Biomarker Panel (biomarker + panel)

Distribution by Scientific Domains


Selected Abstracts


The Incremental Benefit of a Shortness-of-breath Biomarker Panel in Emergency Department Patients with Dyspnea

ACADEMIC EMERGENCY MEDICINE, Issue 6 2009
Adam J. Singer MD
Abstract Objectives:, The objective was to determine the incremental benefit of a shortness-of-breath (SOB) point-of-care biomarker panel on the diagnostic accuracy of emergency department (ED) patients presenting with dyspnea. Methods:, Adult ED patients at 10 U.S. EDs with SOB were included. The physician's estimates of the pretest clinical probability of heart failure (HF), acute myocardial infarction (MI), and pulmonary embolism (PE) were recorded using deciles (0%,100%). Blood samples were analyzed using a SOB point-of-care biomarker panel (troponin I, myoglobin, creatinine kinase-myocardial band isoenzyme [CK-MB], D-dimer, and B-type natriuretic peptide [BNP]). Thirty-day follow-up for MI, HF, and PE was performed. Data were analyzed using logistic regression and receiver operating characteristics (ROC) curve analysis. Results:, Of 301 patients, the mean (±standard deviation [SD]) age was 61 (±18) years; 56% were female, 58% were white, and 38% were African American. Diagnoses included MI (n = 54), HF (n = 91), and PE (n = 16) in a total of 129 (43%) of the patients. High pretest clinical certainty (,80%) identified 60 of these 129 (46.5%) cases. The SOB point-of-care biomarker panel identified 66 additional cases of MI (n = 24), HF (n = 31), and PE (n = 11). The overall adjusted sensitivity for any diagnosis was increased from 65% to 70% with the addition of the SOB point-of-care biomarker panel (difference = 5%, 95% CI = ,1.1% to 11%) while specificity was increased from 82% to 83% (difference = 1%, 95% CI = ,4% to 7%). The model containing pretest probability and the results of the SOB panel had an area under the curve (AUC) of 83.4% (95% CI = 78.4% to 88.5%), which was not significantly better than the AUC of 80.4% (95% CI = 75.1% to 85.7%) for clinical probability alone. Conclusions:, The addition of the SOB panel of markers did not improve the AUC for diagnosing the combined set of clinical conditions. Using the disease-specific SOB biomarkers increased the sensitivity on a disease-by-disease basis; however, specificity was reduced. [source]


Biomarker-assisted diagnosis of ovarian, cervical and pulmonary small cell carcinomas: the role of TTF-1, WT-1 and HPV analysis

HISTOPATHOLOGY, Issue 3 2007
J W Carlson
Aims:, Small cell carcinoma of the ovary, hypercalcaemic-type (SCCOH) is morphologically similar to small cell carcinomas from other sites. The aims of this study were to (i) determine if a biomarker panel would distinguish small cell carcinomas of the ovary, cervix (SCCCx) and lung (SCCLu) and (ii) potentially determine the histogenesis of SCCOH. Methods and results:, Nine ovarian small cell carcinomas (seven hypercalcaemic type; two pulmonary type), eight SCCCx and 22 SCCLu were immunostained for thyroid transcription factor (TTF)-1, WT-1, p16, cKIT and OCT3/4; a subset of cases were tested for human papillomavirus (HPV). WT-1 was diffusely positive in 6/7 SSCOH versus two of 33 other small cell carcinomas (P , 0.001). TTF-1 was diffusely positive in 20/22 SCCLu and 1/8 SCCCx, and negative in all SCCOH. p16 and cKIT demonstrated variable patterns of immunoreactivity in all cases. HPV was identified in 5/6 SCCCx; SCCOH and SCCLu were negative for HPV. Conclusions:, Combined staining with WT-1 and TTF-1 will distinguish SCCOH from SCCLu and SCCCx with a sensitivity of 86% and specificity of 97%. HPV is specific for tumours of cervical origin, but p16 immunohistochemistry is not useful for this purpose. The presence of diffuse WT-1 supports a Müllerian origin for SCCOH, whereas the absence of cKIT and OCT3/4 argues against a germ cell origin. [source]


