Prognostic value of delta inflammatory biomarker-based nomograms in patients with inoperable locally advanced NSCLC

Monocyte-to-lymphocyte ratio is a prognostic predictor for patients with non-small cell lung cancer treated with stereotactic body radiation therapy

Background

The monocyte-to-lymphocyte ratio (MLR), a systemic inflammation biomarker, has been shown to predict patient outcomes in several types of cancer. This study aimed to determine the association between MLR and local control (LC) and cause-specific survival (CSS) rates in patients with non-small cell lung cancer (NSCLC) treated with stereotactic body radiation therapy (SBRT).

Materials and methods

The median age of the 194 included participants (144 men, 50 women) was 80 (range, 50-96) years. The median follow-up period was 19 (range, 1-108) months. The LC and CSS rates were calculated using the Kaplan-Meier method. Univariate and multivariate Cox proportional hazard regression models were used to estimate the LC and CSS rates.

Results

Local recurrence was observed in 25 patients during the follow-up. Univariate Cox proportional hazards regression analysis revealed that MLR, performance status, and tumor diameter were significant factors for LC. Multivariate analysis showed MLR and tumor diameter as significant factors (p = 0.041 and 0.031, respectively). The 1- and 2-year LC rates for the lower and higher MLR groups were 97.5% and 97.5%, and 89.7% and 81.2%, respectively. During the follow-up period, 14 patients died due to NSCLC. Although MLR tended to predict CSS in univariate analysis (p = 0.086), none of the parameters was significant in predicting CSS. However, MLR as a continuous variable was a significant factor for CSS in the univariate analysis (p = 0.004).

Conclusions

Our data suggest that MLR is correlated with LC and CSS rates in NSCLC patients treated with SBRT.

Prognostic value of neutrophil-to-lymphocyte ratio change in patients with locally advanced non-small cell lung cancer treated with thoracic radiotherapy

In prior investigations, a correlation was established between patient outcomes in locally advanced non-small cell lung cancer (LA-NSCLC) following thoracic irradiation and parameters, such as pre/post-treatment neutrophil-to-lymphocyte ratio (NLR) and NLR change (ΔNLR). However, these parameters could potentially be influenced by radiation-related variables, such as gross tumor volume (GTV). The primary aim of this study was to elucidate the factors impacting post-treatment NLR and ΔNLR and to further assess their prognostic relevance. In this retrospective study, a cohort of 188 LA-NSCLC patients who underwent thoracic radiation between 2012 and 2017 was assessed. The calculation of pre/post-treatment NLR involved the use of absolute neutrophil and lymphocyte counts. ΔNLR was defined as the difference between post- and pre-treatment NLR values. To assess the relationships between various variables and overall survival (OS), local progression-free survival (LPFS), and distant metastasis-free survival (DMFS), the Kaplan-Meier technique and Cox proportional hazards regression were employed. Additionally, Spearman's rank correlation analysis was carried out to investigate correlations between the variables. The analysis revealed that both post-treatment NLR (r = 0.315, P < 0.001) and ΔNLR (r = 0.156, P = 0.032) were associated with GTV. However, OS, LPFS, and DMFS were not independently correlated with pre/post-treatment NLR. ΔNLR, on the other hand, exhibited independent associations with OS and DMFS (HR = 1.054, P = 0.020, and P = 0.046, respectively). Elevated ΔNLR values were linked to poorer OS (P = 0.023) and DMFS (P = 0.018) in the Kaplan-Meier analysis. Furthermore, when stratifying by GTV, a higher ΔNLR remained to be associated with worse OS and DMFS (P = 0.047 and P = 0.035, respectively) in the GTV ≤ 67.41 cm3 group, and in the GTV > 67.41 cm3 group (P = 0.028 and P = 0.042, respectively), highlighting ΔNLR as the sole independent predictive factor for survival and metastasis, irrespective of GTV.

Predictive value of the neutrophil-to-lymphocyte ratio in the prognosis and risk of death for adult sepsis patients: a meta-analysis

Background

The neutrophil-to-lymphocyte ratio (NLR) is a commonly used biomarker for acute inflammation that often rises during sepsis, making it a valuable diagnostic indicator for clinical practice. However, no consensus has been reached on the prognostic value of NLR for predicting the prognosis and mortality risk in adult sepsis patients. In light of this controversy, we conducted a meta-analysis to clarify the prognostic significance of NLR in adult sepsis patients. The meta-analysis was registered in the PROSPERO database (registration number CRD42023433143).

