scholarly journals Assessment and Prognostic Value of Immediate Changes in Post-Ablation Intratumor Density Heterogeneity of Pulmonary Tumors via Radiomics-Based Computed Tomography Features

2021 ◽  
Vol 11 ◽  
Author(s):  
Bo Liu ◽  
Chunhai Li ◽  
Xiaorong Sun ◽  
Wei Zhou ◽  
Jing Sun ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Regression Model ◽  
Treatment Response ◽  
Prognostic Value ◽  
Cox Regression ◽  
Ct Image ◽  
Roc Curve Analysis ◽  
Prognostic Features ◽  
The Mean ◽  
Pulmonary Tumors

ObjectivesTo retrospectively observe the instantaneous changes in intratumor density heterogeneity after microwave ablation (MWA) of lung tumors and to determine their prognostic value in predicting treatment response and local tumor progression (LTP).MethodsPre- and post-MWA computed tomography (CT) images of 50 patients (37-males; 13-females; mean-age 65.9 ± 9.7y, 39 primary and 11 metastasis) were analyzed to evaluate changes in intratumor density. Global, regional, and local scale radiomics features were extracted to assess intratumor density heterogeneity. In four to six weeks, chest enhanced CT was used as the baseline evaluation of treatment response. The correlations between the parametric variation immediately after ablation and the visual score of ablation response (Rvisu) were analyzed by nonparametric Spearman correlation analysis. The 1-year LTP discrimination power was assessed using the area under the receiver operating characteristic (ROC) curves. A Cox proportional hazards regression model was used to identify the independent prognostic features.ResultsAlthough no significant volume changes were observed after ablation, the radiomics parameters changed in different directions and degrees. The mean intensity value from baseline CT image was 30.3 ± 23.2, and the post-MWA CT image was -60.9 ± 89.8. The ratio of values change was then calculated by a unified formulation. The largest increase (522.3%) was observed for cluster prominence, while the mean CT value showed the largest decline (321.4%). The pulmonary tumors had a mean diameter of 3.4 ± 0.8 cm. Complete ablation was documented in 36 patients. Significant correlations were observed between Rvisu and quantitative features. The highest correlations were observed for changes in local features after MWA, with r ranging from 0.594 to 0.782. LTP developed in 22 patients. The Cox regression model revealed Δcontrast% and response score as independent predictors (Δcontrast%: odds ratio [OR]=5.61, p=0.001; Rvisu: OR=1.73, p=0019). ROC curve analysis showed that Δcontrast% was a better predictor of 1-year LTP. with higher sensitivity (83.5% vs. 71.2%) and specificity (87.1% vs. 76.8%) than those for Rvisu.ConclusionsThe changes in intratumor density heterogeneity after MWA could be characterized by analysis of radiomics features. Real-time density changes could predict treatment response and LTP in patients with pulmonary tumors earlier, especially for tumors with larger diameters.

scholarly journals Prognostic Value of Pre-operative Plasma NT-proBNP Combined With Creatinine in Early Outcomes After Adult Cardiac Valve Surgery

2021 ◽  
Author(s):  
Tianyuan Li ◽  
Hanjun Cao ◽  
Liangchao Qu ◽  
Dingde Long ◽  
Xiaoping Zhu
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Prognostic Value ◽  
Logistic Regression Model ◽  
Valve Surgery ◽  
Curve Analysis ◽  
Cardiac Valve ◽  
Plasma Creatinine ◽  
Roc Curve Analysis ◽  
Cardiac Valve Surgery

