The Combination of Inflammatory Biomarkers as Prognostic Indicator in Salivary Gland Malignancy

Predictive value of neutrophil to lymphocyte ratio, platelet to lymphocyte ratio, and systemic inflammatory index for detection of recurrence of pleomorphic adenoma of the major salivary glands: a multicenter study

OBJECTIVE

The aim of this study was to investigate the correlation among inflammatory biomarkers, such as the systemic immune-inflammation index (SII), the neutrophil-to-lymphocyte ratio (NLR) and the platelet-to-lymphocyte ratio (PLR), and the recurrence of pleomorphic adenomas (PAs).

STUDY DESIGN

This was a retrospective multicenter study. Six hundred eight patients diagnosed with PA and treated by tumor enucleation were included in the analyses. The patients were extracted from a 20-year database of 2 referral centers (January 2000 to January 2020). Data about age, gender, voluntary habits, tumor characteristics, tumor treatment, and values of NLR, PLR, and SII were collected. A receiver operating characteristic (ROC) curve was used to calculate the optimal cutoff values for SII, PLR, and NLR. A linear regression model (LRM) and a nonlinear logistic regression model (NLRM) were implemented for NLR, PLR, and SII.

RESULTS

All 3 inflammatory parameters were statistically significant correlated to the recurrence of the tumor. The best performance was achieved by NLR (cutoff of 2.960) with area under the ROC curve (AUC) = 0.91, accuracy of 96.1%, sensitivity of 78.4% and specificity of 97.2%, PPV = 64.4%, and NPV = 98.6%. LRM and NLRM including all hematological parameters did not improve performance in terms of recurrence detection.

CONCLUSIONS

The use of 3 inflammatory biomarkers could be a useful tool to predict recurrence of tumor in case of PA ≤ 3 cm. NLR in particular could be sensitive with a cutoff of 2.960. The use of NLR, PLR, and SII could be a good reference point for surgical decision making and follow-up in clinical practice. (Oral Surg Oral Med Oral Pathol Oral Radiol YEAR;VOL:page range).

New perspectives in the differential diagnosis of jaw lesions: Machine learning and inflammatory biomarkers

This study aimed to assess the diagnostic performance of a machine learning approach that utilized radiomic features extracted from Cone Beam Computer Tomography (CBCT) images and inflammatory biomarkers for distinguishing between Dentigerous Cysts (DCs), Odontogenic Keratocysts (OKCs), and Unicystic Ameloblastomas (UAs). This retrospective study involves 103 patients who underwent jaw lesion surgery in the Maxillofacial Surgery Unit of Federico II University Of Naples between January 2018 and January 2023. Nonparametric Wilcoxon-Mann-Whitney and Kruskal Wallis tests were used for continuous variables. Linear and non-logistic regression models (LRM and NLRM) were employed, along with machine learning techniques such as decision tree (DT), k-nearest neighbor (KNN), and support vector machine (SVM), to predict the outcomes. When individual inflammatory biomarkers were considered alone, their ability to differentiate between OKCs, UAs, and DCs was below 50 % accuracy. However, a linear regression model combining four inflammatory biomarkers achieved an accuracy of 95 % and an AUC of 0.96. The accuracy of single radiomics predictors was lower than that of inflammatory biomarkers, with an AUC of 0.83. The Fine Tree model, utilizing NLR, SII, and one radiomic feature, achieved an accuracy of 94.3 % (AUC = 0.95) on the training and testing sets, and a validation set accuracy of 100 %. The Fine Tree model demonstrated the capability to discriminate between OKCs, UAs, and DCs. However, the LRM utilizing four inflammatory biomarkers proved to be the most effective algorithm for distinguishing between OKCs, UAs, and DCs.

A Low Systemic Inflammatory Response Index Is Associated With Improved Survival in Adenoid Cystic Carcinoma Patients

BACKGROUND

Predicting the long-term survival in adenoid cystic carcinoma (ACC) patients remains challenging. Inflammatory cell-based indices are emerging as prognostic indicators of oncology.

PURPOSE

This study aimed to determine the associations between the preoperative systemic inflammatory response index (SIRI) and the systemic immunoinflammatory index (SII) and the 10-year survival rates in patients with ACC of the head and neck (ACCHN).