Comparison of proteomic biomarker panels in urine and serum for ovarian cancer diagnosis

PROTEOMICS - CLINICAL APPLICATIONS, Issue 3 2010
Anette Lykke Petri
Abstract Purpose: The purposes of this study were to confirm previously found candidate epithelial ovarian cancer biomarkers in urine and to compare a paired serum biomarker panel and a urine biomarker panel from the same study cohort with regard to the receiver operating characteristic curve (ROC) area under the ROC curve (AUC) values. Experimental design: Four significant urine biomarkers were confirmed among 130 pelvic mass patients in the present study. The four biomarkers form a potential urine biomarker panel. From the same study cohort, the potential urine biomarker panel was compared to a serum biomarker panel, consisting of seven proteins/peptides, OvaRI. Results: Multivariate analysis of the urine panel demonstrated a significant differentiation (p<0.0001) between epithelial ovarian cancer patients and patients with benign ovarian pelvic masses. The ROC AUC of the urine panel was 0.84 and the ROC AUC of OvaRI was 0.83. Combining the urine panel with OvaRI demonstrated a significant contribution from both, for urine peaks, OR=2.12 and for OvaRI, OR=1.39; the ROC AUC of this model was 0.88. Conclusions and clinical relevance: We demonstrated that both urine and serum can be used individually or in combination to potentially aid in ovarian cancer diagnostics. Urine proteomic profiling could provide biomarkers for the non-invasive test required in clinical practice. [source]


The Incremental Benefit of a Shortness-of-breath Biomarker Panel in Emergency Department Patients with Dyspnea

ACADEMIC EMERGENCY MEDICINE, Issue 6 2009
Adam J. Singer MD
Abstract Objectives:, The objective was to determine the incremental benefit of a shortness-of-breath (SOB) point-of-care biomarker panel on the diagnostic accuracy of emergency department (ED) patients presenting with dyspnea. Methods:, Adult ED patients at 10 U.S. EDs with SOB were included. The physician's estimates of the pretest clinical probability of heart failure (HF), acute myocardial infarction (MI), and pulmonary embolism (PE) were recorded using deciles (0%,100%). Blood samples were analyzed using a SOB point-of-care biomarker panel (troponin I, myoglobin, creatinine kinase-myocardial band isoenzyme [CK-MB], D-dimer, and B-type natriuretic peptide [BNP]). Thirty-day follow-up for MI, HF, and PE was performed. Data were analyzed using logistic regression and receiver operating characteristics (ROC) curve analysis. Results:, Of 301 patients, the mean (±standard deviation [SD]) age was 61 (±18) years; 56% were female, 58% were white, and 38% were African American. Diagnoses included MI (n = 54), HF (n = 91), and PE (n = 16) in a total of 129 (43%) of the patients. High pretest clinical certainty (,80%) identified 60 of these 129 (46.5%) cases. The SOB point-of-care biomarker panel identified 66 additional cases of MI (n = 24), HF (n = 31), and PE (n = 11). The overall adjusted sensitivity for any diagnosis was increased from 65% to 70% with the addition of the SOB point-of-care biomarker panel (difference = 5%, 95% CI = ,1.1% to 11%) while specificity was increased from 82% to 83% (difference = 1%, 95% CI = ,4% to 7%). The model containing pretest probability and the results of the SOB panel had an area under the curve (AUC) of 83.4% (95% CI = 78.4% to 88.5%), which was not significantly better than the AUC of 80.4% (95% CI = 75.1% to 85.7%) for clinical probability alone. Conclusions:, The addition of the SOB panel of markers did not improve the AUC for diagnosing the combined set of clinical conditions. Using the disease-specific SOB biomarkers increased the sensitivity on a disease-by-disease basis; however, specificity was reduced. [source]


