Pre-treatment neutrophil-to-lymphocyte ratio predicts tumor pathology in newly diagnosed renal tumors

A nomogram based on the preoperative neutrophil-to-lymphocyte ratio to distinguish sarcomatoid renal cell carcinoma from clear cell renal cell carcinoma

Objective

Our study aimed to assess the predictive value of the preoperative neutrophil-to-lymphocyte ratio(NLR) in distinguishing sarcomatoid renal cell carcinoma (SRCC) from clear cell renal cell carcinoma(CCRCC) and to developing a nomogram based on the preoperative NLR and other factors to distinguish SRCC from CCRCC.

Materials and methods

The database involved 280 patients, including 46 SRCC and 234 CCRCC. logistic analysis was conducted to select the variables associated with identifying SRCC preoperatively, and subgroup analysis was used to further validate the ability of NLR with preoperative identification of SRCC.In addition, The data were randomly separated into a training cohort(n=195) and a validation cohort(n=85). And an NLR-based nomogram was plotted based on the logistic analysis results. The nomogram was evaluated according to its discrimination, consistency, and clinical benefits.

Results

Multivariate analysis indicated that NLR, flank pain, tumor size, and total cholesterol(TC) were independent risk factors for identifying SRCC. The results of subgroup analysis showed that higher NLR was associated with a higher probability of SRCC in most subgroups. The area under the curve(AUC) of the training and validation cohorts were 0.801 and 0.738, respectively. The results of the calibration curve show high consistency between predicted and actual results. Decision Curve Analysis(DCA) showed clinical intervention based on the model was beneficial over most of the threshold risk range.

Conclusion

NLR is a potential indicator for preoperative differentiation of SRCC and CCRCC, and the predictive model constructed based on NLR has a good predictive ability. The new model could provide suggestions for the early identification of SRCC.

Clinical Data based XGBoost Algorithm for infection risk prediction of patients with decompensated cirrhosis: a 10-year (2012-2021) Multicenter Retrospective Case-control study

OBJECTIVES

To appraise effective predictors for infection in patients with decompensated cirrhosis (DC) by using XGBoost algorithm in a retrospective case-control study.

METHODS

Clinical data were retrospectively collected from 6,648 patients with DC admitted to five tertiary hospitals. Indicators with significant differences were determined by univariate analysis and least absolute contraction and selection operator (LASSO) regression. Further multi-tree extreme gradient boosting (XGBoost) machine learning-based model was used to rank importance of features selected from LASSO and subsequently constructed infection risk prediction model with simple-tree XGBoost model. Finally, the simple-tree XGBoost model is compared with the traditional logical regression (LR) model. Performances of models were evaluated by area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity.

RESULTS

Six features, including total bilirubin, blood sodium, albumin, prothrombin activity, white blood cell count, and neutrophils to lymphocytes ratio were selected as predictors for infection in patients with DC. Simple-tree XGBoost model conducted by these features can predict infection risk accurately with an AUROC of 0.971, sensitivity of 0.915, and specificity of 0.900 in training set. The performance of simple-tree XGBoost model is better than that of traditional LR model in training set, internal verification set, and external feature set (P < 0.001).

CONCLUSIONS

The simple-tree XGBoost predictive model developed based on a minimal amount of clinical data available to DC patients with restricted medical resources could help primary healthcare practitioners promptly identify potential infection.

Pathological diagnostic nomograms for predicting malignant histology and unfavorable pathology in patients with endophytic renal tumor

Purpose

To develop and validate nomograms for pre-treatment prediction of malignant histology (MH) and unfavorable pathology (UP) in patients with endophytic renal tumors (ERTs).

Methods

We retrospectively reviewed the clinical information of 3245 patients with ERTs accepted surgical treatment in our center. Eventually, 333 eligible patients were included and randomly enrolled into training and testing sets in a ratio of 7:3. We performed univariable and multivariable logistic regression analyses to determine the independent risk factors of MH and UP in the training set and developed the pathological diagnostic models of MH and UP. The optimal model was used to construct a nomogram for MH and UP. The area under the receiver operating characteristics (ROC) curves (AUC), calibration curves and decision curve analyses (DCA) were used to evaluate the predictive performance of models.

