scholarly journals Circulating miRNA as Biomarkers for Colorectal Cancer Diagnosis and Liver Metastasis

Diagnostics ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 341
Author(s):  
Farah J. Nassar ◽  
Zahraa S. Msheik ◽  
Maha M. Itani ◽  
Remie El Helou ◽  
Ruba Hadla ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Liver Metastasis ◽  
Diagnostic Accuracy ◽  
Area Under The Curve ◽  
Stage Iv ◽  
Screening Tests ◽  
Operating Characteristics ◽  
Diagnostic Biomarkers ◽  
Circulating Mirna ◽  
Non Invasive

Colorectal cancer (CRC) is the second leading cause of cancer deaths worldwide. Stage IV CRC patients have poor prognosis with a five-year survival rate of 14%. Liver metastasis is the main cause of mortality in CRC patients. Since current screening tests have several drawbacks, effective stable non-invasive biomarkers such as microRNA (miRNA) are needed. We aim to investigate the expression of miRNA (miR-21, miR-19a, miR-23a, miR-29a, miR-145, miR-203, miR-155, miR-210, miR-31, and miR-345) in the plasma of 62 Lebanese Stage IV CRC patients and 44 healthy subjects using RT-qPCR, as well as to evaluate their potential for diagnosis of advanced CRC and its liver metastasis using the Receiver Operating Characteristics (ROC) curve. miR-21, miR-145, miR-203, miR-155, miR-210, miR-31, and miR-345 were significantly upregulated in the plasma of surgery naïve CRC patients when compared to healthy individuals. We identified two panels of miRNA that could be used for diagnosis of Stage IV CRC (miR-21 and miR-210) with an area under the curve (AUC) of 0.731 and diagnostic accuracy of 69% and liver metastasis (miR-210 and miR-203) with an AUC = 0.833 and diagnostic accuracy of 72%. Panels of specific circulating miRNA, which require further validation, could be potential non-invasive diagnostic biomarkers for CRC and liver metastasis.

scholarly journals Pentraxin 3 and the TyG Index as Two Novel Markers to Diagnose NAFLD in Children

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Xiaolin Ye ◽  
Jing Li ◽  
Hongyu Wang ◽  
Jie Wu
Keyword(s):  
Diagnostic Accuracy ◽  
Area Under The Curve ◽  
Diagnostic Value ◽  
Enzyme Linked Immunosorbent Assay ◽  
Healthy Children ◽  
Pentraxin 3 ◽  
Operating Characteristics ◽  
Diagnostic Biomarkers ◽  
Tyg Index ◽  
Receiver Operating Characteristics Curve

Background. The diagnosis of NAFLD requires a liver biopsy, which is difficult in children. This study explored the diagnostic value of pentraxin 3 (PTX-3) and the triglyceride-glucose (TyG) index for NAFLD in children. Methods. Sixty-eight children with NAFLD were selected as study subjects, and 68 healthy children enrolled during the same period served as controls. The TyG index was calculated, serum PTX-3 expression was detected by enzyme-linked immunosorbent assay, and the correlations between PTX-3 or the TyG index and clinical and biochemical indicators were analyzed. A receiver operating characteristics curve analysis and area under the curve (AUC) were used to evaluate diagnostic accuracy. Results. Serum PTX-3 level and the TyG index of the NAFLD patients were significantly higher than those of the healthy controls ( P < 0.001 ), which was closely related with the BMI, ALT, and insulin resistance. The AUC of PTX-3 for diagnosing NAFLD was 0.731 (95% confidence interval [CI] 0.646-0.806), and the AUC of the TyG index for diagnosing NAFLD was 0.765 (95% CI 0.682-0.835). The AUC of PTX-3, the TyG index, and ALT for the combined diagnosis of NAFLD was 0.964 (95% CI 0.916-0.989). Conclusion. PTX-3 and the TyG index are novel diagnostic biomarkers for NAFLD, as they effectively improved the diagnostic accuracy for NAFLD when combined with ALT.

