Jennifer Pillay, BSc; Marni J. Armstrong, PhD, RCEP; Sonia Butalia, MD, MSc; Lois E. Donovan, MD; Ronald J. Sigal, MD, MPH; Ben Vandermeer, MSc; Pritam Chordiya, BDS, MSc; Sanjaya Dhakal, MBBS, MPH; Lisa Hartling, PhD; Megan Nuspl, BSc; Robin Featherstone, MLIS; Donna M. Dryden, PhD
Disclaimer: The authors of this report are responsible for its content. Statements in the report should not be construed as endorsement by the AHRQ or the U.S. Department of Health and Human Services.
Acknowledgment: The authors thank AHRQ task order officer Aysegul Gozu, MD, MPH, and AHRQ associate editor Jonathan Treadwell, PhD, who reviewed our review protocol and the full report submitted to AHRQ, for their ongoing support. We also thank the key informants and technical expert panel members (listed in the full report online at www.effective healthcare.ahrq.gov/reports/final.cfm) who provided input into the review. Several technical expert panel members also provided peer review of the draft report submitted to AHRQ and available online.
Grant Support: By the AHRQ (contract 290-2012-000131); a New Investigator Salary Award from the Canadian Institutes of Health Research (Dr. Hartling); doctoral awards from the Alliance for Canadian Health Outcomes for Research in Diabetes, Alberta Innovates–Health Solutions, and the University of Calgary–Eyes High program (Dr. Armstrong); and a Health Senior Scholar award from Alberta Innovates–Health Solutions (Dr. Sigal).
Disclosures: Ms. Pillay reports grants from AHRQ during the conduct of the study. Dr. Sigal reports salary support from Alberta Innovates-Health Solutions (Health Senior Scholar salary award) during the conduct of the study. Mr. Vandermeer reports grants from AHRQ during the conduct of the study. Dr. Chordiya reports grants from AHRQ during the conduct of the study. Ms. Nuspl reports grants from AHRQ during the conduct of the study. Ms. Featherstone reports grants from AHRQ during the conduct of the study. Dr. Dryden reports other from AHRQ (contract between AHRQ and research group to prepare a report on the topic; this publication represents one part of the report) during the conduct of the study. Authors not named here have disclosed no conflicts of interest. Forms can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M15-1400.
Editors' Disclosures: Christine Laine, MD, MPH, Editor in Chief, reports that she has no financial relationships or interests to disclose. Darren B. Taichman, MD, PhD, Executive Deputy Editor, reports that he has no financial relationships or interests to disclose. Cynthia D. Mulrow, MD, MSc, Senior Deputy Editor, reports that she has no relationships or interests to disclose. Deborah Cotton, MD, MPH, Deputy Editor, reports that she has no financial relationships or interest to disclose. Jaya K. Rao, MD, MHS, Deputy Editor, reports that she has stock holdings/options in Eli Lilly and Pfizer. Sankey V. Williams, MD, Deputy Editor, reports that he has no financial relationships or interests to disclose. Catharine B. Stack, PhD, MS, Deputy Editor for Statistics, reports that she has stock holdings in Pfizer.
Reproducible Research Statement:Study protocol: PROSPERO registration number CRD42014010515. Statistical code and data set: Available from Ms. Pillay (e-mail, firstname.lastname@example.org).
Requests for Single Reprints: Jennifer Pillay, BSc, Alberta Research Centre for Health Evidence, Department of Pediatrics, 4th Floor, Edmonton Clinic Health Academy, University of Alberta, 11405 87th Avenue, Edmonton, Alberta T6G 1C9, Canada; e-mail, email@example.com.
Current Author Addresses: Ms. Pillay, Mr. Chordiya, Dr. Dhakal, Mr. Vandermeer, Dr. Hartling, Ms. Nuspl, Ms. Featherstone, and Dr. Dryden: Alberta Research Centre for Health Evidence, Department of Pediatrics, 4th Floor, Edmonton Clinic Health Academy, University of Alberta, 11405 87th Avenue, Edmonton, Alberta T6G 1C9, Canada.
Drs. Armstrong, Butalia, Donovan, and Sigal: Division of Endocrinology and Metabolism, University of Calgary, Richmond Road Diagnostic and Treatment Centre, 1820 Richmond Road SW, Calgary, Alberta T2T 5C7, Canada.
Author Contributions: Conception and design: J. Pillay, M.J. Armstrong, S. Butalia, L.E. Donovan, R.J. Sigal, L. Hartling, R. Featherstone, D.M. Dryden.
Analysis and interpretation of the data: J. Pillay, M.J. Armstrong, S. Butalia, L.E. Donovan, B. Vandermeer, P. Chordiya, S. Dhakal, L. Hartling, D.M. Dryden.
Drafting of the article: J. Pillay, S. Butalia, B. Vandermeer, P. Chordiya, S. Dhakal, M. Nuspl, R. Featherstone.
Critical revision of the article for important intellectual content: J. Pillay, M.J. Armstrong, S. Butalia, L.E. Donovan, R.J. Sigal, B. Vandermeer, L. Hartling, D.M. Dryden.
Final approval of the article: J. Pillay, M.J. Armstrong, S. Butalia, L.E. Donovan, R.J. Sigal, B. Vandermeer, P. Chordiya, S. Dhakal, L. Hartling, M. Nuspl, R. Featherstone, D.M. Dryden.
Statistical expertise: B. Vandermeer.
