Biases in Randomized Trials: A Conversation Between Trialists and Epidemiologists
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Trialists and epidemiologists often employ different terminology to refer to biases in randomized trials and observational studies, even though many biases have a similar structure in both types of study. We use causal diagrams to represent the structure of biases, as described by Cochrane for randomized trials, and provide a translation to the usual epidemiologic terms of confounding, selection bias, and measurement bias. This structural approach clarifies that an explicit description of the inferential goal-the intention-to-treat effect or the per-protocol effect-is necessary to assess risk of bias in the estimates. Being aware of each other's terminologies will enhance communication between trialists and epidemiologists when considering key concepts and methods for causal inference.
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We label the domains using descriptions of the causes of bias addressed, avoiding terms used in the original RoB tool (such as 'selection bias' and 'performance bias') because they are used inconsistently or not known by many people outside Cochrane.
“We label the domains using descriptions of the causes of bias addressed, avoiding terms used in the original RoB tool (such as 'selection bias' and 'performance bias') because they are used inconsistently or not known by many people outside Cochrane. 16”
From RoB 2: a revised tool for assessing risk of bias in randomised trials (2019) · cites this paper as [16]
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Viguria, N., Navascués, A., Juanbeltz, R., Echeverría, A. E., Ezpeleta, C., & Castilla, J. (2021) · Human Vaccines & Immunotherapeutics · doi:10.1080/21645515.2020.1843336 · Cited by 32 · see citing works
Virtual reality exercise programs ameliorate frailty and fall risks in older adults: A meta‐analysis
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Endosseous Dental Implant Materials and Clinical Outcomes of Different Alloys: A Systematic Review
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Invited commentary: methodological issues in the design and analysis of randomised trials
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Self-citationPonsonby, A. (2020) · International Journal of Epidemiology · doi:10.1093/ije/dyaa174 · Cited by 25 · see citing works
Community Health Workers as Trust Builders and Healers: A Cohort Study in Primary Care
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Pourahmadi, M., Delavari, S., Hayden, J. A., Keshtkar, A., Ahmadi, M., Aletaha, A., Nazemipour, M., Mansournia, M. A., & Rubinstein, S. M. (2022) · British Journal of Sports Medicine · doi:10.1136/bjsports-2021-104926 · Cited by 28 · see citing works
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Self-citationErrors in causal inference: an organizational schema for systematic error and random error.
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Self-citationDoosti‐Irani, A., Tamtaji, O. R., Mansournia, M. A., Ghayour‐Mobarhan, M., Ferns, G. A., Kakhaki, R. D., Shahmirzadi, A. R., & Asemi, Z. (2019) · Clinical Neurology and Neurosurgery · doi:10.1016/j.clineuro.2019.105564 · Cited by 26 · see citing works
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More, S., Bambidis, V., Benford, D., Bragard, C., Hernandez-Jerez, A., Bennekou, S. H., Koutsoumanis, K. P., Machera, K., Naegeli, H., Nielsen, S., et al. (2020) · EFSA journal. European Food Safety Authority · doi:10.2903/j.efsa.2020.6221 · Cited by 20 · see citing works
Using Causal Diagrams for Biomedical Research
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Liu, Y., Kim, Y.-J., Park, C. W., Suvithayasiri, S., Jitpakdee, K., & Kim, J.-S. L. (2023) · Neurospine · doi:10.14245/ns.2346674.337 · Cited by 26 · see citing works
