scholarly journals Interpretable Machine Learning Model for Locoregional Relapse Prediction in Oropharyngeal Cancers

Cancers ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 57
Author(s):  
Paul Giraud ◽  
Philippe Giraud ◽  
Eliot Nicolas ◽  
Pierre Boisselier ◽  
Marc Alfonsi ◽  
...  
Keyword(s):  
Operating Characteristic ◽  
Intraclass Correlation ◽  
Area Under The Curve ◽  
Good Precision ◽  
Locoregional Relapse ◽  
Machine Learning Model ◽  
Predictive Algorithms ◽  
Relapse Prediction ◽  
Hpv Status ◽  
Shapley Values

Background: There is no evidence to support surgery or radiotherapy as the best treatment for resectable oropharyngeal cancers with a negative HPV status. Predictive algorithms may help to decide which strategy to choose, but they will only be accepted by caregivers and European authorities if they are interpretable. As a proof of concept, we developed a predictive and interpretable algorithm to predict locoregional relapse at 18 months for oropharyngeal cancers as a first step towards that goal. Methods: The model was based on clinical and Pyradiomics features extracted from the dosimetric CT scan. Intraclass correlation was used to filter out features dependant on delineation. Correlated redundant features were also removed. An XGBoost model was cross-validated and optimised on the HN1 cohort (79 patients), and performances were assessed on the ART ORL cohort (45 patients). The Shapley Values were used to provide an overall and local explanation of the model. Results: On the ART ORL cohort, the model trained on HN1 yielded a precision—or predictive positive value—of 0.92, a recall of 0.42, an area under the curve of the receiver operating characteristic of 0.68 and an accuracy of 0.64. The most contributory features were shape Voxel Volume, grey level size zone matrix Small Area Emphasis (glszmSAE), gldm Dependence Non Uniformity Normalized (gldmDNUN), Sex and Age. Conclusions: We developed an interpretable and generalizable model that could yield a good precision—positive predictive value—for relapse at 18 months on a different test cohort.

scholarly journals A novel collagen area fraction index to quantitatively assess bowel fibrosis in patients with Crohn’s disease

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Xue-hua Li ◽  
Zhuang-nian Fang ◽  
Tian-ming Guan ◽  
Jin-jiang Lin ◽  
Can-hui Sun ◽  
...  
Keyword(s):  
Crohn’S Disease ◽  
Crohn's Disease ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Intraclass Correlation ◽  
Area Under The Curve ◽  
Area Fraction ◽  
Strongly Correlated ◽  
Fibrosis Score ◽  
High Repeatability

Abstract Background A validated histopathological tool to precisely evaluate bowel fibrosis in patients with Crohn’s disease is lacking. We attempted to establish a new index to quantify the severity of bowel fibrosis in patients with Crohn’s disease-associated fibrostenosis. Methods We analyzed the histopathological data of 31 patients with Crohn’s disease strictures undergoing surgical resection. The most representative sections of resected strictured segments were stained with Masson trichrome to manifest bowel fibrosis. The collagen area fraction and histological fibrosis score were simultaneously calculated for the same section to evaluate the severity of bowel fibrosis. Results Collagen area fraction strongly correlated with histological fibrosis scores (r = 0.733, P < 0.001). It showed a stronger correlation (r = 0.561, P < 0.001) with the degree of bowel strictures than the histological fibrosis score did (r = 0.468, P < 0.001). It was also shown to be more accurate for diagnosing Crohn’s disease strictures (area under the receiver operating characteristic curve = 0.815, P < 0.001) compared with the histological fibrosis score (area under the curve = 0.771, P < 0.001). High repeatability was observed for the collagen area fraction, with an intraclass correlation coefficient of 0.915 (P < 0.001). Conclusions Collagen area fraction is a simple and reliable index to quantify the severity of bowel fibrosis in patients with Crohn’s disease-associated fibrostenosis.

scholarly journals Accuracy of single-breath counting test to determine slow vital capacity in hospitalized patients

