Evaluation of Receiver Operating Characteristic Curve Data in Terms of Information Theory, with Applications in Radiography

Metz, C.E.; Goodenough, David J.; Rossmann, Kurt

doi:10.1148/109.2.297

Cited by 209 publications

(99 citation statements)

References 3 publications

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“…2, individual relative ERCC1 expression levels were blotted against the respective regression grades, and in Table 2, absolute and relative ERCC1 mRNA expression levels are shown with the respective response grades for each individual patient. Cutoff values (21) for ERCC1 expression and histopathological response were calculated for an expression level of 1.09 (area under the curve, 0.74; 95% confidence interval, 0.58 -0.89) to identify minor histopathological response to neoadjuvant therapy.…”

Section: Ercc1 and Response To Therapy In Esophageal Cancermentioning

confidence: 99%

High Specificity of Quantitative Excision Repair Cross-Complementing 1 Messenger RNA Expression for Prediction of Minor Histopathological Response to Neoadjuvant Radiochemotherapy in Esophageal Cancer

Warnecke-Eberz¹,

Metzger²,

Futoshi

et al. 2004

Clinical Cancer Research

108

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Purpose: The excision repair cross-complementing 1 (ERCC1) gene is coding for a nucleotide excision repair protein involved in the repair of radiation-and chemotherapy-induced DNA damage. We examined the potential of quantitative ERCC1 mRNA expression to predict minor or major histopathological response to neoadjuvant radiochemotherapy (cisplatin, 5-fluorouracil, and 36 Gy of radiation) followed by transthoracic en bloc esophagectomy in patients with locally advanced esophageal cancer (cT 2-4 , N x , M 0 ).Experimental Design: Tissue samples were collected by endoscopic biopsy before treatment. RNA was isolated from biopsies, and quantitative real-time reverse transcriptase PCR assays were performed to determine ERCC1 mRNA expression. Relative mRNA levels (tumor/normal ratios) were calculated as (ERCC1/␤-actin in tumor)/(ERCC1/ ␤-actin in paired normal tissue). ERCC1 expression levels were correlated with the objective histopathological response in resected specimens. Histomorphological regression was defined as major response when resected specimens contained <10% of residual vital tumor cells or in case a pathologically complete response was achieved.Results: Twelve of 36 tumors showed a major histopathological response, and 24 of 36 showed a minor histopathological response. Relative expression levels of ERCC1 of >1.09 were not associated with a major histopathological response (sensitivity, 62.5%; specificity, 100%) and 15 of 24 patients with minor histopathological response to the delivered neoadjuvant radiochemotherapy could be unequivocally identified. This association of dichotomized relative ERCC1 mRNA expression and histopathological response was statistically significant (P < 0.001).Conclusions: Relative expression levels of ERCC1 mRNA determined by quantitative real-time reverse transcriptase-PCR appear highly specific to predict minor response to our neoadjuvant radiochemotherapy protocol in patients with locally advanced esophageal cancer and could be applied to prevent expensive, noneffective, and potentially harmful therapies in a substantial number (42%) of patients.

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Section: Ercc1 and Response To Therapy In Esophageal Cancermentioning

confidence: 99%

High Specificity of Quantitative Excision Repair Cross-Complementing 1 Messenger RNA Expression for Prediction of Minor Histopathological Response to Neoadjuvant Radiochemotherapy in Esophageal Cancer

Warnecke-Eberz¹,

Metzger²,

Futoshi

et al. 2004

Clinical Cancer Research

108

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“…As we described above, the model was found dividing the database in training and CV series (subsampling test). A jackknife validation procedure was carried out in the Receiver Operating Characteristic (ROC) curve for the model was also calculated (Diamond, 1987;Hanley, 1989;Mann et al, 1992;Metz et al, 1973). The fraction of true positives (Sensitivity) is contrasted with the fraction of false positives (1-Specificity) in this type of curves.…”

Section: Resultsmentioning

confidence: 99%

A network-QSAR model for prediction of genetic-component biomarkers in human colorectal cancer

