Application of Receiver Operating Characteristics Curve (ROC) Analysis When Definitive and Suspect Morphologic Flags Appear in the New Coulter LH 750 Analyzer

2004 ◽  
Vol 10 (1) ◽  
pp. 14-23 ◽  
Author(s):  
C. Aulesa ◽  
I. Pastor ◽  
D. Naranjo ◽  
R. Galimany
Keyword(s):  
Roc Analysis ◽  
Receiver Operating Characteristics ◽  
Operating Characteristics ◽  
Receiver Operating Characteristics Curve ◽  
Receiver Operating

scholarly journals qTICI: Quantitative assessment of brain tissue reperfusion on digital subtraction angiograms of acute ischemic stroke patients

2020 ◽  
pp. 174749302090963
Author(s):  
Haryadi Prasetya ◽  
Lucas A Ramos ◽  
Thabiso Epema ◽  
Kilian M Treurniet ◽  
Bart J Emmer ◽  
...  
Keyword(s):  
Functional Outcome ◽  
Digital Subtraction Angiography ◽  
Quantitative Measure ◽  
Receiver Operating Characteristics ◽  
Binary Logistic Regression Analysis ◽  
Digital Subtraction ◽  
Operating Characteristics ◽  
Vessel Occlusion ◽  
Receiver Operating Characteristics Curve ◽  
Receiver Operating

Background The Thrombolysis in Cerebral Infarction (TICI) scale is an important outcome measure to evaluate the quality of endovascular stroke therapy. The TICI scale is ordinal and observer-dependent, which may result in suboptimal prediction of patient outcome and inconsistent reperfusion grading. Aims We present a semi-automated quantitative reperfusion measure (quantified TICI (qTICI)) using image processing techniques based on the TICI methodology. Methods We included patients with an intracranial proximal large vessel occlusion with complete, good quality runs of anteroposterior and lateral digital subtraction angiography from the MR CLEAN Registry. For each vessel occlusion, we identified the target downstream territory and automatically segmented the reperfused area in the target downstream territory on final digital subtraction angiography. qTICI was defined as the percentage of reperfused area in target downstream territory. The value of qTICI and extended TICI (eTICI) in predicting favorable functional outcome (modified Rankin Scale 0–2) was compared using area under receiver operating characteristics curve and binary logistic regression analysis unadjusted and adjusted for known prognostic factors. Results In total, 408 patients with M1 or internal carotid artery occlusion were included. The median qTICI was 78 (interquartile range 58–88) and 215 patients (53%) had an eTICI of 2C or higher. qTICI was comparable to eTICI in predicting favorable outcome with area under receiver operating characteristics curve of 0.63 vs. 0.62 (P = 0.8) and 0.87 vs. 0.86 (P = 0.87), for the unadjusted and adjusted analysis, respectively. In the adjusted regression analyses, both qTICI and eTICI were independently associated with functional outcome. Conclusion qTICI provides a quantitative measure of reperfusion with similar prognostic value for functional outcome to eTICI score.

scholarly journals Evaluating and comparing biomarkers with respect to the area under the receiver operating characteristics curve in two-phase case–control studies

Biostatistics ◽  
2016 ◽  
Vol 17 (3) ◽  
pp. 499-522 ◽  
Author(s):  
Ying Huang
Keyword(s):  
Case Control ◽  
Receiver Operating Characteristics ◽  
Biased Sampling ◽  
Second Phase ◽  
Operating Characteristics ◽  
Case Control Studies ◽  
Two Phase ◽  
Receiver Operating Characteristics Curve ◽  
The Impact ◽  
Receiver Operating

Abstract Two-phase sampling design, where biomarkers are subsampled from a phase-one cohort sample representative of the target population, has become the gold standard in biomarker evaluation. Many two-phase case–control studies involve biased sampling of cases and/or controls in the second phase. For example, controls are often frequency-matched to cases with respect to other covariates. Ignoring biased sampling of cases and/or controls can lead to biased inference regarding biomarkers' classification accuracy. Considering the problems of estimating and comparing the area under the receiver operating characteristics curve (AUC) for a binary disease outcome, the impact of biased sampling of cases and/or controls on inference and the strategy to efficiently account for the sampling scheme have not been well studied. In this project, we investigate the inverse-probability-weighted method to adjust for biased sampling in estimating and comparing AUC. Asymptotic properties of the estimator and its inference procedure are developed for both Bernoulli sampling and finite-population stratified sampling. In simulation studies, the weighted estimators provide valid inference for estimation and hypothesis testing, while the standard empirical estimators can generate invalid inference. We demonstrate the use of the analytical variance formula for optimizing sampling schemes in biomarker study design and the application of the proposed AUC estimators to examples in HIV vaccine research and prostate cancer research.

scholarly journals Effect of Signal Selection in Receiver Operating Characteristics (ROC) Analysis

2010 ◽  
Vol 66 (11) ◽  
pp. 1467-1473
Author(s):  
Satoshi Takeda ◽  
Makoto Goto ◽  
Tatsuya Maruno ◽  
Takuya Honda ◽  
Kousuke Mochidome ◽  
...  
Keyword(s):  
Roc Analysis ◽  
Receiver Operating Characteristics ◽  
Operating Characteristics ◽  
Signal Selection ◽  
Receiver Operating
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