scholarly journals Systemic Inflammation Response Index Predicts Survival Outcomes in Glioblastoma Multiforme Patients Treated with Standard Stupp Protocol

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Erkan Topkan ◽  
Ahmet Kucuk ◽  
Yurday Ozdemir ◽  
Huseyin Mertsoylu ◽  
Ali Ayberk Besen ◽  
...  
Keyword(s):  
Glioblastoma Multiforme ◽  
Roc Curve ◽  
Eligible Patient ◽  
Curve Analysis ◽  
Survival Outcomes ◽  
Newly Diagnosed ◽  
Roc Curve Analysis ◽  
Response Index ◽  
Stupp Protocol ◽  
The Ideal

Objectives. We endeavored to retrospectively assess the prognostic merit of pretreatment systemic immune response index (SIRI) in glioblastoma multiforme (GBM) patients who underwent postoperative partial brain radiotherapy (RT) and concurrent plus adjuvant temozolomide (TMZ), namely, the Stupp protocol. Methods. The records of 181 newly diagnosed GBM patients who received the postoperative Stupp protocol were retrospectively analyzed. The SIRI value for each eligible patient was calculated by utilizing the platelet, neutrophil, and lymphocyte measures obtained on the first day of treatment: SIRI = Neutrophils × Monocytes / Lymphocytes . The ideal cutoff values for SIRI connected with the progression-free- (PFS) and overall survival (OS) results were methodically searched through using the receiver operating characteristic (ROC) curve analysis. Primary and secondary end-points constituted the potential OS and PFS distinctions among the SIRI groups, respectively. Results. The ROC curve analysis labeled the ideal SIRI cutoffs at 1.74 (Area under the curve (AUC): 74.9%; sensitivity: 74.2%; specificity: 71.4%) and 1.78 (AUC: 73.6%; sensitivity: 73.1%; specificity: 70.8%) for PFS and OS status, individually. The SIRI cutoff of 1.78 of the OS status was chosen as the common cutoff for the stratification of the study population (Group 1: SIRI ≤ 1.78 ( N = 96 ) and SIRI > 1.78 ( N = 85 )) and further comparative PFS and OS analyses. Comparisons between the two SIRI cohorts manifested that the SIRI ≤ 1.78 cohort had altogether significantly superior median PFS (16.2 versus 6.6 months; P < 0.001 ) and OS (22.9 versus 12.2 months; P < 0.001 ) than its SIRI > 1.78 counterparts. The results of multivariate Cox regression analyses ratified the independent and significant alliance between a low SIRI and longer PFS ( P < 0.001 ) and OS ( P < 0.001 ) durations, respectively. Conclusions. Present results firmly counseled the pretreatment SIRI as a novel, sound, and independent predictor of survival outcomes in newly diagnosed GBM patients intended to undergo postoperative Stupp protocol.

scholarly journals Prognostic Value of Pretreatment Systemic Immune-Inflammation Index in Glioblastoma Multiforme Patients Undergoing Postneurosurgical Radiotherapy Plus Concurrent and Adjuvant Temozolomide

2020 ◽  
Vol 2020 ◽  
pp. 1-9 ◽  
Author(s):  
Erkan Topkan ◽  
Ali Ayberk Besen ◽  
Yurday Ozdemir ◽  
Ahmet Kucuk ◽  
Huseyin Mertsoylu ◽  
...  
Keyword(s):  
Glioblastoma Multiforme ◽  
Roc Curve ◽  
Prognostic Index ◽  
Progression Free Survival ◽  
Curve Analysis ◽  
Newly Diagnosed ◽  
Roc Curve Analysis ◽  
Adjuvant Temozolomide ◽  
Prognostic Utility ◽  
Immune Inflammation