scholarly journals Application of artificial intelligence in a real-world research for predicting the risk of liver metastasis in T1 colorectal cancer

2022 ◽  
Vol 22 (1) ◽  
Author(s):  
Tenghui Han ◽  
Jun Zhu ◽  
Xiaoping Chen ◽  
Rujie Chen ◽  
Yu Jiang ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Colorectal Cancer ◽  
Liver Metastasis ◽  
Predictive Model ◽  
Area Under The Curve ◽  
Predictive Ability ◽  
Subsequent Treatment ◽  
Training Dataset ◽  
Discriminative Ability ◽  
Fundamental Parameters

Abstract Background Liver is the most common metastatic site of colorectal cancer (CRC) and liver metastasis (LM) determines subsequent treatment as well as prognosis of patients, especially in T1 patients. T1 CRC patients with LM are recommended to adopt surgery and systematic treatments rather than endoscopic therapy alone. Nevertheless, there is still no effective model to predict the risk of LM in T1 CRC patients. Hence, we aim to construct an accurate predictive model and an easy-to-use tool clinically. Methods We integrated two independent CRC cohorts from Surveillance Epidemiology and End Results database (SEER, training dataset) and Xijing hospital (testing dataset). Artificial intelligence (AI) and machine learning (ML) methods were adopted to establish the predictive model. Results A total of 16,785 and 326 T1 CRC patients from SEER database and Xijing hospital were incorporated respectively into the study. Every single ML model demonstrated great predictive capability, with an area under the curve (AUC) close to 0.95 and a stacking bagging model displaying the best performance (AUC = 0.9631). Expectedly, the stacking model exhibited a favorable discriminative ability and precisely screened out all eight LM cases from 326 T1 patients in the outer validation cohort. In the subgroup analysis, the stacking model also demonstrated a splendid predictive ability for patients with tumor size ranging from one to50mm (AUC = 0.956). Conclusion We successfully established an innovative and convenient AI model for predicting LM in T1 CRC patients, which was further verified in the external dataset. Ultimately, we designed a novel and easy-to-use decision tree, which only incorporated four fundamental parameters and could be successfully applied in clinical practice.

scholarly journals The role of red cell distribution width in the differential diagnosis of iron deficiency anemia and non-transfusion dependent thalassemia patients

2018 ◽  
Vol 10 (3) ◽  
Author(s):  
Pokpong Piriyakhuntorn ◽  
Adisak Tantiworawit ◽  
Thanawat Rattanathammethee ◽  
Chatree Chai-Adisaksopha ◽  
Ekarat Rattarittamrong ◽  
...  
Keyword(s):  
Diagnostic Accuracy ◽  
Predictive Value ◽  
Area Under The Curve ◽  
Microcytic Anemia ◽  
Deficiency Anemia ◽  
Operating Characteristics ◽  
Training Set ◽  
Distribution Width ◽  
Validation Set ◽  
Sensitivity Specificity

This study aims to find the cut-off value and diagnostic accuracy of the use of RDW as initial investigation in enabling the differentiation between IDA and NTDT patients. Patients with microcytic anemia were enrolled in the training set and used to plot a receiving operating characteristics (ROC) curve to obtain the cut-off value of RDW. A second set of patients were included in the validation set and used to analyze the diagnostic accuracy. We recruited 94 IDA and 64 NTDT patients into the training set. The area under the curve of the ROC in the training set was 0.803. The best cut-off value of RDW in the diagnosis of NTDT was 21.0% with a sensitivity and specificity of 81.3% and 55.3% respectively. In the validation set, there were 34 IDA and 58 NTDT patients using the cut-off value of >21.0% to validate. The sensitivity, specificity, positive predictive value and negative predictive value were 84.5%, 70.6%, 83.1% and 72.7% respectively. We can therefore conclude that RDW >21.0% is useful in differentiating between IDA and NTDT patients with high diagnostic accuracy

scholarly journals PCN1 META-ANALYSIS OF THE DIAGNOSTIC ACCURACY OF SCREENING TESTS FOR COLORECTAL CANCER

2005 ◽  
Vol 8 (3) ◽  
pp. 343
Author(s):  
JC Slivinskas ◽  
YM Gagnon ◽  
AR Levy ◽  
RA Enns
Keyword(s):  
Colorectal Cancer ◽  
Diagnostic Accuracy ◽  
Meta Analysis ◽  
Screening Tests

