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Calibration logistic regression

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https://www.readbyqxmd.com/read/29780627/a-new-approach-to-predict-lymph-node-metastasis-in-solid-lung-adenocarcinoma-a-radiomics-nomogram
#1
Xinguan Yang, Xiaohuan Pan, Hui Liu, Dashan Gao, Jianxing He, Wenhua Liang, Yubao Guan
Background: Lymph node metastasis (LNM) of lung cancer is an important factor related to survival and recurrence. The association between radiomics features of lung cancer and LNM remains unclear. We developed and validated a radiomics nomogram to predict LNM in solid lung adenocarcinoma. Methods: A total of 159 eligible patients with solid lung adenocarcinoma were divided into training (n=106) and validation cohorts (n=53). Radiomics features were extracted from venous-phase CT images...
April 2018: Journal of Thoracic Disease
https://www.readbyqxmd.com/read/29780255/predicting-initial-margin-status-in-breast-cancer-patients-during-breast-conserving-surgery
#2
Zihao Pan, Liling Zhu, Qian Li, Jianguo Lai, Jingwen Peng, Fengxi Su, Shunrong Li, Kai Chen
Background: We sought to develop and validate a model for prediction of initial margin status during breast-conserving surgery (BCS). Methods: We included eligible breast cancer patients receiving BCS in Sun Yat-sen Memorial Hospital from January 2003 to December 2014. All patients received intraoperative frozen-section analysis for initial margin assessment. We used univariate and multivariate logistic regression analyses to screen for predictors. A nomogram was developed in the training cohort (n=1,193) from the south branch of the hospital and externally validated in the validation cohort (n=499) from the north branch...
2018: OncoTargets and Therapy
https://www.readbyqxmd.com/read/29778349/a-contemporary-prostate-biopsy-risk-calculator-based-on-multiple-heterogeneous-cohorts
#3
Donna P Ankerst, Johanna Straubinger, Katharina Selig, Lourdes Guerrios, Amanda De Hoedt, Javier Hernandez, Michael A Liss, Robin J Leach, Stephen J Freedland, Michael W Kattan, Robert Nam, Alexander Haese, Francesco Montorsi, Stephen A Boorjian, Matthew R Cooperberg, Cedric Poyet, Emily Vertosick, Andrew J Vickers
BACKGROUND: Prostate cancer prediction tools provide quantitative guidance for doctor-patient decision-making regarding biopsy. The widely used online Prostate Cancer Prevention Trial Risk Calculator (PCPTRC) utilized data from the 1990s based on six-core biopsies and outdated grading systems. OBJECTIVE: We prospectively gathered data from men undergoing prostate biopsy in multiple diverse North American and European institutions participating in the Prostate Biopsy Collaborative Group (PBCG) in order to build a state-of-the-art risk prediction tool...
May 16, 2018: European Urology
https://www.readbyqxmd.com/read/29770763/a-radiomics-nomogram-for-preoperative-prediction-of-microvascular-invasion-risk-in-hepatitis-b-virus-related-hepatocellular-carcinoma
#4
Jie Peng, Jing Zhang, Qifan Zhang, Yikai Xu, Jie Zhou, Li Liu
PURPOSE: We aimed to develop and validate a radiomics nomogram for preoperative prediction of microvascular invasion (MVI) in hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC). METHODS: A total of 304 eligible patients with HCC were randomly divided into training (n=184) and independent validation (n=120) cohorts. Portal venous and arterial phase computed tomography data of the HCCs were collected to extract radiomic features. Using the least absolute shrinkage and selection operator algorithm, the training set was processed to reduce data dimensions, feature selection, and construction of a radiomics signature...
May 2018: Diagnostic and Interventional Radiology: Official Journal of the Turkish Society of Radiology
https://www.readbyqxmd.com/read/29763967/machine-learning-algorithms-for-outcome-prediction-in-chemo-radiotherapy-an-empirical-comparison-of-classifiers
#5
Timo M Deist, Frank J W M Dankers, Gilmer Valdes, Robin Wijsman, I-Chow Hsu, Cary Oberije, Tim Lustberg, Johan van Soest, Frank Hoebers, Arthur Jochems, Issam El Naqa, Leonard Wee, Olivier Morin, David R Raleigh, Wouter Bots, Johannes H Kaanders, José Belderbos, Margriet Kwint, Timothy Solberg, René Monshouwer, Johan Bussink, Andre Dekker, Philippe Lambin
PURPOSE: Machine learning classification algorithms (classifiers) for prediction of treatment response are becoming more popular in radiotherapy literature. General machine learning literature provides evidence in favor of some classifier families (random forest, support vector machine, gradient boosting) in terms of classification performance. The purpose of this study is to compare such classifiers specifically for (chemo)radiotherapy datasets and to estimate their average discriminative performance for radiation treatment outcome prediction...
