Neutrophil-to-lymphocyte and platelet-to-lymphocyte ratios may aid in identifying patients with non-small cell lung cancer and predicting Tumor-Node-Metastasis stages

Machine Learning for Prediction of Non-Small Cell Lung Cancer Based on Inflammatory and Nutritional Indicators in Adults: A Cross-Sectional Study

Purpose

The aim of this study was to evaluate the potential benefit of blood inflammation in the diagnosis of non-small cell lung cancer (NSCLC) and propose a machine-learning-based method to predict NSCLC in asymptomatic adults.

Patients and Methods

A cross-sectional study was evaluated using medical records of 139 patients with non-small cell lung cancer and physical examination data from May 2022 to May 2023 of 198 healthy controls. The NSCLC cohort comprised 128 cases of adenocarcinoma, 3 cases of squamous cell carcinoma, and 8 cases of other NSCLC subtypes. The correlation between inflammatory and nutritional markers, such as monocytes, neutrophils, LMR, NLR, PLR, PHR and non-small cell lung cancer was examined. Features were selected using Python's feature selection library and analyzed by five algorithms. The predictive ability of the model for non-small cell lung cancer diagnosis was assessed by precision, accuracy, recall, F1 score, and area under the curve (AUC).

Results

The results showed that the top 14 important factors were PDW, age, TP, RBC, HGB, LYM, LYM%, RDW, PLR, LMR, PHR, MONO, MONO%, gender. Additionally, the naive Bayes (NB) algorithm demonstrated the highest overall performance in predicting adult NSCLC among the five machine learning algorithms, achieving an accuracy of 0.87, a macro average F1 score of 0.85, a weighted average F1 score of 0.87, and an AUC of 0.84.

Conclusion

In feature ranking, platelet distribution width was the most important feature, and the NB algorithm performed best in predicting adult NSCLC diagnosis.

The role of adenocarcinoma subtypes and immunohistochemistry in predicting lymph node metastasis in early invasive lung adenocarcinoma

BACKGROUND

Identifying lymph node metastasis areas during surgery for early invasive lung adenocarcinoma remains challenging. The aim of this study was to develop a nomogram mathematical model before the end of surgery for predicting lymph node metastasis in patients with early invasive lung adenocarcinoma.

METHODS

In this study, we included patients with invasive lung adenocarcinoma measuring ≤ 2 cm who underwent pulmonary resection with definite pathology at Qilu Hospital of Shandong University from January 2020 to January 2022. Preoperative biomarker results, clinical features, and computed tomography characteristics were collected. The enrolled patients were randomized into a training cohort and a validation cohort in a 7:3 ratio. The training cohort was used to construct the predictive model, while the validation cohort was used to test the model independently. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors. The prediction model and nomogram were established based on the independent risk factors. Recipient operating characteristic (ROC) curves were used to assess the discrimination ability of the model. Calibration capability was assessed using the Hosmer-Lemeshow test and calibration curves. The clinical utility of the nomogram was assessed using decision curve analysis (DCA).

RESULTS

The overall incidence of lymph node metastasis was 13.23% (61/461). Six indicators were finally determined to be independently associated with lymph node metastasis. These six indicators were: age (P < 0.001), serum amyloid (SA) (P = 0.008); carcinoma antigen 125 (CA125) (P = 0. 042); mucus composition (P = 0.003); novel aspartic proteinase of the pepsin family A (Napsin A) (P = 0.007); and cytokeratin 5/6 (CK5/6) (P = 0.042). The area under the ROC curve (AUC) was 0.843 (95% CI: 0.779-0.908) in the training cohort and 0.838 (95% CI: 0.748-0.927) in the validation cohort. the P-value of the Hosmer-Lemeshow test was 0.0613 in the training cohort and 0.8628 in the validation cohort. the bias of the training cohort corrected C-index was 0.8444 and the bias-corrected C-index for the validation cohort was 0.8375. demonstrating that the prediction model has good discriminative power and good calibration.