Abstract Objective To assess to prognostic value of pre-operative plasma NT-proBNP combined with creatinine in early outcomes after adult cardiac valve surgery. Methods A total of 125 patients who underwent cardiac valve surgery in the first affiliated hospital of nanchang university between October 2016 and October 2018 were retrospectively reviewed. including age, gender, weight, height, pre-operative plasma creatinine, preoperative plasma NT-proBNP, number of valves involved, pre-operative EF and early postoperative outcomes. The independent pre-operative factors that have a significant impact on early post-operative outcomes after adult cardiac valve surgery were investigated. Prognostic value in early outcomes after adult cardiac valve surgery was analyzed by ROC curve analysis. Results preoperative plasma creatinine, preoperative plasma NT-proBNP and the number of valves involved in the complication group were significantly higher than that in non-complication group;BMI and pre-operative EF in the complication group was lower than that in the non-complication group ,with a statistically significant difference(P<0.05). Factors having P-value < 0.15 in the bivariable logistic regression model were entered into a multivariable logistic regression model. The multivariate logistic regression analysis indicated that the preoperative plasma creatinine, preoperative plasma NT-proBNP,BMI and the number of valves involved were correlated with the early postoperative outcomes, and the differences were statistically significant (P < 0.05). ROC curve analysis was used to explore the predictive performance. Results in ROC curve analysis, the AUC for the preoperative plasma NT-proBNP was 0.806 (95% CI 0.712～0.900，P<0.00). Logistic regression model found that the predictive value increased after adding the pre-operative plasma creatinine.the joint prediction AUC was 0.843, the sensitivity and specificity were 85.0%, 72.4% respectively. Conclusion The elevated NT-proBNP and creatinine levels were independently correlated with the early post-operative outcomes, were two promising prognostic predictors for predicting the worse clinical outcomes . The pre-operative plasma NT-proBNP and the plasma creatinine combination was determined to help identify high-risk patients and make appropriate clinical decisions.

scholarly journals Evaluation of prediction score of contrast-induced nephropathy in inpatients undergone to digital or CT angiography

2020 ◽  
Vol 10 (3) ◽  
pp. 78-84
Author(s):  
Seleno Glauber de Jesus-Silva ◽  
Ana Elisa Chaves ◽  
Caio Augusto Alves Maciel ◽  
Edson Eziel Ferreira Scotini ◽  
Pablo Girardelli Mendonça Mesquita ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Roc Curve ◽  
Computed Tomography Angiography ◽  
Score Test ◽  
Area Under The Curve ◽  
Roc Curve Analysis ◽  
Contrast Induced Nephropathy ◽  
Mean Values ◽  
Iodinated Contrast ◽  
The Mean

Objectives: To assess the incidence of contrast-induced nephropathy (CIN) and determine the Mehran Score's (MS) ability to predict CIN in patients undergoing digital angiography or computed tomography angiography. Methods: 252 medical records of inpatients who underwent DA or CTA over 28 months in a quaternary hospital were reviewed. CIN was defined as serum creatinine> 0.5 mg / dL or > 25% increase in baseline creatinine, 48 h after administration of iodinated contrast. The ROC curve and the area under the curve (AUC) were used as a score test. Results: The majority (159; 63.1%) were male, and the average age was 60.4 years. Anemia, diabetes mellitus, and age > 75 years were the most prevalent factors. The incidence of CIN was 17.8% (n = 45). There was a decrease in the mean values ​​of creatinine pre and post among patients who did not suffer CIN (1.38 ± 1.22 vs 1.19 ± 0.89; t = 3.433; p = 0.0007), while among patients who suffering CIN, the mean increase was 1.03 mg / dL (1.43 ± 1.48 vs 2.46 ± 2.35 mg / dL; t = 5.44; p = 0.117). The ROC curve analysis identified a low correlation between MS and the occurrence of CIN (AUC = 0.506). Conclusion: The incidence of CIN in hospitalized patients undergoing angiography or computed tomography angiography was high. The EM did not allow the prediction of NIC.

Systemic immune inflammation index and treatment response in patients with metastatic renal cell cancer.

2018 ◽  
Vol 36 (6_suppl) ◽  
pp. 591-591 ◽  
Author(s):  
Kadriye Bir Yücel ◽  
Arzu Yasar ◽  
Gokhan Ucar ◽  
Gungor Utkan ◽  
Nuriye Yildirim ◽  
...  
Keyword(s):  
Overall Survival ◽  
Multivariate Analysis ◽  
Treatment Response ◽  
Renal Cell ◽  
Prognostic Value ◽  
Cox Regression ◽  
Performance Status ◽  
Univariate Analysis ◽  
Cell Cancer ◽  
Immune Inflammation

