The method is described to compare the quality of two diagnostic approaches as based on comparing surfaces under the ROC test curve. Apart from small deviations, this method may be applied on independent samples and paired observations carried on identical individuals. Experimental data are issued from comparing two methods of prediction of the survival in dogs on the radiobiologic experiment.

• MeSH
• analýza přežití * MeSH
• chybná diagnóza * MeSH
• experimentální radiační poranění mortalita   MeSH
• pravděpodobnost MeSH
• psi MeSH
• ROC křivka * MeSH
• zvířata MeSH
• Check Tag
• psi MeSH
• zvířata MeSH
• Publikační typ
• anglický abstrakt MeSH
• časopisecké články MeSH

BACKGROUND: Embryos are regeneration and wound healing masters. They rapidly close wounds and scarlessly remodel and regenerate injured tissue. Regeneration has been extensively studied in many animal models using new tools such as single-cell analysis. However, until now, they have been based primarily on experiments assessing from 1 day post injury. RESULTS: In this paper, we reveal that critical steps initiating regeneration occur within hours after injury. We discovered the regeneration initiating cells (RICs) using single-cell and spatial transcriptomics of the regenerating Xenopus laevis tail. RICs are formed transiently from the basal epidermal cells, and their expression signature suggests they are important for modifying the surrounding extracellular matrix thus regulating development. The absence or deregulation of RICs leads to excessive extracellular matrix deposition and defective regeneration. CONCLUSION: RICs represent a newly discovered transient cell state involved in the initiation of the regeneration process.

• Klíčová slova
• Xenopus laevis, RICs, ROCs, Regeneration,
• MeSH
• analýza jednotlivých buněk MeSH
• extracelulární matrix metabolismus   MeSH
• hojení ran MeSH
• ocas * MeSH
• regenerace * MeSH
• transkriptom MeSH
• Xenopus laevis * MeSH
• zvířata MeSH
• Check Tag
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH

An overview of the use of Receiver Operating Characteristic (ROC) analysis within medicine is provided. A survey of the theory behind the analysis is offered together with a presentation on how to create a ROC curve and how to use Cost--Benefit analysis to determine the optimal cut-off point or threshold. The use of ROC analysis is exemplified in the "Cost--Benefit analysis" section of the paper. In these examples, it can be seen that the determination of the optimal cut-off point is mainly influenced by the prevalence and the severity of the disease, by the risks and adverse events of treatment or the diagnostic testing, by the overall costs of treating true and false positives (TP and FP), and by the risk of deficient or non-treatment of false negative (FN) cases.

• MeSH
• analýza nákladů a výnosů * metody   MeSH
• ROC křivka * MeSH
• Publikační typ
• anglický abstrakt MeSH
• časopisecké články MeSH

BACKGROUND: The heterogeneity and lack of validation of existing severity scores for food allergic reactions limit standardization of case management and research advances. We aimed to develop and validate a severity score for food allergic reactions. METHODS: Following a multidisciplinary experts consensus, it was decided to develop a food allergy severity score (FASS) with ordinal (oFASS) and numerical (nFASS) formats. oFASS with 3 and 5 grades were generated through expert consensus, and nFASS by mathematical modeling. Evaluation was performed in the EuroPrevall outpatient clinic cohort (8232 food reactions) by logistic regression with request of emergency care and medications used as outcomes. Discrimination, classification, and calibration were calculated. Bootstrapping internal validation was followed by external validation (logistic regression) in 5 cohorts (3622 food reactions). Correlation of nFASS with the severity classification done by expert allergy clinicians by Best-Worst Scaling of 32 food reactions was calculated. RESULTS: oFASS and nFASS map consistently, with nFASS having greater granularity. With the outcomes emergency care, adrenaline and critical medical treatment, oFASS and nFASS had a good discrimination (receiver operating characteristic area under the curve [ROC-AUC]>0.80), classification (sensitivity 0.87-0.92, specificity 0.73-0.78), and calibration. Bootstrapping over ROC-AUC showed negligible biases (1.0 × 10-6 -1.23 × 10-3 ). In external validation, nFASS performed best with higher ROC-AUC. nFASS was strongly correlated (R 0.89) to best-worst scoring of 334 expert clinicians. CONCLUSION: FASS is a validated and reliable method to measure severity of food allergic reactions. The ordinal and numerical versions that map onto each other are suitable for use by different stakeholders in different settings.

