, p:0.02) values got higher. On the other hand, there was a strong positive association between mean survival and the lymphocyte-monocyte ratio (LMR) (r:0.21, p:0.01). When the parameters that had statistically significant differences among the groups were taken as control variables and the statistical analysis was re-performed, it was found that Hgb and Hct values as well as NLR and LMR ratios lost their significant correlations with survival. However, the SII ratio was still negatively correlated with survival (r:-0.16, p:0.04). Conclusion: Pretreatment SII is a noninvasive and easy-to-calculate biomarker that predicts the prognosis of MPM. It is negatively correlated with mean survival regardless of the tumor stage and surgical management.

Emerging Biomarkers in Immune Oncology to Guide Lung Cancer Management

Over the last decade, the use of targeted therapies and immune therapies led to drastic changes in the management lung cancer and translated to improved survival outcomes. This growing arsenal of therapies available for the management of non-small cell lung cancer added more complexity to treatment decisions. The genomic profiling of tumors and the molecular characterization of the tumor microenvironment gradually became essential steps in exploring and identifying markers that can enhance patient selection to facilitate treatment personalization and narrow down therapy options. The advent of innovative diagnostic platforms, such as next-generation sequencing and plasma genotyping (also known as liquid biopsies), has aided in this quest. Currently, programmed cell death ligand 1 expression remains the most recognized and fully validated predictive biomarker of response to immune checkpoint inhibitors. Other markers such as tumor mutational burden, tumor infiltrating lymphocytes, driver mutations, and other molecular elements of the tumor microenvironment bear the potential to be predictive tools; however, the majority are still investigational. In this review, we describe the advances noted thus far on currently validated as well as novel emerging biomarkers that have the potential to guide the use of immunotherapy agents in the management of non-small cell lung cancer.

Prognostic value of hematologic parameters in advanced non-small cell lung cancer patients receiving anti-PD-1 inhibitors

Background

The association between hematologic parameters and anti-programmed death-1 (PD-1) inhibitors was generally examined without considering therapy lines and medicine types. The study was aimed to identify potential hematologic biomarkers associated with clinical outcome in patients with non-small cell lung cancer (NSCLC) treated with first-line pembrolizumab and subsequent-line nivolumab.

Materials and methods

161 NSCLC patients were categorized into first-line pembrolizumab group (pembrolizumab group) and subsequent-line nivolumab group (nivolumab group). Univariate and multivariate Cox regression analyses were used to evaluate the prognostic value of hematologic parameters for clinical outcomes.

Results

The median progression-free survival (mPFS) was 9.6 months in the pembrolizumab group and 4.1 months in the nivolumab group (HR =1.61; P = 0.012); the median overall survival (mOS) was not reached in the pembrolizumab group and 17.7 months in the nivolumab group (HR =1.37; P = 0.23). Of the 79 patients in the pembrolizumab group, baseline PD-L1 tumor proportion score (TPS)≥1% was an independent factor of longer PFS and OS. Age≥60 years, absolute platelet count (APC)≥220×109/L and platelet-to-lymphocyte ratio (PLR)≥120 were associated with inferior PFS. Of the 82 patients in the nivolumab group, absolute neutrophil count (ANC)≥3×109/L was associated with longer PFS, while LDH (lactate dehydrogenase)≥160 U/L was associated with inferior PFS and derived neutrophil-to-lymphocyte ratio (dNLR)≥1.2 was associated with longer OS.

Conclusion

Our study identified multiple clinically accessible prognostic biomarkers in the peripheral blood in both the pembrolizumab and nivolumab subgroups.

Prognostic significance of modified lung immune prognostic index in osteosarcoma patients

Purpose: Osteosarcoma is the most common primary malignancy of bone with a dismal prognosis for patients with pulmonary metastases. Evaluation of osteosarcoma prognosis would facilitate the prognosis consultation as well as the development of personalized treatment decisions. However, there is limited effective prognostic predictor at present. Lung Immune Prognostic Index (LIPI) is a novel prognostic factor in pulmonary cancers, whereas, the prognostic significance of LIPI in osteosarcoma has not yet been well clarified. In this study, we firstly explore the prognostic role of LIPI and further modify this predictive model in osteosarcoma.

Patients and methods: A retrospectively study was conducted at Musculoskeletal Tumor Center of West China Hospital between January 2016 and January 2021. Hematological factors and clinical features of osteosarcoma patients were collected and analyzed. The area under curve (AUC) and optimal cuff-off of each single hematological factor was calculated.

Results: In this study, lactate dehydrogenase (LDH), derived neurtrophil to lymphocyte ratio (dNLR), and Hydroxybutyrate dehydrogenase (HBDH) have higher AUC values. LIPI was composed of LDH and dNLR and was further modified by combing the HBDH, forming the osteosarcoma immune prognostic index (OIPI). OIPI divided 223 osteosarcoma patients divided into four groups, none, light, moderate, and severe (p < 0.0001). OIPI has a higher AUC value than LIPI and other hematological indexes in t-ROC curve. According to the univariate and multivariate analysis, pathological fracture, metastasis, NLR, platelet–lymphocyte ratio (PLR), and OIPI were associated with the prognosis; and metastasis and OIPI were independent prognostic factors of osteosarcoma patients. An OIPI-based nomogram was also established and could predict the 3-year and 5-year overall survival. In addition, OIPI was also revealed correlated with metastasis and pathological fracture in osteosarcoma.

Conclusion: This study first explore the prognostic significance of LIPI in osteosarcoma patients. In addition, we developed a modified LIPI, the OIPI, for osteosarcoma patients. Both the LIPI and OIPI could predict the overall survival of osteosarcoma patients well, while OIPI may be more suitable for osteosarcoma patients. In particular, OIPI may have the ability to identify some high-risk patients from clinically low-risk patients.

The clinical relevance of neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio in chronic obstructive pulmonary disease with lung cancer

Background

Chronic obstructive pulmonary disease (COPD) coexisting with lung cancer is associated with severe mortality and a worse prognosis. Inflammation plays an important role in common pathogenic pathways and disease progression. However, a few studies have identified the clinical value of the neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) in COPD with lung cancer, which are systemic inflammatory response markers in the blood. This study aimed to determine the association of the NLR or PLR with clinical characteristics and whether NLR or PLR can be diagnostic markers for COPD with lung cancer.