Methods

We performed a comprehensive literature search in PubMed, Cochrane Library, Ovid, and Springer databases, using retrieval terms "sepsis" or "septic shock" and "prognosis" or "mortality" for studies published between January 1, 2000, and May 31, 2023. Children and neonates with sepsis were excluded from our research. Two independent researchers conducted the literature search and data extraction. Consensus was reached when discrepancies occurred, and in case of persistent discrepancies, the final decision was made by the research supervisor. The hazard ratio (HR) and its corresponding 95% confidence interval (95% CI) were extracted from each study included in the analysis. A random-effects model was used to synthesize all HRs and their 95% CIs. Sensitivity analysis was performed to investigate heterogeneity. Sensitivity analysis was conducted to identify studies that had a significant impact on the overall results of the meta-analysis. Subgroup analysis and meta-regression were performed to explore sources of heterogeneity. Egger's test was also used to investigate publication bias in this meta-analysis.

Results

After a comprehensive literature search and screening, we included 12 studies comprising 10,811 patients for the meta-analysis. The pooled results indicated that patients with a higher NLR level were associated with a poor prognosis (Random-effects model, HR: 1.6273, 95% CI: 1.3951-1.8981). Heterogeneity testing showed significant heterogeneity (I2 = 87.2%, 95% CI: 79.5-92, p<0.0001). Sensitivity analysis was performed to investigate the sources of heterogeneity, which revealed that the omission of one highly sensitive study significantly reduced the I2 value. After removing this study, a strong association was found between a higher NLR level and poor prognosis and risk of death in adult sepsis patients (Random-effects model, HR: 1.6884, 95% CI: 1.4338-1.9882). Both subgroup analysis and meta-regression indicated that the study design and testing time of NLR were sources of heterogeneity. Egger's test showed no obvious publication bias in this meta-analysis.

Conclusion

NLR is a reliable and valuable biomarker for predicting prognosis and the risk of death in adult sepsis patients.

Systematic Review Registration

[https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023433143] PROSPERO, identifier [CRD42023433143].

The potential of high-order features of routine blood test in predicting the prognosis of non-small cell lung cancer

BACKGROUND

Numerous studies have demonstrated that the high-order features (HOFs) of blood test data can be used to predict the prognosis of patients with different types of cancer. Although the majority of blood HOFs can be divided into inflammatory or nutritional markers, there are still numerous that have not been classified correctly, with the same feature being named differently. It is an urgent need to reclassify the blood HOFs and comprehensively assess their potential for cancer prognosis.

METHODS

Initially, a review of existing literature was conducted to identify the high-order features (HOFs) and classify them based on their calculation method. Subsequently, a cohort of patients diagnosed with non-small cell lung cancer (NSCLC) was established, and their clinical information prior to treatment was collected, including low-order features (LOFs) obtained from routine blood tests. The HOFs were then computed and their associations with clinical features were examined. Using the LOF and HOF data sets, a deep learning algorithm called DeepSurv was utilized to predict the prognostic risk values. The effectiveness of each data set's prediction was evaluated using the decision curve analysis (DCA). Finally, a prognostic model in the form of a nomogram was developed, and its accuracy was assessed using the calibration curve.

RESULTS

From 1210 documents, over 160 blood HOFs were obtained, arranged into 110, and divided into three distinct categories: 76 proportional features, 6 composition features, and 28 scoring features. Correlation analysis did not reveal a strong association between blood features and clinical features; however, the risk value predicted by the DeepSurv LOF- and HOF-models is significantly linked to the stage. Results from DCA showed that the HOF model was superior to the LOF model in terms of prediction, and that the risk value predicted by the blood data model could be employed as a complementary factor to enhance the prognosis of patients. A nomograph was created with a C-index value of 0.74, which is capable of providing a reasonably accurate prediction of 1-year and 3-year overall survival for patients.

CONCLUSIONS

This research initially explored the categorization and nomenclature of blood HOF, and proved its potential in lung cancer prognosis.

A new prognostic nomogram in patients with mucosa-associated lymphoid tissue lymphoma: a multicenter retrospective study

Background

The present study sought to understand how clinical factors and inflammatory biomarkers affected the prognosis of mucosa-associated lymphoid tissue (MALT) lymphoma and develop a predictive nomogram to assist in clinical practice.

Methods

We conducted a retrospective study on 183 cases of newly diagnosed MALT lymphoma from January 2011 to October 2021, randomly divided into two groups: a training cohort (75%); and a validation cohort (25%). The least absolute shrinkage and selection operator (LASSO) regression analysis was combined with multivariate Cox regression analysis to construct a nomogram for predicting the progression-free survival (PFS) in patients with MALT lymphoma. To evaluate the accuracy of the nomogram model, the area under the receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) were used.