Results

Overall, 172 patients with MH and 50 patients with UP were enrolled in the training set; and 74 patients with MH and 21 patients with UP were enrolled in the validation set. Sex, neutrophil-to-lymphocyte ratio (NLR), R score, N score and R.E.N.A.L. score were the independent predictors of MH; and BMI, NLR, tumor size and R score were the independent predictors of UP. Single-variable and multiple-variable models were constructed based on these independent predictors. Among these predictive models, the malignant histology-risk nomogram consisted of sex, NLR, R score and N score and the unfavorable pathology-risk nomogram consisted of BMI, NLR and R score performed an optimal predictive performance, which reflected in the highest AUC (0.842 and 0.808, respectively), the favorable calibration curves and the best clinical net benefit. In addition, if demographic characteristics and laboratory tests were excluded from the nomograms, only the components of the R.E.N.A.L. Nephrometry Score system were included to predict MH and UP, the AUC decreased to 0.781 and 0.660, respectively (P=0.001 and 0.013, respectively).

Conclusion

In our study, the pathological diagnostic models for predicting malignant and aggressive histological features for patients with ERTs showed outstanding predictive performance and convenience. The use of the models can greatly assist urologists in individualizing the management of their patients.

Role of 18F-FDG-PET/CT in Combination With Neutrophil-Lymphocyte Ratio in the Diagnosis of Upper Urinary Tract Lesion: Can We Accurately Predict Malignant Tumor?

Objective

To explore whether preoperative 18Fluorine-Fluorodeoxyglucose-positron emission tomography/computed tomography (18F-FDG-PET/CT) in combination with neutrophil–lymphocyte ratio (NLR) could accurately predict malignant lesions of upper urinary tract (UUT).

Methods and Materials

The clinicopathologic data of a total of 252 patients with UUT lesions receiving surgical treatment at our center from January 2012 to November 2019 were retrospectively analyzed. All patients performed routine preoperative hematological examination, urine cytology, computed tomography urography (CTU), and 18F-FDG-PET/CT. Clinicopathologic data between 179 cases with malignancy (Group 1) and 73 cases with benign lesions (Group 2) were compared. Multivariate logistic regression analysis was used to explore the independent predictors of malignant UUT lesions. Receiver operating characteristic (ROC) curve was used to evaluate the predictive ability.

Results

Among all patients, univariate analysis showed that NLR, hydronephrosis, CTU indicating malignancy, and PET/CT indicating malignancy were significantly associated with malignant UUT lesions; multivariate analysis revealed that NLR, CTU indicating malignancy, and PET/CT indicating malignancy were independent predictors of malignant UUT lesions; the area under ROC curve (AUC) of NLR, CTU, PET/CT, combining CTU and NLR, combining PET/CT and NLR, and combining PET/CT and CTU were 0.735, 0.788, 0.857, 0.863, 0.913, and 0.919, respectively, for postoperative pathological malignancy. Among 68 patients undergoing ureteroscopy biopsy, univariate analysis suggested that NLR, positive urine exfoliation cytology, CTU indicating malignancy, and PET/CT indicating malignancy were significantly associated with malignant UUT lesions; multivariate analysis demonstrated that positive urine cytology, PET/CT indicating malignancy, and NLR were independent predictors of malignant UUT lesions; the AUC of NLR, ureteroscopy biopsy, and combining PET/CT and NLR were 0.768, 0.853, and 0.839, respectively, for postoperative pathological malignancy.

Conclusions

Combining preoperative NLR and PET/CT performed well in differentiating benign from malignant UUT lesions, which could not be identified by traditional imaging or urine cytology. Combining preoperative NLR and PET/CT could be used to reduce unnecessary ureteroscopy biopsy, which might result in tumor cell dissemination and risk of associated complications.