Objectives. To evaluate the potential prognostic utility of pretreatment systemic immune-inflammation index (SII) in newly diagnosed glioblastoma multiforme (GBM) patients who underwent postneurosurgical radiotherapy and concurrent plus adjuvant temozolomide. Methods. The retrospective data of GBM patients who underwent postneurosurgical radiotherapy and concurrent plus adjuvant temozolomide were analyzed. For each patient, SII was calculated using the platelet, neutrophil, and lymphocyte measures obtained on the first day of treatment: SII=platelets×neutrophils/lymphocytes. The receiver operating characteristic (ROC) curve analysis was utilized for the evaluation of optimal cut-off values for SII those linked with the outcomes. Primary and secondary endpoints constituted the overall (OS) and progression-free survival (PFS) per conveyance SII group. Results. A total of 167 patients were included. The ROC curve analysis identified the optimum SII cut-off at a rounded 565 value that significantly interacted with the PFS and OS and stratified patients into two groups: low-SII (SII<565; n=71) and high-SII (SII≥565; n=96), respectively. Comparative survival analyses exhibited that the high-SII cohort had significantly shorter median PFS (6.0 versus 16.6 months; P<0.001) and OS (11.1 versus 22.9 months; P<0.001) than the low-SII cohort. The relationship between the high-SII and poorer PFS (P<0.001) and OS (P<0.001) further retained its independent significance in multivariate analysis, as well. Conclusions. The outcomes displayed here qualified the pretreatment SII as a novel independent prognostic index for predicting survival outcomes of newly diagnosed GBM patients undergoing postneurosurgical radiotherapy and concurrent plus adjuvant temozolomide.

scholarly journals Prognostic Value of C-Reactive Protein to Albumin Ratio in Glioblastoma Multiforme Patients Treated with Concurrent Radiotherapy and Temozolomide

2020 ◽  
Vol 2020 ◽  
pp. 1-8 ◽  
Author(s):  
Erkan Topkan ◽  
Ali A. Besen ◽  
Huseyin Mertsoylu ◽  
Ahmet Kucuk ◽  
Berrin Pehlivan ◽  
...  
Keyword(s):  
Glioblastoma Multiforme ◽  
Roc Curve ◽  
Curve Analysis ◽  
Prognostic Impact ◽  
C Reactive Protein ◽  
Roc Curve Analysis ◽  
Albumin Ratio ◽  
Cutoff Value ◽  
Entire Cohort ◽  
Reactive Protein

Objective. We investigated the prognostic impact of C-reactive protein to albumin ratio (CRP/Alb) on the survival outcomes of newly diagnosed glioblastoma multiforme (GBM) patients treated with radiotherapy (RT) and concurrent plus adjuvant temozolomide (TMZ). Methods. The pretreatment CRP and Alb records of GBM patients who underwent RT and concurrent plus adjuvant TMZ were retrospectively analyzed. The CRP/Alb was calculated by dividing serum CRP level by serum Alb level obtained prior to RT. The availability of significant cutoff value for CRP/Alb that interacts with survival was assessed with the receiver-operating characteristic (ROC) curve analysis. The primary endpoint was the association between the CRP/Alb and the overall survival (OS). Results. A total of 153 patients were analyzed. At a median follow-up of 14.7 months, median and 5-year OS rates were 16.2 months (95% CI: 12.5–19.7) and 9.5%, respectively, for the entire cohort. The ROC curve analysis identified a significant cutoff value at 0.75 point (area under the curve: 74.9%; sensitivity: 70.9%; specificity: 67.7%; P<0.001) for CRP/Alb that interacts with OS and grouped the patients into two: CRP/Alb <0.75 (n = 61) and ≥0.75 (n = 92), respectively. Survival comparisons revealed that the CRP/Alb <0.75 was associated with a significantly superior median (22.5 versus 15.7 months; P<0.001) and 5-year (20% versus 0%) rates than the CRP/Alb ≥0.75, which retained its independent significance in multivariate analysis (P<0.001). Conclusion. Present results suggested the pretreatment CRP/Alb as a significant and independent inflammation-based index which can be utilized for further prognostic lamination of GBM patients.

scholarly journals Betatrophin Acts as a Diagnostic Biomarker in Type 2 Diabetes Mellitus and Is Negatively Associated with HDL-Cholesterol

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Min Yi ◽  
Rong-ping Chen ◽  
Rui Yang ◽  
Xian-feng Guo ◽  
Jia-chun Zhang ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Roc Curve ◽  
Diagnostic Value ◽  
Curve Analysis ◽  
Newly Diagnosed ◽  
Diagnostic Biomarker ◽  
Roc Curve Analysis