Results

The PFS was significantly associated with the Ann Arbor Stage, targeted therapy, radiotherapy, and platelet-to-lymphocyte ratio (PLR) in MALT lymphoma. These four variables were combined to establish a nomogram to predict the PFS rates at three and five years. Importantly, our nomogram yielded good predictive value with area under the ROC curve (AUC) values of 0.841 and 0.763 in the training cohort and 0.860 and 0.879 in the validation cohort for the 3-year and 5-year PFS, respectively. Furthermore, the 3-year and 5-year PFS calibration curves revealed a high degree of consistency between the prediction and the actual probability of relapse. Additionally, DCA demonstrated the net clinical benefit of this nomogram and its ability to identify high-risk patients accurately.

Conclusion

The new nomogram model could accurately predict the prognosis of MALT lymphoma patients and assist clinicians in designing individualized treatments.

Effects of yoga practice on physiological distress, fatigue and QOL in patients affected by breast cancer undergoing adjuvant radiotherapy

Background and purpose

In this study we want to evaluate the efficacy of yoga practice on dysfunctional stress, inflammation and QOL in breast cancer patients undergoing adjuvant radiotherapy.

Patients and methods

Patients with stage 0 to III breast cancer were recruited before starting radiotherapy (XRT) and were randomly assigned to yoga group (YG) two times a week during XRT or control group (CG). Self-report measures of QOL, fatigue and sleep quality, and blood samples were collected at day 1 of treatment, day 15, end of treatment and 1, 3 and 6 months later. Cortisol blood level, IL6, IL10, IL1RA, TNFα and lymphocyte-to-monocyte ratio were analyzed as measures of dysfunctional stress and inflammation.

Results

Patients started XRT and yoga classes in October 2019. Due to COVID-19 pandemic we closed the enrollment in March 2020. We analysed 24 patients, 12 YG and 12 CG. The analysis of blood cortisol levels revealed an interaction (p = 0.04) between yoga practice and time, in particular YG had lower cortisol levels at the end of XRT respect to CG (p-adj = 0.02). The analysis of IL-1RA revealed an interaction effect (p = 0.04) suggesting differences between groups at some time points that post-hoc tests were not able to detect.

Conclusions

To our knowledge, this is the first study to evaluate the effects of yoga in a cancer population studying inflammation markers, cortisol trend and QOL during and until 6 months after XRT. This study suggests that yoga practice is able to reduce stress and inflammation levels over time. Besides including a larger number of patients to increase the power, future studies should consider other inflammatory or pro inflammatory factors and long-term yoga program to gain more evidence on yoga practice benefits.

Inflammatory Indexes as Predictive Biomarkers of Postoperative Complications in Oncological Thoracic Surgery

The role of inflammatory responses in predicting outcomes in oncological thoracic surgery is still unclear. The aim of this study was to evaluate a series of blood count inflammation indexes as predicting factors for postoperative complications. We retrospectively studied 249 patients undergoing elective thoracic surgery in our institution between 2008 and 2020. A total of 184 patients underwent open surgery, and 65 underwent VATS. The neutrophil-to-lymphocyte (NLR), monocyte-to-lymphocyte (MLR), and platelet-to-lymphocyte (PLR) ratios, Systemic Inflammation Response Index (SIRI) were calculated preoperatively and on the first and fourth postoperative days, as well as a new derivative index, the Aggregate Inflammation Systemic Index (AISI). Univariate correlations evidenced a statistically significant association between the NLR at the fourth postoperative day and the occurrence of surgical complications in the global cohort (rho = 0.15, p = 0.03). A similar significant association with MLR on the fourth postoperative day is found in the open group (rho = −0.15, p = 0.048). NLR and LMR on the fourth postoperative day are associated with postoperative complications in the whole and open groups, respectively. Simple, easy-to-perform and inexpensive, blood cell count indexes may be useful in predicting complications in oncological thoracic surgery. A greater number of broader, prospective, randomized studies are necessary to confirm these findings.

Predicting 2-year survival in stage I-III non-small cell lung cancer: the development and validation of a scoring system from an Australian cohort

Background

There are limited data on survival prediction models in contemporary inoperable non-small cell lung cancer (NSCLC) patients. The objective of this study was to develop and validate a survival prediction model in a cohort of inoperable stage I-III NSCLC patients treated with radiotherapy.