May 15, 2018: Medical Physics
https://www.readbyqxmd.com/read/29742138/a-novel-early-risk-assessment-tool-for-detecting-clinical-outcomes-in-patients-with-heat-related-illness-j-erato-score-development-and-validation-in-independent-cohorts-in-japan
#6
Kei Hayashida, Yutaka Kondo, Toru Hifumi, Junya Shimazaki, Yasutaka Oda, Shinichiro Shiraishi, Tatsuma Fukuda, Junichi Sasaki, Keiki Shimizu
BACKGROUND: We sought to develop a novel risk assessment tool to predict the clinical outcomes after heat-related illness. METHODS: Prospective, multicenter observational study. Patients who transferred to emergency hospitals in Japan with heat-related illness were registered. The sample was divided into two parts: 60% to construct the score and 40% to validate it. A binary logistic regression model was used to predict hospital admission as a primary outcome. The resulting model was transformed into a scoring system...
2018: PloS One
https://www.readbyqxmd.com/read/29741602/statistical-primer-developing-and-validating-a-risk-prediction-model
#7
Stuart W Grant, Gary S Collins, Samer A M Nashef
A risk prediction model is a mathematical equation that uses patient risk factor data to estimate the probability of a patient experiencing a healthcare outcome. Risk prediction models are widely studied in the cardiothoracic surgical literature with most developed using logistic regression. For a risk prediction model to be useful, it must have adequate discrimination, calibration, face validity and clinical usefulness. A basic understanding of the advantages and potential limitations of risk prediction models is vital before applying them in clinical practice...
May 7, 2018: European Journal of Cardio-thoracic Surgery
https://www.readbyqxmd.com/read/29738542/microvascular-retinopathy-and-angiographically-demonstrated-coronary-artery-disease-a-cross-sectional-observational-study
#8
Lisa Cheng, Peter Barlis, Joel Gibson, Deb Colville, Anastasia Hutchinson, Geoff Gleeson, Ecosse Lamoureux, William VanGaal, Judy Savige
Epidemiological studies suggest retinal microvascular abnormalities predict cardiac events. This study examined microvascular features associated with coronary artery abnormalities. This was a single-centre, cross-sectional, observational study of 144 consecutive subjects undergoing coronary angiography for clinical indications. Their angiograms were deidentified and graded for disease (Leaman score, LAD stenosis ≥ 70%, number of vessels stenosed ≥ 70%), and Thrombolysis in Myocardial Infarction (TIMI) blush score...
2018: PloS One
https://www.readbyqxmd.com/read/29730620/predicting-risk-of-hospitalisation-a-retrospective-population-based-analysis-in-a-paediatric-population-in-emilia-romagna-italy
#9
Daniel Z Louis, Clara A Callahan, Mary Robeson, Mengdan Liu, Jacquelyn McRae, Joseph S Gonnella, Marco Lombardi, Vittorio Maio
OBJECTIVES: Develop predictive models for a paediatric population that provide information for paediatricians and health authorities to identify children at risk of hospitalisation for conditions that may be impacted through improved patient care. DESIGN: Retrospective healthcare utilisation analysis with multivariable logistic regression models. DATA: Demographic information linked with utilisation of health services in the years 2006-2014 was used to predict risk of hospitalisation or death in 2015 using a longitudinal administrative database of 527 458 children aged 1-13 years residing in the Regione Emilia-Romagna (RER), Italy, in 2014...
May 5, 2018: BMJ Open
https://www.readbyqxmd.com/read/29730071/predictive-factors-of-synchronous-colorectal-peritoneal-metastases-development-of-a-nomogram-and-study-of-its-utilities-using-decision-curve-analysis
#10
Shaobo Mo, Weixing Dai, Wenqiang Xiang, Qingguo Li, Renjie Wang, Guoxiang Cai
BACKGROUND: The objective of this study was to summarize the clinicopathological and molecular features of synchronous colorectal peritoneal metastases (CPM). We then combined clinical and pathological variables associated with synchronous CPM into a nomogram and confirmed its utilities using decision curve analysis. MATERIALS AND METHODS: Synchronous metastatic colorectal cancer (mCRC) patients who received primary tumor resection and underwent KRAS, NRAS, and BRAF gene mutation detection at our center from January 2014 to September 2015 were included in this retrospective study...