Obtaining of funding: S. Butalia, L. Hartling, D.M. Dryden.
Administrative, technical, or logistic support: J. Pillay, M. Nuspl, R. Featherstone, D.M. Dryden.
Collection and assembly of data: J. Pillay, P. Chordiya, S. Dhakal, L. Hartling, M. Nuspl, R. Featherstone, D.M. Dryden.
Behavioral programs may improve outcomes for individuals with type 2 diabetes mellitus, but there is a large diversity of behavioral interventions and uncertainty about how to optimize the effectiveness of these programs.
To identify factors moderating the effectiveness of behavioral programs for adults with type 2 diabetes.
6 databases (1993 to January 2015), conference proceedings (2011 to 2014), and reference lists.
Duplicate screening and selection of 132 randomized, controlled trials evaluating behavioral programs compared with usual care, active controls, or other behavioral programs.
One reviewer extracted and another verified data. Two reviewers independently assessed risk of bias.
Behavioral programs were grouped on the basis of program content and delivery methods. A Bayesian network meta-analysis showed that most lifestyle and diabetes self-management education and support programs (usually offering ≥11 contact hours) led to clinically important improvements in glycemic control (≥0.4% reduction in hemoglobin A1c [HbA1c]), whereas most diabetes self-management education programs without added support—especially those offering 10 or fewer contact hours—provided little benefit. Programs with higher effect sizes were more often delivered in person than via technology. Lifestyle programs led to the greatest reductions in body mass index. Reductions in HbA1c seemed to be greater for participants with a baseline HbA1c level of 7.0% or greater, adults younger than 65 years, and minority persons (subgroups with ≥75% nonwhite participants).
All trials had medium or high risk of bias. Subgroup analyses were indirect, and therefore exploratory. Most outcomes were reported immediately after the interventions.
Diabetes self-management education offering 10 or fewer hours of contact with delivery personnel provided little benefit. Behavioral programs seem to benefit persons with suboptimal or poor glycemic control more than those with good control.
Agency for Healthcare Research and Quality. (PROSPERO registration number: CRD42014010515)
Appendix Table 1. Search Strategy for MEDLINE*
Table. Categorization of Program Components and Delivery Factors
Appendix Table 2. Characteristics of Studies of Behavioral Programs for T2DM
Appendix Table 2–Continued
Summary of evidence search and selection.
T1DM = type 1 diabetes mellitus; T2DM = type 2 diabetes mellitus.
* One study was included for both T1DM and T2DM.
Appendix Table 3. Pairwise Meta-analysis Results for Behavioral Programs Compared With Usual Care
Appendix Table 4. Pairwise Meta-analysis Results for Behavioral Programs Compared With Active Controls
Appendix Table 5. Pairwise Meta-analysis Results for Comparative Effectiveness Between 2 Behavioral Programs
Rank order of relative effectiveness for HbA1c of behavioral programs and active comparators versus usual care.
Results of a network meta-analysis incorporating direct and indirect comparisons for the outcome of HbA1c are shown, with nodes for program components and delivery factors. All arms in each study were categorized and then grouped into “nodes” of similar arms. Arms defined as behavioral programs were grouped on the basis of their components and delivery factors. All nodes were then compared with the usual care node, using direct and indirect evidence while maintaining the randomization within each individual study. Each node of behavioral programs differs from the others by only 1 level in a category of program component, intensity, mode of communication, delivery method, and (for DSME programs only) delivery personnel. The dots and horizontal lines represent the mean difference and 95% credible interval for the nodes relative to usual care. Our predetermined threshold for clinical importance was a reduction in HbA1c of 0.4% or greater. Values for the mean differences and 95% credible intervals are included in Appendix Table 6. DSME = diabetes self-management education; HbA1c = hemoglobin A1c; HCP = health care professional.
Appendix Table 6. Network Meta-analysis Results for HbA1cAssessing Impact, by Program Components and Delivery Factors
Network diagram for hemoglobin A1c.
Each node in the network is depicted; the lines show the comparisons that contributed to the analysis. The largest circle indicates the usual care node, with which all other nodes were compared directly or indirectly. The numbering of the nodes reflects the rank order of their effectiveness in reducing hemoglobin A1c relative to usual care; for definitions of the program components and delivery factors that correspond to each rank number, see Figure 2. The number of studies and sample size are provided.
Rank order of relative effectiveness for BMI of behavioral programs and active comparators versus usual care.
Results of a network meta-analysis for BMI are shown, with nodes of programs characterized by program components and delivery factors. Usual care is the reference comparison. Each group differs by at least 1 level in the categories of program component, intensity, mode of communication, and delivery method. The dots and horizontal lines represent the mean difference and 95% credible intervals relative to usual care. Values for the mean differences and 95% credible intervals are included in Appendix Table 7. BMI = body mass index; DSME = diabetes self-management education.
Appendix Table 7. Network Meta-analysis Results for BMI
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Jennifer Pillay, Marni J. Armstrong, Sonia Butalia, Lois E. Donovan, Ronald J. Sigal, Ben Vandermeer, et al. Behavioral Programs for Type 2 Diabetes Mellitus: A Systematic Review and Network Meta-analysis. Ann Intern Med. 2015;163:848–860. doi: 10.7326/M15-1400
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Published: Ann Intern Med. 2015;163(11):848-860.
Published at www.annals.org on 29 September 2015
Cardiology, Coronary Risk Factors, Diabetes, Endocrine and Metabolism.
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