591 Background: To investigate the prognostic value of the pretreatment inflammatory characteristics on treatment response and survival. Methods: We included 151 patients with metastatic renal cell carcinoma (mRCC) Patients’ charts were retrospectively analyzed for their clinical, pathological and demographic features. Systemic immune inflammation index (SII) cut off is estimated with median value. Overall survival (OS) was estimated by Kaplan-Meier method for univariate analysis and Cox-regression for multivariate analysis. Results: In high SII group (SII > 844) overall survival is 11 months and in low SII group (SII < 844) overall survival is 22 months (p = 0,008). Median OS is lower in the hypercalcemic group (7 months vs.18 months, P = 0,013). In patients with anemia and thrombocytosis, OS is lower (41 months vs. 13 months p = 0,001 and 6 months vs. 18 months p = 0,01). In multivariate analysis, anemia, SII, and ECOG performance status were able to predict OS (HR = 2,69, HR = 2,04, HR = 2,57) Conclusions: In patients with mRCC, SII may have a prognostic value and higher score may related with decreased overall survival.

High WT1 Expression Has An Independent Positive Influence On CR Rate and EFS in Non M3 AML Patients Treated with Chemotherapy.

Blood ◽  
2009 ◽  
Vol 114 (22) ◽  
pp. 4675-4675
Author(s):  
Nicoletta Colombo ◽  
Raffaella Grasso ◽  
Maurizio Miglino ◽  
Marino Clavio ◽  
Gianmatteo Pica ◽  
...  
Keyword(s):  
Regression Model ◽  
Prognostic Value ◽  
Cox Regression ◽  
Conflicts Of Interest ◽  
Categorical Variables ◽  
P Value ◽  
Prognostic Impact ◽  
Chi Square Analysis ◽  
The Impact

Abstract Abstract 4675 The prognostic value of WT1 expression at diagnosis is still controversial. It has been retrospectively evaluated in 99 consecutive non pretreated non M3 AML patients who had undergone a complete prognostic work up at diagnosis and had received intensive chemotherapy. Biological markers were evaluated on fresh marrow samples collected at diagnosis. WT1 expression was evaluated using TaqMan Gene Expression Assays as described. All patients received induction therapy with combination of fludarabine, Ara-C and anthracycline ± low dose gemtuzumab ozogamicin (n. 59) or with a conventional combination of Ara-C and anthracycline (n. 40) A conventional post-induction chemotherapy including intermediate dosage Ara-C was administered to all responding patients. Univariate comparisons between patients in CR vs non CR were performed using chi-square analysis or Fisher's exact test for categorical variables and t-test for continuous variables. P values < 0.05 were considered statistically significant. Analyses were performed using SPSS. The prognostic impact of WT1 expression was evaluated using quartiles as cut off point and selecting the one with the lowest p value. The event free survival and OS were calculated using the Kaplan Meier method. Non CR after the first induction course, relapse and death due to any cause were considered events. OS and EFS duration were calculated from start of treatment. The impact of multiple predictor variables was assessed by multivariate analyses according to the Cox regression model for OS and EFS while for the evaluation of RC was used the Logistic regression model. Median age of patients was 59 years (range 17-81). Cytogenetic alterations were prognostically favorable in 3 patients and belonged to the intermediate prognostic group in 77 patients (normal karyotype in 75 patients and +8 in two). Nineteen patients had a poor prognosis cytogenetics. For statistical analyses we considered two karyotipic groups: unfavorable (19 patients) and not unfavorable (80 patients). CRs were 60/99 (60%), of which 40 in 51 patients aged 60 or less (78%) and 20 in 48 older than 60 years (41%). Twenty-six patients relapsed, 54 are alive, 45 have died, with a median follow up of 360 days (range 20-2300). In Table 1 are reported clinical indicators of outcome being patients grouped according to the percentile of WT1 expression with the lowest p value (75th). Statystical analysis showed that all WT1 quartiles were balanced for other prognostic factors, such as cytogenetics, BAALC expression, FLT3 and NPMA and B mutations, age, blast count and therapy. The lack of consense on the role of WT1 level at diagnosis in the prognostic stratification indicate that further clinical studies are required. The clear correlation between the level of WT1 transcript and the tumor burden explains why WT1 is used in the follow up of leukemic patients as universal marker of residual disease, also in patients with specific chimeric products. On the contrary, the biological explanation of the prognostic impact of WT1 transcript level at diagnosis remains uncertain. Over the years WT1 gene has been considered as an oncogene or a tumor suppressor gene. In our experience the protective influence of high WT1 expression cannot be explained with an association with good prognosis biological features (such as mut NPM and / or low BAALC). The positive prognostic value of high WT1 expression might be implicated either with WT1 antioncogenic function, or with the stimulating effect of WT1 oncogene on leukemic cellular cycle, possibly associated with an enhanced response to chemotherapy.Table 1WT1 <= 2400 N./N.pts (%)WT1 > 2400 N./N.pts (%)p univ,p multiv.*RR (95% CI)CR (all karyotypes)41/ 75 (54)19/24 (82)0,0260.063.364 (0.927-12.202)CR (int/good karyot.)36/59 (61)19/210.010,0276.649 (1.240-35.645)CR (denovo AML int kar)31/45 (69)14/15 (98)0.020,03412.557 (1.218-129.446)CR (denovo, N.K.)26/40 (65)15/16 (94)0.0250.0413.430 (1.111-162.318)EFS at 24 months (all karyotypes)8%6%0.0020.050.486 (0.235-1.007)EFS at 24 months (int / good karyot.)9%64%0.0010.0230.360 (0.150-0.866)EFS at 24 months (de novo, N.K.)5%70%0.0010.0070.227 (0.077-0.671)OS (all karyot)15%55%0,110,660.837 (0.371-1.890)OS (int/good kar.)18%63%0,050,180.507 (0.186-1.381)Table 1 legend: * for multivariate analysis age, karyotype, FLT3, NPM mutation, BAALC expression, denovo/secondary disease were considered. Disclosures: No relevant conflicts of interest to declare.