Revista CEFAC ◽  
2019 ◽  
Vol 21 (2) ◽  
Author(s):  
Anna Luiza Escóssio ◽  
Rodrigo Cappato de Araújo ◽  
Nicole Oliver ◽  
Emília Chagas Costa ◽  
José Ângelo Rizzo ◽  
...  
Keyword(s):  
Receiver Operating Characteristic ◽  
Correlation Coefficient ◽  
Intraclass Correlation Coefficient ◽  
Vital Capacity ◽  
Operating Characteristic ◽  
Intraclass Correlation ◽  
Area Under The Curve ◽  
Hospitalized Patients ◽  
Single Breath ◽  
Receiver Operating

ABSTRACT Purpose: to identify the accuracy of the single-breath counting test to determine slow vital capacity in hospitalized patients and to evaluate the repeatability of the same examiner. Methods: a diagnostic study and the choice of techniques were randomly assigned. The area under the curve (receiver operating characteristic) was calculated from the slow vital capacity (20ml/kg) to evaluate the best psychometric characteristics of single-breath counting Test for this cutoff point. Repeatability observed by the same examiner was assessed using the Intraclass Correlation Coefficient. Results: 516 patients hospitalized for various diseases were analyzed. In the curve analysis (receiver operating characteristic/slow vital capacity=20ml/Kg), the value of 21 in single-breath counting test with a sensitivity of 94.44% and specificity of 76.62% (area under the curve =0.93, p<0.005) was found. The intraclass correlation coefficient value for the single-breath counting test was 0.976 with p>0.005. Conclusion: the single-breath counting test was a valid and repetitive technique, and may be an important screening option for assessment of lung function in the absence of specific equipment. This technique opens perspectives to replace slow vital capacity measurement in hospitals, which lack spirometric equipment, or in patients who may have a contagious disease, which has a risk of contamination and spread of disease from one patient to another.

scholarly journals Physiologically Based Pharmacokinetic Modelling of Cabozantinib to Simulate Enterohepatic Recirculation, Drug–Drug Interaction with Rifampin and Liver Impairment

Pharmaceutics ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 778
Author(s):  
Bettina Gerner ◽  
Oliver Scherf-Clavel
Keyword(s):  
Hepatic Impairment ◽  
Kinase Inhibitor ◽  
Plasma Concentrations ◽  
Area Under The Curve ◽  
Enterohepatic Recirculation ◽  
Maximum Plasma ◽  
Good Precision ◽  
Physiologically Based Pharmacokinetic ◽  
Starting Point ◽  
Physiologically Based

Cabozantinib (CAB) is a receptor tyrosine kinase inhibitor approved for the treatment of several cancer types. Enterohepatic recirculation (EHC) of the substance is assumed but has not been further investigated yet. CAB is mainly metabolized via CYP3A4 and is susceptible for drug–drug interactions (DDI). The goal of this work was to develop a physiologically based pharmacokinetic (PBPK) model to investigate EHC, to simulate DDI with Rifampin and to simulate subjects with hepatic impairment. The model was established using PK-Sim® and six human clinical studies. The inclusion of an EHC process into the model led to the most accurate description of the pharmacokinetic behavior of CAB. The model was able to predict plasma concentrations with low bias and good precision. Ninety-seven percent of all simulated plasma concentrations fell within 2-fold of the corresponding concentration observed. Maximum plasma concentration (Cmax) and area under the curve (AUC) were predicted correctly (predicted/observed ratio of 0.9–1.2 for AUC and 0.8–1.1 for Cmax). DDI with Rifampin led to a reduction in predicted AUC by 77%. Several physiological parameters were adapted to simulate hepatic impairment correctly. This is the first CAB model used to simulate DDI with Rifampin and hepatic impairment including EHC, which can serve as a starting point for further simulations with regard to special populations.

scholarly journals Evaluation of alpha-l-fucosidase for the diagnosis of hepatocellular carcinoma based on meta-analysis

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Lei Xi ◽  
Chunqing Yang
Keyword(s):  
Hepatocellular Carcinoma ◽  
Operating Characteristic ◽  
Meta Analysis ◽  
Area Under The Curve ◽  
Diagnostic Odds Ratio ◽  
Diagnostic Value ◽  
Receiver Operating Characteristic Curves ◽  
Sensitivity Specificity ◽  
Review Manager

