Nomogram for Predicting Pulmonary Hypertension in Patients without Pulmonary Embolism

Huang, Yanqi; Liang, Changhong; Liu, Zaiyi

doi:10.1148/radiol.2016152584

Cited by 5 publications

(8 citation statements)

References 6 publications

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“…Kazakhs in Xinjiang have unique regional characteristics and special diet and living habits, which cause differences in the risk factors of hypertension. Our previous results [ 11 ] found that among Kazakh herders in Xinjiang, the factors of age, smoking, alcohol consumption, salt consumption, family history of hypertension, prehypertension, abdominal circumference, BMI, total cholesterol, triacylglycerol, and high-density lipoprotein were related to the onset of hypertension. Unhealthy lifestyles such as smoking and high salt intake could increase the risk of hypertension among Kazakh herders in pastoral areas in Xinjiang.…”

Section: Discussionmentioning

confidence: 99%

“…Unhealthy lifestyles such as smoking and high salt intake could increase the risk of hypertension among Kazakh herders in pastoral areas in Xinjiang. [ 11 ] The dietary salt intake of most countries in the world is estimated to be 9 to 12 g/d. [ 29 ] However, the daily salt intake of the Kazakh population in the Nanshan pastoral area of Xinjiang was about 16.66 g, which is nearly 3 times the recommended salt intake of the WHO.…”

Section: Discussionmentioning

confidence: 99%

“…BMI and waist circumference were independent risk factors for the risk of hypertension in female and male herders, respectively. [ 11 ] Herders have long used animal fats to make various pastries and stir-fries. Few intake of fresh fruits and vegetables and excessive intake of high-fat diets such as bacon, bacon, yak-butter, etc, causes fat to accumulate in the body, accompanied by changes in serological indicators, such as abnormal blood lipids, which are importantly related to vascular diseases such as high blood pressure.…”

Section: Discussionmentioning

confidence: 99%

“…At present, the commonly used analysis methods for risk prediction include Logistic regression analysis, Cox regression, artificial neural network, multilevel model, linear mixed model, Joint model analysis method, nomogram, and support vector machine model. [ 10 , 11 ] Among these models, the nomogram model allows for personalized and evidence-based risk assessment, and has gradually become a reliable and convenient tool for quantifying risks. [ 12 ] Kim et al [ 13 ] constructed a hypertension prediction model based on the Korean population, in which the included variables were age, body mass index (BMI), stroke, and family history.…”

Section: Introductionmentioning

confidence: 99%

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Establishment and verification of a nomogram prediction model of hypertension risk in Xinjiang Kazakhs

Liu

Wang

et al. 2021

Medicine

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Hypertension is the main risk factor for cardiovascular and renal diseases. It is of great importance to develop effective risk prediction models to identify high-risk groups of hypertension. This study is to establish and verify a nomogram model for predicting the risk of hypertension among Kazakh herders in Xinjiang, China. This is a prospective cohort study. Totally, 5327 Kazakh herders from the Nanshan pastoral area of Xinjiang were enrolled. They were randomly divided into the modeling set of 3729 cases (70%) and the validation set of 1598 cases (30%). In the modeling set, univariate analysis, least absolute shrinkage and selection operator regression and multivariate Logistic regression were used to analyze the influencing factors of hypertension, and a nomogram prediction model was constructed. We then validated the model in the validation set, and evaluated the accuracy of the model using receiver operating characteristic and calibration curve. Based on univariate analysis, least absolute shrinkage and selection operator regression and multivariate logistic regression analysis, we identified 14 independent predictors of hypertension in the modeling set, including age, smoking, alcohol consumption, baseline body mass index, baseline diastolic blood pressure, baseline systolic blood pressure, daily salt intake, yak-butter intake, daily oil intake, fruit and vegetable intake, low-density lipoprotein, cholesterol, abdominal circumference, and family history. The area under the receiver operating characteristic curve of the modeling set and the verification set was 0.803 and 0.809, respectively. Moreover, the calibration curve showed a higher agreement between the nomogram prediction and the actual observation of hypertension. The risk prediction nomogram model has good predictive ability and could be used as an effective tool for the risk prediction of hypertension among Kazakh herders in Xinjiang.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Establishment and verification of a nomogram prediction model of hypertension risk in Xinjiang Kazakhs

Liu

Wang

et al. 2021

Medicine

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“…The present study aimed to determine whether LODDS could be utilized to predict the cancer-specific survival (CSS) or overall survival (OS) of patients with node-positive (N1/N2 classification) LNET using the Surveillance, Epidemiology, and End Results (SEER) database. Based on LODDS, the research intended to construct two visualized and online nomograms which are practical tools for clinical prediction used in many diseases (28)(29)(30)(31)(32). To facilitate clinical use, we also constructed two visualized and online nomograms for LNETs.…”

Section: Introductionmentioning

confidence: 99%

Construction and validation of nomograms based on the log odds of positive lymph nodes to predict the prognosis of lung neuroendocrine tumors

Wang

Wei

Guo³

et al. 2022

Front. Immunol.