STUDY DESIGN, SETTING, SAMPLE

This retrospective cohort study comprised ACCHN patients treated at the Chinese People's Liberation Army General Hospital between November 2003 and December 2020.

PREDICTOR VARIABLE

The inflammatory response, assessed using the SIRI and SII, was the predictor variable. The optimal cutoff values were based on the maximum Youden index values (sensitivity ＋ specificity－1). The patients were divided into two groups each, based on the SIRI (low, ≤ 0.15) and (high, > 0.15), and SII (low, ≤ 562.8 and high, > 562.8) values.

MAIN OUTCOME VARIABLE(S)

Overall survival (OS), or the number of days, weeks, or months between treatment initiation and death (or the last follow-up date), was the primary outcome variable.

COVARIATES

The covariates were classified as demographic (age, gender, body mass index), medical (hypertension, diabetes), inflammatory (neutrophils, lymphocytes, monocytes, platelets, lymphocyte-monocyte ratio, platelet-lymphocyte ratio, neutrophil-lymphocyte ratio), and perioperative (tumor stage, lymph node metastasis, tumor size, treatment type).

ANALYSES

Descriptive, univariate, and multivariate Cox proportional risk regression analyses were performed to determine whether the SIRI and SII were independent prognostic factors for OS. Kaplan-Meier survival curves and log-rank tests were used to determine their associations with the OS.

RESULTS

The study sample comprised 162 patients (mean age, 52 ± 14; males, 39.5%). The median follow-up time was 6.81 ± 0.23, and the 10-year OS rate was 7.68 ± 0.25. The low and high SIRI groups comprised 109 and 53 patients, while the low and high SII groups comprised 116 and 46 patients, respectively. SIRI was identified as a prognostic factor (P < .01; hazard ratio, 2.45; 95% confidence interval, 1.35-4.45).

CONCLUSION AND RELEVANCE

The SIRI has the advantages of reproducibility, convenience, noninvasiveness, and affordability, making it a promising prognostic inflammatory index for patients with ACCHN.

Derived Neutrophils to Lymphocyte Ratio Predicts Survival Benefit from TPF Induction Chemotherapy in Local Advanced Oral Squamous Cellular Carcinoma

BACKGROUND

This study aimed to evaluate the derived neutrophil to lymphocyte ratio (dNLR) in predicting the prognosis of patients with locally advanced oral squamous cell carcinoma (LAOSCC) and to assess the survival benefits from docetaxel, cisplatin, and 5-fluorouracil (5-FU) (TPF) induction chemotherapy (IC).

METHODS

Patients from a phase III trial involving TPF IC in stage III/IVA OSCC patients (NCT01542931) were enrolled. Receiver operating characteristic curves were constructed, and the area under the curve was computed to determine dNLR cutoff points. Kaplan-Meier survival estimates and Cox proportional hazards models were used for longitudinal analysis.

RESULTS

A total of 224 patients were identified (median age: 55.4 years; range: 26 to 75 years; median follow-up: 90 months; range: 3.2 to 93 months). The cutoff point for the dNLR was 1.555. Multivariate analysis showed that the dNLR was an independent negative predictive factor for survival (overall survival (OS): hazard ratio (HR) = 1.154, 95% confidence interval (CI): 1.018-1.309, p = 0.025; disease-free survival (DFS): HR = 1.123, 95% CI: 1.000-1.260, p = 0.050; local recurrence-free survival (LRFS): HR = 1.134, 95% CI: 1.002-1.283, p = 0.047; distant metastasis-free survival (DMFS): HR = 1.146, 95% CI: 1.010-1.300, p = 0.035). A low dNLR combined with cTNM stage III disease predicted benefit from TPF IC for the patients [OS (χ2 = 4.674, p = 0.031), DFS (χ2 = 7.134, p = 0.008), LRFS (χ2 = 5.937, p = 0.015), and DMFS (χ2 = 4.832, p = 0.028)].

CONCLUSIONS

The dNLR is an independent negative predictive factor in LAOSCC patients. Patients with cTNM stage III disease and a low dNLR can benefit from TPF IC.

