The DOI matches its Crossref record; 61 of the 61 references it cites were found in a registry or an index.
Observational research--opportunities and limitations
Open accessAbstract
Medical research continues to progress in its ability to identify treatments and characteristics associated with benefits and adverse outcomes. The principal engine for the evaluation of treatment efficacy is the randomized controlled trial (RCT). Due to the cost and other considerations, RCTs cannot address all clinically important decisions. Observational research often is used to address issues not addressed or not addressable by RCTs. This article provides an overview of the benefits and limitations of observational research to serve as a guide to the interpretation of this category of research designs in diabetes investigations. The potential for bias is higher in observational research but there are design and analysis features that can address these concerns although not completely eliminate them. Pharmacoepidemiologic research may provide important information regarding relative safety and effectiveness of diabetes pharmaceuticals. Such research must effectively address the important issue of confounding by indication in order to produce clinically meaningful results. Other methods such as instrumental variable analysis are being employed to enable stronger causal inference but these methods also require fulfillment of several key assumptions that may or may not be realistic. Nearly all clinical decisions involve probabilistic reasoning and confronting uncertainly, so a realistic goal for observational research may not be the high standard set by RCTs but instead the level of certainty needed to influence a diagnostic or treatment decision.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“although the risk for confounding was taken into account during the analysis of the data [50].”
From The Modified A-DIVA Scale as a Predictive Tool for Prospective Identification of Adult Patients at Risk of a Difficult Intravenous Access: A Multicenter Validation Study (2019) · cites this paper as [50]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“Considering that observational epidemiological studies have inherent limitations is also important, with residual confounding being perhaps most pertinent.”
From Ultra-processed food exposure and adverse health outcomes: umbrella review of epidemiological meta-analyses (2024) · cites this paper as [77]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Diagnosis and Classification of Diabetes Mellitus
American Diabetes Association (2010) · Diabetes Care · doi:10.2337/dc11-s062 · Cited by 14,075
OLSSON, A. G., McMurray, J. J. V., Thorgeirsson, G., Spaulding, C. M., Slattery, J., Pyörälà, K., Færgeman, O., Wright, R. S., Berg, K. M., Wilhelmsen, L., et al. (1994) · The Lancet · Cited by 8,467
Turner, R. C., Fox, C., Matthews, McElroy, H. H., Cull, C. A., Holman, R. R., Neil, P., Hadden, D. R., Wright, D., Manley, E., et al. (1998) · The Lancet · Cited by 8,419
The environment and disease: association or causation?
Hill, A. B. (2015) · Journal of the Royal Society of Medicine · doi:10.1177/0141076814562718 · Cited by 7,804
The Environment and Disease: Association or Causation?
Hill, A. B. (1965) · Proceedings of the Royal Society of Medicine · doi:10.1177/003591576505800503 · Cited by 6,974
SCANDINAVIANSIMVASTATINSURVIVAL (1994) · The Lancet · doi:10.1016/s0140-6736(94)90566-5 · Cited by 3,638
Randomized, Controlled Trials, Observational Studies, and the Hierarchy of Research Designs
Concato, J., Shah, N., & Horwitz, R. I. (2000) · New England Journal of Medicine · doi:10.1056/nejm200006223422507 · Cited by 3,563
Pedersen, T. R. (2004) · Atherosclerosis Supplements · doi:10.1016/j.atherosclerosissup.2004.08.027 · Cited by 3,098
Explaining the decrease in U.S. deaths from coronary disease, 1980–2000
Ford, E. S., Ajani, U. A., Croft, J. B., Critchley, J. A., Labarthe, D. R., Kottke, T. E., Giles, W. H., & Capewell, S. (2007) · New England Journal of Medicine · doi:10.1056/nejmsa053935 · Cited by 2,757
A comparison of observational studies and randomized, controlled trials.
Benson, K., & Hartz, A. J. (2000) · New England Journal of Medicine · doi:10.1056/nejm200006223422506 · Cited by 2,347
Diagnosis and classification of diabetes mellitus
American Diabetes Association (2013) · Diabetes Care · doi:10.2337/dc13-s067 · Cited by 2,245
Dawber, T. R. (1980) · Harvard University Press eBooks · doi:10.4159/harvard.9780674492097 · Cited by 1,965
Surrogate End Points in Clinical Trials: Are We Being Misled?