Objective. By assessing its circulating concentrations in type 2 diabetes mellitus (T2DM) patients, we aimed to explore the associations of betatrophin with various metabolic parameters and evaluate its diagnostic value in T2DM.Methods. A total of 58 non-diabetes-mellitus (NDM) subjects and 73 age- and sex-matched newly diagnosed T2DM patients were enrolled. Correlation analyses between circulating betatrophin levels and multiple metabolic parameters were performed. Receiver operating characteristic (ROC) curve analysis was used to assess the diagnostic value of betatrophin concentration in T2DM.Results. Circulating betatrophin levels were approximately 1.8 times higher in T2DM patients than in NDM individuals (median 747.12 versus 407.41 pg/mL,P<0.001). Correlation analysis showed that betatrophin was negatively associated with high-density lipoprotein cholesterol (HDL-C) levels in all subjects. ROC curve analysis identified betatrophin as a potent diagnostic biomarker for T2DM. The optimal cut-off point of betatrophin concentration for predicting T2DM was 501.23 pg/mL.Conclusions. Serum betatrophin levels were markedly increased in newly diagnosed T2DM patients and further elevated in obese T2DM subjects. Betatrophin was negatively correlated with HDL-C levels. Our findings indicate that betatrophin could be a potent diagnostic biomarker for T2DM.

Acute heart failure: predicting early in-hospital outcomes

2021 ◽  
Vol 28 (Supplement_1) ◽  
Author(s):  
M Santos ◽  
S Paula ◽  
I Almeida ◽  
H Santos ◽  
H Miranda ◽  
...  
Keyword(s):  
Heart Failure ◽  
Logistic Regression ◽  
Acute Heart Failure ◽  
Roc Curve ◽  
Real Life ◽  
Study Data ◽  
Curve Analysis ◽  
Older Age ◽  
Invasive Ventilation ◽  
Roc Curve Analysis

Abstract Funding Acknowledgements Type of funding sources: None. Introduction Patients (P) with acute heart failure (AHF) are a heterogeneous population. Risk stratification at admission may help predict in-hospital complications and needs. The Get With The Guidelines Heart Failure score (GWTG-HF) predicts in-hospital mortality (M) of P admitted with AHF. ACTION ICU score is validated to estimate the risk of complications requiring ICU care in non-ST elevation acute coronary syndromes. Objective To validate ACTION-ICU score in AHF and to compare ACTION-ICU to GWTG-HF as predictors of in-hospital M (IHM), early M [1-month mortality (1mM)] and 1-month readmission (1mRA), using real-life data. Methods Based on a single-center retrospective study, data collected from P admitted in the Cardiology department with AHF between 2010 and 2017. P without data on previous cardiovascular history or uncompleted clinical data were excluded. Statistical analysis used chi-square, non-parametric tests, logistic regression analysis and ROC curve analysis. Results Among the 300 P admitted with AHF included, mean age was 67.4 ± 12.6 years old and 72.7% were male. Systolic blood pressure (SBP) was 131.2 ± 37.0mmHg, glomerular filtration rate (GFR) was 57.1 ± 23.5ml/min. 35.3% were admitted in Killip-Kimball class (KKC) 4. ACTION-ICU score was 10.4 ± 2.3 and GWTG-HF was 41.7 ± 9.6. Inotropes’ usage was necessary in 32.7% of the P, 11.3% of the P needed non-invasive ventilation (NIV), 8% needed invasive ventilation (IV). IHM rate was 5% and 1mM was 8%. 6.3% of the P were readmitted 1 month after discharge. Older age (p &lt; 0.001), lower SBP (p = 0,035) and need of inotropes (p &lt; 0.001) were predictors of IHM in our population. As expected, patients presenting in KKC 4 had higher IHM (OR 8.13, p &lt; 0.001). Older age (OR 1.06, p = 0.002, CI 1.02-1.10), lower SBP (OR 1.01, p = 0.05, CI 1.00-1.02) and lower left ventricle ejection fraction (LVEF) (OR 1.06, p &lt; 0.001, CI 1.03-1.09) were predictors of need of NIV. None of the variables were predictive of IV. LVEF (OR 0.924, p &lt; 0.001, CI 0.899-0.949), lower SBP (OR 0.80, p &lt; 0.001, CI 0.971-0.988), higher urea (OR 1.01, p &lt; 0.001, CI 1.005-1.018) and lower sodium (OR 0.92, p = 0.002, CI 0.873-0.971) were predictors of inotropes’ usage. Logistic regression showed that GWTG-HF predicted IHM (OR 1.12, p &lt; 0.001, CI 1.05-1.19), 1mM (OR 1.10, p = 1.10, CI 1.04-1.16) and inotropes’s usage (OR 1.06, p &lt; 0.001, CI 1.03-1.10), however it was not predictive of 1mRA, need of IV or NIV. Similarly, ACTION-ICU predicted IHM (OR 1.51, p = 0.02, CI 1.158-1.977), 1mM (OR 1.45, p = 0.002, CI 1.15-1.81) and inotropes’ usage (OR 1.22, p = 0.002, CI 1.08-1.39), but not 1mRA, the need of IV or NIV. ROC curve analysis revealed that GWTG-HF score performed better than ACTION-ICU regarding IHM (AUC 0.774, CI 0.46-0-90 vs AUC 0.731, CI 0.59-0.88) and 1mM (AUC 0.727, CI 0.60-0.85 vs AUC 0.707, CI 0.58-0.84). Conclusion In our population, both scores were able to predict IHM, 1mM and inotropes’s usage.