Vilar

González-Dı́az

Santana

et al. 2009

Journal of Theoretical Biology

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The combination of the network theory and the calculation of Topological Indices (TIs) allow establishing relationships between the molecular structure of large molecules like the genes and proteins and their properties at a biological level. This type of models can be considered Quantitative Structure-Activity Relationships (QSAR) for biopolymers. In the present work a QSAR model is reported for proteins, related to Human Colorectal Cancer (HCC) and codified by different genes that have been identified experimentally by Sjöblom et al.(Science, 314 (2006)

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“…The difference between the a priori uncertainty and the expected value of the a posteriori uncertainty gives the gain in information provided by the diagnostic test. It is referred to as the diagnostic information or IC of the diagnostic test (4)(5)(6). This difference is also called mutual information.…”

Section: Methodsmentioning

confidence: 99%

“…Metz et al (5) introduced the equation for IC for the binary case in terms of the sensitivity and specificity of the test. Benish (4) provided the expression for IC for the more general case as follows:…”

Section: Methodsmentioning

confidence: 99%

Evaluation of Diagnostic Tests Using Information Theory for Multi-Class Diagnostic Problems and its Application for the Detection of Occlusal Caries Lesions

Arslan¹,

Karaağaoğlu²,

Özkan³

et al. 2014

Balkan Med J

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Diagnostic tests are widely used in medical science for diagnosing the presence or absence of a disease. These tests may not discriminate between subjects with and without the disease or disorder with perfect accuracy. Several methods are available to evaluate the performance of diagnostic tests when the purpose of the test is to discriminate between two possible disease states. Different performance indices have been proposed to determine the accuracy of diagnostic tests when both the disease state and the test result are binary. However, in some cases, the disease state may have more than two categories. For this reason, there is a need for other methods to characterize the accuracy of diagnostic tests. In this study, we propose a method which is useful in terms of selecting the most appropriate diagnostic test when the disease state and test results have three or more classes. In this study, information content (IC) and proportional reduction in diagnostic uncertainty (PRDU) were introduced as measures of diagnostic test accuracy. To demonstrate the applicability of these statistics, we evaluated the diagnostic performance of four different diagnostic methods which are used for dental caries detection: visual inspection, radiography, laser fluorescence (LF) and micro-computed tomography (M-CT) examination.Background: Several methods are available to evaluate the performance of the tests when the purpose of the diagnostic test is to discriminate between two possible disease states. However multi-class diagnostic problems frequently appear in many areas of medical science. Hence, there is a need for methods which will enable us to characterize the accuracy of diagnostic tests when there are more than two possible disease states. Aims: To show that two information theory measures, information content (IC) and proportional reduction in diagnostic uncertainty (PRDU), can be used for the evaluation of the performance of diagnostic tests for multi-class diagnostic problems that may appear in different areas of medical science. Study Design: Diagnostic accuracy study. Methods: Sixty freshly extracted permanent human molar and premolar teeth suspected to have occlusal caries lesions were selected for the study and were assessed by two experienced examiners. Each examiner performed two evaluations. Histological examination was used as the gold standard. The scores of the histological examination were defined as sound (n=11), enamel caries (n=22) and dentin caries (n=27). Diagnostic performance of i) visual inspection, ii) radiography, iii) laser fluorescence (LF) and iv) micro-computed tomography (M-CT) caries detection methods was evaluated by calculating IC and PRDU. Results: Micro-computed tomography examination was the best method among the diagnostic techniques for the diagnosis of occlusal caries in terms of both IC and PRDU. M-CT examination supplied the maximum diagnostic information about the diagnosis of occlusal caries in the first (IC: 1.056; p<0.05), (PRDU: 70.5%) and second evaluation (IC: 1.105; p<0.05),...

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Evaluation of Receiver Operating Characteristic Curve Data in Terms of Information Theory, with Applications in Radiography

Cited by 209 publications

References 3 publications

High Specificity of Quantitative Excision Repair Cross-Complementing 1 Messenger RNA Expression for Prediction of Minor Histopathological Response to Neoadjuvant Radiochemotherapy in Esophageal Cancer

High Specificity of Quantitative Excision Repair Cross-Complementing 1 Messenger RNA Expression for Prediction of Minor Histopathological Response to Neoadjuvant Radiochemotherapy in Esophageal Cancer

A network-QSAR model for prediction of genetic-component biomarkers in human colorectal cancer

Evaluation of Diagnostic Tests Using Information Theory for Multi-Class Diagnostic Problems and its Application for the Detection of Occlusal Caries Lesions

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