Fleming, T. R., & DeMets, D. L. (1996) · Annals of Internal Medicine · doi:10.7326/0003-4819-125-7-199610010-00011 · Cited by 1,651
Bias and causal associations in observational research
Grimes, D. A., & Schulz, K. F. (2002) · The Lancet · doi:10.1016/s0140-6736(02)07451-2 · Cited by 1,553
Fox, C. S., Matsushita, K., Woodward, M., Bilo, H. J., Chalmers, J., Heerspink, H. J. L., Lee, B. J., Perkins, R. M., Rossing, P., Sairenchi, T., et al. (2012) · The Lancet · doi:10.1016/s0140-6736(12)61350-6 · Cited by 1,401
The Threshold Approach to Clinical Decision Making
Pauker, S. G., & Kassirer, J. P. (1980) · New England Journal of Medicine · doi:10.1056/nejm198005153022003 · Cited by 1,371
Causation and Causal Inference in Epidemiology
Rothman, K. J., & Greenland, S. (2005) · American Journal of Public Health · doi:10.2105/ajph.2004.059204 · Cited by 1,260
Instruments for Causal Inference: An Epidemiologist's Dream?
Hernán, M. A., & Robins, J. M. (2006) · Epidemiology · doi:10.1097/01.ede.0000222409.00878.37 · Cited by 961
Proceedings of the Royal Society of Medicine
Almkvist, J., Wagner, F., Alexander, A., Tecklenborg, & Jordan, A. (1912) · Dermatology · doi:10.1159/000245425 · Cited by 910
Pirie, K., Peto, R., Reeves, G. K., Green, J., & Beral, V. (2013) · The Lancet · doi:10.1016/s0140-6736(12)61720-6 · Cited by 799
Sex hormone-binding globulin and risk of type 2 diabetes in women and men
Ding, E. L., Song, Y., Manson, J. E., Hunter, D. J., Lee, C. C., Rifai, N., Buring, J. E., Gaziano, J. M., & Liu, S. (2009) · New England Journal of Medicine · doi:10.1056/nejmoa0804381 · Cited by 726
Epidemiologic assessment of the role of blood pressure in stroke. The Framingham study
Kannel, W. B. (1970) · JAMA · doi:10.1001/jama.214.2.301 · Cited by 706
Stürmer, T., Joshi, M., Glynn, R. J., Avorn, J., Rothman, K. J., & Schneeweiß, S. (2005) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2005.07.004 · Cited by 668
Blocked randomization with randomly selected block sizes
Efird, J. (2010) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph8010015 · Cited by 564
Lipoproteins, Cardiovascular Disease, and Death
Gordon, T. (1981) · Archives of Internal Medicine · doi:10.1001/archinte.1981.00340090024008 · Cited by 528
Shah, B. R., Laupacis, A., Hux, J. E., & Austin, P. C. (2005) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2004.10.016 · Cited by 493
Wysowski, D. K., & Swartz, L. (2005) · Archives of Internal Medicine · doi:10.1001/archinte.165.12.1363 · Cited by 471
A comparison of observational studies and randomized, controlled trials
Benson, K., & Hartz, A. J. (2000) · American Journal of Ophthalmology · doi:10.1016/s0002-9394(00)00754-6 · Cited by 456
Withdrawal of Cerivastatin from the World Market
Furberg, C. D., & Pitt, B. (2001) · Trials · doi:10.1186/cvm-2-5-205 · Cited by 400
Gm3;5,13,14 and type 2 diabetes mellitus: an association in American Indians with genetic admixture.