scholarly journals Presepsin values and prognostic nutritional index predict mortality in intensive care unit patients with sepsis: a pilot study

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Yuichiro Shimoyama ◽  
Osamu Umegaki ◽  
Noriko Kadono ◽  
Toshiaki Minami
Keyword(s):  
Multivariate Analysis ◽  
Roc Curve ◽  
Operating Characteristic ◽  
Prognostic Nutritional Index ◽  
Early Mortality ◽  
Curve Analysis ◽  
Rank Test ◽  
Roc Curve Analysis ◽  
Log Rank Test ◽  
Nutritional Index

Abstract Objective Sepsis is a major cause of mortality for critically ill patients. This study aimed to determine whether presepsin values can predict mortality in patients with sepsis. Results Receiver operating characteristic (ROC) curve analysis, Log-rank test, and multivariate analysis identified presepsin values and Prognostic Nutritional Index as predictors of mortality in sepsis patients. Presepsin value on Day 1 was a predictor of early mortality, i.e., death within 7 days of ICU admission; ROC curve analysis revealed an AUC of 0.84, sensitivity of 89%, and specificity of 77%; and multivariate analysis showed an OR of 1.0007, with a 95%CI of 1.0001–1.0013 (p = 0.0320).

scholarly journals Soluble cytotoxic T-lymphocyte–associated antigen 4 (sCTLA-4) as a potential biomarker for diagnosis and evaluation of the prognosis in Glioma

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Jiajia Liu ◽  
Xiaoyi Tian ◽  
Yan Wang ◽  
Xixiong Kang ◽  
Wenqi Song
Keyword(s):  
T Lymphocyte ◽  
Roc Curve ◽  
Cytotoxic T Lymphocyte ◽  
Tumor Grade ◽  
Curve Analysis ◽  
Enzyme Linked Immunosorbent Assay ◽  
Low Grade ◽  
High Grade ◽  
Healthy Individuals ◽  
Roc Curve Analysis

Abstract Background The cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) is widely considered as a pivotal immune checkpoint molecule to suppress antitumor immunity. However, the significance of soluble CTLA-4 (sCTLA-4) remains unclear in the patients with brain glioma. Here we aimed to investigate the significance of serum sCTLA-4 levels as a noninvasive biomarker for diagnosis and evaluation of the prognosis in glioma patients. Methods In this study, the levels of sCTLA-4 in serum from 50 patients diagnosed with different grade gliomas including preoperative and postoperative, and 50 healthy individuals were measured by an enzyme-linked immunosorbent assay (ELISA). And then ROC curve analysis and survival analyses were performed to explore the clinical significance of sCTLA-4. Results Serum sCTLA-4 levels were significantly increased in patients with glioma compared to that of healthy individuals, and which was also positively correlated with the tumor grade. ROC curve analysis showed that the best cutoff value for sCTLA-4 for glioma is 112.1 pg/ml, as well as the sensitivity and specificity with 82.0 and 78.0%, respectively, and a cut-off value of 220.43 pg/ml was best distinguished in patients between low-grade glioma group and high-grade glioma group with sensitivity 73.1% and specificity 79.2%. Survival analysis revealed that the patients with high sCTLA-4 levels (> 189.64 pg/ml) had shorter progression-free survival (PFS) compared to those with low sCTLA-4 levels (≤189.64 pg/ml). In the univariate analysis, elder, high-grade tumor, high sCTLA-4 levels and high Ki-67 index were significantly associated with shorter PFS. In the multivariate analysis, sCTLA-4 levels and tumor grade remained an independent prognostic factor. Conclusion These findings indicated that serum sCTLA-4 levels play a critical role in the pathogenesis and development of glioma, which might become a valuable predictive biomarker for supplementary diagnosis and evaluation of the progress and prognosis in glioma.