Methods

Data from inoperable stage I-III NSCLC patients diagnosed from 1/1/2016 to 31/12/2017 were collected from three radiation oncology clinics. Patient, tumour and treatment-related variables were selected for model inclusion using univariate and multivariate analysis. Cox proportional hazards regression was used to develop a 2-year overall survival prediction model, the South West Sydney Model (SWSM) in one clinic (n = 117) and validated in the other clinics (n = 144). Model performance, assessed internally and on one independent dataset, was expressed as Harrell’s concordance index (c-index).

Results

The SWSM contained five variables: Eastern Cooperative Oncology Group performance status, diffusing capacity of the lung for carbon monoxide, histological diagnosis, tumour lobe and equivalent dose in 2 Gy fractions. The SWSM yielded a c-index of 0.70 on internal validation and 0.72 on external validation. Survival probability could be stratified into three groups using a risk score derived from the model.

Conclusions

A 2-year survival model with good discrimination was developed. The model included tumour lobe as a novel variable and has the potential to guide treatment decisions. Further validation is needed in a larger patient cohort.

Elevated Neutrophil-to-Lymphocyte Ratio in Perioperative Periods is Suggestive of Poor Prognosis in Patients with Colorectal Cancer

Background

Recent data suggest that alterations in the neutrophil-to-lymphocyte ratio (NLR) in the perioperative periods can serve as prognostic factors. However, research on the clinical impact has been limited and even discordant in patients with colorectal cancer (CRC).

Patients and Methods

The optimal cut-off value of preoperative NLR (NLR-pre), postoperative NLR (NLR-post), and its change (NLR-delta) were determined to maximize differences in overall survival (OS) between groups. Patients were categorized into four groups (NLR-trend) as follows: G1, low NLR-pre and NLR-post; G2, low NLR-pre and high NLR-post; G3, high NLR-pre and low NLR-post; and G4, high NLR-pre and NLR-post. Discriminatory performance was compared using integrated AUC (iAUC) between all indicators.

Results

A total of 576 patients diagnosed with stage I–IV CRC were included. The cut-off points were determined as 2.33 for NLR-pre, 2.06 for NLR-post, and −1.08 for NLR-delta. Subgroup dichotomization using NLR-pre, NLR-post, NLR-delta and NLR-trend were all identified as significant prognostic factors by univariate analysis. However, NLR-trend was only remained as an independent prognostic factor in the multivariate analysis. The iAUC of the NLR-trend was superior to that of NLR-pre (bootstrap iAUC mean difference=0.036; 95% CI 0.013–0.073), NLR-post (bootstrap iAUC mean difference=0.045; 95% CI 0.019–0.081) and NLR-delta (bootstrap iAUC mean difference=0.061; 95% CI 0.025–0.104).

Conclusion

Risk stratification and combining of preoperative and postoperative NLR (NLR-trend) can improve prognostic discrimination compared with single measurements or simple changes in NLR in patients with CRC.

Changes in the neutrophil to lymphocyte ratio as predictors of outcome in pediatric patients with central nervous system tumors undergoing surgical resection

BACKGROUND

Changes in neutrophil to lymphocyte ratio (ΔNLR) have been used as a clinical tool for stratification and prognosis of patients with solid tumors, there is scarce evidence of their clinical relevance in patients with tumors of the central nervous system who have also undergone surgical resection.

OBJECTIVE

Determine if (ΔNLR) are associated with poor response to treatment and worse prognosis in pediatric patients with central nervous system tumors (CNST) who underwent surgical resection.

METHODS

We performed a retrospective cohort study; demographic, clinical, and hematological variables were evaluated, Kaplan-Meier survival curves and Cox proportional hazards regression model were performed to evaluate prognosis.

RESULTS

The ΔNLR cutoff value obtained through the third interquartile range was 4.30; The probability of survival and complete response to treatment was different between patients with high ΔNLR when compared to patients with low ΔNLR (p= 0.013, p=≪ 0.001, respectively). A high ΔNLR behaved as an independent predictor of worse Overall Survival (HR 2,297; 95% CI: 1,075-4.908, p= 0.032).

CONCLUSION

An elevated ΔNLR was a predictor of poor response to treatment and a prognostic factor for worse Overall Survival in pediatric patients with CNST undergoing surgical resection.

The Influence of Severe Radiation-Induced Lymphopenia on Overall Survival in Solid Tumors: A Systematic Review and Meta-Analysis

PURPOSE

Emerging evidence suggests a detrimental prognostic association between radiation-induced lymphopenia (RIL) and pathologic response, progression-free survival, and overall survival (OS) in patients who undergo radiation therapy for cancer. The aim of this study was to systematically review and meta-analyze the prognostic impact of RIL on OS in patients with solid tumors.

