Nature as a Trialist?: Deconstructing the Analogy between Mendelian Randomization and Randomized Trials

Epidemiology

Volumn 28, Issue 5, 2017, Pages 653-659

  Swanson, Sonja A ^a,b   Tiemeier, Henning ^a   Ikram, M Arfan ^a   Hernán, Miguel A ^b,c  

^a ERASMUS MEDICAL CENTER   (Netherlands)

^b HARVARD SCHOOL OF PUBLIC HEALTH   (United States)

^c MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; CLINICAL OUTCOME; GENETIC VARIABILITY; HUMAN; INTENTION TO TREAT ANALYSIS; MEASUREMENT ERROR; MENDELIAN RANDOMIZATION ANALYSIS; METHODOLOGY; PRIORITY JOURNAL; PROTOCOL COMPLIANCE; RANDOMIZED CONTROLLED TRIAL (TOPIC); COMPARATIVE STUDY; GENETIC VARIATION; PROCEDURES; TREATMENT OUTCOME;

GENETIC VARIATION; HUMANS; MENDELIAN RANDOMIZATION ANALYSIS; RANDOMIZED CONTROLLED TRIALS AS TOPIC; TREATMENT OUTCOME;

EID: 85020245258     PISSN: 10443983     EISSN: 15315487     Source Type: Journal    
DOI: 10.1097/EDE.0000000000000699     Document Type: Article

References (44)