CONCLUSIONS

The column line graphs created showed excellent discrimination and calibration to predict lymph node status in patients with ≤ 2 cm invasive lung adenocarcinoma. In addition, the predictive model has predictive potential before the end of surgery and can inform clinical decision making.

Neutrophil-Lymphocyte and Platelet-Lymphocyte Ratios in Distinguishing Lung Cancer in People with HIV

Objective

The neutrophil-lymphocyte ratio (NLR) and platelet-lymphocyte ratio (PLR) demonstrate good diagnostic accuracy in distinguishing lung cancer patients from healthy individuals, primarily in HIV-negative populations. We determined the sensitivity (Se), specificity (Sp), and area under the curve (AUC) of the NLR and PLR in discriminating between people living with HIV (PLWH) with and without lung cancer.

Methods

This is a comparative analysis of secondary data. Cases were PLWH with lung cancer from a retrospective cohort treated at the Uganda Cancer Institute. Controls were unmatched PLWH without lung cancer who were randomly selected from three HIV clinics in Uganda. Se, Sp, and AUC analysis and determination of optimal cutoffs were performed using receiver operating characteristic (ROC) curves.

Results

Of 115 PLWH (18 cases and 97 controls), 83 (72.2%) were female, 110 (95.7) were on ART, and the median (IQR) age was 46 (38-51) years. The median (IQR) NLR was higher among cases than controls (3.53 (3.14-7.71) vs. 0.92 (0.67-1.09), p  < 0.001). Similarly, the PLR was higher among cases than controls (237.5 (177.8-361.6) vs. 123.6 (100.6-155.4), p=0.001). At a cutoff of 2.44, the respective Se, Sp, and AUC of the NLR were 87.5% (95% CI: 61.7%-98.4%), 100% (95% CI: 96.2%-100%), and 0.94 (95% CI: 0.85-1.00, p  < 0.001). Similarly, the respective Se, Sp, and AUC for the PLR were 75% (95% CI: 47.6%-92.7%), 87.2% (95% CI: 78.8%-93.2%), and 0.81 (95% CI: 0.70-0.93, p  < 0.001) at a cutoff of 196.3.

Conclusion

The NLR and PLR discriminated PLWH with and without lung cancer and could be useful in PLWH with respiratory symptoms in whom lung cancer can easily be misdiagnosed as other lung pathology.

Prognostic Value of Inflammation and Nutrition-Based Scores in Non-Small Cell Lung Cancer

OBJECTIVE

In studies conducted on non-small cell lung cancer (NSCLC) patients, many factors such as age, stage, weight loss, lymph node, and pleural involvement have been shown to affect survival. On the other hand, systemic inflammation plays a critical role in proliferation, migration, invasion, and metastasis. Inflammation and nutrition-based prognostic scores are reported to be associated with survival in patients with NSCLC. The aim of our study is to show the effects of these scores on survival and disease progression in NSCLC patients.

SUBJECTS AND METHODS

Neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), modified Glasgow prognostic score (mGPS), and prognostic nutritional index (PNI) values in 102 patients with stages 1, 2, and 3A NSCLC were analyzed retrospectively.

RESULTS

NLR (p < 0.001), PLR (p = 0.001), PNI (p < 0.001), and mGPS (p = 0.001) variables showed a statistically significant difference according to mortality groups. NLR and PLR values were higher in exitus patients. However, PNI values were higher in surviving patients. NLR (p < 0.001), PLR (p = 0.004), PNI (p = 0.001), and mGPS (p = 0.015) variables showed a statistically significant difference in terms of locoregional recurrence. PNI (p = 0.001) and mGPS (p = 0.001) in terms of distant metastasis development during follow-up and treatment showed a statistically significant difference.

CONCLUSION

NLR, PLR, PNI, and mGPS are easily accessible noninvasive parameters and provide predictive information about survival and disease course. We showed the effect of these parameters on the prognosis.