Comparison and development of preoperative systemic inflammation markers-based models for the prediction of unfavorable pathology in newly diagnosed clinical T1 renal cell carcinoma

BACKGROUND

We sought to investigate the preoperative risk factors associated with the unfavorable pathology (UP) of clinical T1 (cT1) renal lesions. The aims of this study were to develop and compare several novel models capable of accurately identifying those patients at high risk of harboring occult adverse histopathological characteristics.

METHODS

The clinical parameters and preoperative laboratory test results from 1281 cT1 renal cell carcinomas (RCCs) patients who underwent partial nephrectomy (PN) or radical nephrectomy (RN) were collected. The data was randomly split into training (70%) and testing (30%) datasets. We performed univariable and multivariable logistic regression analyses for significant predictors and, subsequently, constructed predictive models based on those significant risk factors. Receiver operating characteristic (ROC) analysis was used to determine the model with the highest discrimination power with corresponding area under the curve (AUC). Calibration curves were plotted and decision curve analyses (DCAs) were applied to explore clinical net benefit.

RESULTS

UP was identified in 21.1% (n = 270), 21.0% (n = 188) and 21.3% (n = 82) patients in the total population, training cohort and validation cohort, respectively. R.E.N.A.L. (radius, exophytic/endophytic properties, nearness of tumor to collecting system or sinus, anterior/posterior, location relative to the polar lines) nephrometry score, tumor size, neutrophil-to-lymphocyte ratio (NLR) and albumin-to-globulin ratio (AGR) were independent predictors of UP. Among those predictive models, the model that consisted of tumor size, hemoglobin, NLR and AGR performs best according to the highest AUC of 0.70 and the highest net benefit. When tumor histology was added to the biomarker-based model, including tumor size, hemoglobin, NLR and AGR, the AUC improved from 0.60 to 0.63 in the validation cohort.

CONCLUSIONS

In this analytical model study, our findings verified that systemic inflammation response markers showed high potential for identifying UP. Our biomarker-based models well predicted occult aggressive histopathological characteristics among patients with cT1 renal lesions, and the use of models may be greatly beneficial to urologists in tailoring precise management and therapy for patients. Robust validation is warranted prior to adoption into clinical practice.

Radiomics Analysis of Contrast-Enhanced CT Predicts Survival in Clear Cell Renal Cell Carcinoma

Purpose

To develop and validate the radiomics nomogram that combines clinical factors and radiomics features to estimate overall survival (OS) in patients with clear cell renal cell carcinoma (ccRCC), and assess the incremental value of radiomics for OS estimation.

Materials and Methods

One hundred ninety-four ccRCC cases were included in the training cohort and 188 ccRCC patients from another hospital as the test cohort. Three-dimensional region-of-interest segmentation was manually segmented on multiphasic contrast-enhanced abdominal CT images. Radiomics score (Rad-score) was calculated from a formula generated via least absolute shrinkage and selection operator (LASSO) Cox regression, after which the association between the Rad-score and OS was explored. The radiomics nomogram (clinical factors + Rad-score) was developed to demonstrate the incremental value of the Rad-score to the clinical nomogram for individualized OS estimation, which was then evaluated in relation to calibration and discrimination.

Results

Rad-score, calculated using a linear combination of the 11 screened features multiplied by their respective LASSO Cox coefficients, was significantly associated with OS. Calibration curves showed good agreement between the OS predicted by the nomograms and observed outcomes. The radiomics nomogram presented higher discrimination capability compared to clinical nomogram in the training (C-index: 0.884; 95% CI: 0.808–0.940 vs. 0.803; 95% CI: 0.705–0.899, P < 0.05) and test cohorts (C-index: 0.859; 95% CI: 0.800–0.921 vs. 0.846; 95% CI: 0.777–0.915, P < 0.05).

Conclusions

The radiomics nomogram may be used for predicting OS in patients with ccRCC, and radiomics is useful to assist quantitative and personalized treatment.