Comparison of proteomic biomarker panels in urine and serum for ovarian cancer diagnosis

PROTEOMICS - CLINICAL APPLICATIONS, Issue 3 2010
Anette Lykke Petri
Abstract Purpose: The purposes of this study were to confirm previously found candidate epithelial ovarian cancer biomarkers in urine and to compare a paired serum biomarker panel and a urine biomarker panel from the same study cohort with regard to the receiver operating characteristic curve (ROC) area under the ROC curve (AUC) values. Experimental design: Four significant urine biomarkers were confirmed among 130 pelvic mass patients in the present study. The four biomarkers form a potential urine biomarker panel. From the same study cohort, the potential urine biomarker panel was compared to a serum biomarker panel, consisting of seven proteins/peptides, OvaRI. Results: Multivariate analysis of the urine panel demonstrated a significant differentiation (p<0.0001) between epithelial ovarian cancer patients and patients with benign ovarian pelvic masses. The ROC AUC of the urine panel was 0.84 and the ROC AUC of OvaRI was 0.83. Combining the urine panel with OvaRI demonstrated a significant contribution from both, for urine peaks, OR=2.12 and for OvaRI, OR=1.39; the ROC AUC of this model was 0.88. Conclusions and clinical relevance: We demonstrated that both urine and serum can be used individually or in combination to potentially aid in ovarian cancer diagnostics. Urine proteomic profiling could provide biomarkers for the non-invasive test required in clinical practice. [source]


Differential Capture of Serum Proteins for Expression Profiling and Biomarker Discovery in Pre- and Posttreatment Head and Neck Cancer Samples,

THE LARYNGOSCOPE, Issue 1 2008
Gary L. Freed MD
Abstract Introduction: A long-term goal of our group is to develop proteomic-based approaches to the detection and use of protein biomarkers for improvement in diagnosis, prognosis, and tailoring of treatment for head and neck squamous cell cancer (HNSCC). We have previously demonstrated that protein expression profiling of serum can identify multiple protein biomarker events that can serve as molecular fingerprints for the assessment of HNSCC disease state and prognosis. Methods: An automated Bruker Daltonics (Billerica, MA) ClinProt matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometer was used. Magnetic chemical affinity beads were used to differentially capture serum proteins prior to MALDI-TOF analysis. The resulting spectra were analyzed using postprocessing software and a pattern recognition genetic algorithm (ClinProt 2.0). An HNSCC cohort of 48 sera samples from 24 patients consisting of matched pretreatment and 6 to 12 month posttreatment samples was used for further analysis. Low-mass differentially expressed peptides were identified using MALDI-TOF/TOF. Results: In the working mass range of 1,000 to 10,000 m/z, approximately 200 peaks were resolved for ionic bead capture approaches. For spectra generated from weak cation bead capture, a k-nearest neighbor genetic algorithm was able to correctly classify 94% normal from pretreatment HNSCC samples, 80% of pretreatment from posttreatment samples, and 87% of normal from posttreatment samples. These peptides were then analyzed by MALDI-TOF/TOF mass spectometry for sequence identification directly from serum processed with the same magnetic bead chemistry or alternatively after gel electrophoresis separation of the captured proteins. We were able to compare this with similar studies using surface-enhanced laser desorption ionization (SELDI)-TOF to show this method as a valid tool for this process with some improvement in the identification of our groups. Conclusions: This initial study using new high-resolution MALDI-TOF mass spectrometry coupled with bead fractionation is suitable for automated protein profiling and has the capability to simultaneously identify potential biomarker proteins for HNSCC. In addition, we were able to show improvement with the MALDI-TOF in identifying groups with HNSCC when compared with our prior data using SELDI-TOF. Using this MALDI-TOF technology as a discovery platform, we anticipate generating biomarker panels for use in more accurate prediction of prognosis and treatment efficacies for HNSCC. [source]