Methods

Between 2015 and 2021, we conducted a retrospective analysis of 236 COPD patients with lung cancer and 500 patients without lung cancer (control group). Clinical information, blood routine examination, and spirometry results were collected and analyzed. The receiver operating characteristic (ROC) curve was used to identify the best cutoff point of NLR or PLR. Multivariate logistic regression analysis was performed to evaluate the association of NLR or PLR with the diagnosis and prognosis of COPD with lung cancer.

Results

Compared to patients in the COPD-only group, patients in the lung cancer group had a higher percentage of current smoking and emphysema, and it was found that NLR or PLR was significantly higher in the lung cancer group. Multivariate analysis showed that age, smoking status, FEV1%pred, emphysema, NLR, and PLR were independent risk factors for lung cancer development in COPD. Furthermore, the high level of NLR or PLR was associated with age over 70 years old, current smoking status, and ineligible surgery treatment. The level of PLR or NLR markedly increased with hypercoagulation status, the severity of airflow limitation, and advanced progression of lung cancer. Additionally, the ROC analysis also revealed that elevated NLR or PLR was an independent predictor of COPD in lung cancer patients, TNM stages IIIB–IV at first diagnosis in lung cancer, and ineligible surgery in lung cancer patients.

Conclusion

Increased NLR or PLR values might be an important and easily measurable inflammation biomarker to predict the diagnosis and severity of lung cancer with COPD.

Neutrophil-to-Lymphocyte Ratio and Platelet-to-Lymphocyte Ratio as Prognostic Markers for Advanced Non-Small-Cell Lung Cancer Treated with Immunotherapy: A Systematic Review and Meta-Analysis

Background and Objectives: Advanced non-small-cell lung cancer (NSCLC) has led to a high number of mortalities. Immunotherapy, as a first-line treatment in advanced NSCLC, currently has no clarity regarding its prognostic markers to assess the treatment outcome. This systematic review aimed to evaluate neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) as prognostic markers in advanced NSCLC patients treated with immunotherapy. Materials and Methods: This systematic review was conducted using the PRISMA guidelines, starting from screening for relevant studies from several databases. Each included cohort study was further assessed by using the Newcastle−Ottawa Quality Assessment Scale, and the available data were extracted for qualitative and quantitative synthesis in pooled and subgroup analysis. Results: A total of 1719 patients were included in this meta-analysis. Hazard ratio (HR) outcomes for progression-free survival (PFS) and overall survival (OS) for NLR and PLR showed significant results, supporting NLR and PLR as prognostic markers (NLR: HR PFS 2.21 [95% CI: 1.50−3.24; p < 0.0001] and HR OS 2.68 [95% CI: 2.24−3.6; p < 0.0001]; PLR: HR PFS 1.57 [95% CI: 1.33−1.84; p < 0.00001] and HR OS 2.14 [95% CI: 1.72−2.67; p < 0.00001]). Subgroup analysis with a cut-off value of 5 for NLR and 200 for PLR also demonstrated notable outcomes. Higher NLR and PLR levels are associated with poor prognostic. Conclusions: There is considerable evidence regarding both markers as prognostic markers in NSCLC patients treated with immunotherapy. However, further studies with more homogeneous baseline characteristics are required to confirm these findings.

Osteosarcoma immune prognostic index can indicate the nature of indeterminate pulmonary nodules and predict the metachronous metastasis in osteosarcoma patients

Purpose

The relationship between indeterminate pulmonary nodules (IPNs) and metastasis is difficult to determine. We expect to explore a predictive model that can assist in indicating the nature of IPNs, as well as predicting the probability of metachronous metastasis in osteosarcoma patients.

Patients and methods

We conducted a retrospective study including 184 osteosarcoma patients at West China Hospital from January 2016 to January 2021. Hematological markers and clinical features of osteosarcoma patients were collected and analyzed.

Results

In this study, we constructed an osteosarcoma immune prognostic index (OIPI) based on the lung immune prognostic index (LIPI). Compared to other hematological markers and clinical features, OIPI had a better ability to predict metastasis. OIPI divided 184 patients into four groups, with the no-OIPI group (34 patients), the light-OIPI group (35 patients), the moderate-OIPI group (75 patients), and the severe-OIPI group (40 patients) (P < 0.0001). Subgroup analysis showed that the OIPI could have a stable predictive effect in both the no-nodule group and the IPN group. Spearman’s rank correlation test and Kruskal–Wallis test demonstrated that the OIPI was related to metastatic site and metastatic time, respectively. In addition, patients with IPNs in high-OIPI (moderate and severe) groups were more likely to develop metastasis than those in low-OIPI (none and light) groups. Furthermore, the combination of OIPI with IPNs can more accurately identify patients with metastasis, in which the high-OIPI group had a higher metastasis rate, and the severe-OIPI group tended to develop metastasis earlier than the no-OIPI group. Finally, we constructed an OIPI-based nomogram to predict 3- and 5-year metastasis rates. This nomogram could bring net benefits for more patients according to the decision curve analysis and clinical impact curve.

Conclusion

This study is the first to assist chest CT in diagnosing the nature of IPNs in osteosarcoma based on hematological markers. Our findings suggested that the OIPI was superior to other hematological markers and that OIPI can act as an auxiliary tool to determine the malignant transformation tendency of IPNs. The combination of OIPI with IPNs can further improve the metastatic predictive ability in osteosarcoma patients.

Lung Immune Prognostic Index Could Predict Metastasis in Patients With Osteosarcoma

Background

The lung immune prognostic index (LIPI), composed of serum lactate dehydrogenase (LDH) and the derived neutrophil to lymphocyte ratio (dNLR), is a novel prognostic factor of lung cancer. The prognostic effect of the LIPI has never been verified in osteosarcoma.

Methods

We retrospectively reviewed the osteosarcoma patients with metachronous metastasis from January 2016 to January 2021 in West China Hospital. We collected and analyzed the clinical data and constructed the LIPI for osteosarcoma. The correlation between the LIPI and metastasis was analyzed according to the Kaplan–Meier method and Cox regression analysis with hazard ratios (HRs) and 95% confidence intervals (CIs). Univariate analysis and multivariate analysis were conducted to clarify the independent risk factors of metastasis. The nomogram model was established by R software, version 4.1.0.