Gene Signature And Prognostic Values of m5C-Related Regulators In Colon Adenocarcinoma

2021 ◽  
Author(s):  
Yuancheng Huang ◽  
Chaoyuan Huang ◽  
Xiaotao Jiang ◽  
Yanhua Yan ◽  
Kunhai Zhuang ◽  
...  
Keyword(s):  
Prognostic Value ◽  
Cox Regression ◽  
Colon Adenocarcinoma ◽  
Predictive Biomarkers ◽  
Roc Curves ◽  
The Cancer Genome Atlas ◽  
Risk Scores ◽  
Rna Modification ◽  
Regression Analyses ◽  
Prognostic Features

Abstract Objectives: The purpose of this study was to investigate the role of 13 m5C-related regulators in colon adenocarcinoma (COAD) and determine their prognostic value.Main Methods: Gene expression and clinicopathological data were obtained from The Cancer Genome Atlas (TCGA) datasets. The expression of m5C-related regulators were analyzed with clinicopathological characteristics and alterations within m5C-related regulators. Subsequently, different subtypes of patients with COAD were identified. Then, the prognostic value of m5C-related regulators in COAD were confirmed via univariate Cox regression and least absolute shrinkage and selection operator (LASSO) Cox regression analyses. The prognostic value of risk scores was evaluated using the Kaplan-Meier method, receiver operating characteristic (ROC) curves, and univariate and multivariate regression analyses. Additionally, Gene Set Enrichment Analysisc (GSEA), Kyoto Encyclopedia of Genes and Genomes c (KEGG) pathways, and Gene Ontologyc (GO) analysis were performed for biological functional analysis.Results: m5C-related regulators were found to be differentially expressed in COAD with different clinicopathological features. We observed a high alteration frequency in these genes, which were significantly correlated with their mRNA expression levels. Two clusters with different prognostic features were identified. Based on two independent prognostic m5C-related regulators (NSUN6 and ALYREF), a risk signature with good predictive significance was constructed. Univariate and multivariate Cox regression analyses suggested that the risk score was an independent prognostic factor. Biological processes and pathways associated with cancer, immune response, and RNA processing were identified.Conclusion: We revealed the genetic signatures and prognostic values of m5C-related regulators in COAD. Together, this has improved our understanding of m5C RNA modification and provided novel insights to identify predictive biomarkers and develop molecular targeted therapy for COAD.

scholarly journals Prognostic Value of an Immunohistochemical Signature in Patients With Bladder Cancer Undergoing Radical Cystectomy