1. Nitsch D, Molokhia M, Smeeth L, DeStavola BL, Whittaker JC, Leon DA. Limits to causal inference based on Mendelian randomization: a comparison with randomized controlled trials. Am J Epidemiol. 2006;163:397-403.
2. Burgess S, Thompson SG. Mendelian Randomization: Methods for Using Genetic Variants in Causal Estimation. Boca Raton, FL: Chapman & Hall/CRC Press; 2015.
3. Gidding SS, Daniels SR, Kavey RE; Expert Panel on Cardiovascular Health and Risk Reduction in Youth. Developing the 2011 Integrated Pediatric Guidelines for Cardiovascular Risk Reduction. Pediatrics. 2012;129:e1311-e1319.
4. Urbina EM, de Ferranti SD. Lipid screening in children and adolescents. JAMA. 2016;316:589-591.
5. Hernán MA, Hernández-Díaz S, Robins JM. Randomized trials analyzed as observational studies. Ann Intern Med. 2013;159:560-562.
6. Davey Smith G, Hemani G. Mendelian randomization: genetic anchors for causal inference in epidemiological studies. Hum Mol Genet. 2014;23:R89-R98.
7. VanderWeele TJ, Tchetgen Tchetgen EJ, Cornelis M, Kraft P. Methodological challenges in Mendelian randomization. Epidemiology. 2014;25:427-435.
8. Voight BF, Pritchard JK. Confounding from cryptic relatedness in casecontrol association studies. PLoS Genet. 2005;1:e32.
9. Boef AG, Dekkers OM, le Cessie S. Mendelian randomization studies: a review of the approaches used and the quality of reporting. Int J Epidemiol. 2015;44:496-511.
10. Hernán MA, Sauer BC, Hernández-Díaz S, Platt R, Shrier I. Specifying a target trial prevents immortal time bias and other self-inflicted injuries in observational analyses. J Clin Epidemiol. 2016;79:70-75.
11. Simon KC, Eberly S, Gao X, et al.; Parkinson Study Group. Mendelian randomization of serum urate and Parkinson disease progression. Ann Neurol. 2014;76:862-868.
12. Zhang G, Bacelis J, Lengyel C, et al. Assessing the causal relationship of maternal height on birth size and gestational age at birth: a Mendelian randomization analysis. PLoS Med. 2015;12:e1001865.
13. Lewis SJ, Araya R, Smith GD, et al. Smoking is associated with, but does not cause, depressed mood in pregnancy-a Mendelian randomization study. PLoS One. 2011;6:e21689.
14. Lawlor DA, Nordestgaard BG, Benn M, Zuccolo L, Tybjaerg-Hansen A, Davey Smith G. Exploring causal associations between alcohol and coronary heart disease risk factors: findings from a Mendelian randomization study in the Copenhagen General Population Study. Eur Heart J. 2013;34:2519-2528.
15. Boef AG, le Cessie S, Dekkers OM. Mendelian randomization studies in the elderly. Epidemiology. 2015;26:e15-e16.
16. Swanson SA, Robins JM, Miller M, Hernán MA. Selecting on treatment: a pervasive form of bias in instrumental variable analyses. Am J Epidemiol. 2015;181:191-197.
17. Swanson SA, Hernán MA. The challenging interpretation of instrumental variable estimates under monotonicity. Int J Epidemiol. 2017.
18. Hernán MA, Robins JM. Instruments for causal inference: an epidemiologist's dream Epidemiology. 2006;17:360-372.
19. Kivimäki M, Jokela M, Hamer M, et al. Examining overweight and obesity as risk factors for common mental disorders using fat mass and obesity-associated (FTO) genotype-instrumented analysis: The Whitehall II Study, 1985-2004. Am J Epidemiol. 2011;173:421-429.
20. Glymour MM, Tchetgen Tchetgen EJ, Robins JM. Credible Mendelian randomization studies: approaches for evaluating the instrumental variable assumptions. Am J Epidemiol. 2012;175:332-339.
21. Bjørngaard JH, Carslake D, Lund Nilsen TI, et al. Association of body mass index with depression, anxiety and suicide-an instrumental variable analysis of the HUNT Sstudy. PLoS One. 2015;10:e0131708.
22. Claussnitzer M, Dankel SN, Kim KH, et al. FTO obesity variant circuitry and adipocyte browning in humans. N Engl J Med. 2015;373:895-907.
23. Hernán MA, Hernández-Díaz S. Beyond the intention-to-treat in comparative effectiveness research. Clin Trials. 2012;9:48-55.
24. Swanson SA, Holme Ø, Løberg M, et al. Bounding the per-protocol effect in randomized trials: an application to colorectal cancer screening. Trials. 2015;16:541.
25. Robins JM. Correction for non-compliance in equivalence trials. Stat Med. 1998;17:269-302; discussion 387.
26. Robins JM. The analysis of randomized and nonrandomized AIDS treatment trials using a new approach to causal inference in longitudinal studies. In: Sechrest L, Freeman H, Mulley A, eds. Health Service Research Methodology: A Focus on AIDS. Washington, DC: US Public Health Service; 1989;113-159.
27. Swanson SA, Hernán MA. Commentary: how to report instrumental variable analyses (suggestions welcome). Epidemiology. 2013;24:370-374.
28. Swanson SA, Hernán MA. Think globally, act globally: an epidemiologist's perspective on instrumental variable estimation. Stat Sci. 2014;29:371-374.
29. Angrist JD, Imbens GW, Rubin DB. Identification of causal effects using instrumental variables. J Am Stat Assoc. 1996;91:444-455.
30. Balke A, Pearl J. Bounds on treatment effects for studies with imperfect compliance. J Am Stat Assoc. 1997;92:1171-1176.
31. Robins JM. Correcting for non-compliance in randomized trials using structural nested mean models. Comm Stat. 1994;23:2379-2412.
32. Burgess S, Bowden J, Fall T, Ingelsson E, Thompson SG. Sensitivity analyses for robust causal inference from Mendelian randomization analyses with multiple genetic variants. Epidemiology. 2017;28:30-42.
33. Katan MB. Apolipoprotein E isoforms, serum cholesterol, and cancer. Lancet. 1986;1:507-508.
34. Didelez V, Sheehan N. Mendelian randomization as an instrumental variable approach to causal inference. Stat Methods Med Res. 2007;16:309-330.
35. Davies NM, von Hinke Kessler Scholder S, Farbmacher H, Burgess S, Windmeijer F, Smith GD. The many weak instruments problem and Mendelian randomization. Stat Med. 2015;34:454-468.
36. Burgess S, Thompson SG. Bias in causal estimates from Mendelian randomization studies with weak instruments. Stat Med. 2011;30:1312-1323.
37. Bound J, Jaeger D, Baker R. Problems with instrumental variables estimation when the correlation between the instruments and the endogenous explanatory variable is weak. J Am Stat Assoc. 1995;90:443-450.
38. Hernán MA, Robins JM. Using big data to emulate a target trial when a randomized trial is not available. Am J Epidemiol. 2016;183:758-764.
39. Hernán MA. Does water kill A call for less casual causal inferences. Ann Epidemiol. 2016;26:674-680.
40. Kaufman JS. There is no virtue in vagueness: Comment on: causal identification: a charge of epidemiology in danger of marginalization by Sharon Schwartz, Nicolle M. Gatto, and Ulka B. Campbell. Ann Epidemiol. 2016;26:683-684.
41. Burgess S, Timpson NJ, Ebrahim S, Davey Smith G. Mendelian randomization: where are we now and where are we going Int J Epidemiol. 2015;44:379-388.
42. Swanson SA. Commentary: Can we see the forest for the IVs Mendelian randomization studies with multiple genetic variants. Epidemiology. 2017;28:43-46.
43. Jackson JW, Swanson SA. Toward a clearer portrayal of confounding bias in instrumental variable applications. Epidemiology. 2015;26:498-504.
44. Baiocchi M, Cheng J, Small DS. Instrumental variable methods for causal inference. Stat Med. 2014;33:2297-2340.