METHODS AND MATERIALS

PubMed/MEDLINE and Embase were systematically searched. The analysis included intervention and prognostic studies that reported on the prognostic relationship between RIL and survival in patients with solid tumors. An overall pooled adjusted hazard ratio (aHR) was calculated using a random-effects model. Subgroup analyses for different patient-, tumor-, treatment-, and study-related characteristics were performed using meta-regression.

RESULTS

Pooling of 21 cohorts within 20 eligible studies demonstrated a statistically significant association between OS and grade ≥3 versus grade 0-2 RIL (n = 16; pooled aHR, 1.65; 95% confidence interval [CI], 1.43-1.90) and grade 4 RIL versus grade 0-3 (n = 5; aHR, 1.53; 95% CI, 1.24-1.90). Moderate heterogeneity among aHRs was observed, mostly attributable to overestimated aHRs in 7 studies likely subject to model-overfitting. Subgroup analysis showed significant prognostic impact of grade ≥3 RIL in 4 brain tumor (aHR, 1.63; 95% CI, 1.06-2.51), 4 lung cancer (aHR, 1.52; 95% CI, 1.01-2.29), and 3 pancreatic cancer (aHR, 1.92; 95% CI, 1.10-3.36) cohorts.

CONCLUSIONS

This meta-analysis demonstrates a significant detrimental prognostic association between grade ≥3 lymphopenia and OS in patients receiving radiation therapy for solid tumors. This finding appears consistent for tumors of the brain, thorax, and upper abdomen and provides an imperative to further elucidate the potential survival benefit of lymphopenia-mitigating strategies.

Prognostic value of baseline and change in neutrophil-to-lymphocyte ratio for survival in advanced non-small cell lung cancer patients with poor performance status receiving PD-1 inhibitors

Background

Advanced non-small cell lung cancer (NSCLC) patients with poor performance status (PS) are likely to receive programmed cell death 1 (PD-1) inhibitors, despite limited evidence. The aim of the present study was to report the clinical outcomes and potential prognostic biomarkers in advanced NSCLC patients with poor PS receiving PD-1 inhibitors.

Methods

We conducted a retrospective study enrolling 101 advanced NSCLC patients from our hospital. Data of patients with poor PS 2-4 receiving PD-1 inhibitors were retrieved from medical records. Patients were stratified based on dichotomized baseline neutrophil-to-lymphocyte ratio (NLR), change in NLR (ΔNLR; 6 weeks post-treatment NLR minus baseline NLR), and their combination. The receiver-operating characteristic curve was used to assess the best cutoff for NLR. Multivariate Cox analysis was used to evaluate the prognostic value of NLR and ΔNLR for patients' survival.

Results

The optimal cutoff for NLR was 4.5. The median follow-up was 25.7 months, baseline NLR ≥4.5, and ΔNLR ≥0, which were independently and significantly associated with shorter overall survival (both P=0.002) and progression-free survival (P=0.004 for NLR and P<0.001 for ΔNLR). Furthermore, simultaneous elevation of the 2 factors was associated with worsened prognosis; patients with both NLR ≥4.5 and ΔNLR ≥0 had significantly increased risk of death [hazards ratio (HR): 10.79, 95% confidence interval (CI): 4.30-27.10] and disease progression (HR: 10.49, 95% CI: 4.39-25.09), compared with both low NLR and ΔNLR patients. Patients with either NLR ≥4.5 or ΔNLR ≥0 showed an intermediate risk for death (HR: 3.12, 95% CI: 1.35-7.21) and progression (HR: 3.45, 95% CI: 1.62-7.36).

Conclusions

High baseline NLR and increased post-treatment NLR might aid in the stratification of high progression and death risk groups in advanced NSCLC patients with poor PS receiving PD-1 inhibitors.

Preoperative peripheral blood neutrophil-to-lymphocyte ratios (NLR) and platelet-to-lymphocyte ratio (PLR) related nomograms predict the survival of patients with limited-stage small-cell lung cancer

Background

We aim to establish neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) related nomograms based on the clinical data and peripheral blood markers to predict the survivals of patients with limited-stage small-cell lung cancer (LS-SCLC).

Methods

A total of 299 LS-SCLC patients after surgery were enrolled in this study. Univariate and multivariate analyses were conducted to select independent prognostic factors to develop the nomograms and then subjected to bootstrap internal validation. The optimal cutoff value of NLR and PLR before surgery was calculated by X-tile (version 3.6.1) and the overall survival (OS) was analyzed by Kaplan-Meier method and compared by log-rank test.