2021 ◽  
Vol 11 ◽  
Author(s):  
Jie Wu ◽  
Jun-Miao Wen ◽  
Yu-Chen Wang ◽  
Wen-Jie Luo ◽  
Qi-Feng Wang ◽  
...  
Keyword(s):  
Bladder Cancer ◽  
High Risk ◽  
Regression Model ◽  
Radical Cystectomy ◽  
Prognostic Value ◽  
Cox Regression ◽  
Risk Group ◽  
High Risk Group ◽  
Training Cohort ◽  
Risk Patients

BackgroundThis study aimed to assess the prognostic value of various diagnostic immunohistochemical (IHC) markers and develop an IHC-based classifier to predict the disease-free survival (DFS) of patients with bladder cancer undergoing radical cystectomy.MethodsIHC was performed on tumor specimens from 366 patients with transitional cell bladder cancer. The least absolute shrinkage and selection operator (LASSO) Cox regression model was used to develop a multi-marker classifier for predicting DFS of patients with bladder cancer. The Kaplan–Meier estimate was performed to assess DFS, and unadjusted and adjusted Cox regression models were used to identify independent risk factors to predict DFS of patients with bladder cancer.ResultsBased on the LASSO Cox regression model, nine prognostic markers were identified in the training cohort. Patients were stratified into low- and high-risk groups using the IHC-based classifier. In the training cohort, the 10-year DFS was significantly better in low-risk patients (71%) compared with high-risk patients (18%) (p &lt; 0.001); in the validation cohort, the 10-year DFS was 86% for the low-risk group and 20% for the high-risk group (p &lt; 0.001). Multivariable Cox regression analyses showed that the high-risk group based on the classifier was associated with poorer DFS adjusted by clinicopathological characteristics. Finally, a nomogram comprising the classifier and clinicopathological factors was developed for clinical application.ConclusionThe nine-IHC-based classifier is a reliable prognostic tool, which can eventually guide clinical decision making regarding treatment strategy and follow-up scheduling of bladder cancer.

Pancreatic cancer: Assessment of neoadjuvant chemotherapy outcome based on radiomics of pretreatment computed tomography.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e15767-e15767
Author(s):  
Xiang Li ◽  
Tianyu Tang ◽  
Xueli Bai ◽  
Tingbo Liang
Keyword(s):  
Computed Tomography ◽  
Pancreatic Cancer ◽  
Regression Analysis ◽  
Neoadjuvant Chemotherapy ◽  
Treatment Response ◽  
Cancer Patients ◽  
Tumor Size ◽  
Cox Regression ◽  
Cox Regression Analysis ◽  
Histopathologic Response

e15767 Background: The objective response rate to neoadjuvant chemotherapy (NAC) was limited to around 35% in pancreatic cancer and as more as 30% patients show no benefit to NAC. In this instance, predicting the response to NAC may play an important role in individual treatment for pancreatic cancer patients. We aim to evaluate contrast enhanced-computed tomography (CE-CT) features in predicting treatment response and survival after neoadjuvant chemotherapy (NAC) for patients with borderline resectable and locally advanced pancreatic cancer. Methods: Sixty-one pancreatic cancer patients receiving NAC were enrolled and underwent abdominal CE-CT before treatment. All patients were divided into groups according to the changes of tumor size after treatment. 396 radiomics features were extracted from three-dimensional ROIs (region of interest) based on pretreatment CE-CT images of each patient. The optimal features were selected and three supervised machine learning classifiers were developed. Finally, univariate and multivariate analyses were performed to evaluate the capability of the selected features in predicting histopathologic response and outcomes. Results: Nine, seven and five radiomics features were selected as optimal features for three experiments respectively. Two features, Haralick Entropy and Histogram Entropy, were found consistent in experiments and were both higher in patients with tumor enlargement. Moreover, lower Histogram Entropy was significantly associated with a better histopathologic response (p = 0.008) and smaller tumor size (p = 0.041) in patients with tumor resection. In univariate Cox regression analysis, lower Histogram Entropy (P = 0.006) and lower Haralick Entropy (P = 0.001) predicted a better prognosis. Meanwhile, lower Haralick Entropy (p = 0.048) was independent predictor for longer survival time in multivariate Cox regression analysis. Conclusions: Radiomics features are strongly correlated with NAC treatment response and prognosis in pancreatic cancer, suggesting the great potential of imaging radiomics to help tailoring the treatment into the era of personalized medicine

scholarly journals Diagnostic and Prognostic Value of miR-16, miR-146a, miR-192 and miR-221 in Exosomes of Hepatocellular Carcinoma and Liver Cirrhosis Patients