Treatment monitoring of metastatic colorectal cancer by quantification and genotyping of mutated KRAS in circulating cell-free DNA.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e15037-e15037 ◽  
Author(s):  
Thomas Seufferlein ◽  
Daniel Schwerdel ◽  
Hanna Welz ◽  
Ralf Marienfeld ◽  
Stefan A. Schmidt ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Mutational Analysis ◽  
Early Stage ◽  
Therapy Monitoring ◽  
Stage Iv ◽  
Therapy Resistance ◽  
Disease Monitoring ◽  
Liquid Biopsies ◽  
Kras Mutations ◽  
Non Invasive

e15037 Background: Treatment of stage IV colorectal cancer (mCRC) has made substantial progress over the last years but therapy monitoring still is in its early stage. A facile, non-invasive, repeatable assessment of the mutational state of a given tumor even during treatment could constitute a desirable biomarker for therapy stratification and disease monitoring. "Liquid biopsies" analyzing circulating free and circulating tumor DNA (cfDNA/ctDNA) from patients’ blood have been proposed as a a simple, non-invasive method that could fulfil this requirement. Methods: 27 patients with histologically confirmed mCRC were enrolled into a treatment surveillance cohort. For the analysis of concordance between tumor tissue DNA and cfDNA we analyzed 40 tissue and blood pairs from therapy naïve patients regarding their KRAS mutation status. The course of cfDNA values combined with targeted genotyping of KRAS mutations were assessed during several palliative chemotherapeutic regimens. cfDNA data were correlated with clinical parameters to establish its prognostic and predictive value. Results: Baseline cfDNA levels allow to significantly differentiate mCRC from healthy controls (14.23 ± 6.33 ng/ml vs. 2.60 ± 1.59 ng/ml; p < 0.0001). cfDNA values at baseline in therapy naïve patients correlate well with tumor burden (p < 0.05) and CEA levels (p < 0.05). cfDNA values significantly increased upon disease progression during 1st (p < 0.01) and 2nd line (p < 0.05) treatment, enabling a non-invasive disease monitoring approach. Moreover, there was a significant correlation between the cfDNA levels upon treatment and progression-free survival (p < 0.05). In addition, our data show that KRAS genotyping of cfDNA under therapy is feasible (80% blood-tissue concordance) and might benefit the patient due to early detection of therapy resistance. Conclusions: Repetitive quantitative and mutational analysis of cfDNA is likely to complement current diagnostic standards in stage IV CRC over the whole continuum of treatment.

scholarly journals The salivary metatranscriptome as an accurate diagnostic indicator of oral cancer

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Guruduth Banavar ◽  
Oyetunji Ogundijo ◽  
Ryan Toma ◽  
Sathyapriya Rajagopal ◽  
Yen Kai Lim ◽  
...  
Keyword(s):  
Area Under The Curve ◽  
Average Risk ◽  
Operating Characteristics ◽  
Early Diagnostics ◽  
New Era ◽  
Oral Cancers ◽  
Non Invasive ◽  
Roc Area ◽  
Stage 1 ◽  
Invasive Diagnostics

AbstractDespite advances in cancer treatment, the 5-year mortality rate for oral cancers (OC) is 40%, mainly due to the lack of early diagnostics. To advance early diagnostics for high-risk and average-risk populations, we developed and evaluated machine-learning (ML) classifiers using metatranscriptomic data from saliva samples (n = 433) collected from oral premalignant disorders (OPMD), OC patients (n = 71) and normal controls (n = 171). Our diagnostic classifiers yielded a receiver operating characteristics (ROC) area under the curve (AUC) up to 0.9, sensitivity up to 83% (92.3% for stage 1 cancer) and specificity up to 97.9%. Our metatranscriptomic signature incorporates both taxonomic and functional microbiome features, and reveals a number of taxa and functional pathways associated with OC. We demonstrate the potential clinical utility of an AI/ML model for diagnosing OC early, opening a new era of non-invasive diagnostics, enabling early intervention and improved patient outcomes.