scholarly journals Predictive CT features for the diagnosis of primary pulmonary mucoepidermoid carcinoma: comparison with squamous cell carcinomas and adenocarcinomas

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xiaohua Ban ◽  
Xinping Shen ◽  
Huijun Hu ◽  
Rong Zhang ◽  
Chuanmiao Xie ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Roc Curve ◽  
Multinomial Logistic Regression ◽  
Univariate Analysis ◽  
Ct Imaging ◽  
Squamous Cell Carcinomas ◽  
Curve Analysis ◽  
Imaging Features ◽  
Roc Curve Analysis ◽  
Ct Features

Abstract Background To determine the predictive CT imaging features for diagnosis in patients with primary pulmonary mucoepidermoid carcinomas (PMECs). Materials and methods CT imaging features of 37 patients with primary PMECs, 76 with squamous cell carcinomas (SCCs) and 78 with adenocarcinomas were retrospectively reviewed. The difference of CT features among the PMECs, SCCs and adenocarcinomas was analyzed using univariate analysis, followed by multinomial logistic regression and receiver operating characteristic (ROC) curve analysis. Results CT imaging features including tumor size, location, margin, shape, necrosis and degree of enhancement were significant different among the PMECs, SCCs and adenocarcinomas, as determined by univariate analysis (P < 0.05). Only lesion location, shape, margin and degree of enhancement remained independent factors in multinomial logistic regression analysis. ROC curve analysis showed that the area under curve of the obtained multinomial logistic regression model was 0.805 (95%CI: 0.704–0.906). Conclusion The prediction model derived from location, margin, shape and degree of enhancement can be used for preoperative diagnosis of PMECs.

scholarly journals Mortality risk prediction in lupus patients complicated with invasive infection in the emergency department: LUPHAS score

2019 ◽  
Vol 11 ◽  
pp. 1759720X1988555 ◽  
Author(s):  
Wanlong Wu ◽  
Jun Ma ◽  
Yuhong Zhou ◽  
Chao Tang ◽  
Feng Zhao ◽  
...  
Keyword(s):  
Emergency Department ◽  
Prediction Model ◽  
Risk Score ◽  
Roc Curve ◽  
Curve Analysis ◽  
Multivariable Logistic Regression Analysis ◽  
Invasive Infection ◽  
Roc Curve Analysis ◽  
All Cause Mortality ◽  
Qsofa Score

Background: Infection remains a major cause of morbidity and mortality in patients with systemic lupus erythematosus (SLE). This study aimed to establish a clinical prediction model for the 3-month all-cause mortality of invasive infection events in patients with SLE in the emergency department. Methods: SLE patients complicated with invasive infection admitted into the emergency department were included in this study. Patient’s demographic, clinical, and laboratory characteristics on admission were retrospectively collected as baseline data and compared between the deceased and the survivors. Independent predictors were identified by multivariable logistic regression analysis. A prediction model for all-cause mortality was established and evaluated by receiver operating characteristic (ROC) curve analysis. Results: A total of 130 eligible patients were collected with a cumulative 38.5% 3-month mortality. Lymphocyte count <800/ul, urea >7.6mmol/l, maximum prednisone dose in the past ⩾60 mg/d, quick Sequential Organ Failure Assessment (qSOFA) score, and age at baseline were independent predictors for all-cause mortality (LUPHAS). In contrast, a history of hydroxychloroquine use was protective. In a combined, odds ratio-weighted LUPHAS scoring system (score 3–22), patients were categorized to three groups: low-risk (score 3–9), medium-risk (score 10–15), and high-risk (score 16–22), with mortalities of 4.9% (2/41), 45.9% (28/61), and 78.3% (18/23) respectively. ROC curve analysis indicated that a LUPHAS score could effectively predict all-cause mortality [area under the curve (AUC) = 0.86, CI 95% 0.79–0.92]. In addition, LUPHAS score performed better than the qSOFA score alone (AUC = 0.69, CI 95% 0.59–0.78), or CURB-65 score (AUC = 0.69, CI 95% 0.59–0.80) in the subgroup of lung infections ( n = 108). Conclusions: Based on a large emergency cohort of lupus patients complicated with invasive infection, the LUPHAS score was established to predict the short-term all-cause mortality, which could be a promising applicable tool for risk stratification in clinical practice.

scholarly journals Right choice of a method for determination of cut-off values: A statistical tool for a diagnostic test