Results

According to the X-tile calculation, the NLR value and PLR cutoff values are 2.6 and 156.7, respectively. The prognosis of patients with elevated NLR or PLR value was significantly worse than patients with lower NLR (HR =1.798, 95% CI: 1.284–2.518, P=0.001) or PLR (HR =1.781, 95% CI: 1.318–2.407, P<0.001) value. Two Nomograms were developed according to the two multivariate cox regression models based on NLR and PLR. Concordance index (C-index) curves and calibration curves show that the two models have a better effect in predicting prognosis. At the same time, compared with the tumor node metastasis (TNM) staging system, our models also show better accuracy and stability.

Conclusions

Elevated NLR and PLR predict poor prognosis in their respective nomograms in patients with LS-SCLC.

Combined prognostic value of the SUVmax derived from FDG-PET and the lymphocyte-monocyte ratio in patients with stage IIIB-IV non-small cell lung cancer receiving chemotherapy

Background

We evaluated the prognostic potential of tumor ¹⁸F-fluorodeoxyglucose (FDG) uptake derived from positron emission tomography (PET) and known inflammatory hematological markers, both individually and in combination, for chemosensitivity and survival in patients with stage IIIB-IV non-small cell lung cancer (NSCLC) receiving first-line chemotherapy.

Methods

A total of 149 patients with stage IIIB and IV NSCLC (based on TNM 7th edition) were retrospectively reviewed. Maximum standardized uptake value (SUVmax) were used to quantitatively assess FDG uptake. The lymphocyte-monocyte ratio (LMR), neutrophil-lymphocyte ratio (NLR) and platelet-lymphocyte ratio (PLR) were selected as hematological markers. Receiver operating characteristic (ROC) curves were constructed for the determination of optimal cut-off values to predict chemotherapeutic response.

Results

Patients with SUVmax > 11.6 or LMR ≤3.73 exhibited a significantly lower objective response rate (ORR) to chemotherapy (p < 0.001 and p < 0.001). Through multivariable logistic regression analysis, both the SUVmax and LMR were identified as independent predictive factors for chemotherapeutic response (p = 0.001 and p < 0.001). Furthermore, a multivariable Cox proportional hazard model identified a high SUVmax (> 11.6) and low LMR (≤3.73) as independent predictors of poor PFS (p < 0.001 and p = 0.025) and OS (p < 0.001 and p = 0.032). A novel score system was constructed based on the SUVmax and LMR (SUV_LMR score), and patients were stratified into three subgroups. The patients with a score of 0 had a significantly higher ORR (88.9%) than did those with a score of 1 (59.6%) and score of 2 (25.0%) (p < 0.001). Moreover, multivariable Cox analysis further identified the SUV_LMR score as an independent prognostic factor for PFS (p < 0.001) and OS (p < 0.001).

Conclusions

Pre-treatment SUVmax and LMR were not only predictive factors for chemotherapeutic response but also independent prognostic factors of survival in stage IIIB-IV NSCLC. Moreover, the SUV_LMR score, which is based on primary tumor metabolic activity and the systemic inflammatory response, might provide a promising tool to predict chemosensitivity, recurrence and survival of advanced NSCLC.

Prognostic Value of Pretreatment Lymphocyte-to-Monocyte Ratio in Lung Cancer: A Systematic Review and Meta-Analysis

BACKGROUND

The overall prognosis of lung cancer remains unfavorable and novel prognostic biomarkers of lung cancer are needed warranted. Accumulating evidence indicate that systemic inflammation plays a vital role in lung cancer. The lymphocyte-to-monocyte ratio (LMR) is biomarker that reflects the level of systemic inflammation.

OBJECTIVE

To perform a comprehensive meta-analysis exploring the correlation of pretreatment LMR with the overall survival (OS) and progression-free survival (PFS) of lung cancer patients.

METHODS

We conducted searches of the PubMed, Embase, Cochrane Library, and Web of Science databases to May 2020 to identify relevant studies and calculated combined hazard ratios (HRs) to evaluate the association between pretreatment LMR and survival time in patients with lung cancer.

RESULTS

A total of 23 studies comprising 8361 lung cancer patients were included. Among the patients, 5702 (68%) were males, 4548 were current smokers and 2212 were diagnosed with squamous carcinoma. The pooled analysis revealed that decreased pretreatment LMR was significantly correlated with reduced of PFS (HR = 1.49, 95% CI: 1.34-1.67, p < 0.01) and reduced OS (HR = 1.61, 95% CI: 1.45-1.79, p < 0.01) among lung cancer patients. Furthermore, in the subgroup analyses according to histologic type, a lower level of pretreatment LMR seemed to be unrelated to the poorer OS of small cell lung cancer (SCLC) patients (HR = 1.21, 95%CI: 0.87-1.67, P = 0.25).