• Klíčová slova
• allergic reactions, anaphylaxis, food allergy, score, severity,
• MeSH
• alergeny MeSH
• lidé MeSH
• plocha pod křivkou MeSH
• potravinová alergie * diagnóza   MeSH
• potraviny MeSH
• ROC křivka MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• alergeny MeSH

The author draws attention to general principles which must be respected in the selection and interpretation of diagnostic methods. He discusses the importance of basic characteristics of the diagnostic test (reliability, accuracy, sensitivity, specificity, predictive value) and their application in the examination process. He explains the importance of ROC analysis in the selection of the optimal diagnostic method. He refers to the criteria which must be taken into account when introducing and evaluating a new examination method.

• MeSH
• diagnóza * MeSH
• lidé MeSH
• prediktivní hodnota testů MeSH
• ROC křivka MeSH
• senzitivita a specificita MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• anglický abstrakt MeSH
• časopisecké články MeSH

This paper describes the excellent performance of a newly developed scoring function (SF), based on the semiempirical QM (SQM) PM6-D3H4X method combined with the conductor-like screening implicit solvent model (COSMO). The SQM/COSMO, Amber/GB and nine widely used SFs have been evaluated in terms of ranking power on the HSP90 protein with 72 biologically active compounds and 4469 structurally similar decoys. Among conventional SFs, the highest early and overall enrichment measured by EF1 and AUC% obtained using single-scoring-function ranking has been found for Glide SP and Gold-ASP SFs, respectively (7, 75 % and 3, 76 %). The performance of other standard SFs has not been satisfactory, mostly even decreasing below random values. The SQM/COSMO SF, where P-L structures were optimised at the advanced Amber level, has resulted in a dramatic enrichment increase (47, 98 %), almost reaching the best possible receiver operator characteristic (ROC) curve. The best SQM frame thus inserts about seven times more active compounds into the selected dataset than the best standard SF.

• Klíčová slova
• docking, enrichment, non-covalent interactions, semiempirical quantum mechanics-based scoring function, virtual screening,
• MeSH
• kvantová teorie * MeSH
• ligandy MeSH
• molekulární modely MeSH
• proteiny tepelného šoku HSP90 antagonisté a inhibitory   metabolismus   MeSH
• ROC křivka MeSH
• termodynamika MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• ligandy MeSH
• proteiny tepelného šoku HSP90 MeSH

Problems related to the optimization of diagnosis making are scrutinized. Applied immunological tests for diagnosis of ovarian cancers are used as an example of ROC curve calculation. Moreover, sensitivity and specificity grades are computed in order to obtain the optimum of diagnostical robustness. The ROC analysis is supplemented with application of Bayes diagnostical algorithm. The analysis is given also of other problems concerning with implementation of quantitative characteristics in the course of diagnostical decision making.

• MeSH
• Bayesova věta MeSH
• diagnóza * MeSH
• lidé MeSH
• nádory vaječníků diagnóza   MeSH
• ROC křivka MeSH
• rozhodování * MeSH
• senzitivita a specificita MeSH
• Check Tag
• lidé MeSH
• ženské pohlaví MeSH
• Publikační typ
• anglický abstrakt MeSH
• časopisecké články MeSH