Results

The area under the curve (AUC) and best cutoff value were 0.535 and 91, 0.519, and 5.02, 0.594 and 2.77, 0.569 and 227.14, 0.59 and 158, and 0.607 and 2.05 for ALP, LMR, NLR, PLR, LDH, and dNLR, respectively. The LIPI was composed of LDH and dNLR and showed a larger AUC than other hematological factors in the time-dependent operator curve (t-ROC). In total, 184 patients, 42 (22.8%), 96 (52.2%), and 46 (25.0%) patients had LIPIs of good, moderate, and poor, respectively (P &lt; 0.0001). Univariate analysis revealed that pathological fracture, the initial CT report of suspicious nodule, and the NLR, PLR, ALP, and the LIPI were significantly associated with metastasis, and multivariate analysis showed that the initial CT report of suspicious nodule and the PLR, ALP, and LIPI were dependent risk factors for metastasis. Metastatic predictive factors were selected and incorporated into the nomogram construction, including the LIPI, ALP, PLR, initial CT report, and pathological fracture. The C-index of our model was 0.71. According to the calibration plot, this predictive nomogram could accurately predict 3- and 5-year metachronous metastasis. Based on the result of decision curve and clinical impact curve, this predictive nomogram could also help patients obtain significant net benefits.

Conclusion

We first demonstrated the metastatic predictive effect of the LIPI on osteosarcoma. This LIPI-based model is useful for clinicians to predict metastasis in osteosarcoma patients and could help conduct timely intervention and facilitate personalized management of osteosarcoma patients.

Predicting checkpoint inhibitors pneumonitis in non-small cell lung cancer using a dynamic online hypertension nomogram

OBJECTIVES

Checkpoint inhibitors pneumonitis (CIP) is one of the most lethal adverse events in non-small cell lung cancer (NSCLC) patients treated with immune checkpoint inhibitors (ICIs). Currently, there is no recognized and effective predictive model to predict CIP in NSCLC.

MATERIALS AND METHODS

This study retrospectively analyzed 460 NSCLC patients who were first treated with ICIs. Patients were divided into three cohorts based on the occurrence of CIP: any grade CIP cohort, grade ≥ 2 CIP cohort and grade ≥ 3 CIP cohort.

RESULTS

A dynamic hypertension nomogram was constructed with elements including hypertension, interstitial lung disease (ILD), emphysema at baseline, and higher baseline platelet/lymphocyte ratio (PLR). The C indices of the training cohort and the internal and external validation cohort in any grade CIP cohort were 0.872, 0.833 and 0.840, respectively. The constructed hypertension nomogram was applied to grade ≥ 2 cohort and grade ≥ 3 cohort, and their C indices were 0.844 and 0.866, respectively. Compared with the non-hypertension nomogram, the hypertension nomogram presented better predictive power.

CONCLUSIONS

After validated by internal and external validation cohorts, the dynamic online hypertension has the potential to become a convenient, intuitive, and personalized clinical tool for assessing the risk of CIP in NSCLC patients.

Biomarkers of systemic inflammation predict survival with first-line immune checkpoint inhibitors in non-small-cell lung cancer

INTRODUCTION

Pembrolizumab is an established first-line option for patients with advanced non-small-cell lung cancer (NSCLC) expressing programmed death-ligand 1 ≥50%. Durable responses are seen in a subset of patients; however, many derive little clinical benefit. Biomarkers of the systemic inflammatory response predict survival in NSCLC. We evaluated their prognostic significance in patients receiving first-line pembrolizumab for advanced NSCLC.

METHODS

Patients treated with first-line pembrolizumab for advanced NSCLC with programmed death-ligand 1 expression ≥50% at two regional Scottish cancer centres were identified. Pretreatment inflammatory biomarkers (white cell count, neutrophil count, neutrophil/lymphocyte ratio, platelet/lymphocyte ratio, albumin, prognostic nutritional index) were recorded. The relationship between these and progression-free survival (PFS) and overall survival (OS) were examined.

RESULTS

Data were available for 219 patients. On multivariate analysis, albumin and neutrophil count were independently associated with PFS (P < 0.001, P = 0.002, respectively) and OS (both P < 0.001). A simple score combining these biomarkers was explored. The Scottish Inflammatory Prognostic Score (SIPS) assigned 1 point each for albumin <35 g/l and neutrophil count >7.5 × 10⁹/l to give a three-tier categorical score. SIPS predicted PFS [hazard ratio 2.06, 95% confidence interval (CI) 1.68-2.52 (P < 0.001)] and OS [hazard ratio 2.33, 95% CI 1.86-2.92 (P < 0.001)]. It stratified PFS from 2.5 (SIPS2), to 8.7 (SIPS1) to 17.9 months (SIPS0) (P < 0.001) and OS from 5.1 (SIPS2), to 12.4 (SIPS1) to 28.7 months (SIPS0) (P < 0.001). The relative risk of death before 6 months was 2.96 (95% CI 1.98-4.42) in patients with SIPS2 compared with those with SIPS0-1 (P < 0.001).

CONCLUSIONS

SIPS, a simple score combining albumin and neutrophil count, predicts survival in patients with NSCLC receiving first-line pembrolizumab. Unlike many proposed prognostic scores, SIPS uses only routinely collected pretreatment test results and provides a categorical score. It stratifies survival across clinically meaningful time periods that may assist clinicians and patients with treatment decisions. We advocate validation of the prognostic utility of SIPS in this and other immune checkpoint inhibitor treatment settings.

Biomarkers and risk factors for the early prediction of immune-related adverse events: a review

In recent years, immunotherapy has been widely used to treat patients with malignant tumors. While immune checkpoint inhibitors (ICIs) significantly improve the prognosis of cancer patients, the incidence of immune-related adverse events (irAEs) is increasing. Not only can irAEs accumulate in multiple organ systems throughout the body, but rare adverse reactions may also occur continuously. In severe cases, irAEs can be life-threatening or even lead to death. Therefore, the early identification, diagnosis and treatment of irAEs are very important. Early identification of patients with high-risk irAEs as well as the reduction or avoidance of severe irAEs have important clinical significance. This article will review the research progress of early predictive biomarkers and risk factors for the occurrence of irAEs and propose potential future directions for follow-up research and clinical applications.