CONCLUSIONS

Decreased pretreatment LMR in peripheral blood was associated with shorter OS and PFS in lung cancer patients, suggesting its potential prognostic value.

A nomogram to predict short-term outcome of radiotherapy or chemoradiotherapy based on pre/post-treatment inflammatory biomarkers and their dynamic changes in esophageal squamous cell carcinoma

OBJECTIVE

We initially aimed to investigate pre/post-treatment inflammatory biomarkers (pre/post-IBs) and their dynamic changes (delta-IBs) on the short-term outcome (STO) of radiotherapy or chemoradiotherapy in esophageal squamous cell carcinoma (ESCC). Furthermore, a nomogram was built to provide an accurate prediction of STO.

METHODS

The STO using the treatment response evaluation was assessed according to RECIST 1.1 at 1 month after radiotherapy or chemoradiotherapy. The IBs (absolute lymphocyte counts (ALC), neutrophil/lymphocyte (NLR), platelet/lymphocyte (PLR), and lymphocyte/monocyte (LMR)) and clinical variables were collected and analyzed from 398 ESCC patients at Shandong Cancer Hospital between 2015 and 2019. The nomogram was then established for predicting STO.

RESULTS

Pre-ALC and pre-LMR significantly increased, pre-NLR and pre-PLR significantly decreased during radiotherapy or chemoradiotherapy (all P < 0.001). Meanwhile, there was a positive correlation between delta-NLR as well as delta-PLR (r = 0.621) and delta-LMR (r = 0.613), whereas a negatively correlated between delta-LMR and delta-PLR (r = -0.573). Multivariate analysis indicated that gender [OR, 0.473; 95%CI, 0.274-0.816; P = 0.007], pre-ALC [OR, 0.554; 95%CI, 0.335-0.915; P = 0.021], pre-NLR [OR, 3.176; 95%CI, 1.733-5.823; P < 0.001], post-NLR [OR, 2.418; 95%CI, 1.271-4.600; P = 0.007] and delta-NLR [OR, 1.929; 95%CI, 1.035-3.595; P = 0.039] were statistically significant with STO. And c-index of the nomogram established by combining all independent predictors for STO was 0.770 [95%CI, 0.719-0.820].

CONCLUSION

Pre-NLR, pre-ALC, post-NLR, and delta-NLR were significant with STO in ESCC patients treated with radiotherapy or chemoradiotherapy. Further, pre-NLR had the best predictive value, and the developed nomogram with superior prediction ability for STO could assist in patients counseling and guide to make individual treatments.

Multiple Immune Features-Based Signature for Predicting Recurrence and Survival of Inoperable LA-NSCLC Patients

Introduction

The immune status of the tumor microenvironment is extremely complex. One single immune feature cannot reflect the integral immune status, and its prognostic value was limited. We postulated that the immune signature based on multiple immuno-features could markedly improve the prediction of post-chemoradiotherapeutic survival in inoperable locally advanced non-small-cell lung cancer (LA-NSCLC) patients.

Methods

In this study, 100 patients who were diagnosed as having inoperable LA-NSCLC between January 2005 and January 2016 were analyzed. A five immune features-based signature was then constructed using the nested repeat 10-fold cross validation with least absolute shrinkage and selection operator (LASSO) Cox regression model. Nomograms were then established for predicting prognosis.

Results

The immune signature combining five immuno-features was significantly associated with overall survival (OS) and progression-free survival (PFS) (P = 0.002 and P = 0.014, respectively) in patients with inoperable LA-NSCLC, and at a cutoff of −0.05 stratified patients into two groups with 5-year OS rates of 39.8 and 8.8%, and 2-year PFS rates of 22.2 and 5.5% for the high- and low-immune signature groups, respectively. Integrating immune signature, we proposed predictive nomograms that were better than the traditional TNM staging system in terms of discriminating ability (OS: 0.692 vs. 0.588; PFS: 0.672 vs. 0.586, respectively) or net weight classification (OS: 32.96%; PFS: 9.22%), suggesting that the immune signature plays a significant role in improving the prognostic value.

Conclusion

Multiple immune features-based immune signature could effectively predict recurrence and survival of inoperable LA-NSCLC patients and complemented the prognostic value of the TNM staging system.

