StAR: a simple tool for the statistical comparison of ROC curves

Background  

As in many different areas of science and technology, most important problems in bioinformatics rely on the proper development and assessment of binary classifiers. A generalized assessment of the performance of binary classifiers is typically carried out through the analysis of their receiver operating characteristic (ROC) curves. The area under the ROC curve (AUC) constitutes a popular indicator of the performance of a binary classifier. However, the assessment of the statistical significance of the difference between any two classifiers based on this measure is not a straightforward task, since not many freely available tools exist. Most existing software is either not free, difficult to use or not easy to automate when a comparative assessment of the performance of many binary classifiers is intended. This constitutes the typical scenario for the optimization of parameters when developing new classifiers and also for their performance validation through the comparison to previous art.     

DIC Score in Pregnant Women – A Population Based Modification of the International Society on Thrombosis and Hemostasis Score

Objectives

The objectives of this study were: 1) To determine the component needed to generate a validated DIC score during pregnancy. 2) To validate such scoring system in the identification of patients with clinical diagnosis of DIC.

Material and Methods

This is a population based retrospective study, including all women who gave birth at the ‘Soroka University Medical Center’ during the study period, and have had blood coagulation tests including complete blood cell count, prothrombin time (PT)(seconds), partial thromboplastin time (aPTT), fibrinogen, and D-dimers. Nomograms for pregnancy were established, and DIC score was constructed based on ROC curve analyses.

Results

1) maternal plasma fibrinogen concentrations increased during pregnancy; 2) maternal platelet count decreased gradually during gestation; 3) the PT and PTT values did not change with advancing gestation; 4) PT difference had an area under the curve (AUC) of 0.96 (p<0.001), and a PT difference ≥1.55 had an 87% sensitivity and 90% specificity for the diagnosis of DIC; 5) the platelet count had an AUC of 0.87 (p<0.001), an 86% sensitivity and 71% specificity for the diagnosis of DIC; 6) fibrinogen concentrations had an AUC of 0.95 (p<0.001) and a cutoff point ≤3.9 g/L had a sensitivity of 87% and a specificity of 92% for the development of DIC; and 7) The pregnancy adjusted DIC score had an AUC of 0.975 (p<0.001) and at a cutoff point of ≥26 had a sensitivity of 88%, a specificity of 96%, a LR(+) of 22 and a LR(−) of 0.125 for the diagnosis of DIC.

Conclusion

We could establish a sensitive and specific pregnancy adjusted DIC score. The positive likelihood ratio of this score suggests that a patient with a score of ≥26 has a high probability to have DIC.     

The Neutrophil-Lymphocyte Count Ratio in Patients with Community-Acquired Pneumonia

Study Objective

The neutrophil-lymphocyte count ratio (NLCR) has been identified as a predictor of bacteremia in medical emergencies. The aim of this study was to investigate the value of the NLCR in patients with community-acquired pneumonia (CAP).

Methods and Results

Consecutive adult patients were prospectively studied. Pneumonia severity (CURB-65 score), clinical characteristics, complications and outcomes were related to the NLCR and compared with C-reactive protein (CRP), neutrophil count, white blood cell (WBC) count. The study cohort consisted of 395 patients diagnosed with CAP. The mean age of the patients was 63.4±16.0 years. 87.6% (346/395) of the patients required hospital admission, 7.8% (31/395) patients were admitted to the Intensive Care Unit (ICU) and 5.8% (23/395) patients of the study cohort died. The NLCR was increased in all patients, predicted adverse medical outcome and consistently increased as the CURB-65 score advanced. NLCR levels (mean ± SD) were significantly higher in non-survivors (23.3±16.8) than in survivors (13.0±11.4). The receiver-operating characteristic (ROC) curve for NLCR predicting mortality showed an area under the curve (AUC) of 0.701. This was better than the AUC for the neutrophil count, WBC count, lymphocyte count and CRP level (0.681, 0.672, 0.630 and 0.565, respectively).

Conclusion

Admission NLCR at the emergency department predicts severity and outcome of CAP with a higher prognostic accuracy as compared with traditional infection markers.     

