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Paper Information

Journal:   INTERNATIONAL JOURNAL OF ENDOCRINOLOGY AND METABOLISM (IJEM)   APRIL 2016 , Volume 14 , Number 2; Page(s) 0 To 0.
 
Paper: 

SURVIVAL REGRESSION MODELING STRATEGIES IN CVD PREDICTION

 
 
Author(s):  BARKHORDARI MAHNAZ, PADYAB MOJGAN, SARDARINIA MAHSA, HADAEGH FARZAD, AZIZI FEREIDOUN, BOZORGMANESH MOHAMMADREZA*
 
* PREVENTION OF METABOLIC DISORDERS RESEARCH CENTER, RESEARCH INSTITUTE FOR ENDOCRINE SCIENCES, SHAHID BEHESHTI UNIVERSITY OF MEDICAL SCIENCES, TEHRAN, I.R. IRAN
 
Abstract: 

Background: A fundamental part of prevention is prediction. Potential predictors are the sine qua non of prediction models. However, whether incorporating novel predictors to prediction models could be directly translated to added predictive value remains an area of dispute. The difference between the predictive power of a predictive model with (enhanced model) and without (baseline model) a certain predictor is generally regarded as an indicator of the predictive value added by that predictor. Indices such as discrimination and calibration have long been used in this regard. Recently, the use of added predictive value has been suggested while comparing the predictive performances of the predictive models with and without novel biomarkers.
Objectives: User-friendly statistical software capable of implementing novel statistical procedures is conspicuously lacking. This shortcoming has restricted implementation of such novel model assessment methods. We aimed to construct Stata commands to help researchers obtain the aforementioned statistical indices.
Materials and Methods: We have written Stata commands that are intended to help researchers obtain the following.1, Nam-D’Agostino X2 goodness of fit test; 2, Cut point-free and cut point-based net reclassification improvement index (NRI), relative absolute integrated discriminatory improvement index (IDI), and survival-based regression analyses. We applied the commands to real data on women participating in the Tehran lipid and glucose study (TLGS) to examine if information relating to a family history of premature cardiovascular disease (CVD), waist circumference, and fasting plasma glucose can improve predictive performance of Framingham’s general CVD risk algorithm.
Results: The command is adpredsurv for survival models.
Conclusions: Herein we have described the Stata package “adpredsurv” for calculation of the Nam-D’Agostino X2 goodness of fit test as well as cut point-free and cut point-based NRI, relative and absolute IDI, and survival-based regression analyses. We hope this work encourages the use of novel methods in examining predictive capacity of the emerging plethora of novel biomarkers.

 
Keyword(s): ADDED PREDICTIVE ABILITY, CALIBRATION, INTEGRATED DISCRIMINATION IMPROVEMENT, NET RECLASSIFICATION IMPROVEMENT, SOFTWARE, STATA
 
 
References: 
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Citations: 
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+ Click to Cite.
APA: Copy

BARKHORDARI, M., & PADYAB, M., & SARDARINIA, M., & HADAEGH, F., & AZIZI, F., & BOZORGMANESH, M. (2016). SURVIVAL REGRESSION MODELING STRATEGIES IN CVD PREDICTION. INTERNATIONAL JOURNAL OF ENDOCRINOLOGY AND METABOLISM (IJEM), 14(2), 0-0. https://www.sid.ir/en/journal/ViewPaper.aspx?id=511101



Vancouver: Copy

BARKHORDARI MAHNAZ, PADYAB MOJGAN, SARDARINIA MAHSA, HADAEGH FARZAD, AZIZI FEREIDOUN, BOZORGMANESH MOHAMMADREZA. SURVIVAL REGRESSION MODELING STRATEGIES IN CVD PREDICTION. INTERNATIONAL JOURNAL OF ENDOCRINOLOGY AND METABOLISM (IJEM). 2016 [cited 2021July27];14(2):0-0. Available from: https://www.sid.ir/en/journal/ViewPaper.aspx?id=511101



IEEE: Copy

BARKHORDARI, M., PADYAB, M., SARDARINIA, M., HADAEGH, F., AZIZI, F., BOZORGMANESH, M., 2016. SURVIVAL REGRESSION MODELING STRATEGIES IN CVD PREDICTION. INTERNATIONAL JOURNAL OF ENDOCRINOLOGY AND METABOLISM (IJEM), [online] 14(2), pp.0-0. Available: https://www.sid.ir/en/journal/ViewPaper.aspx?id=511101.



 
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