AbstractObjectivesThe main aim of the present study was to assess the diagnostic value of alpha-l-fucosidase (AFU) for hepatocellular carcinoma (HCC).MethodsStudies that explored the diagnostic value of AFU in HCC were searched in EMBASE, SCI, and PUBMED. The sensitivity, specificity, and DOR about the accuracy of serum AFU in the diagnosis of HCC were pooled. The methodological quality of each article was evaluated with QUADAS-2 (quality assessment for studies of diagnostic accuracy 2). Receiver operating characteristic curves (ROC) analysis was performed. Statistical analysis was conducted by using Review Manager 5 and Open Meta-analyst.ResultsEighteen studies were selected in this study. The pooled estimates for AFU vs. α-fetoprotein (AFP) in the diagnosis of HCC in 18 studies were as follows: sensitivity of 0.7352 (0.6827, 0.7818) vs. 0.7501 (0.6725, 0.8144), and specificity of 0.7681 (0.6946, 0.8283) vs. 0.8208 (0.7586, 0.8697), diagnostic odds ratio (DOR) of 7.974(5.302, 11.993) vs. 13.401 (8.359, 21.483), area under the curve (AUC) of 0.7968 vs. 0.8451, respectively.ConclusionsAFU is comparable to AFP for the diagnosis of HCC.

scholarly journals Statistical Assessment of Discrimination Capabilities of a Fractional Calculus Based Image Watermarking System for Gaussian Watermarks

Entropy ◽  
2021 ◽  
Vol 23 (2) ◽  
pp. 255
Author(s):  
Mario Gonzalez-Lee ◽  
Hector Vazquez-Leal ◽  
Luis J. Morales-Mendoza ◽  
Mariko Nakano-Miyatake ◽  
Hector Perez-Meana ◽  
...  
Keyword(s):  
Fractional Calculus ◽  
Roc Curve ◽  
Gaussian Noise ◽  
False Positive ◽  
Operating Characteristic ◽  
Image Watermarking ◽  
Area Under The Curve ◽  
Statistical Assessment ◽  
Watermarking Scheme ◽  
Fractional Equation

In this paper, we explore the advantages of a fractional calculus based watermarking system for detecting Gaussian watermarks. To reach this goal, we selected a typical watermarking scheme and replaced the detection equation set by another set of equations derived from fractional calculus principles; then, we carried out a statistical assessment of the performance of both schemes by analyzing the Receiver Operating Characteristic (ROC) curve and the False Positive Percentage (FPP) when they are used to detect Gaussian watermarks. The results show that the ROC of a fractional equation based scheme has 48.3% more Area Under the Curve (AUC) and a False Positives Percentage median of 0.2% whilst the selected typical watermarking scheme has 3%. In addition, the experimental results suggest that the target applications of fractional schemes for detecting Gaussian watermarks are as a semi-fragile image watermarking systems robust to Gaussian noise.

scholarly journals Cut-off points between pain intensities of the postoperative pain using receiver operating characteristic (ROC) curves

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Sooyoung Cho ◽  
Youn Jin Kim ◽  
Minjin Lee ◽  
Jae Hee Woo ◽  
Hyun Jung Lee
Keyword(s):  
Postoperative Pain ◽  
Receiver Operating Characteristic ◽  
Severe Pain ◽  
Operating Characteristic ◽  
Rating Scale ◽  
Intraclass Correlation ◽  
Pain Medication ◽  
Patient Specific ◽  
Moderate Pain ◽  
Receiver Operating