Smelling the Diagnosis: The Electronic Nose as Diagnostic Tool in Inflammatory Arthritis. A Case-Reference Study

Objective

To investigate whether exhaled breath analysis using an electronic nose can identify differences between inflammatory joint diseases and healthy controls.

Methods

In a cross-sectional study, the exhaled breath of 21 rheumatoid arthritis (RA) and 18 psoriatic arthritis (PsA) patients with active disease was compared to 21 healthy controls using an electronic nose (Cyranose 320; Smiths Detection, Pasadena, CA, USA). Breathprints were analyzed with principal component analysis, discriminant analysis, and area under curve (AUC) of receiver operating characteristics (ROC) curves. Volatile organic compounds (VOCs) were identified by gas chromatography and mass spectrometry (GC-MS), and relationships between breathprints and markers of disease activity were explored.

Results

Breathprints of RA patients could be distinguished from controls with an accuracy of 71% (AUC 0.75, 95% CI 0.60–0.90, sensitivity 76%, specificity 67%). Breathprints from PsA patients were separated from controls with 69% accuracy (AUC 0.77, 95% CI 0.61–0.92, sensitivity 72%, specificity 71%). Distinction between exhaled breath of RA and PsA patients exhibited an accuracy of 69% (AUC 0.72, 95% CI 0.55–0.89, sensitivity 71%, specificity 72%). There was a positive correlation in RA patients of exhaled breathprints with disease activity score (DAS28) and number of painful joints. GC-MS identified seven key VOCs that significantly differed between the groups.

Conclusions

Exhaled breath analysis by an electronic nose may play a role in differential diagnosis of inflammatory joint diseases. Data from this study warrant external validation.     

PHQ-9 and PHQ-2 for Screening Depression in Chinese Rural Elderly

Objectives

This study aimed to explore cut-off scores of the 9-item Patient Health Questionnaire (PHQ-9) and 2-item Patient Health Questionnaire (PHQ-2) for depression screening in Chinese rural elderly.

Methods

A cross-sectional study was conducted on 839 residents aged 60 years and above in rural areas of Liuyang County. PHQ-9 was adopted to evaluate depression. The Structured Clinical Interview for DSM Disorders (SCID-I) was adopted to diagnose major depressive disorder (MDD) as a golden standard. Sensitivity, specificity, positive and negative predictive value, positive and negative likelihood ratio, Youden’s index and the receiver operating characteristic (ROC) curve were analyzed on PHQ-9 and PHQ-2.

Results

The Cronbach''s alphas of PHQ-9 and PHQ-2 were 0.82 and 0.76, respectively. The score of 8 of the PHQ-9 showed the highest Youden’s index of 0.85, with a sensitivity of 0.97 and specificity of 0.89 respectively, and the area under the ROC curve (AUC) was 0.97 (95% CI: 0.96–0.98). The score of 3 of PHQ-2 showed the highest Youden’s index of 0.79, with both sensitivity and specificity were 0.90 and the AUC was 0.94 (95% CI: 0.90–0.97).

Conclusions

Both PHQ-9 and PHQ-2 are valid screening instruments for depression in the rural elderly in China, with recommended cut-off scores of 8 and 3 respectively.     

Screening for Differentially Expressed Proteins Relevant to the Differential Diagnosis of Sarcoidosis and Tuberculosis

Background

In this study, we sought to identify differentially expressed proteins in the serum of patients with sarcoidosis or tuberculosis and to evaluate these proteins as markers for the differential diagnosis of sarcoidosis and sputum-negative tuberculosis.

Methods

Using protein microarrays, we identified 3 proteins exhibiting differential expression between patients with sarcoidosis and tuberculosis. Elevated expression of these proteins was verified using the enzyme-linked immunosorbent assay (ELISA) and was further confirmed by immunohistochemistry. Receiver operating characteristic (ROC) curve, logistic regression analysis, parallel, and serial tests were used to evaluate the diagnostic efficacy of the proteins.

