Thresholding of prominent biomarkers of breast cancer on overall survival using classification and regression tree

2021 ◽  
pp. 1-10
Author(s):  
Pragya Kumari ◽  
Gajendra K. Vishwakarma ◽  
Atanu Bhattacharjee
Keyword(s):  
Breast Cancer ◽  
Overall Survival ◽  
Survival Analysis ◽  
Regression Tree ◽  
Vital Role ◽  
Classification And Regression Tree ◽  
Brier Score ◽  
Risk Of Death ◽  
Cart Analysis ◽  
Classification And Regression

BACKGROUND: HER2, ER, PR, and ERBB2 play a vital role in treating breast cancer. These are significant predictive and prognosis biomarkers of breast cancer. OBJECTIVE: We aim to obtain a unique biomarker-specific prediction on overall survival to know their survival and death risk. METHODS: Survival analysis is performed on classified data using Classification and Regression Tree (CART) analysis. Hazard ratio and Confidence Interval are computed using MLE and the Bayesian approach with the CPH model for univariate and multivariable illustrations. Validation of CART is executed with the Brier score, and accuracy and sensitivity are obtained using the k-nn classifier. RESULTS: Utilizing CART analysis, the cut-off value of continuous-valued biomarkers HER2, ER, PR, and ERBB2 are obtained as 14.707, 8.128, 13.153, and 6.884, respectively. Brier score of CART is 0.16 towards validation of methodology. Survival analysis gives a demonstration of the survival estimates with significant statistical strategies. CONCLUSIONS: Patients with breast cancer are at low risk of death, whose HER2 value is below its cut-off value, and ER, PR, and ERBB2 values are greater than their cut-off values. This comparison is with the patient having the opposite side of these cut-off values for the same biomarkers.

scholarly journals Artificial liver support system therapy in acute-on-chronic hepatitis B liver failure: Classification and regression tree analysis

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Kaizhou Huang ◽  
Feiyang Ji ◽  
Zhongyang Xie ◽  
Daxian Wu ◽  
Xiaowei Xu ◽  
...  
Keyword(s):  
High Risk ◽  
Hepatitis B ◽  
Regression Tree ◽  
Classification And Regression Tree ◽  
Artificial Liver ◽  
Liver Support ◽  
Artificial Liver Support ◽  
Cart Analysis ◽  
Classification And Regression ◽  
Cart Model

Abstract Artificial liver support systems (ALSS) are widely used to treat patients with hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF). The aims of the present study were to investigate the subgroups of patients with HBV-ACLF who may benefit from ALSS therapy, and the relevant patient-specific factors. 489 ALSS-treated HBV-ACLF patients were enrolled, and served as derivation and validation cohorts for classification and regression tree (CART) analysis. CART analysis identified three factors prognostic of survival: hepatic encephalopathy (HE), prothrombin time (PT), and total bilirubin (TBil) level; and two distinct risk groups: low (28-day mortality 10.2–39.5%) and high risk (63.8–91.1%). The CART model showed that patients lacking HE and with a PT ≤ 27.8 s and a TBil level ≤455 μmol/L experienced less 28-day mortality after ALSS therapy. For HBV-ACLF patients with HE and a PT > 27.8 s, mortality remained high after such therapy. Patients lacking HE with a PT ≤ 27.8 s and TBil level ≤ 455 μmol/L may benefit markedly from ALSS therapy. For HBV-ACLF patients at high risk, unnecessary ALSS therapy should be avoided. The CART model is a novel user-friendly tool for screening HBV-ACLF patient eligibility for ALSS therapy, and will aid clinicians via ACLF risk stratification and therapeutic guidance.

scholarly journals Classification and regression tree (CART) analyses of genomic signatures reveal sets of tetramers that discriminate temperature optima of archaea and bacteria

Archaea ◽  
2008 ◽  
Vol 2 (3) ◽  
pp. 159-167 ◽  
Author(s):  
Betsey Dexter Dyer ◽  
Michael J. Kahn ◽  
Mark D. LeBlanc
Keyword(s):  
Environmental Conditions ◽  
Convergent Evolution ◽  
Regression Tree ◽  
Classification And Regression Tree ◽  
Evolutionary Divergence ◽  
Cart Analysis ◽  
Genomic Signatures ◽  
Genome Wide ◽  
Classification And Regression ◽  
Temperature Optima