Impact of Pre-Treatment NLR and Other Hematologic Biomarkers on the Outcomes of Early-Stage Non-Small-Cell Lung Cancer Treated with Stereotactic Body Radiation Therapy

Introduction: We evaluated the association of pre-treatment immunologic biomarkers on the outcomes of early-stage non-small-cell lung cancer (NSCLC) patients treated with stereotactic body radiation therapy (SBRT). Materials and methods: In this retrospective study, all newly diagnosed early-stage NSCLC treated with SBRT between January 2010 and December 2017 were screened and included for further analysis. The pre-treatment neutrophil-lymphocyte ratio (NLR), monocyte lymphocyte ratio (MLR), and platelet-lymphocyte ratio (PLR) were calculated. Overall survival (OS) and recurrence-free survival (RFS) were estimated by Kaplan–Meier. Multivariable models were constructed to determine the impact of different biomarkers and the Akaike information criterion (AIC), index of adequacy, and scaled Brier scores were calculated. Results: A total of 72 patients were identified and 61 were included in final analysis. The median neutrophil count at baseline was 5.4 × 10⁹/L (IQR: 4.17–7.05 × 10⁹/L). Median lymphocyte count was 1.63 × 10⁹/L (IQR: 1.29–2.10 × 10⁹/L), median monocyte count was 0.65 × 10⁹/L (IQR: 0.54–0.83 × 10⁹/L), median platelet count was 260.0 × 10⁹/L (IQR: 211.0–302.0 × 10⁹/L). The median NLR was 3.42 (IQR: 2.38–5.04), median MLR was 0.39 (IQR: 0.31–0.53), and median PLR was 156.4 (IQR: 117.2–197.5). On multivariable regression a higher NLR was associated with worse OS (p = 0.01; HR-1.26; 95% CI 1.04–1.53). The delta AIC between the two multivariable models was 3.4, suggesting a moderate impact of NLR on OS. On multivariable analysis, higher NLR was associated with poor RFS (p = 0.001; NLR^1 HR 0.36; 0.17–0.78; NLR^2 HR-1.16; 95% CI 1.06–1.26) with a nonlinear relationship. The delta AIC between the two multivariable models was 16.2, suggesting a strong impact of NLR on RFS. In our cohort, MLR and PLR were not associated with RFS or OS in multivariable models. Conclusions: Our study suggests NLR, as a biomarker of systemic inflammation, is an independent prognostic factor for OS and RFS. The nonlinear relationship with RFS may indicate a suitable immunological environment is needed for optimal SBRT action and tumoricidal mechanisms. These findings require further validation in independent cohorts.

Machine Learning for Prediction of Immunotherapy Efficacy in Non-Small Cell Lung Cancer from Simple Clinical and Biological Data

BACKGROUND

Immune checkpoint inhibitors (ICIs) are now a therapeutic standard in advanced non-small cell lung cancer (NSCLC), but strong predictive markers for ICIs efficacy are still lacking. We evaluated machine learning models built on simple clinical and biological data to individually predict response to ICIs.

METHODS

Patients with metastatic NSCLC who received ICI in second line or later were included. We collected clinical and hematological data and studied the association of this data with disease control rate (DCR), progression free survival (PFS) and overall survival (OS). Multiple machine learning (ML) algorithms were assessed for their ability to predict response.

RESULTS

Overall, 298 patients were enrolled. The overall response rate and DCR were 15.3% and 53%, respectively. Median PFS and OS were 3.3 and 11.4 months, respectively. In multivariable analysis, DCR was significantly associated with performance status (PS) and hemoglobin level (OR 0.58, p < 0.0001; OR 1.8, p < 0.001). These variables were also associated with PFS and OS and ranked top in random forest-based feature importance. Neutrophil-to-lymphocyte ratio was also associated with DCR, PFS and OS. The best ML algorithm was a random forest. It could predict DCR with satisfactory efficacy based on these three variables. Ten-fold cross-validated performances were: accuracy 0.68 ± 0.04, sensitivity 0.58 ± 0.08; specificity 0.78 ± 0.06; positive predictive value 0.70 ± 0.08; negative predictive value 0.68 ± 0.06; AUC 0.74 ± 0.03.

CONCLUSION

Combination of simple clinical and biological data could accurately predict disease control rate at the individual level.

The value of lymphocyte-to-monocyte ratio and neutrophil-to-lymphocyte ratio in differentiating pneumonia from upper respiratory tract infection (URTI) in children: a cross-sectional study

BACKGROUNDS

Early and accurate diagnosis of pediatric pneumonia in primary health care can reduce the chance of long-term respiratory diseases, related hospitalizations and mortality while lowering medical costs. The aim of this study was to assess the value of blood biomarkers, clinical symptoms and their combination in assisting discrimination of pneumonia from upper respiratory tract infection (URTI) in children.

METHODS

Both univariate and multivariate logistic regressions were used to build the pneumonia screening model based on a retrospective cohort, comprised of 5211 children (age ≤ 18 years). The electronic health records of the patients, who had inpatient admission or outpatient visits between February 15, 2012 to September 30, 2018, were extracted from the hospital information system of Zhejiang Provincial People's Hospital, Hangzhou, Zhejiang Province, China. The children who were diagnosed with pneumonia and URTI were enrolled and their clinical features and levels of blood biomarkers were compared. Using the area under the ROC curve, both two screening models were evaluated under 80% (training) versus 20% (test) cross-validation data split for their accuracy.

RESULTS

In the retrospective cohort, 2548 of 5211 children were diagnosed with the defined pneumonia. The univariate screening model reached predicted AUCs of 0.76 for lymphocyte/monocyte ratio (LMR) and 0.71 for neutrophil/lymphocyte ratio (NLR) when identified overall pneumonia from URTI, attaining the best performance among the biomarker candidates. In subgroup analysis, LMR and NLR attained AUCs of 0.80 and 0.86 to differentiate viral pneumonia from URTI, and AUCs of 0.77 and 0.71 to discriminate bacterial pneumonia from URTI respectively. After integrating LMR and NLR with three clinical symptoms of fever, cough and rhinorrhea, the multivariate screening model obtained increased predictive values, reaching validated AUCs of 0.84, 0.95 and 0.86 for distinguishing pneumonia, viral pneumonia and bacterial pneumonia from URTI respectively.

CONCLUSIONS

Our study demonstrated that combining LMR and NLR with critical clinical characteristics reached promising accuracy in differentiating pneumonia from URTI, thus could be considered as a useful screening tool to assist the diagnosis of pneumonia, in particular, in community healthcare centers. Further researches could be conducted to evaluate the model's clinical utility and cost-effectiveness in primary care scenarios to facilitate pneumonia diagnosis, especially in rural settings.

The Addition of Peripheral Blood Inflammatory Indexes to Nomogram Improves the Predictive Accuracy of Survival in Limited-Stage Small Cell Lung Cancer Patients

Background

Accumulated evidence for systemic inflammation response in several solid tumors prompts a possibility of prediction of patients’ prognosis in a more accessible and valuable manner. However, the prognostic value of peripheral blood inflammatory markers in limited-stage small cell lung cancer (LS-SCLC) remains unclear. Therefore, we investigated the prognostic values of pretreatment inflammatory indexes in LS-SCLC patients.