OBJECTIVES: Progression of chronic allograft nephropathy (CAN) is associated with a progressive decrease in graft function. Prediction of the Banff CAN grade on the basis of correlation between the grade of histological changes and Scr is difficult because of the big spread of individual values. This study sought to predict the Banff CAN grade based on Scr, Ccr and proteinuria using ROC analysis. METHODS: Graft protocol biopsy and functional testing (Scr, Ccr and proteinuria) were performed in 77 subjects (43 men, 34 women, mean age 48.4 +/- 12.8 years) at 33.8 +/- 1.0 months after their first renal transplantation. Immunosuppression was provided with the triple combination of cyclosporin A, prednisone and azathioprine (or mycophenolate mofetil). Statistical evaluation was performed using receiver-operating curve (ROC) analysis. The cut-off value of the Banff CAN score was set at 1. RESULTS: The mean values and SD of the investigated functional parameters in study subjects were as follows: Scr = 201.5 (+/- 100.0) mumol/l Ccr = 48.1 (+/- 21.2) ml/min/1.73 m2, proteinuria = 0.89 (+/- 1.96) g/24 h. ROC analysis showed the highest AUC (+/- SEM) for Scr 0.806 (+/- 0.063). The respective values were 0.790 (+/- 0.053) for Ccr and 0.643 (+/- 0.075) for proteinuria. The AUC (area under the ROC curve) for Scr was significantly higher (P < 0.043) compared with proteinuria. The values for sensitivity (specificity) were as follows: Scr 65.0 (91.2). Ccr 75.0 (82.5), proteinuria 60.0 (68.4). The best fit values (best combination of sensitivity and specificity) were 257.2 umol/l for Scr, 33.6 ml/min/1.73 m2 for Ccr and 0.40 g/24 hr for proteinuria. CONCLUSIONS: Our findings support the assumption that Scr > 275 mumol/l and Ccr < 33.6 ml/min/1.73 m2 suggest a Banff CAN grade higher than 1 (P < 0.001). Proteinuria had the lowest predictive values. Values > 0.40 g/24 hr were probably associated with a Banff CAN grade higher than 1 (p < 0.05).

• MeSH
• biopsie MeSH
• chronická nemoc MeSH
• homologní transplantace MeSH
• kreatinin krev   metabolismus   MeSH
• lidé MeSH
• proteinurie patologie   MeSH
• ROC křivka MeSH
• transplantace ledvin škodlivé účinky   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• Názvy látek
• kreatinin MeSH

The informational efficacy is evaluated of diagnostic tests that are employed in both screening programs and clinical routine. The main data concerning with the decision making theory are summarized and may be successfully applied in order to obtain diagnoses in practical conditions. Various diagnostic algorithms are demonstrated on practical examples. The attention is focused on such diagnostic methods which are issued from binary input data, ROC curve, the use of information theory and Bayes formula. Also the problem related to the statistical induction in evaluating diagnostic tests is treated.

• MeSH
• diagnóza * MeSH
• lidé MeSH
• pravděpodobnost MeSH
• prediktivní hodnota testů MeSH
• ROC křivka MeSH
• rozhodovací teorie MeSH
• senzitivita a specificita MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• anglický abstrakt MeSH
• časopisecké články MeSH

The Arteriovenous Access Stage (AVAS) classification simplifies information about suitability of vessels for vascular access (VA). It's been previously validated in a clinical study. Here, AVAS performance was tested against multiple ultrasound mapping measurements using machine learning. A prospective multicentre international study (NCT04796558) with patient recruitment from March 2021-July 2024. Demographics, risk factors, vessels parameters, types of predicted and created VA (pVA, cVA) were collected. We modelled pVA and cVA using the Random Forest algorithm. Model performance was estimated and compared using Bayesian generalized linear models. ROC AUC with 95% credible intervals was the performance metric. 1151 patients were included. ROC AUC for pVA prediction by AVAS was 0.79 (0.77;0.82) and by mapping was 0.85 (0.83;0.88). ROC AUC for cVA prediction by AVAS was 0.71 (0.69;0.74) and by mapping was 0.8 (0.78;0.83). Using AVAS with other parameters increased the ROC AUC to 0.87 for pVA (0.84;0.89) and 0.82 (0.79;0.84) for cVA. Using mapping with other parameters increased the ROC AUC to 0.88 for pVA (0.86;0.91) and 0.85 (0.83;0.88) for cVA. Multiple mapping measurements showed higher performance at VA prediction than AVAS. However, AVAS is simpler and quicker, so may be preferable for routine clinical practice.

• Klíčová slova
• Arteriovenous access, Classification system, Dialysis, Mapping, Random forest, Renal replacement therapy,
• MeSH
• algoritmy MeSH
• Bayesova věta MeSH
• dialýza ledvin * metody   MeSH
• lidé středního věku MeSH
• lidé MeSH
• prospektivní studie MeSH
• ROC křivka MeSH
• senioři MeSH
• strojové učení * MeSH
• ultrasonografie metody   MeSH
• Check Tag
• lidé středního věku MeSH
• lidé MeSH
• mužské pohlaví MeSH
• senioři MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• multicentrická studie MeSH
• práce podpořená grantem MeSH
• srovnávací studie MeSH