Association between immune-inflammatory indexes and lower urinary tract symptoms: an analysis of cross-sectional data from the US National Health and Nutrition Examination Survey (2005-2008)

OBJECTIVE

This study aimed to systematically investigate the relationship between immune-inflammatory indexes with lower urinary tract symptoms (LUTSs).

DESIGN

Cross-sectional study.

SETTING

National Health and Nutrition Examination Survey (NHANES) (2005-2008).

PARTICIPANTS

A total of 2709 men with complete information for immune-inflammatory indexes and LUTSs were included from NHANES 2005-2008.

OUTCOMES AND ANALYSES

Automated haematology analysing devices are used to measure blood cell counts, and LUTSs were presented by standard questionnaires. Non-linear and logistic regression analyses were used to estimate their association after adjustment for confounders.

RESULTS

Multivariate logistic regression showed that pan-immune-inflammation value (OR (95% CI)=1.60 (1.14 to 2.23)), systemic inflammation response index (SIRI) (OR (95% CI)=1.82 (1.21 to 2.73)), neutrophil/lymphocyte ratio (NLR) (OR (95% CI)=1.81 (1.31 to 2.49)), derived NLR (dNLR) (OR (95% CI)=1.91 (1.35 to 2.70)) and C reactive protein (CRP) (OR (95% CI)=1.71 (1.05 to 2.79)) was positively associated with LUTS. Additionally, composite immune-inflammation markers exhibited a stronger association with LUTS than any single index, with the ORs for high SIRI+high CRP, high NLR+high CRP and high dNLR+high CRP being 2.26, 2.44 and 2.16, respectively (all p<0.05). Furthermore, subgroup analyses revealed that age, smoking status and hypertension have different effects on the relationship between immune-inflammatory markers and LUTS.

CONCLUSIONS

This study indicated that high levels of immune-inflammatory markers were associated with an increased risk of clinical LUTS. The combination of CRP with SIRI, NLR and dNLR, respectively, showed a stronger positive correlation with clinical LUTS compared with any single index.

Impact of Sarcopenia on Survival of Patients With Malignant Salivary Glands Tumors

OBJECTIVE

Malignant salivary glands tumors (MSGTs) are a quite rare and heterogeneous group of tumors. Management of these lesions remains controversial and challenging. Thus, finding new prognostic factors that can help to guide the decision-making process, appears to be paramount. The aim of this study was to evaluate the prognostic performance of preoperative sarcopenia to stratify MSGTs patients at high risk of disease progression.

STUDY DESIGN

Retrospective study.

SETTING

A single-institution analysis (Maxillo-facial Surgery Unit, University of Naples Federico II).

METHODS

The study consists of a retrospective analysis of 74 patients surgically treated for MSGTs. For all patients, the skeletal muscle index (SMI) was calculated and sarcopenia was defined as SMI < 41 in females and <43 in males. The correlation between sarcopenia and tumor variables was analyzed. The prognostic performance of sarcopenia was evaluated through survival Kaplan-Meier curves.

RESULTS

Sarcopenia resulted statistically related to age (P < .001), tumor size (P < .001), lymph node metastases (P < .001), and American Joint Committee on Cancer tumor, node, metastasis stage (P < .001). Kaplan-Meier survival curves show that 47.3% of sarcopenic patients died before their final follow-up.

CONCLUSION

Data obtained from our study seem to confirm the correlation between sarcopenia and other high-risk features. The early detection of sarcopenia in patients with negative prognostic factors could be used to implement the support therapeutic strategies aimed at restore the clinical conditions of the patients. Sarcopenia may be routinely investigated before surgery to suggest the implementation of precautionary therapeutic strategies to improve the standard treatment response, reducing possible complications.

Nomograms integrating the collagen signature and systemic immune-inflammation index for predicting prognosis in rectal cancer patients

BACKGROUND

This study aimed to develop and validate a model based on the collagen signature and systemic immune-inflammation index to predict prognosis in rectal cancer patients who underwent neoadjuvant treatment.

