An Effective Evaluation Tool for Hyperspectral Target Detection: 3D Receiver Operating Characteristic Curve Analysis

Aims To investigate whether an intraperitoneal contamination index (ICI) derived from combined preoperative levels of C-reactive protein, lactate, neutrophils, lymphocytes and albumin could predict the extent of intraperitoneal contamination in patients with acute abdominal pathology. Methods Patients aged over 18 who underwent emergency laparotomy for acute abdominal pathology between January 2014 and October 2018 were randomly divided into primary and validation cohorts. The proposed intraperitoneal contamination index was calculated for each patient in each cohort. Receiver operating characteristic curve analysis was performed to determine discrimination of the index and cut-off values of preoperative intraperitoneal contamination index that could predict the extent of intraperitoneal contamination. Results Overall, 468 patients were included in this study; 234 in the primary cohort and 234 in the validation cohort. The analyses identified intraperitoneal contamination index of 24.77 and 24.32 as cut-off values for purulent contamination in the primary cohort (area under the curve (AUC): 0.73, P < 0.0001; sensitivity: 84%, specificity: 60%) and validation cohort (AUC: 0.83, P < 0.0001; sensitivity: 91%, specificity: 69%), respectively. Receiver operating characteristic curve analysis also identified intraperitoneal contamination index of 33.70 and 33.41 as cut-off values for feculent contamination in the primary cohort (AUC: 0.78, P < 0.0001; sensitivity: 87%, specificity: 64%) and validation cohort (AUC: 0.79, P < 0.0001; sensitivity: 86%, specificity: 73%), respectively. Conclusions As a predictive measure which is derived purely from biomarkers, intraperitoneal contamination index may be accurate enough to predict the extent of intraperitoneal contamination in patients with acute abdominal pathology and to facilitate decision-making together with clinical and radiological findings.

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Diagnostic accuracy of four assays of prostatic acid phosphatase. Comparison using receiver operating characteristic curve analysis

JAMA ◽

10.1001/jama.253.5.665 ◽

1985 ◽

Vol 253 (5) ◽

pp. 665-669 ◽

Cited By ~ 3

Author(s):

J. L. Carson

Keyword(s):

Acid Phosphatase ◽

Diagnostic Accuracy ◽

Receiver Operating Characteristic Curve ◽

Receiver Operating Characteristic ◽

Operating Characteristic ◽

Characteristic Curve ◽

Prostatic Acid Phosphatase ◽

Curve Analysis ◽

Operating Characteristic Curve ◽

Receiver Operating

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Adjustment for the measurement error in evaluating biomarker performances at baseline for future survival outcomes: Time-dependent receiver operating characteristic curve within a joint modelling framework

Research Methods in Medicine & Health Sciences ◽

10.1177/2632084320972257 ◽

2020 ◽

pp. 263208432097225

Author(s):

Ruwanthi Kolamunnage-Dona ◽

Adina Najwa Kamarudin

Keyword(s):

Measurement Error ◽

Receiver Operating Characteristic Curve ◽

Receiver Operating Characteristic ◽

Operating Characteristic ◽

Characteristic Curve ◽

Curve Analysis ◽

Time Dependent ◽

Survival Outcomes ◽

Operating Characteristic Curve ◽

Receiver Operating

The performance of a biomarker is defined by how well the biomarker is capable to distinguish between healthy and diseased individuals. This assessment is usually based on the baseline value of the biomarker; the value at the earliest time point of the patient follow-up, and quantified by ROC (receiver operating characteristic) curve analysis. However, the observed baseline value is often subjected to measurement error due to imperfect laboratory conditions and limited machine precision. Failing to adjust for measurement error may underestimate the true performance of the biomarker, and in a direct comparison, useful biomarkers could be overlooked. We develop a novel approach to account for measurement error when calculating the performance of the baseline biomarker value for future survival outcomes. We adopt a joint longitudinal and survival data modelling formulation and use the available longitudinally repeated values of the biomarker to make adjustment of the measurement error in time-dependent ROC curve analysis. Our simulation study shows that the proposed measurement error-adjusted estimator is more efficient for evaluating the performance of the biomarker than estimators ignoring the measurement error. The proposed method is illustrated using Mayo Clinic primary biliary cirrhosis (PBC) study.

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Evaluating Predictors of Apple Scab with Receiver Operating Characteristic Curve Analysis

Phytopathology ◽

10.1094/phyto-95-0679 ◽

2005 ◽

Vol 95 (6) ◽

pp. 679-691 ◽

Cited By ~ 32

Author(s):

William W. Turechek ◽

Wayne F. Wilcox

Keyword(s):

Receiver Operating Characteristic Curve ◽

Receiver Operating Characteristic ◽

Operating Characteristic ◽

Characteristic Curve ◽

Apple Scab ◽

Curve Analysis ◽

Immature Fruit ◽

Action Threshold ◽

Operating Characteristic Curve ◽

Receiver Operating

Apple scab (Venturia inaequalis) is a perennial threat to apple production in temperate climates throughout the world. In the eastern United States, apple scab is managed almost exclusively through the regular application of fungicides. Management of the primary phase of disease is focused on preventing infection by ascospores. Management of secondary cycles of infection is largely dependent on how well primary infections were controlled. In this study, we used receiver operating characteristic curve analysis to evaluate how well mid-season assessments of the incidence of apple scab on cluster leaves, clusters (i.e., the whorl of cluster leaves), or immature fruit can serve as predictors of apple scab on harvested fruit (harvest scab) and whether these mid-season assessments of scab could be used reliably to manage scab under various damage thresholds. Results showed that assessment of scab on immature fruit was superior at predicting harvest scab than were assessments made on clusters or cluster leaves at all damage thresholds evaluated. A management action threshold of 7% scab incidence on immature fruit was identified by Youden's index as the optimal action threshold to prevent harvest scab incidence from exceeding 5%. Action thresholds could be higher or lower than 7% when economic assumptions were factored in to the decision process. The utility of such a predictor is discussed.

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