Identification of novel potential drugs and miRNAs biomarkers in lung cancer based on gene co-expression network analysis

Non-small cell lung cancer (NSCLC) is an important cause of cancer-associated deaths worldwide. Therefore, the exact molecular mechanisms of NSCLC are unidentified. The present investigation aims to identify the miRNAs with predictive value in NSCLC. The two datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed miRNAs (DEmiRNA) and mRNAs (DEmRNA) were selected from the normalized data. Next, miRNA-mRNA interactions were determined. Then, co-expression network analysis was completed using the WGCNA package in R software. The co-expression network between DEmiRNAs and DEmRNAs was calculated to prioritize the miRNAs. Next, the enrichment analysis was performed for DEmiRNA and DEmRNA. Finally, the drug-gene interaction network was constructed by importing the gene list to dgidb database. A total of 3,033 differentially expressed genes and 58 DE miRNA were recognized from two datasets. The co-expression network analysis was utilized to build a gene co-expression network. Next, four modules were selected based on the Zsummary score. In the next step, a bipartite miRNA-gene network was constructed and hub miRNAs (let-7a-2-3p, let-7d-5p, let-7b-5p, let-7a-5p, and let-7b-3p) were selected. Finally, a drug-gene network was constructed while SUNITINIB, MEDROXYPROGESTERONE ACETATE, DOFETILIDE, HALOPERIDOL, and CALCITRIOL drugs were recognized as a beneficial drug in NSCLC. The hub miRNAs and repurposed drugs may act a vital role in NSCLC progression and treatment, respectively; however, these results must validate in further clinical and experimental assessments.

Role and research progress of hematological markers in laryngeal squamous cell carcinoma

Laryngeal cancer is one of the most common malignant tumors of the head and neck, accounting for about 20%. Due to its high disability rate, the diagnosis and treatment of laryngeal cancer have always been the focus and difficulty of head and neck surgery. The outcome of cancer is affected not only by tumor-related factors but also by host-related factors, especially systemic inflammation, this is usually reflected by a variety of hematological markers. Studies have confirmed that there is a significant correlation between hematological markers and the occurrence, development, and prognosis of laryngeal squamous cell carcinoma (LSCC), and has a certain value in auxiliary diagnosis and prognosis prediction of LSCC. We reviewed various hematological markers related to LSCC aim to summarize the role and research progress of hematological markers in LSCC.

The Prognostic Significance of Preoperative Platelet-to-Lymphocyte and Neutrophil-to-Lymphocyte Ratios in Patients Operated for Non-Small Cell Lung Cancer

Introduction

The aim of the study was to determine the prognostic significance of PLR and NLR ratios in patients operated due to non-small cell lung cancer.

Material

The study group consisted of 532 (174 women, 358 men) patients with non-small cell lung cancer (NSCLC) staged IA-IIIA. The mean age was 63.6 years (range 36 to 84 years). Together with platelet/lymphocyte ratio (PLR) and neutrophil/lymphocyte ratio (NLR), the following factors were included in the statistical analysis: age, sex, smoking history, the number of leukocytes, neutrophils, and platelets, histopathology, T-stage, N-stage, concomitant diseases according to the Charlson Comorbidity Index (CCI), type of operation, adjuvant chemotherapy, and overall survival.

Results

Univariate analysis showed an association between the value of PLR and NLR and the length of survival. Multivariate analysis found that the stage of advancement of the neoplastic disease (p=0.00003), adjuvant chemotherapy (p=0.009), CCI > 4 (0.00008), and PLR > 144 (p=0.001) were negative prognostic factors for survival > 2 years; however, this effect diminishes in patients surviving more than 5 years.

Conclusion

PLR might serve as a prognostic factor in patients affected by NSCLC with expected two-year overall survival.

Systemic Immune-Inflammation Index Predicts Overall Survival in Patients with Gastric Cancer: a Propensity Score-Matched Analysis

BACKGROUND

The systemic immune-inflammation index (SII), integrated by peripheral lymphocyte, neutrophil, and platelet counts, is used as an objective biomarker that reflects the balance between host inflammatory and immune response status in cancer patients. Herein, we examined the prognostic significance of SII in gastric cancer patients.

