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decision curve

M Strijker, J W Chen, T H Mungroop, N B Jamieson, C H van Eijck, E W Steyerberg, J W Wilmink, B Groot Koerkamp, H W van Laarhoven, M G Besselink
BACKGROUND: As more therapeutic options for pancreatic cancer are becoming available, there is a need to improve outcome prediction to support shared decision-making. A systematic evaluation of prediction models in resectable pancreatic cancer is lacking. METHODS: This systematic review followed the CHARMS and PRISMA guidelines. PubMed, Embase and Cochrane Library databases were searched up to 11 October 2017. Studies reporting development or validation of models predicting survival in resectable pancreatic cancer were included...
February 13, 2019: British Journal of Surgery
Mora Maldonado, Ewan Dunbar, Emmanuel Chemla
Mouse tracking promises to be an efficient method to investigate the dynamics of cognitive processes: It is easier to deploy than eyetracking, yet in principle it is much more fine-grained than looking at response times. We investigated these claimed benefits directly, asking how the features of decision processes-notably, decision changes-might be captured in mouse movements. We ran two experiments, one in which we explicitly manipulated whether our stimuli triggered a flip in decision, and one in which we replicated more ecological, classical mouse-tracking results on linguistic negation (Dale & Duran, Cognitive Science, 35, 983-996, 2011)...
February 12, 2019: Behavior Research Methods
Hye Lim Park, Ie Ryung Yoo, Sun Ha Boo, Sonya Youngju Park, Jae Kil Park, Sook Whan Sung, Seok Whan Moon
PURPOSE: To evaluate the prognostic value of FDG PET/CT metabolic parameter compared to clinico-pathological risk factors in surgical margin-negative stage IA non-small cell lung cancer (NSCLC) patients. METHODS: 167 patients with consecutive FDG PET/CT scans from 2009 to 2015 performed for staging of NSCLC stage IA with plans for curative surgery were retrospectively reviewed. Maximum standardized uptake value (SUVmax) of primary tumor and mean SUV of liver were acquired from PET/CT...
February 13, 2019: Journal of Cancer Research and Clinical Oncology
Kundan Iqbal, Dennis W Lendrem, Ben Hargreaves, John D Isaacs, Ben Thompson, Arthur G Pratt
Objective: The diagnostic value added by musculoskeletal ultrasound (MSUS) over standard clinical and laboratory parameters has proved difficult to quantify. The additive contribution to diagnostic classification of a pragmatic, 15 min MSUS protocol was appraised in a large, unselected cohort of early arthritis clinic attendees. Methods: Detailed baseline characteristics were recorded. Semi-quantitative MSUS scoring of the most symptomatic wrist, second/third MCPs and PIPs and second/fifth MTPs was recorded, along with the sonographer's scan impression (definitely inflammatory, possibly inflammatory or non-inflammatory)...
February 8, 2019: Rheumatology
Rahul S Dalal, Mark T Osterman, Anna M Buchner, Amy Praestgaard, James D Lewis, Gary R Lichtenstein
Background: Many patients with ulcerative colitis (UC) fear the potential side effects of immunosuppressive therapies. However, those with medically refractory disease often require total proctocolectomy (TPC) with a permanent ostomy or pouch, which may reduce quality of life. Prior studies have identified TPC predictors; however, no clinically useful prognostic tools exist to guide shared therapeutic decision-making. We therefore sought to develop a prediction tool of future TPC risk in UC patients...
February 8, 2019: Inflammatory Bowel Diseases
Farzaneh Sajedi-Hosseini, Arash Malekian, Bahram Choubin, Omid Rahmati, Sabrina Cipullo, Frederic Coulon, Biswajeet Pradhan
This study aimed to develop a novel framework for risk assessment of nitrate groundwater contamination by integrating chemical and statistical analysis for an arid region. A standard method was applied for assessing the vulnerability of groundwater to nitrate pollution in Lenjanat plain, Iran. Nitrate concentration were collected from 102 wells of the plain and used to provide pollution occurrence and probability maps. Three machine learning models including boosted regression trees (BRT), multivariate discriminant analysis (MDA), and support vector machine (SVM) were used for the probability of groundwater pollution occurrence...
December 10, 2018: Science of the Total Environment
Wei Chen, Shuai Zhang, Renwei Li, Himan Shahabi
The main aim of the present study is to explore and compare three state-of-the art data mining techniques, best-first decision tree, random forest, and naïve Bayes tree, for landslide susceptibility assessment in the Longhai area of China. First, a landslide inventory map with 93 landslide locations was randomly divided, with 70% of the area used for training landslide models and 30% used for the validation process. A spatial database of 14 conditioning factors was constructed under a geographic information system environment...