May 3, 2018: International Journal of Surgery
https://www.readbyqxmd.com/read/29727831/building-ct-radiomics-based-nomogram-for-preoperative-esophageal-cancer-patients-lymph-node-metastasis-prediction
#11
Chen Shen, Zhenyu Liu, Zhaoqi Wang, Jia Guo, Hongkai Zhang, Yingshu Wang, Jianjun Qin, Hailiang Li, Mengjie Fang, Zhenchao Tang, Yin Li, Jinrong Qu, Jie Tian
PURPOSE: To build and validate a radiomics-based nomogram for the prediction of pre-operation lymph node (LN) metastasis in esophageal cancer. PATIENTS AND METHODS: A total of 197 esophageal cancer patients were enrolled in this study, and their LN metastases have been pathologically confirmed. The data were collected from January 2016 to May 2016; patients in the first three months were set in the training cohort, and patients in April 2016 were set in the validation cohort...
May 1, 2018: Translational Oncology
https://www.readbyqxmd.com/read/29727787/predicting-umbilical-artery-ph-during-labour-development-and-validation-of-a-nomogram-using-fetal-heart-rate-patterns
#12
Rajeev Ramanah, Sikiyah Omar, Alicia Guillien, Aurore Pugin, Alain Martin, Didier Riethmuller, Nicolas Mottet
OBJECTIVE: Nomograms are statistical models that combine variables to obtain the most accurate and reliable prediction for a particular risk. Fetal heart rate (FHR) interpretation alone has been found to be poorly predictive for fetal acidosis while other clinical risk factors exist. The aim of this study was to create and validate a nomogram based on FHR patterns and relevant clinical parameters to provide a non-invasive individualized prediction of umbilical artery pH during labour...
April 16, 2018: European Journal of Obstetrics, Gynecology, and Reproductive Biology
https://www.readbyqxmd.com/read/29727784/a-risk-prediction-model-for-medical-treatment-failure-in-tubal-pregnancy
#13
Jae Hoon Lee, Sunghoon Kim, Inha Lee, Jisun Yun, Bo Hyon Yun, Young Sik Choi, Byung Seok Lee, Seok Kyo Seo
OBJECTIVE: Methotrexate is an alternative treatment for tubal pregnancy. However, despite initial treatment, ∼15% of women eventually require surgery. This study aimed to identify the risk factors for medical treatment failure in tubal pregnancy and apply them to a risk prediction model. STUDY DESIGN: This single-center retrospective cohort study included 123 participants initially treated medically for tubal pregnancy between January 2006 and December 2015. Logistic regression analysis was used to construct a risk prediction model (visually presented as a nomogram) for medical treatment failure...
April 20, 2018: European Journal of Obstetrics, Gynecology, and Reproductive Biology
https://www.readbyqxmd.com/read/29709069/predicting-suicide-attempts-in-adolescents-with-longitudinal-clinical-data-and-machine-learning
#14
Colin G Walsh, Jessica D Ribeiro, Joseph C Franklin
BACKGROUND: Adolescents have high rates of nonfatal suicide attempts, but clinically practical risk prediction remains a challenge. Screening can be time consuming to implement at scale, if it is done at all. Computational algorithms may predict suicide risk using only routinely collected clinical data. We used a machine learning approach validated on longitudinal clinical data in adults to address this challenge in adolescents. METHODS: This is a retrospective, longitudinal cohort study...
April 30, 2018: Journal of Child Psychology and Psychiatry, and Allied Disciplines
https://www.readbyqxmd.com/read/29691779/nomogram-and-validity-of-a-model-for-predicting-malnutrition-in-patients-on-liver-transplant-lists
#15
María Teresa García-Rodríguez, Sonia Pértega-Díaz, Beatriz López-Calviño, María Del Carmen Piñón-Villar, Alejandra Otero-Ferreiro, Francisco Suárez-López, Manuel Gómez-Gutiérrez, María Teresa Seoane-Pillado, Salvador Pita-Fernández
BACKGROUND: Malnutrition is associated with increased morbimortality in liver transplant patients, and it is important to identify factors related to nutritional status in these patients. AIMS: Determine variables associated with malnutrition and create a nomogram in liver transplant candidates. METHODS: Cross-sectional study (n = 110). VARIABLES: demographic variables, imbalances due to the disease, transplant aetiology and analytical parameters...