Classification and regression tree (CART) analysis was applied to genome-wide tetranucleotide frequencies (genomic signatures) of 195 archaea and bacteria. Although genomic signatures have typically been used to classify evolutionary divergence, in this study, convergent evolution was the focus. Temperature optima for most of the organisms examined could be distinguished by CART analyses of tetranucleotide frequencies. This suggests that pervasive (nonlinear) qualities of genomes may reflect certain environmental conditions (such as temperature) in which those genomes evolved. The predominant use of GAGA and AGGA as the discriminating tetramers in CART models suggests that purine-loading and codon biases of thermophiles may explain some of the results.

Identifying patterns of breast cancer care provided at high volume hospitals: A classification and regression tree analysis.

2015 ◽  
Vol 33 (28_suppl) ◽  
pp. 69-69
Author(s):  
Amanda L. Kong ◽  
Liliana E Pezzin ◽  
Ann B Nattinger
Keyword(s):  
Breast Cancer ◽  
Hospital Volume ◽  
Regression Tree ◽  
High Volume ◽  
Patterns Of Care ◽  
Classification And Regression Tree ◽  
Breast Cancer Care ◽  
Processes Of Care ◽  
Classification And Regression ◽  
Low Volume

69 Background: There is a growing body of literature linking hospital volume to outcomes in breast cancer. However, the mechanism through which volume influences outcome is poorly understood. The purpose of this study was to examine the relationship between hospital volume of breast cancer cases and patterns of processes of care in a population-based cohort of Medicare patients. Methods: A previously described and validated algorithm was applied to Medicare claims for newly diagnosed breast cancer cases in 2003 to identify potential subjects. Breast cancer patients were recruited to participate in a survey study examining breast cancer outcomes, and data was merged with Medicare claims and state tumor registries. Hospital volume was divided into tertiles. A Classification and Regression Tree (CART) model was performed to look for statistically significant relationships between patterns of processes of care and hospital volume. Results: Using CART analysis, eight patterns of care were identified that differentiated breast cancer care at high versus low volume hospitals. Sentinel lymph node dissection (SLND) was the single process of care that demonstrated the greatest differentiation across hospitals with differing volumes. Four patterns of care significantly predicted that a patient was less likely to be treated at a high volume hospital. Conclusions: Our study demonstrates differences in patterns of processes of care between low and high volume hospitals. Hospital volume was associated with several patterns of care that reflect the most current standards of care, particularly SLND. Greater adoption of these patterns by low volume hospitals could improve the overall quality of care for breast cancer.

scholarly journals A diagnostic strategy for Parkinsonian syndromes using quantitative indices of DAT SPECT and MIBG scintigraphy: an investigation using the classification and regression tree analysis

2021 ◽  
Author(s):  
Yu Iwabuchi ◽  
Masashi Kameyama ◽  
Yohji Matsusaka ◽  
Hidetoshi Narimatsu ◽  
Masahiro Hashimoto ◽  
...  
Keyword(s):  
Decision Tree ◽  
Regression Tree ◽  
Classification And Regression Tree ◽  
Mibg Scintigraphy ◽  
Tree Model ◽  
Quantitative Indices ◽  
Cart Analysis ◽  
Parkinsonian Syndromes ◽  
Dat Spect ◽  
Classification And Regression

Abstract Purpose We aimed to evaluate the diagnostic performances of quantitative indices obtained from dopamine transporter (DAT) single-photon emission computed tomography (SPECT) and 123I-metaiodobenzylguanidine (MIBG) scintigraphy for Parkinsonian syndromes (PS) using the classification and regression tree (CART) analysis. Methods We retrospectively enrolled 216 patients with or without PS, including 80 without PS (NPS) and 136 with PS [90 Parkinson’s disease (PD), 21 dementia with Lewy bodies (DLB), 16 progressive supranuclear palsy (PSP), and 9 multiple system atrophy (MSA). The striatal binding ratio (SBR), putamen-to-caudate ratio (PCR), and asymmetry index (AI) were calculated using DAT SPECT. The heart-to-mediastinum uptake ratio (H/M) based on the early (H/M [Early]) and delayed (H/M [Delay]) images and cardiac washout rate (WR) were calculated from MIBG scintigraphy. The CART analysis was used to establish a diagnostic decision tree model for differentiating PS based on these quantitative indices. Results The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were 87.5, 96.3, 93.3, 92.9, and 93.1 for NPS; 91.1, 78.6, 75.2, 92.5, and 83.8 for PD; 57.1, 95.9, 60.0, 95.4, and 92.1 for DLB; and 50.0, 98.0, 66.7, 96.1, and 94.4 for PSP, respectively. The PCR, WR, H/M (Delay), and SBR indices played important roles in the optimal decision tree model, and their feature importance was 0.61, 0.22, 0.11, and 0.05, respectively. Conclusion The quantitative indices showed high diagnostic performances in differentiating NPS, PD, DLB, and PSP, but not MSA. Our findings provide useful guidance on how to apply these quantitative indices in clinical practice.