scholarly journals Performance of the Rowland Universal Dementia Assessment Scale for the Detection of Mild Cognitive Impairment and Dementia in a Diverse Cohort of Illiterate Persons From Rural Communities in Peru

2021 ◽  
Vol 12 ◽  
Author(s):  
Nilton Custodio ◽  
Rosa Montesinos ◽  
Monica M. Diaz ◽  
Eder Herrera-Perez ◽  
Kristhy Chavez ◽  
...  
Keyword(s):  
Rural Communities ◽  
Diagnostic Accuracy ◽  
Psychometric Properties ◽  
Gold Standard ◽  
Area Under The Curve ◽  
Assessment Scale ◽  
Screening Tools ◽  
Operating Characteristics ◽  
Clinical Dementia Rating ◽  
Optimal Cutoff

Background: The accurate diagnosis of neurocognitive disorders in illiterate Peruvian populations is challenging, largely owing to scarcity of brief cognitive screening tools (BCST) validated in these diverse populations. The Peruvian version of the Rowland Universal Dementia Assessment Scale (RUDAS-PE) is a BCST that relies minimally on educational attainment and has shown good diagnostic accuracy in an urban illiterate population in Peru, yet its psychometric properties in illiterate populations in rural settings of the country have not been previously investigated.Objectives: To establish the diagnostic accuracy of the RUDAS-PE compared to expert clinical diagnosis using the Clinical Dementia Rating (CDR) Scale in healthy and cognitively impaired illiterate persons living in two culturally and geographically distinct rural communities of Peru.Methods: A cross-sectional, population-based study of residents ≥ 50 years of age living in the Peruvian rural communities of Santa Clotilde and Chuquibambilla. A total of 129 subjects (76 from Santa Clotilde and 53 from Chuquibambilla) were included in this study. Gold standard diagnostic neurocognitive evaluation was based on expert neurological history and examination and administration of the CDR. Receiver operating characteristics, areas under the curve (AUC), and logistic regression analyses were conducted to determine the performance of RUDAS-PE compared to expert gold standard diagnosis.Results: Compared to gold standard diagnosis, the RUDAS-PE was better at correctly discriminating between MCI and dementia than discriminating between MCI and controls in both sites (97.0% vs. 76.2% correct classification in Chuquibambilla; 90.0% vs. 64.7% in Santa Clotilde). In Chuquibambilla, the area under the curve (AUC) of the RUDAS to discriminate between dementia and MCI was 99.4% (optimal cutoff at &lt;18), whereas between MCI and controls it was 82.8% (optimal cutoff at &lt;22). In Santa Clotilde, the area under the curve (AUC) of the RUDAS to discriminate between dementia and MCI was 99.1% (optimal cutoff at &lt;17), whereas between MCI and controls it was 75.5% (optimal cutoff at &lt;21).Conclusions: The RUDAS-PE has acceptable psychometric properties and performed well in its ability to discriminate MCI and dementia in two cohorts of illiterate older adults from two distinct rural Peruvian communities.

scholarly journals Prognostic Factors of Colorectal Cancer: A Comparative Study on Patients With or Without Liver Metastasis

2021 ◽  
Vol 11 ◽  
Author(s):  
Honghua Peng ◽  
Guifeng Liu ◽  
Ying Bao ◽  
Xi Zhang ◽  
Lehong Zhou ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Risk Factors ◽  
Risk Factor ◽  
Liver Metastasis ◽  
Adjuvant Therapy ◽  
Independent Risk Factor ◽  
Stage Iv ◽  
Genetic Alterations ◽  
Stage Ii ◽  
Independent Risk Factors