Results

Intercellular Adhesion Molecule 1(ICAM-1) and leptin were screened for differentially expressed proteins relevant to sarcoidosis and tuberculosis. Using ROC curves, we found that ICAM-1 (cutoff value: 57740 pg/mL) had an area under the curve (AUC), sensitivity, and specificity of 0.718, 62.3%, and 79.5% respectively, while leptin (cutoff value: 1193.186 pg/mL) had an AUC, sensitivity, and specificity of 0.763, 88.3%, and 65.8%, respectively. Logistic regression analysis revealed that the AUC, sensitivity, and specificity of combined leptin and ICAM-1 were 0.787, 89.6%, and 65.8%, respectively, while those of combined leptin, ICAM-1, and body mass index (BMI) were 0.837, 90.9%, and 64.4%, respectively, which had the greatest diagnostic value. Parallel and serial tests indicated that the BMI-leptin parallel with the ICAM-1 serial was the best diagnostic method, achieving a sensitivity and specificity of 86.5% and 73.1%, respectively. Thus, our results identified elevated expression of ICAM-1 and leptin in serum and granulomas of sarcoidosis patients.

Conclusions

ICAM-1 and leptin were found to be potential markers for the diagnosis of sarcoidosis and differential diagnosis of sarcoidosis and sputum-negative tuberculosis.     

Evaluation of MCM-2 expression in TMA cervical specimens

Background

Minichromosome maintenance proteins (MCM) are highly expressed in actively replicating cells. The need for biological markers for cervical carcinoma and its precursor lesions is emerging. Our main aim was to determine the immunohistochemical expression of MCM-2 in HIV-positive and -negative dysplastic cervical specimens.

Methods

Immunohistochemical analysis of MCM-2 was performed in a total of 352 cervical TMA specimens of normal control, low-grade CIN, high-grade CIN and invasive tumor. 38 specimens were from HIV-positive women. A receiver operating characteristic (ROC) curve was constructed to determine the best cutoff to diagnose high-grade CIN and invasive cervical cancer.

Results

In the progression from normal epithelium to high-grade CIN and invasive tumor we found significant differences in the MCM-2 expression (p<0.05). Based on the ROC curve of 80% with an area under the curve (AUC) of 0.78, expression of MCM-2 to diagnose high-grade CIN and invasive tumor resulted in sensitivity of 81%, specificity of 66%, a positive predictive value (PPV) of 86% and a negative predictive value (NPV) of 57%. HIV-positive cervices revealed a decreasing expression of MCM-2 in both LGCIN and HGCIN compared with HIV-negative specimens (p<0.0001).

Conclusions

The present study suggests that immunohistochemical MCM-2 may not be a promising biomarker for diagnosing high-grade CIN and invasive cancer.     

The effects of postprandial glucose and insulin levels on postprandial endothelial function in subjects with normal glucose tolerance

Background

Type 2 diabetes mellitus (T2DM) patients are at increased risk of developing cardiovascular events. Unfortunately traditional risk assessment scores, including the Framingham Risk Score (FRS), have only modest accuracy in cardiovascular risk prediction in these patients.

Methods

We sought to determine the prognostic values of different non-invasive markers of atherosclerosis, including brachial artery endothelial function, carotid artery atheroma burden, ankle-brachial index, arterial stiffness and computed tomography coronary artery calcium score (CACS) in 151 T2DM Chinese patients that were identified low-intermediate risk from the FRS recalibrated for Chinese (<20% risk in 10?years). Patients were prospectively followed-up and presence of atherosclerotic events documented for a mean duration of 61?±?16?months.

Results

A total of 17 atherosclerotic events in 16 patients (11%) occurred during the follow-up period. The mean FRS of the study population was 5.0?±?4.6% and area under curve (AUC) from receiver operating characteristic curve analysis for prediction of atherosclerotic events was 0.59?±?0.07 (P?=?0.21). Among different vascular assessments, CACS?>?40 had the best prognostic value (AUC 0.81?±?0.06, P?<?0.01) and offered significantly better accuracy in prediction compared with FRS (P?=?0.038 for AUC comparisons). Combination of FRS with CACS or other surrogate vascular markers did not further improve the prognostic values over CACS alone. Multivariate Cox regression analysis identified CACS?>?40 as an independent predictor of atherosclerotic events in T2DM patients (Hazards Ratio 27.11, 95% Confidence Interval 3.36-218.81, P?=?0.002).