Abstract Background Pain assessment and management are important in postoperative circumstances as overdosing of opioids can induce respiratory depression and critical consequences. We aimed this study to check the reliability of commonly used pain scales in a postoperative setting among Korean adults. We also intended to determine cut-off points of pain scores between mild and moderate pain and between moderate and severe pain by which can help to decide to use pain medication. Methods A total of 180 adult patients undergoing elective non-cardiac surgery were included. Postoperative pain intensity was rated with a visual analog scale (VAS), numeric rating scale (NRS), faces pain scale revised (FPS-R), and verbal rating scale (VRS). The VRS rated pain according to four grades: none, mild, moderate, and severe. Pain assessments were performed twice: when the patients were alert enough to communicate after arrival at the postoperative care unit (PACU) and 30 min after arrival at the PACU. The levels of agreement among the scores were evaluated using intraclass correlation coefficients (ICCs). The cut-off points were determined by receiver operating characteristic curves. Results The ICCs among the VAS, NRS, and FPS-R were consistently high (0.839–0.945). The pain categories were as follow: mild ≦ 5.3 / moderate 5.4 ~ 7.1 /severe ≧ 7.2 in VAS, mild ≦ 5 / moderate 6 ~ 7 / severe ≧ 8 in NRS, mild ≦ 4 / moderate 6 / severe 8 and 10 in FPS-R. The cut-off points for analgesics request were VAS ≧ 5.5, NRS ≧ 6, FPS-R ≧ 6, and VRS ≧ 2 (moderate or severe pain). Conclusions During the immediate postoperative period, VAS, NRS, and FPS-R were well correlated. The boundary between mild and moderate pain was around five on 10-point scales, and it corresponded to the cut-off point of analgesic request. Healthcare providers should consider VRS and other patient-specific signs to avoid undertreatment of pain or overdosing of pain medication.

scholarly journals Snoring: a source of noise pollution and sleep apnea predictor

SLEEP ◽  
2019 ◽  
Vol 43 (6) ◽  
Author(s):  
Mudiaga Sowho ◽  
Francis Sgambati ◽  
Michelle Guzman ◽  
Hartmut Schneider ◽  
Alan Schwartz
Keyword(s):  
Sleep Apnea ◽  
Operating Characteristic ◽  
Area Under The Curve ◽  
Noise Pollution ◽  
Apnea Hypopnea Index ◽  
Sleep Study ◽  
Sound Levels ◽  
Obstructive Sleep ◽  
Single Night ◽  
The Relationship

Abstract Snoring is a highly prevalent condition associated with obstructive sleep apnea (OSA) and sleep disturbance in bed partners. Objective measurements of snoring in the community, however, are limited. The present study was designed to measure sound levels produced by self-reported habitual snorers in a single night. Snorers were excluded if they reported nocturnal gasping or had severe obesity (BMI &gt; 35 kg/m2). Sound was measured by a monitor mounted 65 cm over the head of the bed on an overnight sleep study. Snoring was defined as sound ≥40 dB(A) during flow limited inspirations. The apnea hypopnea index (AHI) and breath-by-breath peak decibel levels were measured. Snore breaths were tallied to determine the frequency and intensity of snoring. Regression models were used to determine the relationship between objective measures of snoring and OSA (AHI ≥ 5 events/h). The area under the curve (AUC) for the receiver operating characteristic (ROC) was used to predict OSA. Snoring intensity exceeded 45 dB(A) in 66% of the 162 participants studied, with 14% surpassing the 53 dB(A) threshold for noise pollution. Snoring intensity and frequency were independent predictors of OSA. AUCs for snoring intensity and frequency were 77% and 81%, respectively, and increased to 87% and 89%, respectively, with the addition of age and sex as predictors. Snoring represents a source of noise pollution in the bedroom and constitutes an important target for mitigating sound and its adverse effects on bed partners. Precise breath-by-breath identification and quantification of snoring also offers a way to risk stratify otherwise healthy snorers for OSA.

scholarly journals Soluble SIGLEC5: A New Prognosis Marker in Colorectal Cancer Patients

Cancers ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 3896
Author(s):  
Karla Montalbán-Hernández ◽  
Ramón Cantero-Cid ◽  
Roberto Lozano-Rodríguez ◽  
Alejandro Pascual-Iglesias ◽  
José Avendaño-Ortiz ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Operating Characteristic ◽  
Prognostic Markers ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Significant Heterogeneity ◽  
Kaplan Meier ◽  
Prognosis Marker ◽  
Colorectal Cancer Patients ◽  
Healthy Participants

Colorectal cancer (CRC) is the second most deadly and third most commonly diagnosed cancer worldwide. There is significant heterogeneity among patients with CRC, which hinders the search for a standard approach for the detection of this disease. Therefore, the identification of robust prognostic markers for patients with CRC represents an urgent clinical need. In search of such biomarkers, a total of 114 patients with colorectal cancer and 67 healthy participants were studied. Soluble SIGLEC5 (sSIGLEC5) levels were higher in plasma from patients with CRC compared with healthy volunteers. Additionally, sSIGLEC5 levels were higher in exitus than in survivors, and the receiver operating characteristic curve analysis revealed sSIGLEC5 to be an exitus predictor (area under the curve 0.853; cut-off > 412.6 ng/mL) in these patients. A Kaplan–Meier analysis showed that patients with high levels of sSIGLEC5 had significantly shorter overall survival (hazard ratio 15.68; 95% CI 4.571–53.81; p ≤ 0.0001) than those with lower sSIGLEC5 levels. Our study suggests that sSIGLEC5 is a soluble prognosis marker and exitus predictor in CRC.