METHODS

Patients with rectal cancer who had residual disease after neoadjuvant treatment at two Chinese institutions between 2010 and 2018 were selected, one used as a training cohort and the other as a validation cohort. In total, 142 fully quantitative collagen features were extracted using multiphoton imaging, and a collagen signature was generated by least absolute shrinkage and selection operator Cox regression. Nomograms were developed by multivariable Cox regression. The performance of the nomograms was assessed via calibration, discrimination and clinical usefulness. The outcomes of interest were overall survival and disease-free survival calculated at 1, 2 and 3 years.

RESULTS

Of 559 eligible patients, 421 were selected (238 for the training cohort and 183 for the validation cohort). The eight-collagen-features collagen signature was built and multivariable Cox analysis demonstrated that it was an independent prognostic factor of prognosis along with the systemic immune-inflammation index, lymph node status after neoadjuvant treatment stage and tumour regression grade. Then, two nomograms that included the four predictors were computed for disease-free survival and overall survival. The nomograms showed satisfactory discrimination and calibration with a C-index of 0.792 for disease-free survival and 0.788 for overall survival in the training cohort and 0.793 for disease-free survival and 0.802 for overall survival in the validation cohort. Decision curve analysis revealed that the nomograms could add more net benefit than the traditional clinical-pathological variables.

CONCLUSIONS

The study found that the collagen signature, systemic immune-inflammation index and nomograms were significantly associated with prognosis.

The associations of two novel inflammation indexes, systemic immune-inflammation index (SII) and system inflammation response index (SIRI), with periodontitis: evidence from NHANES 2009-2014

OBJECTIVES

The research's goal is to look for any potential relationships between the systemic immune-inflammation index (SII) and the system inflammation response index (SIRI), along with inflammation indicators and the likelihood of periodontitis.

METHODS

Ten thousand two hundred eighty-two individuals in sum were determined to be eligible for this cross-sectional study from the National Health and Nutrition Examination Survey (NHANES) between 2009 and 2014. Multiple logistic regression, generalized additive model, smooth curve fitting, subgroup analysis, and interaction tests were done for analyzing the association between periodontitis and SII, SIRI, and other inflammatory indicators.

RESULTS

The analysis, adjusted for population weighting, revealed that individuals with moderate/severe periodontitis had SII levels of 545.46 (95% CI (529.10, 561.82), P = 0.0044) and SIRI levels of 1.33 (95% CI (1.29, 1.37), P < 0.0001). In a fully adjusted multivariate logistic regression model, SII was not sensibly associated with moderate/severe periodontitis among the continuous and quartile Q1-Q4 groups (OR = 0.97, 95% CI (0.91, 1.02)). The continuous variable of SIRI (OR = 1.11, 95% CI (1.06, 1.17)) and the quartile Q4 group (OR = 1.58, 95% CI (1.28, 1.94)) had a deemed significant positive association with moderate to severe periodontitis. In addition, other inflammatory indicators, especially NLR, PPN, PLR, MLR, PC, NC, and MC were observed to be notably involved moderate/severe periodontist in this research.

CONCLUSION

We explored the association between periodontitis and two novel comprehensive markers of inflammation (SII and SIRI).

CLINICAL RELEVANCE

These inflammatory markers are expected to serve as tools to assist clinicians in diagnosing periodontitis.

Diagnostic performance of inflammatory biomarkers and cytological analysis in salivary gland tumors

BACKGROUND

This study aimed to evaluate the diagnostic performance of serum inflammatory biomarkers in salivary gland tumors with dubious results following cytological analysis.

METHODS

A retrospective analysis of 239 cases following surgery between January 2011 and June 2022 was performed. Receiver Operating Characteristic curves were drawn and areas under the curves were computed to evaluate the diagnostic performance of the inflammatory biomarkers (SII, SIRI, PLR, and NLR). Optimal cut-offs for each marker were determined by maximizing the Youden index.

RESULTS

Analysis showed that among the major biomarkers examined, SIRI performed an AUC of 0.77. The best SIRI cut-off was 0.94 with an accuracy of 79.9%. The accuracy, sensitivity, and specificity of cytological analysis were 77.8%, 59.6%, and 90.7% respectively. By combining SIRI with cytological analysis we demonstrated an increase in sensitivity to 82.8%.

CONCLUSIONS

Inflammatory biomarkers could be evaluated to support the diagnosis and treatment of salivary gland tumors in difficult cases.

