Tehran University of Medical Sciences

Science Communicator Platform

Stay connected! Follow us on X network (Twitter):
Share this content! On (X network) By
Causal Effects of Intensive Lifestyle and Metformin Interventions on Cardiovascular Disease Risk Factors in Pre-Diabetic People: An Application of G-Estimation Pubmed



Salimi Y1, 2 ; Fotouhi A1 ; Mohammad K1 ; Mansournia N3 ; Mansournia MA1
Authors
Show Affiliations
Authors Affiliations
  1. 1. Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
  2. 2. Department of Epidemiology and Biostatistics, School of Public Health, Kermanshah University of Medical Sciences, Kermanshah, Iran
  3. 3. Department of Endocrinology and Metabolism, AJA University of Medical Sciences, Tehran, Iran

Source: Archives of Iranian Medicine Published:2017


Abstract

Background: In the presence of non-adherence, intention-to-treat analysis preserves randomization, but does not lead to a valid comparison of outcome between the assigned groups. Using a reanalysisof Diabetes Prevention Program, this study aimed to estimate the causal effect of treatment with intensive lifestyle intervention or metformin vs. placebo on blood pressure and lipid profile using G-estimation after accounting for non-adherence. Methods: The Diabetes Prevention Program randomized 3,052 pre-diabetic individuals to metformin (N = 1015), placebo (N = 1014), or an intensive lifestyle intervention (N = 1023). G-estimation was used to estimate the causal effect of intensive lifestyle intervention or metformin vs. placebo on blood pressure and lipid profile in 2,973 patients who had adherence data. For comparison, we also performed the standard intention-to-treat analysis. Result: The G-estimation results showed that intensive lifestyle substantially improves systolic and diastolic blood pressure and lipid profile. The G-estimates of the effects of metformin vs. placebo as well as intensive lifestyle intervention vs. metformin on blood pressure and lipid profile were also stronger than the intention-to-treat effect estimates. Conclusion: G-estimation suggests that intensive lifestyle modification improves known risk factors for cardiovascular disease, including systolic blood pressure, diastolic blood pressure, triglyceride, and HDL levels more than what standard ITT analysis suggests. Adherence to the assigned treatment should be measured in all randomized trials, and G-estimation should be the standard analysis of randomized trialswith substantial non-adherence. © 2017, Academy of Medical Sciences of I.R. Iran. All rights reserved.
Related Docs
View other Related Docs
1. Protective Effect of Intensive Glucose Lowering Therapy on All-Cause Mortality, Adjusted for Treatment Switching Using G-Estimation Method, the Accord Trial, Scientific Reports (2023)
2. Handling Time Varying Confounding in Observational Research, BMJ (Online) (2017)
3. Estimating the Marginal Causal Effect and Potential Impact of Waterpipe Smoking on Risk of Multiple Sclerosis Using the Targeted Maximum Likelihood Estimation Method: A Large, Population-Based Incident Case-Control Study, American Journal of Epidemiology (2021)
4. The Implications of Using Lagged and Baseline Exposure Terms in Longitudinal Causal and Regression Models, American Journal of Epidemiology (2019)
5. Diabetes Risk and Provision of Diabetes Prevention Activities in 44 Low-Income and Middle-Income Countries: A Cross-Sectional Analysis of Nationally Representative, Individual-Level Survey Data, The Lancet Global Health (2023)
6. A Checklist for Statistical Assessment of Medical Papers (The Champ Statement): Explanation and Elaboration, British Journal of Sports Medicine (2021)
7. Standardization As a Tool for Causal Inference in Medical Research, Archives of Iranian Medicine (2016)
8. Estimating the Marginal Causal Effect of Fish Consumption During Adolescence on Multiple Sclerosis: A Population-Based Incident Case-Control Study, Neuroepidemiology (2018)
Experts (# of related papers)
View all Related Experts
Mohammad Ali Mansournia (38)
Saharnaz Nedjat (8)
Other Related Docs
9. Causal Methods for Observational Research: A Primer, Archives of Iranian Medicine (2018)
10. Time-To-Event Analysis for Sports Injury Research Part 1: Time-Varying Exposures, British Journal of Sports Medicine (2019)
11. Case–Control Matching: Effects, Misconceptions, and Recommendations, European Journal of Epidemiology (2018)
12. Longitudinal Causal Effect of Modified Creatinine Index on All-Cause Mortality in Patients With End-Stage Renal Disease: Accounting for Time-Varying Confounders Using G-Estimation, PLoS ONE (2022)
13. The Effect of Smoking on Latent Hazard Classes of Metabolic Syndrome Using Latent Class Causal Analysis Method in the Iranian Population, BMC Public Health (2023)
14. Accounting for Time-Varying Confounding in the Relationship Between Obesity and Coronary Heart Disease: Analysis With G-Estimation, American Journal of Epidemiology (2018)
15. Longitudinal Causal Effects of Normalized Protein Catabolic Rate on All-Cause Mortality in Patients With End-Stage Renal Disease: Adjusting for Time-Varying Confounders Using the G-Estimation Method, American Journal of Epidemiology (2021)
16. Does Weight Mediate the Effect of Smoking on Coronary Heart Disease? Parametric Mediational G-Formula Analysis, PLoS ONE (2022)