Knowler, W. C., Williams, R. C., Pettitt, D. J., & Steinberg, A. G. (1988) · Europe PMC (PubMed Central) · Cited by 378
Brookhart, M. A., Wang, P. S., Solomon, D. H., & Schneeweiß, S. (2006) · Epidemiology · doi:10.1097/01.ede.0000193606.58671.c5 · Cited by 341
Roumie, C. L., Hung, A. M., Greevy, R. A., Grijalva, C. G., Liu, X., Murff, H. J., Elasy, T. A., & Griffin, M. R. (2012) · Annals of Internal Medicine · doi:10.7326/0003-4819-157-9-201211060-00003 · Cited by 304
The InterAct Consortium (614230) (2013) · Diabetologia · doi:10.1007/s00125-013-2899-8 · Cited by 301
Prentice, R. L., Langer, R., Stefanick, M. L., Howard, B. V., Pettinger, M. B., Anderson, G. L., Barad, D. H., Curb, J. D., Kotchen, J. M., Kuller, L. H., et al. (2005) · American Journal of Epidemiology · doi:10.1093/aje/kwi223 · Cited by 263
Channeling bias in the interpretation of drug effects
Petri, H., & Urquhart, J. (1991) · Statistics in Medicine · doi:10.1002/sim.4780100409 · Cited by 246
Commentary: The concept of 'Mendelian Randomization'
Thomas, D. C. (2004) · International Journal of Epidemiology · doi:10.1093/ije/dyh048 · Cited by 217
Psaty, B. M. (1999) · JAMA · doi:10.1001/jama.282.8.786 · Cited by 187
The missed lessons of Sir Austin Bradford Hill
Phillips, C. V., & Goodman, K. J. (2004) · Epidemiologic Perspectives & Innovations · doi:10.1186/1742-5573-1-3 · Cited by 180
A BRIEF HISTORY OF THE RANDOMIZED CONTROLLED TRIAL
Meldrum, M. L. (2000) · Hematology/Oncology Clinics of North America · doi:10.1016/s0889-8588(05)70309-9 · Cited by 176
The Diabetes Prevention Program
The DPP Research Group (2002) · Controlled Clinical Trials · doi:10.1016/s0197-2456(01)00184-2 · Cited by 175
Crownover, R. L. (1999) · Hematology/Oncology Clinics of North America · doi:10.1016/s0889-8588(05)70068-x · Cited by 173
Chrysotile, Tremolite, and Malignant Mesothelioma in Man
Churg, A. (1988) · CHEST Journal · doi:10.1378/chest.93.3.621 · Cited by 139
Statin safety: an assessment using an administrative claims database
Cziraky, M. J., Willey, V. J., McKenney, J. M., Kamat, S. A., Fisher, M. D., Guyton, J. R., Jacobson, T. A., & Davidson, M. H. (2006) · The American Journal of Cardiology · doi:10.1016/j.amjcard.2005.12.011 · Cited by 130
Tinker, L. F., Sarto, G. E., Howard, B. V., Huang, Y., Neuhouser, M. L., Mossavar-Rahmani, Y., Beasley, J. M., Margolis, K. L., Eaton, C. B., Phillips, L. S., et al. (2011) · The American Journal of Clinical Nutrition · doi:10.3945/ajcn.111.018648 · Cited by 122
Pfister, R., Barnes, D. R., Luben, R., Forouhi, N. G., Bochud, M., Khaw, K., Wareham, N. J., & Langenberg, C. (2011) · Diabetologia · doi:10.1007/s00125-011-2235-0 · Cited by 103
Epidemiologic Assessment of the Role of Blood Pressure in Stroke
Lassen, N. A. (1996) · JAMA · doi:10.1001/jama.1996.03540150081041 · Cited by 99
Methods in Epidemiology: Observational Study Designs
DiPietro, N. A. (2010) · Pharmacotherapy The Journal of Human Pharmacology and Drug Therapy · doi:10.1592/phco.30.10.973 · Cited by 91
Rubin, D. B. (2010) · American Journal of Ophthalmology · doi:10.1016/j.ajo.2009.08.024 · Cited by 88 · cited 1×
“The propensity score methodmodels the probability of exposure in relation to predictor variables, and therefore estimates the likelihood, in the case of a pharmacoepidemiology study, of a subject receiving a particular pharmaceutical based on his or her characteristics (Rubin, 2010).”
Backgroundvan Stralen, K. J., Dekker, F. W., Zoccali, C., & Jager, K. J. (2010) · Nephron Clinical Practice · doi:10.1159/000315883 · Cited by 79
Wheeler, S., Moore, K. P., Forsberg, C. W., Riley, K., Floyd, J. S., Smith, N. L., & Boyko, E. J. (2013) · Diabetologia · doi:10.1007/s00125-013-2958-1 · Cited by 56
Self-citationPharmacoepidemiology: a new discipline.