METHODS

We retrospectively reviewed data of 415 patients who underwent curative laparoscopic gastrectomy using propensity score-matched (PSM) analysis. The prognostic value of SII was compared between two groups based on SII values: low SII group (SII < 661.9) and high SII group (SII ≥ 661.9).

RESULTS

In multivariate analysis, the American Society of Anesthesiologists physical status (ASA-PS) (p < 0.001), tumor differentiation (p = 0.019), pathological stage (p = 0.046), carcinoembryonic antigen (CEA) level (p < 0.001), SII (p = 0.006), and operative procedure (p = 0.009) were independent prognostic factors of overall survival (OS) in the overall PSM cohort. The log-rank test demonstrated that patients with a high SII had significantly worse OS than did those with low SII (p = 0.002). In age-stratified subgroups analysis (< 65/≥ 65 years), multivariate analysis revealed that ASA-PS (p < 0.001), tumor differentiation (p = 0.019), CEA level (p = 0.008), SII (p = 0.013), and operative procedure (p = 0.026) were independent prognostic factors of OS in the elderly group. Similarly, elderly patients with a high SII had significantly worse OS than did those with a low SII (p = 0.009). Meanwhile, SII was not an independent prognostic factor of OS, and no significant association was observed between SII and OS in non-elderly patients.

CONCLUSIONS

SII was an independent prognostic indicator in gastric cancer patients, especially in the elderly population.

Prognostic Factors Determining Survival of Patients Operated for Non-Small Cell Lung Cancer with Consideration Given to Morphological Parameters of Blood

Introduction

Prognostic biomarkers are the area of high interest in non-small cell lung cancer (NSCLC). Inflammatory blood markers can be routinely determined from complete blood counts which are inexpensive and reliable. The aim of the study was to determine prognostic parameters which, in early diagnostics, best determine survival of patients, operated on due to NSCLC.

Materials

The study was conducted on 532 (174 females and 358 males) patients, operated on due to NSCLC, in stages IA – III, aged 36–84 years (the mean age: 63.6 years). The following parameters were subjected to a statistical analysis, conducted in order to determine prognostic values of the number of leukocytes, neutrophils, monocytes, platelets, haemoglobin, RDW-CV and MCV, calculated values of PLR, NLR, and LMR ratios, age, sex, smoking, histopathological diagnosis, T stage, N stage, the Charlson Comorbidity Index (CCI), type of surgery, and potential complications.

Results

The univariate analysis revealed an impact of NLR, PLR, and LMR values, RDW-CW and CCI ranges, and also the number of monocytes on patients’ overall survival (OS). The multivariate analysis identified six independent negative prognostic factors: male sex (0.001), CCI > 4 (p=0.000007), RDW-CV > 14.5% and PLR > 144 (p=0.000001, p= 0.001, respectively), the number of metastatic N2 lymphatic nodes (p=0.0003), and existence of post-operative complications (p=0.008).

Conclusion

Patients’ sex, RDW and PLR values, Charlson index, the number of involved N2 nodes by cancer and postoperative complications are independent and significant prognostic factors in patients operated on due to NSCLC.

Systemic immune-inflammation index (SII): A More Promising Inflammation-Based Prognostic Marker for Patients with synchronic colorectal peritoneal carcinomatosis

Objective: Synchronic colorectal peritoneal carcinomatosis (SCRPC) was recognized as a predictor of poor prognosis. The aim of this study was to investigate the role of neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and systemic immune-inflammation index (SII) on the survival outcome, which might help determine the treatment management of SCRPC patients.

Methods: A total of 103 SCRPC patients following cytoreduction surgery (CRS) and systematic chemotherapy (CT) between 1997 and 2013 in the First Affiliated Hospital of Sun Yat-sen University were retrospectively analyzed. The comparison of the clinicopathological variables and systematic inflammatory biomarkers, including NLR, PLR and SII, was performed by Chi-test and Cox regression analysis. According to the results of multivariate analysis, a prognostic nomogram was generated, and its prediction ability was measured by the concordance index (C-index). The survival curves were generated using the Kaplan-Meier method and survival comparison between groups was conducted via the log-rank test.