Cancers ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 2484
Author(s):  
Thorben Fründt ◽  
Linda Krause ◽  
Elaine Hussey ◽  
Bettina Steinbach ◽  
Daniel Köhler ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Liver Cirrhosis ◽  
Regression Model ◽  
Prognostic Value ◽  
Cox Regression ◽  
Healthy Individuals ◽  
Poor Overall Survival ◽  
Exosomal Mirnas ◽  
Differentially Expressed Mirnas ◽  
Diagnostic And Prognostic Value

We aimed to identify a specific microRNA (miRNA) pattern to determine diagnostic and prognostic value in plasma exosomes of hepatocellular carcinoma (HCC) patients. A two-stage study was carried out: exosomal miRNAs were quantified in plasma of HCC patients and healthy individuals by PCR-based microarray cards containing 45 different miRNAs (training cohort). Then, four deregulated miRNAs (miR-16, miR-146a, miR-192, and miR-221) were quantified in the validation analysis using exosomes derived from 85 HCC patients, 50 liver cirrhosis patients, and 20 healthy individuals. Exosomal miR-146a (p = 0.0001), miR-192 (p = 0.002) and miR-221 (p = 0.032) were upregulated only in HCC patients. Repeated 10-fold cross validation showed that miR-146a differentiated HCC from liver cirrhosis patients with AUC of 0.80 ± 0.14 (sensitivity: 81 ± 13%, specificity: 58 ± 22%) in a logistic regression model. High miR-192 presence is associated with poor overall survival (OS) in all HCC patients (p = 0.027) and was predictor of OS in HCC patients in an uni- and multivariate Cox regression model. Moreover, decreased miR-16 levels correlated with OS in liver cirrhosis patients (p = 0.034). Our results emphasized that exosomes secreted into the plasma carry differentially expressed miRNAs of which in particular, miR-192, miR-146, and miR-16 are promising diagnostic and prognostic markers for both HCC and liver cirrhosis patients.

scholarly journals Prognostic Value of an Immunohistochemical Signature in Patients with Bladder Cancer Undergoing Radical Cystectomy

2020 ◽  
Author(s):  
Jie Wu ◽  
Jun-Miao Wen ◽  
Yu-Chen Wang ◽  
Wen-Jie Luo ◽  
Qi-Feng Wang ◽  
...  
Keyword(s):  
Bladder Cancer ◽  
High Risk ◽  
Regression Model ◽  
Radical Cystectomy ◽  
Prognostic Value ◽  
Cox Regression ◽  
Risk Group ◽  
High Risk Group ◽  
Training Cohort ◽  
Risk Patients

Abstract BACKGROUND: This study aimed to assess the prognostic value of a various of diagnostic immunohistochemical (IHC) markers and develop an IHC-based classifier to predict the disease-free survival (DFS) of patients with bladder cancer (BC) undergoing radical cystectomy (RC).METHODS: IHC was performed on tumor specimens from 366 patients with transitional cell BC. The least absolute shrinkage and selection operator (LASSO) Cox regression model was used to develop a multi-marker classifier for predicting DFS of patients with BC. The Kaplan–Meier estimate was performed to assess DFS, and univariate and multivariate Cox regression models were used to identify independent risk factors to predict DFS of patients with BC.RESULTS: Based on the LASSO Cox regression model, nine prognostic markers were identified in the training cohort. Patients were stratified into low- and high-risk groups using the IHC-based classifier. In the training cohort, the 10-year DFS was significantly better in low-risk patients (70.7%) compared with high-risk patients (17.9%) (p＜0.001); in the validation cohort, the 10-year DFS was 85.7% for the low-risk group and 20.4% for the high-risk group (p＜0.001). Multivariable Cox regression analyses showed that the high-risk group based on the nine-IHC-based classifier was associated with poorer DFS adjusted by clinicopathological characteristics. Finally, a nomogram comprising the nine-IHC classifier and clinicopathological factors was developed for clinical application.CONCLUSION: The nine-IHC-based classifier is a reliable prognostic tool, which can eventually guide clinical decision making regarding treatment strategy and follow-up scheduling of BC.

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