Non-randomized studies using causal-modelling may give different answers than RCTs: a meta-epidemiological study.
暂无分享,去创建一个
J. Ioannidis | L. Hemkens | H. Ewald | H. Bucher | Aviv Ladanie | K. M. Cord | Hannah Ewald | Kimberly A. Mc Cord
[1] J. Ioannidis,et al. Marginal structural models and other analyses allow multiple estimates of treatment effects in randomized clinical trials: Meta-epidemiological analysis. , 2019, Journal of clinical epidemiology.
[2] L. Hemkens. How Routinely Collected Data for Randomized Trials Provide Long-term Randomized Real-World Evidence. , 2018, JAMA network open.
[3] Correction notice to paper “Agreement of treatment effects for mortality from routinely collected data and subsequent randomized trials: meta-epidemiological survey” , 2018, British Medical Journal.
[4] J. Ioannidis,et al. Routinely collected data for randomized trials: promises, barriers, and implications , 2018, Trials.
[5] S. Goodman,et al. Using Design Thinking to Differentiate Useful From Misleading Evidence in Observational Research. , 2017, JAMA.
[6] Julian P T Higgins,et al. Biases in Randomized Trials: A Conversation Between Trialists and Epidemiologists. , 2017, Epidemiology.
[7] R. Lewis,et al. Confounding by Indication in Clinical Research. , 2016, JAMA.
[8] M. Hernán,et al. ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions , 2016, British Medical Journal.
[9] J. Ioannidis,et al. Agreement of treatment effects for mortality from routinely collected data and subsequent randomized trials: meta-epidemiological survey , 2016, British Medical Journal.
[10] K. Polkinghorne,et al. Intensive Hemodialysis and Mortality Risk in Australian and New Zealand Populations. , 2011, American journal of kidney diseases : the official journal of the National Kidney Foundation.
[11] Maria Laura Luchetta,et al. Deviation from intention to treat analysis in randomised trials and treatment effect estimates: meta-epidemiological study , 2015, BMJ : British Medical Journal.
[12] Robert D Gibbons,et al. Antidepressant treatment and suicide attempts and self‐inflicted injury in children and adolescents , 2015, Pharmacoepidemiology and drug safety.
[13] K. Lapane,et al. Application of marginal structural models in pharmacoepidemiologic studies: a systematic review , 2014, Pharmacoepidemiology and drug safety.
[14] L. Bero,et al. Healthcare outcomes assessed with observational study designs compared with those assessed in randomized trials. , 2014, The Cochrane database of systematic reviews.
[15] L. Trinquart,et al. Comparison of Treatment Effect Estimates From Prospective Nonrandomized Studies With Propensity Score Analysis and Randomized Controlled Trials of Surgical Procedures , 2014, Annals of surgery.
[16] Lilia R. Lukowsky,et al. Comparing mortality of peritoneal and hemodialysis patients in the first 2 years of dialysis therapy: a marginal structural model analysis. , 2013, Clinical journal of the American Society of Nephrology : CJASN.
[17] Roger Logan,et al. Observational data for comparative effectiveness research: An emulation of randomised trials of statins and primary prevention of coronary heart disease , 2013, Statistical methods in medical research.
[18] Y. Yazdanpanah,et al. Pharmacologic Boosting of Atazanavir in Maintenance HIV-1 Therapy: The COREYA Propensity-Score Adjusted Study , 2012, PloS one.
[19] K. Armstrong. Methods in comparative effectiveness research. , 2012, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.
[20] M. Bhandari,et al. Confounding: what is it and how do we deal with it? , 2012, Canadian journal of surgery. Journal canadien de chirurgie.
[21] M. Marshall,et al. Comparison of Outcomes by Modality for Critically Ill Patients Requiring Renal Replacement Therapy: A Single-Centre Cohort Study Adjusting for Time-Varying Illness Severity and Modality Exposure , 2012, Anaesthesia and intensive care.
[22] M. Hernán,et al. Beyond the intention-to-treat in comparative effectiveness research , 2012, Clinical trials.
[23] E. Porrini,et al. Renin-angiotensin system blockade and kidney transplantation: a longitudinal cohort study. , 2012, Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association.
[24] O. Kuss,et al. Treatments effects from randomized trials and propensity score analyses were similar in similar populations in an example from cardiac surgery. , 2011, Journal of clinical epidemiology.
[25] X. Basagaña,et al. Differences Between Marginal Structural Models and Conventional Models in Their Exposure Effect Estimates: A Systematic Review , 2011, Epidemiology.
[26] James M Robins,et al. When to Initiate Combined Antiretroviral Therapy to Reduce Mortality and AIDS-Defining Illness in HIV-Infected Persons in Developed Countries , 2011, Annals of Internal Medicine.
[27] Sherri Rose,et al. Implementation of G-computation on a simulated data set: demonstration of a causal inference technique. , 2011, American journal of epidemiology.