December 10, 2018: Science of the Total Environment
Danielle Vuichard-Gysin, Dominik Mertz, Eleanor Pullenayegum, Pardeep Singh, Marek Smieja, Mark Loeb
Predictive models have been developed for influenza but have seldom been validated. Typically they have focused on patients meeting a definition of infection that includes fever. Less is known about how models perform when more symptoms are considered. We, therefore, aimed to create and internally validate predictive scores of acute respiratory infection (ARI) symptoms to diagnose influenza virus infection as confirmed by polymerase chain reaction (PCR) from respiratory specimens. Data from a completed trial to study the indirect effect of influenza immunization in Hutterite communities were randomly split into two independent groups for model derivation and validation...
2019: PloS One
Nigel P Murray, Sócrates Aedo, Eduardo Reyes, Cynthia Fuentealba, Omar Jacob
INTRODUCTION: The limitations of serumPSA as a screening test to detect prostate cancer remainproblematic, especially after an initial negative prostatebiopsy. Detection of primary circulating prostate cells(CPCs) has been reported to be useful in the detectionof prostate cancer in men with a serum PSA>4.0ng/ml.We present a prospective study comparing the detectionof CPCs, total PSA, percent free PSA, digital rectal examination(DRE) and prostate volumen (PV) to establisha predictive model for the detection of prostate cancerin men with an indication for a second prostate biopsy...
January 2019: Archivos Españoles de Urología
Bin-Bin Xu, Jun Lu, Zhi-Fang Zheng, Jian-Wei Xie, Jia-Bin Wang, Jian-Xian Lin, Qi-Yue Chen, Long-Long Cao, Mi Lin, Ru-Hong Tu, Ze-Ning Huang, Ju-Li Lin, Chao-Hui Zheng, Chang-Ming Huang, Ping Li
BACKGROUND: The definition and predictors of early recurrence (ER) for gastric cancer (GC) patients after radical gastrectomy are unclear. METHODS: A minimum-p value approach was used to evaluate the optimal cutoff value of recurrence-free survival to determine ER and late recurrence (LR). Receiver operating characteristic curves were generated for inflammatory indices. Potential risk factors for ER were assessed with a Cox regression model. A decision curve analysis was performed to evaluate the clinical utility...
February 9, 2019: Gastric Cancer
Shengqiang Chi, Xinhang Li, Yu Tian, Jun Li, Xiangxing Kong, Kefeng Ding, Chunhua Weng, Jingsong Li
The utility of a prediction model depends on its generalizability to patients drawn from different but related populations. We explored whether a semi-supervised learning model could improve the generalizability of colorectal cancer (CRC) risk prediction relative to supervised learning methods. Data on 113,141 patients diagnosed with nonmetastatic CRC from 2004 to 2012 were obtained from the Surveillance Epidemiology End Results registry for model development, and data on 1,149 patients from the Second Affiliated Hospital, Zhejiang University School of Medicine, who were diagnosed between 2004 and 2011, were collected for generalizability testing...
February 7, 2019: Journal of Biomedical Informatics
Chadarat Ampasavate, Wasimon Jutapakdee, Rungsinee Phongpradist, Singkome Tima, Adisak Tantiworawit, Pimlak Charoenkwan, Dujrudee Chinwong, Songyot Anuchapreeda
BACKGROUND: Overexpression of fms-like tyrosine kinase 3 (FLT3) protein in leukemia is highly related to poor prognosis and reduced survival rate in acute myeloid leukemia (AML) and acute lymphoblastic leukemia (ALL) patients. Simple but efficient quantification of FLT3 protein levels on the leukemic cell surface using flow cytometry had been developed for rapid determination of FLT3 on intact cell surface. METHODS: Quantitation protocol for FLT3 biomarker in clinical samples was developed and validated...
February 8, 2019: Journal of Clinical Laboratory Analysis
Kordo Saeed, Darius Cameron Wilson, Frank Bloos, Philipp Schuetz, Yuri van der Does, Olle Melander, Pierre Hausfater, Jacopo M Legramante, Yann-Erick Claessens, Deveendra Amin, Mari Rosenqvist, Graham White, Beat Mueller, Maarten Limper, Carlota Clemente Callejo, Antonella Brandi, Marc-Alexis Macchi, Nicholas Cortes, Alexander Kutz, Peter Patka, María Cecilia Yañez, Sergio Bernardini, Nathalie Beau, Matthew Dryden, Eric C M van Gorp, Marilena Minieri, Louisa Chan, Pleunie P M Rood, Juan Gonzalez Del Castillo
BACKGROUND: There is a lack of validated tools to assess potential disease progression and hospitalisation decisions in patients presenting to the emergency department (ED) with a suspected infection. This study aimed to identify suitable blood biomarkers (MR-proADM, PCT, lactate and CRP) or clinical scores (SIRS, SOFA, qSOFA, NEWS and CRB-65) to fulfil this unmet clinical need. METHODS: An observational derivation patient cohort validated by an independent secondary analysis across nine EDs...