Conclusions

In T2DM patients identified as low-intermediate risk by the FRS, a raised CACS?>?40 was an independent predictor for atherosclerotic events.     

Performance characteristics of combinations of host biomarkers to identify women with occult placental malaria: a case-control study from Malawi

Background

Because of its propensity to sequester in the placental intervillous space, Plasmodium falciparum can evade detection by peripheral smear in women with placental malaria (PM). We evaluated host biomarkers as potential indicators of occult PM infections.

Methods and Findings

Using a case-control design, we evaluated the ability of biomarkers to identify PM in the absence of circulating peripheral parasites (n = 24) compared to placental smear-negative controls (n = 326). We measured levels of biomarkers (C3a, C5a, CRP, angiopoietin-1, angiopoietin-2, sTie-2, sEndoglin, VEGF, sFlt-1, tissue factor, and leptin) in maternal peripheral plasma at delivery. Using ROC curve analysis, we assessed the ability of clinical parameters and biomarkers to accurately detect PM infections identified by placental smear. We show that decreases in sFlt-1 and leptin and increases in CRP were associated with occult PM infections (p<0.01) and correlated with placental parasitaemia (p<0.01). Individually, all markers had moderate ability to diagnose occult PM infections with areas under the ROC between 0.62 and 0.72. In order to improve diagnostic performance, we generated simple scoring systems to identify PM infections using either a clinical score (0–2), a biomarker score (0–3) or a clinical plus biomarker score (0–5). The combinatorial model that incorporated both clinical parameters and biomarkers had an area under curve (AUC) of 0.85 (95% CI, 0.81-0.89), which was significantly better at identifying occult PM infections than the clinical score alone (p = 0.001).

Conclusion

These data suggest that host biomarkers in the maternal peripheral blood may improve the detection of PM in the absence of peripheral parasitaemia.     

Screening for Depression in Low-Income Elderly Patients at the Primary Care Level: Use of the Patient Health Questionnaire-2

Introduction

Depression is one of the most common mental disorders and a leading cause of disability worldwide. It constitutes a serious public health problem, particularly among elderly individuals. Most depressed elderly patients are treated by primary care (PC) physicians. The “Patient Health Questionnaire” (PHQ-2) is an instrument used for the detection of depression in PC settings.

Objective

Evaluate the performance of the PHQ-2 in a low-income and uneducated elderly PC population.

Methods

A non-probabilistic population sample of 142 individuals was selected from the healthcare unit''s users ≧60 years. Criterion validity was assessed by estimating the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of the PHQ-2 in comparison with the structured interview using the DSM-IV. The estimates of sensitivity and specificity were obtained from varying cut-offs of the PHQ-2 score. A Receiver Operator Characteristic (ROC) curve was constructed and the area under the curve (AUC) was calculated.

Results

The group was predominantly female (73.9%), with low education level (mean 3 years of schooling). The mean age was 72.5 years old. The prevalence of depression was 26.1%. The best values of sensitivity (0.74), specificity (0.77), PPV (0.50) e NPV (0.90) were obtained with score equal to 1. The AUC was 0.77, indicating a modest performance of the test accuracy.

Conclusion

The simplicity of the PHQ-2 is an advantage for its use in PC. The high NPV indicated that 90% of those who tested negative would not need additional tests. However, the low PPV indicated that the PHQ-2 is not sufficient to screen for depression. The application of the instrument could be the first step of the screening, that would include a second step to all those with positive tests formerly.     

Kidney Function,Endothelial Activation and Atherosclerosis in Black and White Africans with Rheumatoid Arthritis

Objective

To determine whether kidney function independently relates to endothelial activation and ultrasound determined carotid atherosclerosis in black and white Africans with rheumatoid arthritis (RA).

Methods

We calculated the Jelliffe, 5 Cockcroft-Gault equations, Salazar-Corcoran, Modification of Diet in Renal Disease (MDRD) and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) estimated glomerular filtration rate (EGFR) equations in 233 (112 black) RA patients.