Laparoscopic versus open gastrectomy for locally advanced gastric cancer after neoadjuvant chemotherapy: a comprehensive contrastive analysis with propensity score matching

BACKGROUND

Laparoscopic gastrectomy (LG) is increasingly applied in locally advanced gastric cancer (LAGC) after neoadjuvant chemotherapy (NC). However, there is no study to comprehensively evaluate the clinicopathological, prognostic, and laboratory data such as nutrition, immune, inflammation-associated indexes, and tumor markers between LG and open gastrectomy (OG) for LAGC following NC.

METHODS

The clinicopathological, prognostic, and laboratory data of LAGC patients with clinical stage of cT2-4aN1-3M0 who underwent gastrectomy after NC were retrospectively collected. The effects of LG and OG were compared after propensity score matching (PSM).

RESULTS

This study enrolled 148 cases, of which 110 cases were included after PSM. The LG group had a shorter length of incision (P < 0.001) and was superior to OG group in terms of blood loss (P < 0.001), postoperative first flatus time (P < 0.001), and postoperative first liquid diet time (P = 0.004). No significant difference was found in postoperative complications (P = 0.482). Laboratory results showed that LG group had less reduced red blood cells (P = 0.039), hemoglobin (P = 0.018), prealbumin (P = 0.010) in 3 days after surgery, and less reduced albumin in 1 day (P = 0.029), 3 days (P = 0.015), and 7 days (P = 0.035) after surgery than the OG group. The systemic immune-inflammation index and systemic inflammatory response index were not significantly different between the two groups. As for oncological outcomes, there were no significant differences in postoperative tumor markers of CEA (P = 0.791), CA199 (P = 0.499), and CA724 (P = 0.378). The 5-year relapse-free survival rates (P = 0.446) were 46.9% and 43.3% in the LG and OG groups, with the 5-year overall survival rates (P = 0.742) being 46.7% and 52.1%, respectively; the differences were not statistically significant. Multivariate Cox regression analysis revealed that tumor size ≥ 4 cm (P = 0.021) and the absence of postoperative adjuvant chemotherapy (P = 0.012) were independent risk factors for overall survival.

CONCLUSIONS

LG has faster gastrointestinal recovery, better postoperative nutritional status, and comparable oncological outcomes than OG, which can serve as an alternative surgical method for LAGC patients after NC.

A nomogram for distinguishing benign and malignant parotid gland tumors using clinical data and preoperative blood markers: development and validation

PURPOSE

This study aimed to construct and validate a nomogram that incorporated clinical data and preoperative blood markers to differentiate BPGTs from MPGTs more efficiently and at low cost.

METHODS

We retrospectively analyzed patients who underwent parotidectomy and histopathological diagnosis at the First Affiliated Hospital of Guangxi Medical University from January 2013 to June 2022. Subjects were randomly divided into training and validation sets with a 7:3 ratio. In the training set, the least absolute shrinkage and selection operator (LASSO) regression analysis was performed to select the most relevant features from 19 variables and built a nomogram using logistic regression. We evaluated the model's performance using receiver-operating characteristic (ROC) curves, calibration curves, clinical decision curve analysis (DCA), and clinical impact curve analysis (CICA).

RESULTS

The final sample consisted of 644 patients, of whom 108 (16.77%) had MPGTs. The nomogram included four features: current smoking status, pain/tenderness, peripheral facial paralysis, and lymphocyte-to-monocyte ratio (LMR). The optimal cut-off value for the nomogram was 0.17. The areas under the ROC curves (AUCs) of the nomogram were 0.748 (95% confidence interval [CI] = 0.689-0.807) and 0.754 (95% CI = 0.636-0.872) in the training and validation sets, respectively. The nomogram also showed good calibration, high accuracy, moderate sensitivity, and acceptable specificity in both sets. The DCA and CICA demonstrated that the nomogram had significant net benefits for a wide range of threshold probabilities (0.06-0.88 for the training set; 0.06-0.57 and 0.73-0.95 for the validation set).

CONCLUSION

The nomogram based on clinical characteristics and preoperative blood markers was a reliable tool for discriminating BPGTs from MPGTs preoperatively.