Tamtaji, O. R., Milajerdi, A., Reiner, Ž., Asemi, Z., Dadgostar, E., Heidari‐Soureshjani, R., Mamsharifi, P., Amirani, E., Mirzaei, H., Hallajzadeh, J., et al. (2020) · Complementary Therapies in Medicine · doi:10.1016/j.ctim.2020.102507 · Cited by 27 · see citing works
Auer, J., Krotka, P., Reichardt, B., Traxler, D., Wendt, R. T., Mildner, M., Ankersmit, H. J., & Graf, A. C. (2024) · European Journal of Cardio-Thoracic Surgery · doi:10.1093/ejcts/ezae214 · Cited by 25 · see citing works
Interaction Contrasts and Collider Bias
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Moura, C., Totton, S. C., Sargeant, J. M., O’Sullivan, T. L., Linhares, D. C. L., & O'Connor, A. M. C. (2019) · Journal of Swine Health and Production · doi:10.54846/jshap/1125 · Cited by 21 · see citing works
Nabeel, A., Al-Sabah, S. K., & Ashrafian, H. (2021) · Surgical Endoscopy · doi:10.1007/s00464-021-08519-6 · Cited by 23 · see citing works
Chang, P., Chen, K.-H., Jhou, H., Lee, C., Chou, S., Chen, P., & Chang, T. (2022) · Journal of Personalized Medicine · doi:10.3390/jpm12040512 · Cited by 24 · see citing works
Benbow, J. H., Rivera, D. R. R., Lund, J. L., Feldman, J., & Kim, E. S. (2022) · American Society of Clinical Oncology Educational Book · doi:10.1200/edbk_350574 · Cited by 23 · see citing works
Bernard, J. Y., Pan, H., Aris, I. M., Moreno‐Betancur, M., Soh, S., Yap, F. K. P., Tan, K. H., Shek, L. P., Chong, Y. S., Gluckman, P. D., et al. (2018) · American Journal of Clinical Nutrition · doi:10.1093/ajcn/nqy079 · Cited by 23 · see citing works
Dawidowski, B., Grelecki, G., Biłgorajski, A., Podwalski, P., Misiak, B., & Samochowiec, J. (2021) · Journal of Clinical Medicine · doi:10.3390/jcm11010232 · Cited by 22 · see citing works
Time-fixed vs time-varying causal diagrams for immortal time bias
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Self-citationInvited Commentary: Dealing With the Inevitable Deficiencies of Bias Analysis—and All Analyses
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Grubic, N., Johnston, A., Randhawa, V. K., Humphries, K. H., Rosella, L. C., & Maximova, K. (2024) · Canadian Journal of Cardiology · doi:10.1016/j.cjca.2024.12.022 · Cited by 20 · see citing works
Higson‐Sweeney, N., Mikkola, A., Smith, L., Shafique, J., Draper, L., Cooper, K., Dunn, B. D., & Loades, M. E. (2022) · Journal of Psychosomatic Research · doi:10.1016/j.jpsychores.2022.111070 · Cited by 20 · see citing works
Ewald, H., Ioannidis, J. P. A., Ladanie, A., Cord, K. A. M., Bucher, H. C., & Hemkens, L. G. (2019) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2019.10.012 · Cited by 20 · see citing works
- Authors
- Mansournia, M. A., Higgins, J. P. T., Sterne, J. A. C., & Hernán, M. A.
- Affiliations
- Harvard University (US)
- Venue
- Epidemiology
- Published
- 2017-01
- Volume
- 28
- Issue
- 1
- Pages
- 54-59
- ISSN
- 1044-3983 (ISSN-L)
- PMC
- PMC5130591
- OpenAlex
- W2336975416
- Cited by
- 285
- References
- 25
- Citations by year
- 2026: 18 · 2025: 30 · 2024: 30 · 2023: 29 · 2022: 40 · 2021: 39 · 2020: 42 · 2019: 29 · 2018: 17 · 2017: 9 · 2016: 2
- FWCI
- 19.21
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Epidemiology (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Bristol Research (University of Bristol) (acceptedVersion, other-oa)
- Explore Bristol Research (submittedVersion, other-oa)
- Funders
- National Institute for Health and Care Research (NF-SI-0611-10168, NF-SI-0616-10111)
- Medical Research Council (MR/M025209/1, MR/K025643/1)
- National Cancer Institute (P01CA134294, R35CA197449)
- National Institute of Allergy and Infectious Diseases (R01AI102634)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Keywords
- confounding, selection bias, measurement bias, causal graphs, intention-to-treat effect, risk of bias, terminology translation, causal inference
- MeSH terms
- Humans, Patient Dropouts, Observer Variation, Bias, Selection Bias, Causality, Confounding Factors, Epidemiologic, Randomized Controlled Trials as Topic, Intention to Treat Analysis
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