Results: Univariate analysis revealed that elevated NLR, PLR and SII were significantly correlate with worse survival outcome. Only low SII value was recognized as an independent favorable prognostic factor for overall survival (HR=1.772, 95% CI=1.015-3.095, P=0.044), except for NLR and PLR. The nomogram could perform well in the prediction of overall survival in SCRPC patients (c-index 0.782). Moreover, SII had strong prognostic discriminatory ability to predict survival outcome for the patients receiving completeness of cytoreduction score (CCR) 0/1 or CCR2/3, rather than NLR and PLR.

Conclusions: SII was a better inflammation factor to predict the outcomes of SCRPC patients receiving CRS and systematic CT. Low SII value was the most favorable factor benefiting from different level of CRS and it was useful for determining the appropriate treatment strategy for SCRPC patients.

Dynamic evaluation of neutrophil-to-lymphocyte ratio as prognostic factor in stage III non-small cell lung cancer treated with chemoradiotherapy

PURPOSE

Locally advanced non-small cell lung cancer (LA-NSCLC) is frequently treated with chemoradiotherapy (CRT). Despite the efforts, long-term outcomes are poor, and novel therapies have been introduced to improve results. Biomarkers are needed to detect early treatment failure and plan future follow-up and therapies. Our aim is to evaluate the role of dynamics of neutrophil-to-lymphocyte ratio (NLR) in patients with locally advanced NSCLC treated with CRT.

METHODS

We retrospectively reviewed patients diagnosed with LA-NSCLC receiving definitive CRT at our center from 2010 to 2015. Baseline and post-treatment NLR were collected from our center database. NLR was dichotomized (threshold = 4) and patients were divided into two groups based on the variation from baseline to post-treatment NLR. The prognostic role and association with response were examined with logistic regression and multivariate Cox regression model, respectively.

RESULTS

Ninety-two patients were included. Our analysis shows that NLR after treatment is associated with response to treatment [OR in the multivariate analysis 4.94 (1.01-24.48); p value = 0.048]. Furthermore, NLR and ECOG are independent prognostic factors for progression-free survival (PFS) and overall survival (OS). Specifically, PFS was 25.79 months for the good prognosis group and 12.09 for the poor prognosis group [HR 2.98 (CI 95% = 1.74-5.10), p < 0.001]; and OS was 42.94 months and 18.86 months, respectively [HR 2.81 (CI 95% = 1.62-4.90), p < 0.001].

CONCLUSION

Dynamics of NLR have a prognostic value in stage III NSCLC treated with definitive CRT. Pre- and post-CRT NLR should be evaluated in prospective clinical trials involving consolidation treatment with immunotherapy.

Microarray data analysis on gene and miRNA expression to identify biomarkers in non-small cell lung cancer

Background

The aim of this study was to gain further investigation of non-small cell lung cancer (NSCLC) tumorigenesis and identify biomarkers for clinical management of patients through comprehensive bioinformatics analysis.

Methods

miRNA and mRNA microarray datasets were downloaded from GEO (Gene Expression Omnibus) database under the accession number GSE102286 and GSE101929, respectively. Genes and miRNAs with differential expression were identified in NSCLC samples compared with controls, respectively. The interaction between differentially expressed genes (DEGs) and differentially expressed miRNAs (DEmiRs) was predicted, followed by functional enrichment analysis, and construction of miRNA-gene regulatory network, protein-protein interaction (PPI) network, and competing endogenous RNA (ceRNA) network. Through comprehensive bioinformatics analysis, we anticipate to find novel therapeutic targets and biomarkers for NSCLC.

Results

A total of 123 DEmiRs (5 up- and 118 down-regulated miRNAs) and 924 DEGs (309 up- and 615 down-regulated genes) were identified. These genes and miRNAs were significantly involved in different pathways including adherens junction, relaxin signaling pathway, and axon guidance. Furthermore, hsa-miR-9-5p, has-miR-196a-5p and hsa-miR-31-5p, as well as hsa-miR-1, hsa-miR-218-5p and hsa-miR-135a-5p were shown to have higher degree in the miRNA-gene regulatory network and ceRNA network, respectively. Furthermore, BIRC5 and FGF2, as well as RTKN2 and SLIT3 were hubs in the PPI network and ceRNA network, respectively.