Tyrosine Kinase Inhibitor Cabozantinib Inhibits Murine Renal Cancer by Activating Innate and Adaptive Immunity

Background

Advanced renal cell carcinoma (RCC) has a very dismal prognosis. Cabozantinib, a tyrosine kinase inhibitor, has been approved for the treatment of advanced RCC. However, the impact of cabozantinib on the immune microenvironment of RCC remains poorly understood.

Methods

Kaplan-Meier survival curves were constructed to examine the correlation between intratumor infiltration of neutrophils and patient prognosis in RCC. Infiltration and effector function of neutrophils and T cells in response to cabozantinib treatment were investigated in a murine RCC model.

Results

A retrospective study of 307 RCC patients indicated that neutrophils were recruited into tumor tissues, and increased neutrophil infiltration was associated with improved clinical outcomes. In a murine model of RCC, cabozantinib treatment significantly increased both intratumor infiltration and anti-tumor function of neutrophils and T cells. Mechanistically, we found that cabozantinib treatment induced expression of neutrophil-related chemokines (CCL11 and CXCL12) and T cell-related chemokines (CCL8 and CX3CL1) in the tumor microenvironment. Furthermore, depletion of neutrophils and CD8⁺ T cells compromised the therapeutic efficacy of cabozantinib. Importantly, cabozantinib treatment induced long-term anti-tumor T cell response.

Conclusions

Our study revealed novel mechanisms of the therapeutic effects of cabozantinib on RCC by activating both neutrophil-mediated innate immunity and T cell-mediated adaptive immunity. These findings are of great significance for guiding the clinical use of cabozantinib and provide a good candidate for future combination therapy with T-cell therapies or other immunotherapies.

Predictive and prognostic impact of preoperative complete blood count based systemic inflammatory markers in testicular cancer

PURPOSE

To determine the utility of preoperative complete blood count (CBC) based systemic inflammatory markers in the prediction of testicular cancer and its prognosis.

MATERIAL AND METHODS

Between 2008-2017 the data of all testicular tumor patients undergoing radical orchiectomy were retrospectively analyzed. Patient baseseline characteristics (age, tumor stage, tumor markers, etc.) and results of routine preoperative blood tests including mean platelet volume (MPV), red cell distribution width (RDW), lymphocyte ratio (LR) and neutrophil ratio (NR) were retrieved. In addition, neutrophil to lymphocyte ratio (NLR) was calculated.

RESULTS

Mean age of the tumor and control group was 36.0±15 and 30.50±11 years, respectively. Mean RDW, NR and NLR were significantly higher in the tumor group with p values<0.001; whereas LR and MPV were signifi cantly higher in the control group (p<0.001). Receiver Operating Characteristic (ROC) analyses of LR, NR, RDW, MPV, and NLR are shown in Table-3. The cut off values for RDW and NR were found as 13,7 (Area under the curve (AUC): 0.687, sensitivity = 42.2%, specifi city = 84.8%) and 55.3 (AUC:0.693, sensitivity 72.2%, specifi city 62%), respectively. Area under the curve for NLR in tumor group was 0.711, with a threshold value of 1.78 and sensitivity=81.8% and specifi city=55.4% (AUC:0.711/sig<0.001) that together with RDW exhibited the best differential diagnosis potential which could be used as an adjuvant tool in the prediction of testicular tumor and its prognosis.

CONCLUSION

Several systemic inflammatory markers, which are obtained by routinely performed cost-effective blood tests, could demonstrate incremental predictive and prognostic information adjuvant to preoperativly achieved testiscular tumor markers.

A preoperative nomogram predicting the pseudocapsule status in localized renal cell carcinoma

Background

Tumor enucleation (TE) surgery for localized renal cell carcinoma (RCC) relies on a complete peritumoral pseudocapsule (PC). Study objective was to develop a preoperative model to predict PC status.

Methods

The prediction model was developed in a cohort that consisted of 170 patients with localized RCC, and data was gathered from 2010 to 2015. Multivariable logistic regression analysis and R were used to generate this prediction model. The statistical performance was assessed with respect to the calibration, discrimination, and clinical usefulness.