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BackgroundThis research aimed to investigate the predictive performance of log odds of positive lymph nodes (LODDS) for the long-term prognosis of patients with node-positive lung neuroendocrine tumors (LNETs).MethodsWe collected 506 eligible patients with resected N1/N2 classification LNETs from the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2015. The study cohort was split into derivation cohort (n=300) and external validation cohort (n=206) based on different geographic regions. Nomograms were constructed based on the derivation cohort and validated using the external validation cohort to predict the 1-, 3-, and 5-year cancer-specific survival (CSS) and overall survival (OS) of patients with LNETs. The accuracy and clinical practicability of nomograms were tested by Harrell’s concordance index (C-index), integrated discrimination improvement (IDI), net reclassification improvement (NRI), calibration plots, and decision curve analyses.ResultsThe Cox proportional-hazards model showed the high LODDS group (-0.79≤LODDS) had significantly higher mortality compared to those in the low LODDS group (LODDS<-0.79) for both CSS and OS. In addition, age at diagnosis, sex, histotype, type of surgery, radiotherapy, and chemotherapy were also chosen as predictors in Cox regression analyses using stepwise Akaike information criterion method and included in the nomograms. The values of C-index, NRI, and IDI proved that the established nomograms were better than the conventional eighth edition of the TNM staging system. The calibration plots for predictions of the 1-, 3-, and 5-year CSS/OS were in excellent agreement. Decision curve analyses showed that the nomograms had value in terms of clinical application.ConclusionsWe created visualized nomograms for CSS and OS of LNET patients, facilitating clinicians to bring individually tailored risk assessment and therapy.

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Meta-research: How many diagnostic or prognostic models published in radiological journals are evaluated externally?

Hameed,

Yeung,

Boone

et al. 2023

Eur Radiol

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Objectives Prognostic and diagnostic models must work in their intended clinical setting, proven via “external evaluation”, preferably by authors uninvolved with model development. By systematic review, we determined the proportion of models published in high-impact radiological journals that are evaluated subsequently. Methods We hand-searched three radiological journals for multivariable diagnostic/prognostic models 2013–2015 inclusive, developed using regression. We assessed completeness of data presentation to allow subsequent external evaluation. We then searched literature to August 2022 to identify external evaluations of these index models. Results We identified 98 index studies (73 prognostic; 25 diagnostic) describing 145 models. Only 15 (15%) index studies presented an evaluation (two external). No model was updated. Only 20 (20%) studies presented a model equation. Just 7 (15%) studies developing Cox models presented a risk table, and just 4 (9%) presented the baseline hazard. Two (4%) studies developing non-Cox models presented the intercept. Just 20 (20%) articles presented a Kaplan–Meier curve of the final model. The 98 index studies attracted 4224 citations (including 559 self-citations), median 28 per study. We identified just six (6%) subsequent external evaluations of an index model, five of which were external evaluations by researchers uninvolved with model development, and from a different institution. Conclusions Very few prognostic or diagnostic models published in radiological literature are evaluated externally, suggesting wasted research effort and resources. Authors’ published models should present data sufficient to allow external evaluation by others. To achieve clinical utility, researchers should concentrate on model evaluation and updating rather than continual redevelopment. Clinical relevance statement The large majority of prognostic and diagnostic models published in high-impact radiological journals are never evaluated. It would be more efficient for researchers to evaluate existing models rather than practice continual redevelopment. Key Points • Systematic review of highly cited radiological literature identified few diagnostic or prognostic models that were evaluated subsequently by researchers uninvolved with the original model. • Published radiological models frequently omit important information necessary for others to perform an external evaluation: Only 20% of studies presented a model equation or nomogram. • A large proportion of research citing published models focuses on redevelopment and ignores evaluation and updating, which would be a more efficient use of research resources. Graphical abstract

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Nomogram for Predicting Pulmonary Hypertension in Patients without Pulmonary Embolism

Abstract: 327 the use of 18 F FPPRGD 2 PET as a tool to detect response to anti-angiogenesis treatment as early as 1 week after initiation of the therapeutic regimen.

Cited by 5 publications

References 6 publications

Establishment and verification of a nomogram prediction model of hypertension risk in Xinjiang Kazakhs

Establishment and verification of a nomogram prediction model of hypertension risk in Xinjiang Kazakhs

Construction and validation of nomograms based on the log odds of positive lymph nodes to predict the prognosis of lung neuroendocrine tumors

Meta-research: How many diagnostic or prognostic models published in radiological journals are evaluated externally?

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