Results

The CKD-EPI eGFR was <90 ml/min/1.73m² in 49.1% and 30.6% of black and white patients, respectively (odds ratio (95% confidence interval) = 2.19 (1.28–3.75), p = 0.004). EGFRs were overall consistently associated with monocyte chemoattractant protein-1 and angiopoietin 2 concentrations in white patients, and with carotid intima-media thickness and plaque in black participants. Amongst black patients, plaque prevalence was 36.7% and the area under the curve (AUC) of the receiver operating characteristic (ROC) curve was not associated with plaque presence for the MDRD equation (p = 0.3), whereas the respective relationship was significant or borderline significant (p = 0.003 to 0.08) and of similar extent (p>0.1 for comparisons of AUC (SE)) for the other 8 equations. Based on optimal eGFR cutoff values with sensitivities and specificities ranging from 42 to 60% and 70 to 91% respectively, as determined in ROC curve analysis, a low eGFR increased the odds ratio for plaque 2.2 to 4.0 fold.

Conclusion

Reduced kidney function is independently associated with atherosclerosis and endothelial activation in black and white Africans with RA, respectively. CKD is highly prevalent in black Africans with RA. Apart from the MDRD, eGFR equations are useful in predicting carotid plaque presence, a coronary heart disease equivalent, amongst black African RA patients.     

Novel Multiple Markers to Distinguish Melanoma from Dysplastic Nevi

Background

Distinguishing melanoma from dysplastic nevi can be challenging.

Objective

To assess which putative molecular biomarkers can be optimally combined to aid in the clinical diagnosis of melanoma from dysplastic nevi.

Methods

Immunohistochemical expressions of 12 promising biomarkers (pAkt, Bim, BRG1, BRMS1, CTHRC1, Cul1, ING4, MCL1, NQO1, SKP2, SNF5 and SOX4) were studied in 122 melanomas and 33 dysplastic nevi on tissue microarrays. The expression difference between melanoma and dysplastic nevi was performed by univariate and multiple logistic regression analysis, diagnostic accuracy of single marker and optimal combinations were performed by receiver operating characteristic (ROC) curve and artificial neural network (ANN) analysis. Classification and regression tree (CART) was used to examine markers simultaneous optimizing the accuracy of melanoma. Ten-fold cross-validation was analyzed for estimating generalization error for classification.

Results

Four (Bim, BRG1, Cul1 and ING4) of 12 markers were significantly differentially expressed in melanoma compared with dysplastic nevi by both univariate and multiple logistic regression analysis (p < 0.01). These four combined markers achieved 94.3% sensitivity, 81.8% specificity and attained 84.3% area under the ROC curve (AUC) and the ANN classified accuracy with training of 83.2% and testing of 81.2% for distinguishing melanoma from dysplastic nevi. The classification trees identified ING4, Cul1 and BRG1 were the most important classification parameters in ranking top-performing biomarkers with cross-validation error of 0.03.

Conclusions

The multiple biomarkers ING4, Cul1, BRG1 and Bim described here can aid in the discrimination of melanoma from dysplastic nevi and provide a new insight to help clinicians recognize melanoma.     

Constructing Hypothetical Risk Data from the Area under the ROC Curve: Modelling Distributions of Polygenic Risk

Background

Modeling studies using hypothetical polygenic risk data can be an efficient tool for investigating the effectiveness of downstream applications such as targeting interventions to risk groups to justify whether empirical investigation is warranted. We investigated the assumptions underlying a method that simulates risk data for specific values of the area under the receiver operating characteristic curve (AUC).

Methods

The simulation method constructs risk data for a hypothetical population based on the population disease risk, and the odds ratios and frequencies of genetic variants. By systematically varying the parameters, we investigated under what conditions AUC values represent unique ROC curves with unique risk distributions for patients and nonpatients, and to what extend risk data can be simulated for precise values of the AUC.

Results

Using larger number of genetic variants each with a modest effect, we observed that the distributions of estimated risks of patients and nonpatients were similar for various combinations of the odds ratios and frequencies of the risk alleles. Simulated ROC curves overlapped empirical curves with the same AUC.