Methods

We retrospectively identified 334 patients with LS-SCLC and collected their pretreatment serum levels of neutrophil, platelet, lymphocyte, leukocyte, hemoglobin, and albumin, then neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic inflammation index (SII) were calculated. Patients were dichotomized as low-Risk or high-Risk group based on their corresponding cutoff values. Univariate and multivariate analyses were conducted with a Cox proportional hazards model. The least absolute shrinkage and selection operator (LASSO)-Cox regression analysis was performed to construct the inflammation-related prognostic scoring system named Risk for OS. Nomograms were established to provide prognostic information, allowing for more individualized prediction of survival.

Results

Higher pretreatment platelet, lymphocyte, and albumin were indicators of favorable overall survival (OS), whereas higher NLR and SII were accompanied by inferior OS. The prognosis of patients with high Risk was significantly worse than that with low Risk in both the training group and the validation group (both p < 0.001). Comparable area under the curve (AUC) values between the training group and the validation group were observed, yielding 1-, 3-, and 5-year OS rates of 67.3% vs. 69.2%, 66.8% vs. 69.5%, and 66.7% vs. 71.4%, respectively. Multivariate analyses revealed that Risk [hazard ratio (HR) = 0.551, p < 0.001] was an independent negative prognostic indicator for OS, which was further verified in the validation set. The addition of Risk to nomogram (C-index = 0.643) harbored improved predictive accuracy for OS when compared with that of clinical factors alone (C-index = 0.606); the AUC values of 1-, 3-, and 5-year OS rates were 71.7% vs. 66.4%, 73.5% vs. 66.6%, and 71.9% vs. 65.6%, respectively.

Conclusions

Pretreatment peripheral blood inflammatory indexes may be a noninvasive serum biomarker for poor prognosis in LS-SCLC. The addition of Risk to the nomogram model could serve as a more powerful, economical, and practical method to predict survival for patients with LS-SCLC.

Direct Comparison Between the Addition of Pembrolizumab or Bevacizumab for Chemotherapy-Based First-Line Treatment of Advanced Non-Squamous Non-Small Cell Lung Cancer Lacking Driver Mutations

Background

The addition of bevacizumab or pembrolizumab to pemetrexed-platinum chemotherapy has produced significant clinical benefits to patients with untreated, advanced non-squamous non-small cell lung cancer (NSCLC) lacking targetable genetic aberrations. However, the direct comparison between these two first-line treatments needs to be investigated.

Methods

We retrospectively investigated the medical records of 102 patients with stage IIIB~IV non-squamous NSCLC, and without sensitizing EGFR/ALK/ROS1 alterations. All patients received pembrolizumab or bevacizumab plus pemetrexed-platinum chemotherapy as the first-line treatment between December 2018 to April 2021 at Fudan University Shanghai Cancer Center. Assessments included progression-free survival (PFS), overall survival (OS), objective response rate (ORR), disease control rate (DCR), and adverse events (AEs). We also evaluated the prognostic biomarkers in the overall population and explored potential predictive biomarkers to aid the selection of optimal treatment regimens.

Results

The median PFS was 10.0 months in the pembrolizumab group and 9.2 months in bevacizumab group (HR = 1.006; P = 0.982), while the median OS was not reached in either group (HR= 1.193; P =0.714). ORR was 36.7% versus 43.4% (P = 0.548) and DCR was 89.8% versus 92.5% (P = 0.735) in the pembrolizumab and bevacizumab groups, respectively. In the overall study population, baseline lymphocyte to monocyte ratio (LMR) >1.95 (HR = 0.312, P < 0.001) was an indicator of longer PFS. The presence of baseline bone metastasis (HR = 4.107, P = 0.009), baseline lactate dehydrogenase (LDH) >300 U/L (HR = 4.300, P = 0.025) and LMR ≤1.95 (HR = 5.291, P = 0.039) were associated with inferior OS. Baseline neutrophil-to-lymphocyte ratio (NLR) ≤3.10 was predictive of significantly favorable OS in the bevacizumab combination treatment (HR = 5.073, P = 0.039). The safety profiles were generally comparable between the two groups.

Conclusions

In patients with chemotherapy-naive, advanced, non-squamous NSCLC who lack driver mutations, the efficacy and safety of pembrolizumab and bevacizumab when combined with pemetrexed-platinum were comparable. For patients with baseline NLR ≤3.10, the bevacizumab combination therapy elicited significantly better OS benefits.

The Value of Population Screening in Advancing Personalized Medicine in the Field of Lung Cancer

During the past decade, progress has been made in the field of lung cancer molecular biology and onco-immunology, leading to prolonged survival of patients. The combination of increased fundamental knowledge and the pharmaceutical pipeline has allowed the development of various tyrosine kinase inhibitors, targeting numerous molecular alterations. These drugs are now available in daily practice and have transformed survival outcomes for patients harboring EGFR, ALK or ROS1 alterations. Multiple clinical trials are now ongoing in order to increase the number of approved drugs, thus overcoming the issues of rare mutations and tyrosine kinase inhibitors resistance. Immune checkpoint inhibitors development has also changed lung cancer outcomes, but underwhelming response rates highlight the need for immune biomarkers. While PD-L1 expression was the first approved immune biomarker, it has shown several limitations and new biomarkers have to be identified to predict response or resistance to immune checkpoint inhibitors. Testing methods, molecular results and targeted therapeutic schedules will be harmonized in the coming years, with the help of dedicated molecular multidisciplinary boards.

Elevated Pretreatment Fibrinogen-to-Lymphocyte Percentage Ratio Predict Tumor Staging and Poor Survival in Non-Small Cell Lung Cancer Patients with Chemotherapy or Surgery Combined with Chemotherapy

Purpose

The objective of our study was to assess the association between lymphocyte percentage (LY%), fibrinogen (FIB), fibrinogen-to-lymphocyte percentage ratio (FLR) and the tumor staging and the clinical outcome role in non-small cell lung cancer (NSCLC) patients with chemotherapy or surgery combined with chemotherapy.