Neutrophil and lymphocyte blood count as potential predictive indicators of nivolumab efficacy in metastatic non-small-cell lung cancer

Aim: We retrospectively evaluated the role of neutrophil-to-lymphocyte ratio (NLR) and lymphocyte-to-monocyte ratio (LMR) as prognostic factors in metastatic non-small-cell lung cancer patients treated with nivolumab. Materials & methods: Medical records of 65 patients were reviewed. NLR and LMR were calculated at baseline (t0) and at first radiological tumor assessment (t1). Results: At univariate analysis, low NLR or high LMR values at t0 were associated with longer overall survival (p = 0.0001). At multivariate analysis including NLR and LMR at t0 and t1 and their trend, only NLR at t1 (p < 0.0001) and NLR trend (p < 0.0001) were significantly associated with overall survival outcomes. Conclusion: Our study suggests that NLR value at first tumor assessment or NLR trend could be used as prognostic indicators during nivolumab treatment in metastatic non-small-cell lung cancer.

Neutrophil or platelet-to-lymphocyte ratios in blood are associated with poor prognosis of pulmonary large cell neuroendocrine carcinoma

Background

Pulmonary large cell neuroendocrine carcinoma (LCNEC) is a rare clinical subtype of lung cancer which has a poor prognosis for patients. This study aimed to explore the relationship between blood-based inflammatory markers, namely neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR), and the prognosis for pulmonary LCNEC.

Methods

Peripheral leukocyte and platelet counts of 106 LCNEC patients were measured within the week leading up to their surgery. Serum neuron specific enolase (NSE) was detected by ELISA. Overall survival (OS) was analyzed by Kaplan-Meier method and compared by log-rank test.

Results

The NLR and PLR cut-off values based on survival receiver operating characteristic curve (ROC) were 2.52 and 133.6, respectively. A correlation was found between dichotomized NLR and tumor size (P=0.006), and PLR and NLR were significantly correlated with each other (P<0.001). Patients with high NLR or PLR had shorter survival than those with low NLR (HR =2.46, 95% CI: 1.508–4.011, P<0.001) or PLR (HR =2.086, 95% CI: 1.279–3.402, P=0.003). Serum NSE also had a significant effect on patient survival (HR =2.651, 95% CI: 1.358–5.178, P=0.004). The effects of peripheral blood lymphocytes (P=0.001), neutrophils (P=0.023) and platelets (P=0.051) on patient survival were compared by log-rank test. In multivariate survival analysis, NLR (P<0.001) and T category were vital for the prognoses of LCNEC patients.

Conclusions

The inflammatory or immunological markers, NLR and PLR in blood, were independent factors of survival prediction for patients with LCNEC, which implied that cellular immunity was involved in the progression of LCNEC. Peripheral blood lymphocytes and neutrophils have a fundamental effect on survival. Whether or not NLR and PLR can be useful biomarkers in efficacy prediction of immunotherapy in LCNEC calls for further investigation.

Pre/Post-Treatment Dynamic of Inflammatory Markers Has Prognostic Value in Patients with Small Hepatocellular Carcinoma Managed by Stereotactic Body Radiation Therapy

Purpose

The neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) are inflammatory indexes that may reflect immune response to tumors and prognosis. We investigated the prognostic values of pre-treatment and post-treatment NLR and PLR and changes in those ratios in patients with small hepatocellular carcinoma (sHCC) treated with stereotactic body radiation therapy (SBRT).

Patients and methods

Sixty patients who received SBRT were retrospectively reviewed. NLR and PLR were calculated by division of neutrophil and platelet counts, respectively, by lymphocyte counts. Independent factors for progression-free survival (PFS) and overall survival (OS) were determined by the Kaplan–Meier method, log-rank test, and Cox multivariate regression. Hazard ratios (HRs) and 95% confidence intervals (CIs) were also calculated.

Results

The median follow-up was 36.9 (range: 4.1–73.5) months. Median PFS was 21.4 (range: 1.8–66.9) months. The 1-year and 2-year PFS rates were 76.7% and 55.0%, respectively. The 1-year and 2-year OS rates were 95.0% and 78.3%, respectively. In multivariate analysis, post-treatment PLR ≥263.0 indicated both poor PFS (HR: 3.70; 95% CI: 1.07–12.76, p=0.038) and OS (HR: 3.23; 95% CI: 1.01–9.11, p=0.043) for sHCC patients treated with SBRT. In addition, the presence of hepatitis infection and a low level of red blood cell count were also proved to be significantly associated with patients’ poor prognosis (p<0.05 for each). Post-treatment increase in NLR ≥2.7-fold was shown to be a negative independent predictor of inferior OS (HR: 3.43; 95% CI: 1.14–10.38, p=0.029).

Conclusion

High post-treatment PLR and change in NLR ≥2.7-fold were associated with poor prognosis in patients treated with SBRT and might be considered as reliable and independent prognostic biomarkers for patients with sHCC.