scholarly journals Classification and regression tree (CART) analysis of endometrial carcinoma: Seeing the forest for the trees

2013 ◽  
Vol 130 (3) ◽  
pp. 452-456 ◽  
Author(s):  
Joyce N. Barlin ◽  
Qin Zhou ◽  
Caryn M. St. Clair ◽  
Alexia Iasonos ◽  
Robert A. Soslow ◽  
...  
Keyword(s):  
Endometrial Carcinoma ◽  
Regression Tree ◽  
Classification And Regression Tree ◽  
Cart Analysis ◽  
Classification And Regression

Correlation of mesothelin expression and CD8 tumor infiltrating lymphocytes with prognosis in cholangiocarcinoma.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e15650-e15650
Author(s):  
Paul Raymond Kunk ◽  
Joseph Mounir Obeid ◽  
Kevin Winters ◽  
Patcharin Pramoonjago ◽  
Dirk G. Brockstedt ◽  
...  
Keyword(s):  
Overall Survival ◽  
Tumor Cells ◽  
Regression Tree ◽  
Tumor Infiltrating Lymphocytes ◽  
Classification And Regression Tree ◽  
Rank Test ◽  
Risk Of Death ◽  
Unmet Treatment Need ◽  
Infiltrating Lymphocytes ◽  
Mesothelin Expression

e15650 Background: Cholangiocarcinoma (CC) is a rapidly progressing malignancy with an unmet treatment need. Little is known about the CC tumor immune microenvironment or about relevant antigenic targets. We hypothesized that lack of T cell infiltration or PD-L1 expression may identify patients at high risk of death, and that mesothelin may be a relevant antigenic target. Methods: A retrospective analysis was conducted of CC tumors at the University of Virginia from 2000-2014. TMAs were constructed of 3-4 cores from each tumor and were stained by IHC for CD4 and CD8 tumor infiltrating lymphocytes (TILs), mesothelin and PD-L1. TMAs were scanned using the Leica SCN400 and analyzed using the Digital Image Hub software. Stain intensity thresholds for defining positive cells were determined by two users and recorded as an average of all cores from each tumor. Mesothelin and PD-L1 expression were measured as a percentage of positive tumor cells. TILs and protein expression were analyzed for association with overall survival, grouped as high or low expression based either on the median or the 33rdpercentile. Correlation with overall survival was assessed using a log rank test and a classification and regression tree with p-values < 0.05 being considered statistically significant. Results: Ninety-nine tumors were available for analysis: 26 intrahepatic, 37 hilar, and 36 distal. PD-L1 and mesothelin expression > 1% of tumor cells were found in 16% and 92% of tumors, respectively. CD4 and CD8 TILs were found in nearly all tumors (98% and 96%), with the majority showing intraepithelial CD4 and CD8 infiltration (73% and 68%). There were no significant associations between survival and PD-L1, mesothelin, or CD4 and CD8 infiltration. However when considered together, the group with low mesothelin/low CD8 (each below 33rdpercentile) had worse survival (9.1 months) compared to high mesothelin/high CD8 (25 months), high mesothelin/low CD8 (30.1 months) and low mesothelin/high CD8 (26.1 months), p = 0.015. Conclusions: CC tumors that lack CD8 infiltration and mesothelin expression have a poor prognosis. Mesothelin represents an attractive target in cholangiocarcinoma, opening the door for future immunotherapy for CC.

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