BackgroundRadical or palliative surgery with subsequent adjuvant therapy is the routine treatment for stage II/III colorectal cancer(CRC) and some stage IV CRC patients. This study aimed to clarify the prognostic clinicopathological and genetic factors for these patients.MethodsFifty-five stage II-IV CRC patients undergoing surgery and adjuvant therapy were recruited, including patients without liver metastasis(5 at stage II, 21 at stage III) and with liver metastasis(29 at stage IV). Genetic alterations of the primary cancer tissues were investigated by whole exome sequencing(WES). Patients were followed up to 1652 days(median at 788 days).ResultsThe mutational landscape of primary CRC tissue of patients with or without liver metastasis was largely similar, although the mutational frequency of TRIM77 and TCF7L2 was significantly higher in patients with liver metastasis. Several main driver gene co-mutations, such as TP53-APC, APC-KRAS, APC-FRG1, and exclusive mutations, such as TP53-CREBBP, were found in patients with liver metastasis, but not in patients without liver metastasis. No significant difference was found between the two groups in aberrant pathways. If stage II-IV patients were studied altogether, relapse status, SUPT20HL1 mutations, Amp27_21q22.3 and Del8_10q23.2 were independent risk factors(P&lt;0.05). If patients were divided into two groups by metastatic status, surgery types and Amp6_20q13.33 were independent risk factors for patients without liver metastasis(P&lt;0.05), while TRIM77 mutations were the only independent risk factor for patients with liver metastasis(P&lt;0.05).ConclusionsSurgery types and Amp6_20q13.33 were independent risk factors for CRC patients without liver metastasis, and TRIM77 mutations were the independent risk factor for CRC patients with liver metastasis.

Diagnostic Accuracy of the AzBio Speech Recognition in Noise Test

2021 ◽  
pp. 1-14
Author(s):  
Andrew J. Vermiglio ◽  
Lauren Leclerc ◽  
Meagan Thornton ◽  
Hannah Osborne ◽  
Elizabeth Bonilla ◽  
...  
Keyword(s):  
Steady State ◽  
Speech Recognition ◽  
Diagnostic Accuracy ◽  
Signal To Noise Ratio ◽  
Area Under The Curve ◽  
Self Report ◽  
Reference Standard ◽  
Operating Characteristics ◽  
Noise Test ◽  
Speech Recognition In Noise

Purpose The goal of this study was to determine the ability of the AzBio speech recognition in noise (SRN) test to distinguish between groups of participants with and without a self-reported SRN disorder and a self-reported signal-to-noise ratio (SNR) loss. Method Fifty-four native English-speaking young adults with normal pure-tone thresholds (≤ 25 dB HL, 0.25–6.0 kHz) participated. Individuals who reported hearing difficulty in a noisy restaurant (Reference Standard 1) were placed in the SRN disorder group. SNR loss groups were created based on the self-report of the ability to hear Hearing in Noise Test (HINT) sentences in steady-state speech-shaped noise, four-talker babble, and 20-talker babble in a controlled listening environment (Reference Standard 2). Participants with HINT thresholds poorer than or equal to the median were assigned to the SNR loss group. Results The area under the curve from the receiver operating characteristics curves revealed that the AzBio test was not a significant predictor of an SRN disorder, or an SNR loss using the steady-state noise Reference Standard 2 condition. However, the AzBio was a significant predictor of an SNR loss using the four-talker babble and 20-talker babble Reference Standard 2 conditions ( p < .05). The AzBio was a significant predictor of an SNR loss when using the average HINT thresholds across the three Reference Standard 2 masker conditions (area under the curve = .79, p = .001). Conclusions The AzBio test was not a significant predictor of a self-reported SRN disorder or a self-reported SNR loss in steady-state noise. However, it was a significant predictor of a self-reported SNR loss in babble noise and the average across all noise conditions. A battery of reference standard tests with a range of maskers in a controlled listening environment is recommended for diagnostic accuracy evaluations of SRN tests.

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