Patients and Methods

Between August 2013 and October 2020, 375 patients initially diagnosed with NSCLC and 201 healthy subjects were enrolled in the retrospective study. The concentrations of LY%, FIB, and FLR were compared between the case group and the control group by using the Mann–Whitney U-test or Kruskal–Wallis test, and then these biomarkers were compared in terms of the tumor category and PTNM stage of the test group, etc. The cutoffs of LY%, FIB, and FLR were determined using X-tile software. The prognostic roles of LY%, FIB, and FLR were identified by the Kaplan–Meier curve and Cox regression model. The biological markers on overall survival (OS) were analyzed.

Results

The study showed that the concentration levels of LY%, FIB, and FLR in the stage III–IV group were significant difference from those in the stage I–II group (P<0.001), indicating that three biomarkers (LY%, FIB, and FLR) were significantly correlated with tumor staging. Pretreatment high FIB and FLR and low LY% indicated an increased risk of death in NSCLC patients. Also, it was found that the clinical outcome of low FLR patients with chemotherapy or chemotherapy combined with surgery was superior to high FLR patients.

Conclusion

Our findings demonstrated that FLR could be used to predict NSCLC staging and was an independent prognosis factor within NSCLC patients receiving chemotherapy or chemotherapy combined with surgery.

Neutrophil-to-Lymphocyte Ratio Is Superior to Other Leukocyte-Based Ratios as a Prognostic Predictor in Non-Small Cell Lung Cancer Patients with Radiosurgically Treated Brain Metastases Under Immunotherapy or Targeted Therapy

OBJECTIVE

To investigate predictive value of preradiosurgery leukocyte-based prognostic ratios in a selected cohort of non-small cell lung cancer (NSCLC) patients with radiosurgery-treated brain metastases (BM) and concomitant immunotherapy (IT) or targeted therapy (TT).

METHODS

We performed a retrospective analysis of 166 patients with NSCLC BM treated with Gamma Knife radiosurgery. Neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio, and lymphocyte-to-monocyte ratio were assessed within 14 days before radiosurgery.

RESULTS

In radiosurgically treated patients with NSCLC BM with concomitant IT or TT, estimated median survival after first Gamma Knife radiosurgery treatment was significantly longer in patients with NLR cutoff value <5 (P = 0.038). Consequently, the Cox regression model for NLR cutoff value groups revealed a significant hazard ratio of 1.519 (95% confidence interval 1.020-2.265, P = 0.040). In addition, each increase in NLR of 1 equaled an increase of 5.4% in risk of death (hazard ratio 1.054, 95% confidence interval 1.024-1.085, P < 0.001). After adjusting for sex, age, Karnofsky performance scale, and presence of extracranial metastases, NLR remained a significant and independent predictor for survival (hazard ratio 1.047, 95% confidence interval 1.017-1.078, P = 0.002). In contrast, platelet-to-lymphocyte ratio and lymphocyte-to-monocyte ratio did not exhibit the same predictive value among patients with radiosurgery-treated BM with concomitant IT or TT.

CONCLUSIONS

In patients with NSCLC BM treated with radiosurgery with concomitant IT or TT, preradiosurgery NLR represents a simple prognostic predictor for survival and is superior to other leukocyte-based ratios. NLR may be relevant for clinical decision making, therapeutic evaluation, patient counseling, and appropriate stratification of future clinical trials among patients with radiosurgery-treated BM.

Can we define any marker associated with brain failure in patients with locally advanced non-small cell lung cancer?

PURPOSE

To define the factors which may be related to brain metastasis (BM) in patients with locally advanced non-small cell lung cancer (LA-NSCLC) who developed brain metastases after definitive treatment.

PATIENTS AND METHODS

A total of 208 patients with LA-NSCLC, without BM who received definitive radiotherapy (RT) or RT+chemotherapy (CT) between January 2005 and January 2016 were evaluated retrospectively. Platelet, neutrophil, lymphocyte counts, LDH, CRP, Hb levels, neutrophil-to-lymphocyte radio (NLR), platelet-to-lymphocyte radio (PLR), advanced lung cancer inflammation index (ALI) and FDG-PET/CT parameters (SUVmax of the primary tumor and mediastinal lymph nodes), and patient characteristics were evaluated for brain metastasis free survival (BMFS).

RESULTS

Median follow-up duration was 25 months (range: 3-130months). Cut-off values for platelet, NLR, PLR, LDH, CRP, and Hb were 290×103/μL, 2.6, 198, 468 IU/L, 2.5mg/dL, and 11.5g/dl. We defined each parameter as low or high according to the cut-off values. 56 patients (26.9%) developed brain metastases during follow-up. In univariate analysis, high NLR (P=0.001), PLR (P=0.037), LDH (P=0.028), CRP (P=0.002) values, value ≥7.5 for lymph nodes (P=0.005) and low ALI value (P=0.002) were poor prognostic factors for BMFS. In multivariate analysis, high NLR (P=0.022), PLR (P=0.017), CRP (P=0.006), stage ≥IIIB disease (P<0.001), multi-stational N2 disease (P=0.036), adenocarcinoma histology (P<0.001) and SUVmax value ≥7.5 (P=0.035) were poor prognostic factors for BMFS.

CONCLUSIONS

High NLR, PLR, LDH, CRP values, SUVmax values for lymph nodes, and low ALI which indicates high tumor burden were additional prognostic factors besides stage, histology, and lymph node status.

Prognostic significance of the neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio for advanced non-small cell lung cancer patients with high PD-L1 tumor expression receiving pembrolizumab

Background

We investigated the association of peripheral blood inflammatory markers with overall survival (OS) in pembrolizumab treated advanced non-small cell lung cancer (aNSCLC) patients with programmed death ligand 1 (PD-L1) expression ≥50%. Clinical risk factors for development of immune-related adverse events (irAE) were also explored.

Methods

aNSCLC patients with high PD-L1 expression receiving pembrolizumab monotherapy outside of clinical trials were identified retrospectively. All patients were treated at one of six British Columbia Cancer clinics between August 2017 and June 2019. Patients were dichotomized using baseline neutrophil-to-lymphocyte ratio (NLR, </≥6.4) and platelet-to-lymphocyte ratio (PLR, </≥441.8). Factors associated with OS were assessed with Cox proportional hazard models. Logistic regression models were utilized in landmark analysis of risk factors for irAE.