Conclusions

Polygenic risk data can be effectively and efficiently created using a simulation method. This allows to further investigate the potential applications of stratifying interventions on the basis of polygenic risk.     

Serum 25-hydroxyvitamin D is not related to cardiac natriuretic peptide in nulliparous and lactating women

Background

Visceral obesity is positively related to insulin resistance. The nature of the relationship between waist circumference and insulin resistance has not been known in Japanese populations. This study examined the relationship between waist circumference and insulin resistance and evaluated the optimal cutoff point for waist circumference in relation to insulin resistance in middle-aged Japanese men.

Methods

Study subjects included 4800 Japanese men aged 39 to 60 years. Insulin resistance was evaluated by the homeostasis model assessment of insulin resistance (HOMA-IR). The relationship of waist circumference with HOMA-IR was assessed by use of adjusted means of HOMA-IR and odds ratios of elevated HOMA-IR defined as the highest quintile (≥2.00). Receiver operating characteristics (ROC) curve analysis using Youden index and the area under curve (AUC) was employed to determine optimal cutoffs of waist circumference in relation to HOMA-IR.

Results

Adjusted geometric means of HOMA-IR and prevalence odds of elevated HOMA-IR were progressively higher with increasing levels of waist circumference. In the ROC curve analysis, the highest value of Youden index was obtained for a cutoff point of 85 cm in waist circumference across different values of HOMA-IR. Multiple logistic regression analysis also indicated that the AUC was consistently the largest for a waist circumference of 85 cm.

Conclusion

Waist circumference is linearly related to insulin resistance, and 85 cm in waist circumference is an optimal cutoff in predicting insulin resistance in middle-aged Japanese men.     

Central poststroke pain: somatosensory abnormalities and the presence of associated myofascial pain syndrome

Background

Mild cognitive impairment (MCI), defined as a transitional zone between normal cognition and dementia, requires a battery of formal neuropsychological tests administered by a trained rater for its diagnosis. The objective of this study was to develop a screening tool for MCI.

Methods

One hundred ninety seven cognitively normal controls (NC), one hundred sixteen patients with amnestic MCI ?Csingle domain (aMCI-sd), one hundred ninety five patients with amnestic MCI-multiple domain (aMCI-md), and two hundred twenty eight patients with mild Alzheimer??s disease (AD) were evaluated by comprehensive neuropsychological tests and by the Memory and Executive Screening (MES).

Results

Correlation analysis showed that the three indicators of the MES were significantly negatively related with age (P<0.05), yet not related with education (P>0.05). There was no ceiling or floor effect. Test completion averaged seven minutes (421.14±168.31 seconds). The receiver operating characteristics (ROC) analyses performed on the aMCI-sd group yielded 0.89 for the area under the curve (AUC) (95% CI, 0.85?C0.92) for the MES-total score, with sensitivity of 0.795 and specificity of 0.828. There was 81% correct classification rate when the cut-off was set at less than 75. Meanwhile, the aMCI-md group yielded 0.95 for the AUC (95% CI, 0.93?C0.97) for the MES-total score, with sensitivity of 0.87 and specificity of 0.91, and 90% correct classification rate when the cut-off was set at less than 72.

Conclusion

The MES, minimally time-consuming, may be a valid and easily administered cognitive screening tool with high sensitivity and specificity for aMCI, with single or multiple domain impairment.     

Not proper ROC curves as new tool for the analysis of differentially expressed genes in microarray experiments

Background  

Most microarray experiments are carried out with the purpose of identifying genes whose expression varies in relation with specific conditions or in response to environmental stimuli. In such studies, genes showing similar mean expression values between two or more groups are considered as not differentially expressed, even if hidden subclasses with different expression values may exist. In this paper we propose a new method for identifying differentially expressed genes, based on the area between the ROC curve and the rising diagonal (ABCR). ABCR represents a more general approach than the standard area under the ROC curve (AUC), because it can identify both proper (i.e., concave) and not proper ROC curves (NPRC). In particular, NPRC may correspond to those genes that tend to escape standard selection methods.     