Association between platelet to lymphocyte ratio and depression and symptom severity among adults in the United States: A cross-sectional study

Background

The pathogenesis of depression has not yet been fully understood. The association between platelet to lymphocyte ratio (PLR) and depression has been investigated in previous studies, however, the results were controversial. The objective of the study was to explore the potential relationship between PLR and depression and symptom severity.

Methods

A cross-sectional study was conducted based on the National Health and Nutrition Examination Survey (NHANES) data from 2005 to 2018. Totally 30,032 adults were analyzed, and 2480 reported depression. Depression and symptom severity were assessed with the Patient Health Questionnaire (PHQ-9). PLR was calculated as the ratio of platelets to lymphocytes. Multivariable weighted-logistic regression models and generalized additive model (GAM) were employed to evaluate the linear and nonlinear association between PLR and depression and symptom severity.

Results

There was a negative association for Q3 (odds ratio [OR]: 0.82, 95% confidence interval [CI]: 0.68 to 0.99) when comparing participants for Q1 between 10-PLR and depression after fully adjusting the covariates; however, there was no significant association between 10-PLR and symptom severity. GAM showed that 10-PLR was associated with depression and symptom severity in a nonlinear manner. The inflection points were at 12.15. Subgroup analyses showed nonlinear relationships only in specific subgroups. Conclusions: PLR is associated with depression among adults in the United States. U-shaped nonlinear relationships and threshold effects were observed between 10-PLR and depression and symptom severity. Additionally, inflammatory mechanisms vary in different sociodemographic subgroups.

Support Tools in the Differential Diagnosis of Salivary Gland Tumors through Inflammatory Biomarkers and Radiomics Metrics: A Preliminary Study

BACKGROUND

The purpose of this study was to investigate how the systemic inflammation response index (SIRI), systemic immune-inflammation index (SII), neutrophil/lymphocyte ratio (NLR) and platelet/lymphocyte ratio (PLR), and radiomic metrics (quantitative descriptors of image content) extracted from MRI sequences by machine learning increase the efficacy of proper presurgical differentiation between benign and malignant salivary gland tumors.

METHODS

A retrospective study of 117 patients with salivary gland tumors was conducted between January 2015 and November 2022. Univariate analyses with nonparametric tests and multivariate analyses with machine learning approaches were used.

RESULTS

Inflammatory biomarkers showed statistically significant differences (p < 0.05) in the Kruskal-Wallis test based on median values in discriminating Warthin tumors from pleomorphic adenoma and malignancies. The accuracy of NLR, PLR, SII, and SIRI was 0.88, 0.74, 0.76, and 0.83, respectively. Analysis of radiomic metrics to discriminate Warthin tumors from pleomorphic adenoma and malignancies showed statistically significant differences (p < 0.05) in nine radiomic features. The best multivariate analysis result was obtained from an SVM model with 86% accuracy, 68% sensitivity, and 91% specificity for six features.

CONCLUSIONS

Inflammatory biomarkers and radiomic features can comparably support a pre-surgical differential diagnosis.

Quantitative Spatial Characterization of Lymph Node Tumor for N Stage Improvement of Nasopharyngeal Carcinoma Patients

This study aims to investigate the feasibility of improving the prognosis stratification of the N staging system of Nasopharyngeal Carcinoma (NPC) from quantitative spatial characterizations of metastatic lymph node (LN) for NPC in a multi-institutional setting. A total of 194 and 284 NPC patients were included from two local hospitals as the discovery and validation cohort. Spatial relationships between LN and the surrounding organs were quantified by both distance and angle histograms, followed by principal component analysis. Independent prognostic factors were identified and combined with the N stage into a new prognostic index by univariate and multivariate Cox regressions on disease-free survival (DFS). The new three-class risk stratification based on the constructed prognostic index demonstrated superior cross-institutional performance in DFS. The hazard ratios of the high-risk to low-risk group were 9.07 (p < 0.001) and 4.02 (p < 0.001) on training and validation, respectively, compared with 5.19 (p < 0.001) and 1.82 (p = 0.171) of N3 to N1. Our spatial characterizations of lymph node tumor anatomy improved the existing N-stage in NPC prognosis. Our quantitative approach may facilitate the discovery of new anatomical characteristics to improve patient staging in other diseases.