Results

Among 220 patients, median age was 70.0 years, 55.0% were female, 40.5% had baseline Eastern Cooperative Oncology Group performance status (ECOG PS) 2/3, and 95.5% received frontline pembrolizumab. Median OS for the cohort was 11.8 months (95% CI: 8.7–15.4). On multivariable analysis, baseline NLR ≥6.4 [hazard ratio (HR): 2.31, 95% confidence interval (CI): 1.46–3.64, P<0.001], baseline PLR ≥441.8 (HR: 2.03, 95% CI 1.22–3.37, P=0.006), and pre-treatment ECOG PS 2/3 (HR: 2.19, 95% CI: 1.48–3.26, P<0.001) were associated with worse OS. The incidence of any grade irAE and irAE grade ≥3 were 40.5% and 12.3%, respectively. ECOG PS 2/3 (vs. 0/1) patients were at 3.76-fold higher risk of developing an irAE by the 8-month landmark (P=0.002).

Conclusions

High NLR and PLR were associated with shorter OS in a cohort of patients receiving largely frontline pembrolizumab for aNSCLC in routine practice. ECOG PS 2/3 was associated with higher risk of developing an irAE. Given that NLR and PLR values are easily obtainable, prospective studies are warranted to confirm their prognostic significance in this patient population and explore a predictive utility.

Impact of Combined Chronic Obstructive Pulmonary Disease Status and Systemic Inflammation on Outcome of Advanced NSCLC: Multicenter Retrospective Cohort Study

Background

In patients with non-small cell lung cancer (NSCLC), both chronic obstructive pulmonary disease (COPD) and systemic inflammatory biomarkers, such as neutrophil-lymphocyte ratio (NLR) and platelet-lymphocyte ratio (PLR), have significant association with prognosis. NLR and PLR also predict mortality in patients with COPD alone. A combination of the two parameters may be helpful in a more individualized approach for predicting prognosis in NSCLC.

Methods

Medical records of patients with stage IIIB and IV NSCLC from January 2012 to January 2018 in seven university hospitals were reviewed. Patients were categorized into four subgroups based on pulmonary function test results and cutoffs for NLR or PLR.

Results

A total of 277 patients were evaluated and categorized into non-COPD and COPD groups; 194 patients were in the non-COPD group and 83 patients were in the COPD group. The non-COPD group showed significantly longer overall survival (OS) compared with the COPD group (P = 0.019). Median survival was significantly different between high/low PLR groups (P < 0.001), between high/low NLR groups (P = 0.001), and between high/low c-reactive protein (CRP) groups (P < 0.001). PLR, NLR and CRP showed significant correlations with each other. PLR showed a significant negative linear correlation with FVC (absolute) (r = −0.149, P = 0.015), FVC (%) (r = −0.192, P = 0.002), DLCO (absolute) (r = −0.271, P < 0.001), DLCO (%) (r = −0.139, P = 0.032), and NLR (r = 0.718, P < 0.001). In the multivariate analysis, the high PLR, COPD sub-group showed significantly higher risk for mortality (HR 2.066 (1.175–3.633), P = 0.012) compared with the low-PLR non-COPD group. However, COPD-NLR subtype was not an independent predictor for OS.

Conclusion

A combination of COPD status and PLR may be a cost-effective and readily available prognostic marker in patients with advanced NSCLC.

Pre-radiosurgery leucocyte ratios and modified glasgow prognostic score predict survival in non-small cell lung cancer brain metastases patients

INTRODUCTION

The predictive value of the pre-radiosurgery Neutrophil-to-Lymphocyte Ratio (NLR), Platelet-to-Lymphocyte Ratio (PLR), Lymphocyte-to-Monocyte Ratio (LMR) and the modified Glasgow Prognostic Score (mGPS) was assessed for the first time in a homogenous group of NSCLC brain metastaes (BM) patients.

METHODS

We retrospectively evaluated 185 NSCLC-BM patients, who were treated with Gamma Knife Radiosurgery (GKRS). Patients with immunotherapy or targeted therapy were excluded. Routine laboratory parameters were reviewed within 14 days before GKRS1.

RESULTS

Median survival after GKRS1 was significantly longer in patients with NLR < 5 (p < 0.001), PLR < 180 (p = 0.003) and LMR ≥ 4 (p = 0.023). The Cox regression model for the continuous metric values revealed that each increase in the NLR of 1 equaled an increase of 4.3% in risk of death (HR: 1.043; 95%CI = 1.020-1.067, p < 0.001); each increase in the PLR of 10 caused an increase of 1.3% in risk of death (HR: 1.013; 95%CI = 1.004-1.021; p = 0.003) and each increase in the LMR of 1 equaled a decrease of 20.5% in risk of death (HR: 0.795; 95%CI = 0.697-0.907; p = 0.001). Moreover, the mGPS group was a highly significant predictor for survival after GKRS1 (p < 0.001) with a HR of 2.501 (95%CI = 1.582-3.954; p < 0.001). NLR, PLR, LMR values and mGPS groups were validated as independent prognostic factors for risk of death after adjusting for sex, KPS, age and presence of extracranial metastases.

CONCLUSION

NLR, PLR, LMR and mGPS represent effective and simple tools to predict survival in NSCLC patients prior to radiosurgery for brain metastases.

Prognostic value of intratumoral lymphocyte-to-monocyte ratio and M0 macrophage enrichment in tumor immune microenvironment of melanoma

Skin cutaneous melanoma is characterized by significant heterogeneity in its molecular, genomic and immunologic features. Whole transcriptome RNA sequencing data from The Cancer Genome Atlas of skin cutaneous melanoma (n = 328) was utilized. CIBERSORT was used to identify immune cell type composition, on which unsupervised hierarchical clustering was performed. Analysis of overall survival was performed using Kaplan–Meier estimates and multivariate Cox regression analyses. Membership in the lymphocyte:monocyte^low, monocyte^high and M0^high cluster was an independently poor prognostic factor for survival (HR: 3.03; 95% CI: 1.12–8.20; p = 0.029) and correlated with decreased predicted response to immune checkpoint blockade. In conclusion, an M0-macrophage-enriched, lymphocyte-to-monocyte-ratio-low phenotype in the primary melanoma tumor site independently characterizes an aggressive phenotype that may differentially respond to treatment.

