BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

133 related articles for article (PubMed ID: 36991336)

  • 1. External validation of the American prediction model for incident type 2 diabetes in the Iranian population.
    Asgari S; Khalili D; Azizi F; Hadaegh F
    BMC Med Res Methodol; 2023 Mar; 23(1):77. PubMed ID: 36991336
    [TBL] [Abstract][Full Text] [Related]  

  • 2. The external validity and performance of the no-laboratory American Diabetes Association screening tool for identifying undiagnosed type 2 diabetes among the Iranian population.
    Asgari S; Lotfaliany M; Fahimfar N; Hadaegh F; Azizi F; Khalili D
    Prim Care Diabetes; 2020 Dec; 14(6):672-677. PubMed ID: 32522438
    [TBL] [Abstract][Full Text] [Related]  

  • 3. External validation of the European risk assessment tool for chronic cardio-metabolic disorders in a Middle Eastern population.
    Asgari S; Moosaie F; Khalili D; Azizi F; Hadaegh F
    J Transl Med; 2020 Jul; 18(1):267. PubMed ID: 32615996
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Development and validation of a model for predicting incident type 2 diabetes using quantitative clinical data and a Bayesian logistic model: A nationwide cohort and modeling study.
    Wilkinson L; Yi N; Mehta T; Judd S; Garvey WT
    PLoS Med; 2020 Aug; 17(8):e1003232. PubMed ID: 32764746
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Performance of Stepwise Screening Methods in Identifying Individuals at High Risk of Type 2 Diabetes in an Iranian Population.
    Lotfaliany M; Hadaegh F; Mansournia MA; Azizi F; Oldenburg B; Khalili D
    Int J Health Policy Manag; 2022 Aug; 11(8):1391-1400. PubMed ID: 34060272
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Cut-off points of homeostasis model assessment of insulin resistance, beta-cell function, and fasting serum insulin to identify future type 2 diabetes: Tehran Lipid and Glucose Study.
    Ghasemi A; Tohidi M; Derakhshan A; Hasheminia M; Azizi F; Hadaegh F
    Acta Diabetol; 2015 Oct; 52(5):905-15. PubMed ID: 25794879
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Non-invasive Risk Prediction Models in Identifying Undiagnosed Type 2 Diabetes or Predicting Future Incident Cases in the Iranian Population.
    Lotfaliany M; Hadaegh F; Asgari S; Mansournia MA; Azizi F; Oldenburg B; Khalili D
    Arch Iran Med; 2019 Mar; 22(3):116-124. PubMed ID: 31029067
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Development and validation of QDiabetes-2018 risk prediction algorithm to estimate future risk of type 2 diabetes: cohort study.
    Hippisley-Cox J; Coupland C
    BMJ; 2017 Nov; 359():j5019. PubMed ID: 29158232
    [No Abstract]   [Full Text] [Related]  

  • 9. The product of fasting plasma glucose and triglycerides improves risk prediction of type 2 diabetes in middle-aged Koreans.
    Lee JW; Lim NK; Park HY
    BMC Endocr Disord; 2018 May; 18(1):33. PubMed ID: 29843706
    [TBL] [Abstract][Full Text] [Related]  

  • 10. The association of parity/live birth number with incident type 2 diabetes among women: over 15 years of follow-up in The Tehran Lipid and Glucose Study.
    Moazzeni SS; Hizomi Arani R; Asgari S; Azizi F; Hadaegh F
    BMC Womens Health; 2021 Oct; 21(1):378. PubMed ID: 34715851
    [TBL] [Abstract][Full Text] [Related]  

  • 11. The development and validation of the Portuguese risk score for detecting type 2 diabetes and impaired fasting glucose.
    Gray LJ; Barros H; Raposo L; Khunti K; Davies MJ; Santos AC
    Prim Care Diabetes; 2013 Apr; 7(1):11-8. PubMed ID: 23357741
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Lipid ratios and appropriate cut off values for prediction of diabetes: a cohort of Iranian men and women.
    Hadaegh F; Hatami M; Tohidi M; Sarbakhsh P; Saadat N; Azizi F
    Lipids Health Dis; 2010 Aug; 9():85. PubMed ID: 20712907
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Impaired fasting glucose cutoff value of 5.6 mmol/l combined with other cardiovascular risk markers is a better predictor for incident Type 2 diabetes than the 6.1 mmol/l value: Tehran lipid and glucose study.
    Harati H; Hadaegh F; Tohidi M; Azizi F
    Diabetes Res Clin Pract; 2009 Jul; 85(1):90-5. PubMed ID: 19414206
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Change in fasting plasma glucose and incident type 2 diabetes mellitus: results from a prospective cohort study.
    Mozaffary A; Asgari S; Tohidi M; Kazempour-Ardebili S; Azizi F; Hadaegh F
    BMJ Open; 2016 May; 6(5):e010889. PubMed ID: 27217283
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Weight change and risk of cardiovascular disease among adults with type 2 diabetes: more than 14 years of follow-up in the Tehran Lipid and Glucose Study.
    Moazzeni SS; Hizomi Arani R; Deravi N; Hasheminia M; Khalili D; Azizi F; Hadaegh F
    Cardiovasc Diabetol; 2021 Jul; 20(1):141. PubMed ID: 34253199
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A risk-score model for predicting risk of type 2 diabetes mellitus in a rural Chinese adult population: A cohort study with a 6-year follow-up.
    Zhang H; Wang C; Ren Y; Wang B; Yang X; Zhao Y; Han C; Zhou J; Zhang L; Qi M; Zhai Y; Pang C; Yin L; Zhao J; Hu D; Zhang M
    Diabetes Metab Res Rev; 2017 Oct; 33(7):. PubMed ID: 28608942
    [TBL] [Abstract][Full Text] [Related]  

  • 17. [Establishing a noninvasive prediction model for type 2 diabetes mellitus based on a rural Chinese population].
    Zhang HY; Shi WH; Zhang M; Yin L; Pang C; Feng TP; Zhang L; Ren YC; Wang BY; Yang XY; Zhou JM; Han CY; Zhao Y; Zhao JZ; Hu DS
    Zhonghua Yu Fang Yi Xue Za Zhi; 2016 May; 50(5):397-403. PubMed ID: 27141894
    [TBL] [Abstract][Full Text] [Related]  

  • 18. A simple risk score effectively predicted type 2 diabetes in Iranian adult population: population-based cohort study.
    Bozorgmanesh M; Hadaegh F; Ghaffari S; Harati H; Azizi F
    Eur J Public Health; 2011 Oct; 21(5):554-9. PubMed ID: 20534689
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Validating prediction scales of type 2 diabetes mellitus in Spain: the SPREDIA-2 population-based prospective cohort study protocol.
    Salinero-Fort MÁ; de Burgos-Lunar C; Mostaza Prieto J; Lahoz Rallo C; Abánades-Herranz JC; Gómez-Campelo P; Laguna Cuesta F; Estirado De Cabo E; García Iglesias F; González Alegre T; Fernández Puntero B; Montesano Sánchez L; Vicent López D; Cornejo Del Río V; Fernández García PJ; Sabín Rodríguez C; López López S; Patrón Barandío P;
    BMJ Open; 2015 Jul; 5(7):e007195. PubMed ID: 26220868
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Choosing the most appropriate existing type 2 diabetes risk assessment tool for use in the Philippines: a case-control study with an urban Filipino population.
    Agarwal G; Guingona MM; Gaber J; Angeles R; Rao S; Cristobal F
    BMC Public Health; 2019 Aug; 19(1):1169. PubMed ID: 31455247
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.