Results

The prediction model incorporated the systemic inflammatory markers [neutrophil-lymphocyte ratio (NLR); albumin-globulin ratio (AGR)], CT imaging features (tumor size and necrosis), and clinical risk factors (BMI). The model showed good discrimination, with a C-index of 0.85 (0.78–0.91), and good calibration (P=0.60). The sensitivity and specificity were 62% and 94% respectively. Decision curves and clinical impact curve demonstrated that the current model was clinically useful.

Conclusions

We constructed a model that incorporated both the systematic inflammatory markers and clinical risk factors. It can be conveniently used to preoperatively predict the individualized risk of PC invasion and identify the best candidates to receive TE surgery.

Elevated neutrophil-lymphocyte ratio combined with hyponatremia indicate poor prognosis in renal cell carcinoma

Background: Elevated neutrophil-lymphocyte ratio (NLR) and hyponatremia each predict poor prognosis in renal cell carcinoma (RCC). Since no previous studies have looked at the combined effect of these two prognostic markers, we examined how NLR and hyponatremia combined associates with mortality and hypothesized that elevated NLR and hyponatremia at RCC diagnosis and at RCC recurrence indicate poorer prognosis.Material and methods: Using Danish medical registries 1999-2015, we included 970 patients from two regions with incident RCC and a measurement of NLR and sodium. NLR was categorized as ≤3.0 and >3.0 and sodium as < lower limit of normal (LLN) and ≥ LLN. Outcomes were survival after RCC diagnosis and first recurrence, respectively. We estimated absolute survival and hazard ratios (HR) using multivariate Cox regression.Results: At RCC diagnosis, 559 (57.6%) had NLR >3.0 and 240 (24.7%) had hyponatremia, the 5 year-survival rate was 35.2% in NLR > 3.0 vs. 69.2% in NLR ≤3.0, adjusted HR 1.8 (95% confidence intervals (CI), 1.4; 2.2). In patients with NLR >3.0 and concomitant hyponatremia vs. NLR ≤3.0 and normal sodium the 5-year survival rate was 21.7% vs. 73.2%, adjusted HR 2.8 (95% CI, 2.1; 3.8). At RCC recurrence, patients with NLR >3.0 and hyponatremia similarly had poorest survival, adjusted HR 3.6 (95% CI, 1.0; 12.8).Conclusion: Elevated NLR alone and in combination with hyponatremia at time of initial RCC diagnosis and at time of RCC recurrence are associated with poor prognosis. Combining these two prognostic markers yield a stronger association than NLR considered alone. This may impact prognostic prediction and its related therapeutic strategy.

The Role of Hematological Parameters in Predicting Fuhrman Grade and Tumor Stage in Renal Cell Carcinoma Patients Undergoing Nephrectomy

Background and objective: We investigated the ability of preoperative serum values of red blood cell distribution width (RDW), neutrophil lymphocyte ratio (NLR) and plateletcrit (PCT) to predict Fuhrman grades (FG) and tumor stages of renal cell carcinoma in patients who underwent radical nephrectomy. Materials and methods: Records of 283 patients that underwent radical or partial nephrectomy of renal masses at our clinic between January 2010 and April 2018, whose pathology results indicated renal cell carcinoma (RCC), and who had their FG and T1–4 N0M0 identified were retrospectively evaluated. The patients were divided into two groups based on their FG as low (I–II) and high (III–IV) and their T stages were similarly grouped as limited to kidney (pT1–pT2) and not limited to kidney (pT3–pT4). Results: Mean RDW, NLR, PCT cut-off values of the patients for FG and T stage were 15.65%, 3.54, 0.28% and 14.35%, 2.69, 0.28%, respectively. The RDW and NLR were determined to be statistically significant predictors of a pathologically high FG, whereas the PCT value was not a statistically significant predictor of high FG (p = 0.003, p = 0.006, p = 0.075, respectively). The relationship of RDW, NLR and PCT values with a limited to the kidney pathological T stage revealed statistically significant correlations for all three values. Conclusions: We determined that only RDW and NLR were markers predicting FG, while PCT had no prognostic value. On the other hand, all three of these values were associated with a limited to the kidney pathological T stage in patients who underwent nephrectomy due to renal masses and whose pathologies suggested RCC.