17. Longitudinal Effects of Lipid Indices on Incident Cardiovascular Diseases Adjusting for Time-Varying Confounding Using Marginal Structural Models: 25 Years Follow-Up of Two Us Cohort Studies, Global Epidemiology (2022)
18. Estimating Effect of Obesity on Stroke Using G-Estimation: The Aric Study, Obesity (2019)
19. Comparative Effectiveness Study in Multiple Sclerosis Patients Using Instrumental Variable Analysis, Archives of Iranian Medicine (2018)
20. Unsafe Injection Is Associated With Higher Hiv Testing After Bayesian Adjustment for Unmeasured Confounding, Archives of Iranian Medicine (2020)
21. To Adjust or Not to Adjust: The Role of Different Covariates in Cardiovascular Observational Studies, American Heart Journal (2021)
22. Methods Matter: Instrumental Variable Analysis May Be a Complementary Approach to Intention-To-Treat Analysis and As Treated Analysis When Analysing Data From Sports Injury Trials, British Journal of Sports Medicine (2021)
23. Worldwide Trends in Diabetes Since 1980: A Pooled Analysis of 751 Population-Based Studies With 4.4 Million Participants, The Lancet (2016)
24. Direct and Indirect Effects of Central and General Adiposity on Cardiovascular Diseases: The Tehran Lipid and Glucose Study, European Journal of Preventive Cardiology (2018)
25. Comparing Different Propensity Score Estimation Methods for Estimating the Marginal Causal Effect Through Standardization to Propensity Scores, Communications in Statistics: Simulation and Computation (2018)
26. Interaction Between Opium Use and Cigarette Smoking on Bladder Cancer: An Inverse Probability Weighting Approach Based on a Multicenter Case-Control Study in Iran, Global Epidemiology (2025)
27. The Effects of Smoking on Metabolic Syndrome and Its Components Using Causal Methods in the Iranian Population, International Journal of Preventive Medicine (2021)
28. Estimation of the Marginal Causal Risk Ratio in Survival Data Using Inverse Probability Treatment Weighting (Iptw), Iranian Journal of Epidemiology (2018)
29. Introduction to Computational Causal Inference Using Reproducible Stata, R, and Python Code: A Tutorial, Statistics in Medicine (2022)
30. Additive Interaction Between Dietary Inflammatory Index and Some Key Risk Factors of Multiple Sclerosis: A Population-Based Incident Case–Control Study, Nutritional Neuroscience (2023)
31. Risk Ratio Estimation in Longitudinal Studies, Archives of Iranian Medicine (2019)
32. Effect of Smoking on Breast Cancer by Adjusting for Smoking Misclassification Bias and Confounders Using a Probabilistic Bias Analysis Method, Clinical Epidemiology (2020)
33. The Causal Effect and Impact of Reproductive Factors on Breast Cancer Using Super Learner and Targeted Maximum Likelihood Estimation: A Case-Control Study in Fars Province, Iran, BMC Public Health (2021)
34. Comparison of Outcomes Between Off-Pump and On-Pump Coronary Artery Bypass Graft Surgery Using Collaborative Targeted Maximum Likelihood Estimation, Scientific Reports (2024)
35. Knowledge Gaps in Diabetes Research: An Evidence Mapping of the Literature, Journal of Diabetes and Metabolic Disorders (2022)
36. The Relation of Dietary Diversity Score and Food Insecurity to Metabolic Syndrome Features and Glucose Level Among Pre-Diabetes Subjects, Primary Care Diabetes (2018)
37. Causal Effect of Donor Source on Survival of Renal Transplantation Using Marginal Structural Models, Iranian Journal of Public Health (2018)
38. Population Attributable Fraction in Textbooks: Time to Revise, Global Epidemiology (2021)
39. Ideal Cardiovascular Health Metrics and Risk of Type 2 Diabetes: A Systematic Review and Dose-Response Meta-Analysis of Prospective Cohort Studies, Nutrition# Metabolism and Cardiovascular Diseases (2023)
40. Impact of Alcohol Consumption on Multiple Sclerosis Using Model-Based Standardization and Misclassification Adjustment Via Probabilistic Bias Analysis, Archives of Iranian Medicine (2023)
41. Factors Associated With Progression to Pre-Diabetes: A Recurrent Events Analysis, Eating and Weight Disorders (2020)
42. The French Maritime Pine Bark Extract Reduce Metabolic Syndrome Risk and Improve Body Composition in Obesity: A New Clinical Approach, Acta Medica Iranica (2018)
43. Errors in Causal Inference: An Organizational Schema for Systematic Error and Random Error, Annals of Epidemiology (2016)
44. Different Combinations of Glucose Tolerance and Blood Pressure Status and Incident Cardiovascular Disease and All-Cause Mortality Events, Journal of Human Hypertension (2017)
45. Global, Regional, and National Disability-Adjusted Life-Years (Dalys) for 359 Diseases and Injuries and Healthy Life Expectancy (Hale) for 195 Countries and Territories, 1990-2017: A Systematic Analysis for the Global Burden of Disease Study 2017, The Lancet (2018)
46. Biases in Randomized Trials, Epidemiology (2017)
47. Social, Economic, Technological, and Environmental Factors Affecting Cardiovascular Diseases: A Systematic Review and Thematic Analysis, International Journal of Preventive Medicine (2022)
48. The Dietary Acid Load Is Higher in Subjects With Prediabetes Who Are at Greater Risk of Diabetes: A Case-Control Study, Diabetology and Metabolic Syndrome (2019)
49. The Bias of Standard Methods in Estimating Causal Effect, Iranian Journal of Epidemiology (2017)
50. Prediabetes and Major Adverse Cardiac Events After Acute Coronary Syndrome: An Overestimated Concept, Clinical Cardiology (2024)