April 25, 2018: Digestive Diseases and Sciences
https://www.readbyqxmd.com/read/29690799/prediction-of-persistent-post-concussion-symptoms-following-mild-traumatic-brain-injury
#16
Maryse C Cnossen, Joukje van der Naalt, Jacoba M Spikman, Daan Nieboer, John K Yue, Ethan A Winkler, Geoffrey Manley, Nicole von Steinbuechel, Suzanne Polinder, Ewout W Steyerberg, Hester Lingsma
Persistent post-concussion symptoms (PPCS) occur frequently after mild traumatic brain injury (mTBI). The identification of patients at risk for poor outcome remains challenging since valid prediction models are missing. The objectives of the current study were to assess the quality and clinical value of prediction models for PPCS , and to develop a new model based on the synthesis of existing models and addition of complaints at emergency department (ED). MTBI patients (Glasgow Coma Scale score 13-15) were prospectively recruited from three Dutch level I trauma centers between 2013-2015 in the UPFRONT study...
April 25, 2018: Journal of Neurotrauma
https://www.readbyqxmd.com/read/29676063/development-and-internal-validation-of-a-side-specific-multiparametric-mri-based-nomogram-for-the-prediction-of-extracapsular-extension-of-prostate-cancer
#17
Alberto Martini, Akriti Gupta, Sara C Lewis, Shivaram Cumarasamy, Kenneth G Haines, Alberto Briganti, Francesco Montorsi, Ash K Tewari
OBJECTIVES: To develop a nomogram for predicting side-specific extracapsular extension (ECE) for planning nerve sparing radical prostatectomy (NSRP). MATERIALS AND METHODS: We retrospectively analyzed data from 561 patients who underwent robot-assisted radical prostatectomy between February 2014 and October 2015. To develop a side-specific predictive model, we considered the prostatic lobes separately. Four variables were included: PSA, highest ipsilateral biopsy Gleason grade, highest ipsilateral percentage core involvement and ECE on multiparametric MRI (mpMRI)...
April 19, 2018: BJU International
https://www.readbyqxmd.com/read/29673825/early-prediction-of-poor-outcome-despite-successful-recanalization-after-endovascular-treatment-for-anterior-large-vessel-occlusion-stroke
#18
Huaiming Wang, Meng Zhang, Yonggang Hao, Wenjie Zi, Dong Yang, Zhiming Zhou, Yu Geng, Zhen Wang, Hua Li, Gelin Xu, Graeme J Hankey, Yunyun Xiong, Xinfeng Liu
OBJECTIVE: Successful recanalization (SR) of the occluded artery does not always translate into a good outcome for patients with acute anterior circulation large-vessel occlusion stroke. This study aimed to develop a scale to predict poor outcome early despite SR after endovascular treatment (EVT) for candidates identified using current guidelines. METHODS: The eligible patients with SR were retrospectively enrolled between 2014 and 2016. Poor outcome was defined as modified Rankin Scale of 3 to 6 at 90 days...
April 16, 2018: World Neurosurgery
https://www.readbyqxmd.com/read/29663014/prediction-and-diagnosis-of-interval-metastasis-after-neoadjuvant-chemoradiotherapy-for-oesophageal-cancer-using-18-f-fdg-pet-ct
#19
Lucas Goense, Jelle P Ruurda, Brett W Carter, Penny Fang, Linus Ho, Gert J Meijer, Richard van Hillegersberg, Wayne L Hofstetter, Steven H Lin
OBJECTIVE: During neoadjuvant chemoradiotherapy for oesophageal cancer, or in the interval prior to surgery, some patients develop systemic metastasis. This study aimed to evaluate the diagnostic performance of 18 F-FDG PET/CT for the detection of interval metastasis and to identify predictors of interval metastases in a large cohort of oesophageal cancer patients. METHODS: In total, 783 consecutive patients with potentially resectable oesophageal cancer who underwent chemoradiotherapy and pre- and post-treatment 18 F-FDG PET/CT between 2006 and 2015 were analyzed from a prospectively maintained database...
April 16, 2018: European Journal of Nuclear Medicine and Molecular Imaging
https://www.readbyqxmd.com/read/29661918/characteristics-of-new-solid-nodules-detected-in-incidence-screening-rounds-of-low-dose-ct-lung-cancer-screening-the-nelson-study
#20
Joan E Walter, Marjolein A Heuvelmans, Geertruida H de Bock, Uraujh Yousaf-Khan, Harry J M Groen, Carlijn M van der Aalst, Kristiaan Nackaerts, Peter M A van Ooijen, Harry J de Koning, Rozemarijn Vliegenthart, Matthijs Oudkerk
PURPOSE: New nodules after baseline are regularly found in low-dose CT lung cancer screening and have a high lung cancer probability. It is unknown whether morphological and location characteristics can improve new nodule risk stratification by size. METHODS: Solid non-calcified nodules detected during incidence screening rounds of the randomised controlled Dutch-Belgian lung cancer screening (NELSON) trial and registered as new or previously below detection limit (15 mm3 ) were included...
April 16, 2018: Thorax
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