Initial neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio as prognostic markers in patients with inoperable locally advanced non-small-cell lung cancer

Aim: To determine whether pretreatment of neutrophil-to-lymphocyte ratio (NLR) or platelet-to-lymphocyte ratio (PLR) has a prognostic value in patients with inoperable locally advanced non-small-cell lung cancer. Materials & methods: A total of 167 patients between 2013 and 2016 were analyzed retrospectively. Results: Appropriate cut-off values for initial NLR (3.06) and PLR (168.03) were determined by receiver operating characteristic curves. High NLR (p < 0.001 and p < 0.001) was related to poor overall survival (OS) and progression-free survival (PFS) via univariate analysis. Multivariable analysis showed that NLR can independently influence OS (hazard ratio: 1.570; p = 0.012) and PFS (hazard ratio: 1.471; p = 0.023). PLR did not correlate with OS or PFS. Conclusion: Pretreatment of NLR could independently predict the prognosis of inoperable locally advanced non-small-cell lung cancer patients, while pretreatment of PLR does not have prognostic value.

Neutrophil-lymphocyte ratio and platelet-lymphocyte ratio associations with heart and body dose and their effects on patient outcomes in locally advanced non-small cell lung cancer treated with definitive radiotherapy

Background

Inflammation plays a vital role in tumor growth and progression and can be affected by radiotherapy (RT) and chemotherapy. We sought to investigate the prognostic significance of neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR), and their associations with dosimetric factors in locally advanced non-small cell lung cancer (LA-NSCLC).

Methods

In this retrospective study, subjects consisted of 244 patients who had received definitive RT ± chemotherapy for LA-NSCLC between 2012 and 2016. Absolute lymphocyte count (ALC), NLR and PLR recorded at pretreatment, during RT and post-RT were analyzed. Multivariable analysis (MVA) was performed to correlate clinical factors and inflammatory biomarkers with progression-free survival (PFS) and overall survival (OS) using a Cox regression model. Relationships between NLR or PLR with OS and PFS were evaluated with Kaplan-Meier analysis and compared with log-rank test results. Multiple stepwise linear regression was used to assess the associations between dosimetric factors and NLR or PLR.

Results

The median PFS and OS for all patients were 8.6 and 15.8 months, respectively. On MVA for PFS and OS, higher 1-month post-RT start NLR [hazard ratio (HR) 1.049; 95% CI: 1.018–1.080; P=0.001] or higher 1-month post-RT start PLR (HR 1.001; 95% CI: 1.000–1.002; P<0.001) was associated with inferior PFS. Higher 1-month post-RT start NLR (HR 1.040; 95% CI: 1.013–1.069; P=0.004) or PLR (HR 1.001; 95% CI: 1.001–1.002; P<0.001) was also an independent predictor of OS. ALCmin, baseline NLR and PLR were not associated with treatment outcomes. Multiple stepwise linear regression analysis confirmed that baseline NLR (P<0.001), heart V20 (P<0.001), heart V40 (P<0.001), and mean body dose (MBD) were significantly associated with 1-month post-RT start NLR. Also, baseline PLR (P<0.001) and MBD (P<0.001) were significantly associated with 1-month post-RT start PLR.

Conclusions

Higher NLR and PLR during treatment were associated with worse patient outcomes, and heart dose or body dose was correlated with NLR or PLR in advanced NSCLC patients treated with definitive RT.

Pretreatment inflammatory indexes as prognostic predictors for survival in osteosarcoma patients

Pretreatment inflammatory indexes including neutrophil-lymphocyte ratio (NLR), lymphocyte-monocyte ratio (LMR), platelet-lymphocyte ratio (PLR), and systemic immune-inflammation index (SII) are associated with poor outcomes in various malignant tumors, but their prognostic value in patients with osteosarcoma is poorly known. This was a retrospective study of patients with osteosarcoma treated between 01/2010 and 12/2013 at Chongqing University Cancer Hospital. Follow-up was calculated from the date of initial histological diagnosis to December 2018 or death or loss of follow-up. Receiver operating characteristic (ROC) analysis was used to determine the NLR, LMR, PLR, and SII cut-off values (low (L) vs. high (H)). The Kaplan-Meier method was used for survival analysis. Univariable and multivariable Cox analyses were performed to determine the independent prognostic factors. Patients with LNLR had better survival than those with HNLR (median, 38.0 vs. 13.0, P<0.001). Patients with LSII had better survival (26.0 vs. 10.0 months, P=0.001) than those with HSII. The areas under the curves for NLR, LMR, PLR, SII, and ALP were 0.761 (P<0.001), 0.683 (P=0.012), 0.697 (P=0.002), 0.653 (P=0.031), and 0.515 (P=0.837), respectively. In the univariable analyses, Enneking's stage, systemic chemotherapy, surgery, NLR, PLR, LMR, and SII were associated with overall survival (OS). The multivariable analysis showed that HNLR (HR=2.507; 95% CI=1.364-4.606; P=0.003) was independent unfavorable prognostic factors. This preliminary study suggests that NLR is associated with poor prognosis in osteosarcoma. NLR could be a potential prognostic marker of osteosarcoma.

Neutrophil-to-Lymphocyte Ratio (NLR), Platelet-to-Lymphocyte Ratio (PLR), and Outcomes with Nivolumab in Pretreated Non-Small Cell Lung Cancer (NSCLC): A Large Retrospective Multicenter Study

INTRODUCTION

Immune checkpoint inhibitors have provided substantial benefit in non-small cell lung cancer (NSCLC) with unprecedented results in terms of survival. However, the identification of reliable predictive biomarkers to these agents is lacking and multiple clinicopathological factors have been evaluated. The aim of this study was to analyze the potential role of neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and lactate dehydrogenase (LDH) levels in patients with pretreated NSCLC receiving nivolumab.

METHODS

This was a retrospective multicenter study involving 14 Italian centers, evaluating the role of some laboratory results in patients with NSCLC treated with nivolumab in the second or later lines of therapy for at least four doses and with a disease re-staging.

RESULTS

A total of 187 patients with available pretreatment laboratory results were included. NLR levels below 5 were associated with an improvement in terms of both progression-free survival (PFS) (p = 0.028) and overall survival (OS) (p = 0.001), but not in terms of overall response rate (ORR) or disease control rate (DCR). Moreover, PLR levels below 200 were associated with longer PFS (p = 0.0267) and OS (p = 0.05), as well as higher ORR (p = 0.04) and DCR (p = 0.001). In contrast, LDH levels above the upper normal limit (UNL) were not associated with significant impact on patient outcomes.

CONCLUSIONS

Patients with pretreated NSCLC and high pretreatment levels of NLR and PLR may experience inferior outcomes with nivolumab. Therefore, in this subgroup of patients with poor prognosis the use of alternative therapeutic strategies may be a valuable option, especially in programmed cell death ligand 1 (PD-L1)-negative patients and/or in the presence of other additional poor prognostic factors.