2014 ◽  
Vol 5 (3) ◽  
pp. 30-34 ◽  
Author(s):  
Balkishan Sharma ◽  
Ravikant Jain
Keyword(s):  
Logistic Regression ◽  
Discriminant Analysis ◽  
Diagnostic Test ◽  
Roc Curve ◽  
Traditional Method ◽  
Statistical Technique ◽  
Curve Analysis ◽  
Operating Characteristics ◽  
Roc Curve Analysis

Objective: The clinical diagnostic tests are generally used to identify the presence of a disease. The cutoff value of a diagnostic test should be chosen to maximize the advantage that accrues from testing a population of human and others. When a diagnostic test is to be used in a clinical condition, there may be an opportunity to improve the test by changing the cutoff value. To enhance the accuracy of diagnosis is to develop new tests by using a proper statistical technique with optimum sensitivity and specificity. Method: Mean±2SD method, Logistic Regression Analysis, Receivers Operating Characteristics (ROC) curve analysis and Discriminant Analysis (DA) have been discussed with their respective applications. Results: The study highlighted some important methods to determine the cutoff points for a diagnostic test. The traditional method is to identify the cut-off values is Mean±2SD method. Logistic Regression Analysis, Receivers Operating Characteristics (ROC) curve analysis and Discriminant Analysis (DA) have been proved to be beneficial statistical tools for determination of cut-off points.Conclusion: There may be an opportunity to improve the test by changing the cut-off value with the help of a correctly identified statistical technique in a clinical condition when a diagnostic test is to be used. The traditional method is to identify the cut-off values is Mean ± 2SD method. It was evidenced in certain conditions that logistic regression is found to be a good predictor and the validity of the same can be confirmed by identifying the area under the ROC curve. Abbreviations: ROC-Receiver operating characteristics and DA-Discriminant Analysis. Asian Journal of Medical Science, Volume-5(3) 2014: 30-34 http://dx.doi.org/10.3126/ajms.v5i3.9296      

Assessment of Biomarkers for Clinical Diagnosis of Papillary Thyroid Carcinoma with Distant Metastasis

2010 ◽  
Vol 25 (1) ◽  
pp. 38-45 ◽  
Author(s):  
Huasheng Liang ◽  
Yuhua Zhong ◽  
Zuojie Luo ◽  
Yu Huang ◽  
Huade Lin ◽  
...  
Keyword(s):  
Growth Factor ◽  
Papillary Thyroid Carcinoma ◽  
Thyroid Carcinoma ◽  
Clinical Diagnosis ◽  
Distant Metastasis ◽  
Roc Curve ◽  
Curve Analysis ◽  
Papillary Thyroid ◽  
Roc Curve Analysis ◽  
Thyroid Carcinomas

Early diagnosis and treatment of thyroid cancers are critical for better prognosis and better survival rates. The purpose of this study was to identify potential diagnostic markers for papillary thyroid carcinomas with distant metastasis. Fifty-eight papillary thyroid tumor specimens (27 papillary thyroid carcinomas with distant metastasis and 31 without metastasis) were examined, and protein expression of pituitary tumor-transforming gene (PTTG), E-cadherin, p27kip1, vascular endothelial growth factor (VEGF)-C, metalloproteinase (MMP) 2, MMP9, chemokine receptor CXCR4, and basic fibroblast growth factor (bFGF) in these tumors was assessed by immunohistochemistry. The clinicopathological variables with diagnostic significance were determined by multivariate analysis, and their diagnostic values were evaluated by ROC curve analysis. PTTG, VEGF-C, MMP2, MMP9, CXCR4, and bFGF were overexpressed in metastatic papillary thyroid carcinomas, whereas p27kip1 expression was elevated only in carcinomas lacking metastasis. Multiple-factor binary ordinal logistic regression analysis revealed that PTTG, VEGF-C, MMP2, and bFGF were independently related to biological metastatic behavior in thyroid tumors, suggesting their potential use as biomarkers. ROC curve analysis showed that among these four proteins, VEGF-C and bFGF were the best diagnostic biomarkers. A VEGF-C and bFGF cluster was the most useful factor for the differential diagnosis between metastatic and non-metastatic papillary thyroid cancers. Thus, the combined use of VEGF-C and bFGF as biomarkers may improve the diagnostic accuracy of papillary thyroid carcinoma and may be useful in multimodal screening programs for the clinical diagnosis of papillary thyroid carcinoma and early detection of papillary thyroid carcinoma with distant metastasis.

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