February 8, 2019: Critical Care: the Official Journal of the Critical Care Forum
Chen-Ye Shao, Kai-Chao Liu, Chu-Ling Li, Zhuang-Zhuang Cong, Li-Wen Hu, Jing Luo, Yi-Fei Diao, Yang Xu, Sai-Guang Ji, Yong Qiang, Yi Shen
BACKGROUND: Anastomotic leakage (AL), a serious complication after esophagectomy, might impair patient quality of life, prolong hospital stay, and even lead to surgery-related death. The aim of this study was to show a novel decision model based on classification and regression tree (CART) analysis for the prediction of postoperative AL among patients who have undergone esophagectomy. METHODS: A total of 450 patients (training set: 356; test set: 94) with perioperative information were included...
February 7, 2019: Thoracic Cancer
Qiu-Xia Feng, Chang Liu, Liang Qi, Shu-Wen Sun, Yang Song, Guang Yang, Yu-Dong Zhang, Xi-Sheng Liu
PURPOSE: The aim of this study was to develop and validate a computational clinical decision support system (DSS) on the basis of CT radiomics features for the prediction of lymph node (LN) metastasis in gastric cancer (GC) using machine learning-based analysis. METHODS: Clinicopathologic and CT imaging data were retrospectively collected from 490 patients who were diagnosed with GC between January 2002 and December 2016. Radiomics features were extracted from venous-phase CT images...
February 4, 2019: Journal of the American College of Radiology: JACR
Mingchi Luo, Lifeng Li
BACKGROUND: Recently, some studies assessed the clinical utility of miniprobe endoscopic ultrasonography for prediction of invasion depth of early gastric cancer (GC). However, the results remain inconsistent. OBJECTIVES: We conducted a meta-analysis to assess the clinical utility of miniprobe endoscopic ultrasonography for diagnostic of invasion depth of early GC. METHODS: We systematically searched several online electronic databases including PubMed, China National Knowledge Infrastructure, Web of Science, Embase, and Wanfang from initial library to July 20, 2018, identifying the study about miniprobe endoscopic ultrasonography for diagnostic of invasion depth of early GC...
February 2019: Medicine (Baltimore)
A Machens, K Lorenz, H Dralle
BACKGROUND: It remains unclear when postoperative serum calcitonin levels should be measured in patients with medullary thyroid cancer (MTC) and, specifically, whether this decision should be based on the preoperative calcitonin level or nodal status. METHODS: A cohort of patients with previously untreated MTC was studied. Kaplan-Meier analyses, stratified by preoperative calcitonin level, nodal status and number of nodal metastases, were performed to determine time to calcitonin normalization after initial surgery, with statistical analysis by means of the log rank test...
February 6, 2019: British Journal of Surgery
Jianhua Liu, Chengzhi Huang, Junjiang Wang, Ling Huang, Shaojie Chen
Background/Aim: To construct quantitative prognostic models for colorectal cancer (CRC) based on COX-2/C-MET/KRAS expression status in clinical practice. Patients and Methods: Clinical factors and COX-2/C-MET/KRAS expression status of 578 eligible patients from two Chinese hospitals were included. The patients were randomly allocated into training and validation datasets. We created several models using Cox proportional hazard models: SignatureC contained clinical factors, SignatureG contained COX-2/C-MET/KRAS expression status, and SignatureCG contained both...
February 1, 2019: Saudi Journal of Gastroenterology: Official Journal of the Saudi Gastroenterology Association
Yong Zhang, Shi-Ming Shi, Hua Yang, Liu-Xiao Yang, Zheng Wang, Xue-Dong Li, Dan Yin, Ying-Hong Shi, Ya Cao, Zhi Dai, Jian Zhou, Qing Chen
Inflammation has a critical role in the development and progression of cancers. We developed a novel systemic inflammation score (SIS) based on lymphocyte, monocyte, and CA19-9 and explored its prognostic value in intrahepatic cholangiocarcinoma (ICC). From January 2005 to December 2011, 322 consecutive ICC patients who underwent curative resection in our center were included in this study, and validated in a retrospective study of 126 patients enrolled from 2012 to 2014. Clinicopathological variables including preoperative serum CA19-9 and LMR were analyzed...
2019: Journal of Cancer
Sangwoo Lee, Eun Kyung Choe, Boram Park
BACKGROUND: Machine learning (ML) is a promising methodology for classification and prediction applications in healthcare. However, this method has not been practically established for clinical data. Hyperuricemia is a biomarker of various chronic diseases. We aimed to predict uric acid status from basic healthcare checkup test results using several ML algorithms and to evaluate the performance. METHODS: We designed a prediction model for hyperuricemia using a comprehensive health checkup database designed by the classification of ML algorithms, such as discrimination analysis, K-nearest neighbor, naïve Bayes (NBC), support vector machine, decision tree, and random forest classification (RFC)...
February 2, 2019: Journal of Clinical Medicine
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