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.

Role of systemic inflammatory response markers in urological malignancy

The systemic inflammatory response is associated with survival in patients with a variety of cancers. This inflammatory response is measured in the peripheral blood, and can be monitored using two categories of indices: concentration of specific serum proteins (albumin, C-reactive protein) and differential blood cell count (neutrophils, lymphocytes and platelets). Furthermore, combinations of these indices, such as the Glasgow Prognostic Score, which consists of the serum C-reactive protein and albumin level; the neutrophil-to-lymphocyte ratio; the platelet-to-lymphocyte ratio; and the prognostic nutritional index, which is based on peripheral blood lymphocyte count and serum albumin level, have also been evaluated and compared in cancer research. To date, there are hundreds of studies that have shown the prognostic value of systemic inflammatory response markers in patients with urological cancer. Most studies have evaluated the prognostic and predictive role of the pretreatment value of the markers, although some have focused on the role of the post-treatment value at specific points during the clinical course. The advantages of systemic inflammatory response markers are that they are easily measurable and inexpensive in the clinical setting. However, it is important to consider how clinicians use these markers in clinical practice. The present review provides a concise overview regarding systemic inflammatory markers in urological cancers, specifically C-reactive protein, Glasgow Prognostic Score/modified Glasgow Prognostic Score, neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio and prognostic nutritional index.

Retrospective evaluation of ultrasound-indeterminate renal multilocular cystic masses by using neutrophil-lymphocyte ratio and computed tomography

PURPOSE

To evaluate the clinical usefulness of neutrophil-lymphocyte ratio (NLR) in differentiating the ultrasound-indeterminate renal multilocular cystic masses (RMCM) in comparison with computed tomography (CT) and whether NLR has additional benefits to CT on sensitivity of detecting the malignant.

MATERIALS AND METHODS

Overall, 93 patients who underwent normal ultrasound with a conclusion of indeterminate RMCM were examined by NLR and CT within 30 days before surgery or follow-up from March to September 2014 at PLA General Hospital and enrolled in this retrospective study. Logistic regression model was performed to find independent predictors for differentiating true nature of RMCM; differences in the validity parameters and diagnostic power of CT, NLR, and their combination were compared using McNemar tests and AUC model, respectively.

RESULTS

The final diagnoses of the 93 patients consisted of 36 patients with benign complex cysts, 16 with multilocular cystic renal cell carcinoma, 9 with multilocular cystic nephroma, and 32 with clear cell renal cell carcinoma. Higher NLR were strongly associated with malignant masses. Multivariate logistic regression analysis revealed that NLR could be an independent predictor for differentiating true nature of these masses (OR = 3.617; 95% CI: 1.219-10.727; P = 0.020). For detecting the malignant masses, the sensitivity, specificity, and accuracy were 71.9%, 80.6%, and 75.3% for CT and 57.9%, 88.9%, and 69.9% for NLR under cutoff value of 2.31, respectively, whereas those of CT+NLR were 89.5%, 69.4%, and 81.7%. No significant difference was found between CT and NLR in sensitivity (P = 0.185), specificity (P = 0.549), and accuracy (P = 0.428). But the sensitivity of CT+NLR was significantly higher than those of CT (P = 0.002) and NLR (P<0.001), respectively; AUC model analysis indicated that CT+NLR got the largest area of 0.795 (P<0.001, 95% CI: 0.693-0.896) in comparison with those of CT (area = 0.795, P<0.001, 95% CI: 0.661-0.864) and NLR (area = 0.734, P<0.001, 95% CI: 0.631-0.836).

CONCLUSIONS

Given that NLR, under cutoff value of 2.31, had no diagnostic difference with CT in evaluating the ultrasound-indeterminate RMCM. However, combination of CT and NLR could increase the sensitivity of detecting malignant masses and acquire the best diagnostic power. Prospectively larger cohort and multicenter studies are still necessary.