Lawson, D. H. (1984) · BMJ · doi:10.1136/bmj.289.6450.940 · Cited by 55
Design issues for drug epidemiology
McMahon, A. D., & MacDonald, T. M. (2000) · British Journal of Clinical Pharmacology · doi:10.1046/j.1365-2125.2000.00289.x · Cited by 44
Big Data: Large-Scale Historical Infrastructure from the Minnesota Population Center
Sobek, M., Cleveland, L., Flood, S., Hall, P. K., King, M. L., Ruggles, S., & Schroeder, M. B. (2011) · Historical Methods A Journal of Quantitative and Interdisciplinary History · doi:10.1080/01615440.2011.564572 · Cited by 43
An analysis of the University Group Diabetes Study Program: data results and conslusions.
LEIBEL, B. S. (1971) · PubMed · Cited by 22
Plasencia, C. M., Alderman, B. W., Barón, A. E., Rolfs, R. T., & Boyko, E. J. (1992) · Medical Decision Making · doi:10.1177/0272989x9201200306 · Cited by 19
Self-citationA new method for determining physician decision thresholds using empiric, uncertain recommendations
Boland, M. V., & Lehmann, H. P. (2010) · BMC Medical Informatics and Decision Making · doi:10.1186/1472-6947-10-20 · Cited by 19
Cummings, P. (2008) · Archives of Pediatrics and Adolescent Medicine · doi:10.1001/archpedi.162.8.734 · Cited by 10
Flagged first, then by citations
Cited by
Sorted by citations
Lane, M. M., Gamage, E., Du, S., Ashtree, D. N., McGuinness, A. J., Gauci, S., Baker, P., Lawrence, M., Rebholz, C. M., Srour, B., et al. (2024) · BMJ · doi:10.1136/bmj-2023-077310 · Cited by 1,153
Ochen, Y., Beks, R. B., van Heijl, M., Hietbrink, F., Leenen, L. P. H., van der Velde, D., Heng, M. M., van der Meijden, O. A. J., Groenwold, R. H. H., & Houwert, R. M. (2019) · BMJ · doi:10.1136/bmj.k5120 · Cited by 369
Dai, W., Leng, X., Wang, J., Cheng, J., Hu, X., & Ao, Y. (2021) · The American Journal of Sports Medicine · doi:10.1177/03635465211030259 · Cited by 181
Operative vs Nonoperative Treatment of Distal Radius Fractures in Adults
Ochen, Y., Peek, J., van der Velde, D., Beeres, F. J. P., van Heijl, M., Groenwold, R. H. H., Houwert, R. M., & Heng, M. M. (2020) · JAMA Network Open · doi:10.1001/jamanetworkopen.2020.3497 · Cited by 166
Gill, D., Efstathiadou, A., Cawood, K., Tzoulaki, I., & Dehghan, A. (2019) · International Journal of Epidemiology · doi:10.1093/ije/dyz200 · Cited by 151
Metadata
- Authors
- Boyko, E. J.
- Affiliations
- University of Washington (US)
- Corresponding author
- Boyko, Edward J.
- ORCID
- Boyko, Edward J.
- Venue
- Journal of Diabetes and its Complications
- Publisher
- Elsevier BV
- Published
- 2013-11
- Volume
- 27
- Issue
- 6
- Pages
- 642-648
- ISSN
- 0891-6632 (ISSN-L)
- 1056-8727
- PMC
- PMC3818421
- OpenAlex
- W2117613909
- Cited by
- 313
- References
- 61
- Citations by year
- 2026: 33 · 2025: 42 · 2024: 84 · 2023: 33 · 2022: 19 · 2021: 37 · 2020: 25 · 2019: 17 · 2018: 8 · 2017: 6 · 2016: 3 · 2015: 3 · 2014: 3
- FWCI
- 0.59
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Journal of Diabetes and its Complications (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- VA Epidemiologic Research and Information Center
- Diabetes Research Center at the University of Washington (DK-017047)
- VA Puget Sound Health Care System
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Keywords
- observational studies, diabetes mellitus, pharmacoepidemiology, confounding by indication, bias, instrumental variables, causal inference, randomized controlled trials, treatment efficacy, drug safety and effectiveness, probabilistic reasoning
- MeSH terms
- Clinical Trials as Topic, Diabetes Mellitus, Humans, Research Design, Cohort Studies, Bias, Causality, Case-Control Studies, Treatment Outcome, Observational Studies as Topic
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