scholarly journals Identification of an optimal prolactin threshold to determine prolactinoma size using receiver operating characteristic analysis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Bianca M. Leca ◽  
Maria Mytilinaiou ◽  
Marina Tsoli ◽  
Andreea Epure ◽  
Simon J. B. Aylwin ◽  
...  
Keyword(s):  
Receiver Operating Characteristic ◽  
Operating Characteristic ◽  
Tumour Size ◽  
Area Under The Curve ◽  
Serum Prolactin ◽  
Pituitary Neoplasms ◽  
Characteristic Analysis ◽  
Roc Curve Analysis ◽  
Baseline Serum ◽  
Receiver Operating

AbstractProlactinomas represent the most common type of secretory pituitary neoplasms, with a therapeutic management that varies considerably based on tumour size and degree of hyperprolactinemia. The aim of the current study was to evaluate the relationship between serum prolactin (PRL) concentrations and prolactinoma size, and to determine a cut-off PRL value that could differentiate micro- from macro-prolactinomas. A retrospective cohort study of 114 patients diagnosed with prolactinomas between 2007 and 2017 was conducted. All patients underwent gadolinium enhanced pituitary MRI and receiver operating characteristic (ROC) analyses were performed. 51.8% of patients in this study were men, with a mean age at the time of diagnosis of 42.32 ± 15.04 years. 48.2% of the total cohort were found to have microadenomas. Baseline serum PRL concentrations were strongly correlated to tumour dimension (r = 0.750, p = 0.001). When performing the ROC curve analysis, the area under the curve was 0.976, indicating an excellent accuracy of the diagnostic method. For a value of 204 μg/L (4338 mU/L), sensitivity and specificity were calculated at 0.932 and 0.891, respectively. When a cut off value of 204 μg/L (4338 mU/L) was used, specificity was 93.2%, and sensitivity 89.1%, acceptable to reliably differentiate between micro- and macro- adenomas.

scholarly journals Prediction of anemia at delivery

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Enav Yefet ◽  
Avishag Yossef ◽  
Zohar Nachum
Keyword(s):  
Risk Factors ◽  
Operating Characteristic ◽  
Complete Blood Count ◽  
Characteristic Curve ◽  
Secondary Analysis ◽  
Area Under The Curve ◽  
Iron Supplement ◽  
Independent Risk Factors ◽  
Operating Characteristic Curve ◽  
Study Database

AbstractWe aimed to assess risk factors for anemia at delivery by conducting a secondary analysis of a prospective cohort study database including 1527 women who delivered vaginally ≥ 36 gestational weeks. Anemia (Hemoglobin (Hb) < 10.5 g/dL) was assessed at delivery. A complete blood count results during pregnancy as well as maternal and obstetrical characteristics were collected. The primary endpoint was to determine the Hb cutoff between 24 and 30 gestational weeks that is predictive of anemia at delivery by using the area under the curve (AUC) of the receiver operating characteristic curve. Independent risk factors for anemia at delivery were assessed using stepwise multivariable logistic regression. Hb and infrequent iron supplement treatment were independent risk factors for anemia at delivery (OR 0.3 95%CI [0.2–0.4] and OR 2.4 95%CI [1.2–4.8], respectively; C statistics 83%). Hb 10.6 g/dL was an accurate cutoff to predict anemia at delivery (AUC 80% 95%CI 75–84%; sensitivity 75% and specificity 74%). Iron supplement was beneficial to prevent anemia regardless of Hb value. Altogether, Hb should be routinely tested between 24 and 30 gestational weeks to screen for anemia. A flow chart for anemia screening and treatment during pregnancy is proposed in the manuscript.Trial registration: ClinicalTrials.gov Identifier: NCT02434653.

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