Arrival Time Correction for Dynamic Susceptibility Contrast MR Permeability Imaging in Stroke Patients

Purpose

To determine if applying an arrival time correction (ATC) to dynamic susceptibility contrast (DSC) based permeability imaging will improve its ability to identify contrast leakage in stroke patients for whom the shape of the measured curve may be very different due to hypoperfusion.

Materials and Methods

A technique described in brain tumor patients was adapted to incorporate a correction for delayed contrast delivery due to perfusion deficits. This technique was applied to the MRIs of 9 stroke patients known to have blood-brain barrier (BBB) disruption on T1 post contrast imaging. Regions of BBB damage were compared with normal tissue from the contralateral hemisphere. Receiver operating characteristic (ROC) analysis was performed to compare the detection of BBB damage before and after ATC.

Results

ATC improved the area under the curve (AUC) of the ROC from 0.53 to 0.70. The sensitivity improved from 0.51 to 0.67 and the specificity improved from 0.57 to 0.66. Visual inspection of the ROC curve revealed that the performance of the uncorrected analysis was worse than random guess at some thresholds.

Conclusions

The ability of DSC permeability imaging to identify contrast enhancing tissue in stroke patients improved considerably when an ATC was applied. Using DSC permeability imaging in stroke patients without an ATC may lead to false identification of BBB disruption.     

Implication of Urinary Complement Factor H in the Progression of Immunoglobulin A Nephropathy

Background

After activation, the complement system is involved in the pathogenesis of Immunoglobulin A nephropathy (IgAN). Complement factor H (CFH) is a crucial inhibitory factor of the alternative pathway of the complement system. The study investigated the effects of urinary CFH levels on IgAN progression.

Methods

A total of 351patients with IgAN participated in this study. They were followed up for an average of 51.8±26.6 months. Renal outcome was defined as a composite endpoint, that included instances of end-stage renal disease (ESRD),≥ 50% decline in estimated glomerular filtration rate (eGFR) or doubling of plasma creatinine levels. Urinary CFH levels were measured by enzyme-linked immunosorbent assay and calculated as the ratio of urinary CFH over creatinine (uCFH/uCr).

Results

In the whole cohort, uCFH/uCr values were associated with disease progression either as continuous [log(uCFH/uCr)] or categorical traits (dichotomous and quartile variables) after adjusting for eGFR, proteinuria, mean arterial blood pressure, histological grading and immunosuppressive therapy in the Cox proportional hazard model. Kaplan-Meier analysis showed that higher uCFH/uCr values at baseline predicted worse renal outcome during follow-up (log-rank, P<0.001). Receiver operating characteristic curve (ROC) analysis showed that log(uCFH/uCr) had predictive value for renal outcome (area under curve [AUC]=0.745), and the AUC increased to 0.805 after being incorporated into baseline eGFR and proteinuria. In subgroup analysis with eGFR≥60 mL/min/1.73m², log(uCFH/uCr) had better predictive value (AUC= 0.724, P=0.002) for renal outcome compared to eGFR (AUC = 0.582, P=0.259) and proteinuria (AUC = 0.615, P=0.114).

Conclusions

Urinary CFH levels are associated with renal function decline and increased urinary CFH levels are a risk factor for progression of IgA nephropathy.     

On the analysis of glycomics mass spectrometry data via the regularized area under the ROC curve

Background  

Novel molecular and statistical methods are in rising demand for disease diagnosis and prognosis with the help of recent advanced biotechnology. High-resolution mass spectrometry (MS) is one of those biotechnologies that are highly promising to improve health outcome. Previous literatures have identified some proteomics biomarkers that can distinguish healthy patients from cancer patients using MS data. In this paper, an MS study is demonstrated which uses glycomics to identify ovarian cancer. Glycomics is the study of glycans and glycoproteins. The glycans on the proteins may deviate between a cancer cell and a normal cell and may be visible in the blood. High-resolution MS has been applied to measure relative abundances of potential glycan biomarkers in human serum. Multiple potential glycan biomarkers are measured in MS spectra. With the objection of maximizing the empirical area under the ROC curve (AUC), an analysis method was considered which combines potential glycan biomarkers for the diagnosis of cancer.