[28] Yi-Wen Chiu,et al. Similar outcomes with hemodialysis and peritoneal dialysis in patients with end-stage renal disease. , 2011, Archives of internal medicine.
[29] Michael Rosenblum,et al. Marginal Structural Models , 2011 .
[30] K. Polkinghorne,et al. Home hemodialysis and mortality risk in Australian and New Zealand populations. , 2011, American journal of kidney diseases : the official journal of the National Kidney Foundation.
[31] G. Heinze,et al. Mycophenolate Mofetil Use Is Associated With Prolonged Graft Survival After Kidney Transplantation , 2009, Transplantation.
[32] Antti Tanskanen,et al. 11-year follow-up of mortality in patients with schizophrenia: a population-based cohort study (FIN11 study) , 2009, The Lancet.
[33] Bryan R Luce,et al. Rethinking Randomized Clinical Trials for Comparative Effectiveness Research: The Need for Transformational Change , 2009, Annals of Internal Medicine.
[34] S. Knight,et al. Mycophenolate Mofetil Decreases Acute Rejection and may Improve Graft Survival in Renal Transplant Recipients When Compared with Azathioprine: A Systematic Review , 2009, Transplantation.
[35] Samy Suissa,et al. Traditional versus marginal structural models to estimate the effectiveness of β‐blocker use on mortality after myocardial infarction , 2009, Pharmacoepidemiology and drug safety.
[36] Tyler J. VanderWeele,et al. Marginal Structural Models for the Estimation of Direct and Indirect Effects , 2009, Epidemiology.
[37] R. Wolfe,et al. The survival advantage for haemodialysis patients taking vitamin D is questioned: findings from the Dialysis Outcomes and Practice Patterns Study. , 2008, Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association.
[38] G. Heinze,et al. Statin use is associated with prolonged survival of renal transplant recipients. , 2008, Journal of the American Society of Nephrology : JASN.
[39] Stephen R Cole,et al. Constructing inverse probability weights for marginal structural models. , 2008, American journal of epidemiology.
[40] E. Delaporte,et al. Long-term efficacy and tolerance of efavirenz- and nevirapine-containing regimens in adult HIV type 1 Senegalese patients. , 2008, AIDS research and human retroviruses.
[41] G. Guyatt,et al. GRADE: an emerging consensus on rating quality of evidence and strength of recommendations , 2008, BMJ : British Medical Journal.
[42] M. J. van der Laan,et al. Virologic efficacy of boosted double versus boosted single protease inhibitor therapy , 2007, AIDS.
[43] C. Roberts,et al. Suicidal behaviour in youths with depression treated with new-generation antidepressants: meta-analysis. , 2006, The British journal of psychiatry : the journal of mental science.
[44] J. Robins,et al. Estimating causal effects from epidemiological data , 2006, Journal of Epidemiology and Community Health.
[45] Jonathan AC Sterne,et al. Long-term effectiveness of potent antiretroviral therapy in preventing AIDS and death: a prospective cohort study , 2005, The Lancet.
[46] M. Hernán,et al. Activated injectable vitamin D and hemodialysis survival: a historical cohort study. , 2005, Journal of the American Society of Nephrology : JASN.
[47] James M. Robins,et al. Association, Causation, And Marginal Structural Models , 1999, Synthese.
[48] Douglas G Altman,et al. Statistical methods for assessing the influence of study characteristics on treatment effects in ‘meta‐epidemiological’ research , 2002, Statistics in medicine.
[49] S. Thompson,et al. Quantifying heterogeneity in a meta‐analysis , 2002, Statistics in medicine.
[50] J. Robins,et al. Marginal Structural Models to Estimate the Joint Causal Effect of Nonrandomized Treatments , 2001 .
[51] J. Robins,et al. Marginal structural models to estimate the causal effect of zidovudine on the survival of HIV-positive men. , 2000, Epidemiology.
[52] J. Robins,et al. Marginal Structural Models and Causal Inference in Epidemiology , 2000, Epidemiology.
[53] James M. Robins,et al. Marginal Structural Models versus Structural nested Models as Tools for Causal inference , 2000 .
[54] J. Robins,et al. Estimation of the Causal Effect of a Time-Varying Exposure on the Marginal Mean of a Repeated Binary Outcome , 1999 .
[55] H. Davies,et al. When can odds ratios mislead? , 1998, BMJ.
[56] J M Robins,et al. Correction for non-compliance in equivalence trials. , 1998, Statistics in medicine.
[57] J. Ioannidis,et al. A meta-analysis of the relative efficacy and toxicity of Pneumocystis carinii prophylactic regimens. , 1996, Archives of internal medicine.
[58] W. Richardson,et al. The well-built clinical question: a key to evidence-based decisions. , 1995, ACP journal club.