Conclusion

Several pathways (adherens junction, relaxin signaling pathway, and axon guidance) miRNAs (hsa-miR-9-5p, has-miR-196a-5p, hsa-miR-31-5p, hsa-miR-1, hsa-miR-218-5p and hsa-miR-135a-5p) and genes (BIRC5, FGF2, RTKN2 and SLIT3) may play important roles in the pathogenesis of NSCLC.

Prognostic value of neutrophil-to-lymphocyte, platelet-to-lymphocyte and lymphocyte-to-monocyte ratio ratios in patients operated on due to non-small cell lung cancer

Background

The aim of the study was to determine a prognostic value of the neutrophil to lymphocyte ratio (NLR), the platelet to lymphocyte ratio (PLR) and the lymphocyte to monocyte ratio (LMR) ratios for survival of patients, operated on due to non-small cell lung cancer (NSCLC).

Methods

The study was conducted on 532 patients, operated on due to NSCLC, in stages IA-IIIA. A total of 174 females and 358 males, aged 36-84 years (the mean age: 63.6 years) were included in the study. The following factors were subject to a statistical analysis, conducted for determination of potential prognostic values of NLR, PLR and LMR ratios: age, sex, nicotinism, the number of leukocytes, neutrophils, monocytes, platelets, histopathological diagnosis, T category, N category, the Charlson comorbidity index (CCI), kind of surgery, patient survival.

Results

The single-factor analysis revealed a relationship between NLR, PLR and LMR values, CCI values, the number of monocytes and the length of survival. The multi-factor analysis confirmed that for patients with expected 2-year survival, PLR above 138 (P=0.0008) is another negative prognostic factor, apart from the stage of the neoplastic disease and CCI above 4. For 5-year survival, such a relationship was not observed.

Conclusions

The PLR ratio is an independent and significant prognostic factor for expected, over 2-year survival of patients operated on due to NSCLC.

May the change of platelet to lymphocyte ratio be a prognostic factor for T3-T4 laryngeal squamous cell carcinoma: A retrospective study

Background

Many blood markers have been shown to predict the recurrence and survival of various malignancies, but the effects of surgery on the body's inflammatory levels may cause changes in these inflammatory markers. Therefore, in this study, we assessed the relationship between changes in platelet to lymphocyte ratio (PLR) and survival and recurrence in patients with T3-T4 laryngeal squamous cell carcinoma (LSCC).

Methods

Data of patients with T3-T4 HSCC were reviewed. Continuous variables were expressed as mean ± SD and were compared using t test or Mann-Whitney U test. The covariate distributions were compared by Chi-square test. Survival curve was estimated by Kaplan-Meier analysis, and Log-Rank test were performed to estimate the survival curve and significance of the difference in survival distribution between groups, respectively. The prognostic value was uncovered by univariate and multivariate Cox hazards analysis.

Results

The 413 consecutive patients with LSCC were reviewed. Of these, 362 patients who met the criteria were selected, multi-factor analysis found that pathological T classification(hazard ratio [HR] = 1.878; 95% confidence interval [CI] = 1.342–3.023; P<0.001), pathological N classification (HR = 1.212; 95% CI = 0.867–2.125; P< 0.001) and change of PLR (HR = 2.158; 95% CI = 1.332–2.889; P = 0.004) associated with postoperative recurrence of T3-T4 LSCC. In addition, the pathological T classification (HR = 1.901; 95% CI = 1.255–2.999; P<0.001), pathological N classification (HR = 1.244; 95% CI = 0.810–2.212; P<0.001) and change of PLR (HR = 2.011; 95% CI = 1.354–2.753; P = 0.001) associated with postoperative survival in patients with T3-T4 LSCC.

Conclusions

Results demonstrate that change in PLR may serve as a useful prognostic predictor for patients with T3-T4 LSCC.