Letters

1. de Mulder M, Umans VA, Cornel JH, et al. Intensive glucose regulation in hyperglycemic acute coronary syndrome: results of the randomized BIOMarker study to identify the acute risk of a coronary syndrome-2 (BIOMArCS-2) glucose trial. JAMA Intern Med. 2013;173(20):1896-1904.

Author Affiliations: American Association of Clinical Endocrinologists, Jacksonville, Florida (Garber, Mechanick); American College of Endocrinology, Jacksonville, Florida (Einhorn); Diabetes and Endocrine Associates, La Jolla, California (Einhorn).

AACE Response to Viewpoint of December 9, 2013

Corresponding Author: Alan J. Garber, MD, PhD, Immediate Past President, American Association of Clinical Endocrinologists, 245 Riverside Ave, Ste 200, Jacksonville, FL 32202 ([email protected]).

To the Editor The Viewpoint by Gionfriddo et al1 regarding the American Association of Clinical Endocrinologists (AACE) Comprehensive Diabetes Management Algorithm reflects a failure to differentiate between an algorithm and a guideline. They conflate algorithms with guidelines and argue against this nonexistent straw man. What we published is explicitly an algorithm, entitled an algorithm, and not a guideline, which is explicitly defined and governed by our own published protocols.2 In fact, our algorithm directs readers to previously published guidelines as needed.3 Algorithms are evidence- and nuance-based clinical practice tools, derived from extant guidelines and new information, to optimize care. More specifically, algorithms rely on diverse layers of evidence in order to clarify complicated management decisions, the totality of which cannot be exclusively guided by published randomized clinical trials or other higher levels of evidence. Thus, responsible clinical decision making requires that each patient encounter uses all available evidence; to do otherwise is to abdicate clinical responsibility for patient care. The authors also express that pharmaceutical industry bias contaminated our algorithm development process. We emphasize that published AACE ethical standards affirm that no pharmaceutical funds be used for algorithm or guideline development and our explicit multilevel review process provides additional diligence and safeguards.2 Gionfriddo et al1 do not consider other sources of bias, which may in fact impact their own judgment, such as the undue influence of governmental agencies and funding limitations on health care that reduce patient access to best possible treatments in favor of less desirable and less costly interventions. Guilt by association is not proof of bias and should not be accepted as such. Lastly, Gionfriddo et al1 argue that our judgments were largely based on efficacy and 3 adverse effects of antidiabetic medications: weight gain, hypoglycemia, and cardiovascular morbidity. Regardless of the authors’ beliefs, these issues are the foci of Food and Drug Administration (FDA) concern, for which guidance and considerable interest have been expressed. These issues are the principal origins of both short-term and long-term harm or benefit for antidiabetic medications. The concerns regarding cardiovascular morbidity of each medication by FDA hardly needs discussion here, nor does the impact of small weight changes on cardiovascular risk.4 The data of the Centers for Disease Control and Prevention5 demonstrate the magnitude of excess emergency department visits and hospitalizations owing to hypoglycemia from antidiabetic medications. We believe it is the responsibility of AACE to provide clinically useable guidance regarding comprehensive treatment of diabetes and to continuously update guidance as new information becomes available.

In Reply Our chief concerns with any expert guidance— whether an algorithm or a guideline—is that the guidance should be produced and reported with transparency and offer evidence-based and patient-centered advice. Garber et al state that in our article1 we conflate algorithms with guidelines and thus argue against a straw man. Because the algorithm of the American Association of Clinical Endocrinologists (AACE) was “developed to provide clinicians with a practical guide”2(p3) to the management of type 2 diabetes mellitus, the Institute of Medicine standards3 are relevant and apply. We agree that many diabetes management decisions cannot be guided by high-confidence evidence when only low-confidence evidence exists. A clear indication of the level of confidence warranted by the available evidence helps improve the credibility of algorithms and therefore their usefulness. We cannot judge the extent to which financial relations between the writers of the algorithm and the pharmaceutical industry were influential, but the existence of these relationships offers users another potential explanation, other than science, for the algorithm’s content. Although full disclosure of such relationships is necessary, disclosure is not sufficient to ensure the trustworthiness of an algorithm. Clinicians must work with patients to formulate achievable plans of care that are congruent with their context and goals.4,5 Weight gain, hypoglycemia, and cardiovascular effects of glucose-lowering medications are important considerations, but so is the patient’s ability to implement a treatment plan. Practical concerns, such as the cost and the inconvenience of treatment, can be important in selecting a medication, thus highlighting the need to engage patients in shared decision making. The AACE algorithm did not address shared decision making.

Alan J. Garber, MD, PhD Daniel Einhorn, MD Jeffrey I. Mechanick, MD, ECNU

Michael R. Gionfriddo, PharmD Rozalina G. McCoy, MD Kasia J. Lipska, MD, MHS

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Conflict of Interest Disclosures: None reported. 1. Gionfriddo MR, McCoy RG, Lipska KJ. The 2013 American Association of Clinical Endocrinologists’ diabetes mellitus management recommendations: improvements needed. JAMA Intern Med. 2014;174(2):179-180. 2. Mechanick JI, Camacho PM, Cobin RH, et al; American Association of Clinical Endocrinologists. American Association of Clinical Endocrinologists protocol for standardized production of clinical practice guidelines. Endocr Pract. 2010;16(2):270-283. 3. Handelsman Y, Mechanick JI, Blonde L, et al. American Association of Clinical Endocrinologists medical guidelines for developing a diabetes mellitus comprehensive care plan. Endocr Pract. 2011;17(suppl 2):1-53. 4. Wilson PWF, Kannel WB, Silbershatz H, D’Agostino RB. Clustering of metabolic factors and coronary heart disease. Arch Intern Med. 1999;159(10):1104-1109. 5. Budnitz DS, Lovegrove MC, Shehab N, Richards CL. Emergency hospitalizations for adverse drug events in older Americans. N Engl J Med. 2011;365(21):2002-2012.

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Author Affiliations: Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota (Gionfriddo); Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Mayo Clinic, Rochester, Minnesota (McCoy); Section of Endocrinology, Yale School of Medicine, New Haven, Connecticut (Lipska). Corresponding Author: Michael R. Gionfriddo, PharmD, Knowledge and Evaluation Research Unit, Mayo Clinic, 200 First St SW, Rochester, MN 55905 ([email protected]). Conflict of Interest Disclosures Dr Gionfriddo is part of the Knowledge and Evaluation Research Unit, which contracts with nonprofit professional organizations and public agencies including The Endocrine Society to conduct systematic reviews and support the formulation of clinical practice guidelines. Dr Lipska reports blogging for Medscape from scientific meetings and is currently supported by the Pepper Center Career Development Award (P30 AG21342) and the Grants for Early Medical/Surgical Specialists’ Transition to Aging Research (R03 AG045086) from the National Institute on Aging. No other disclosures are reported. Funding/Support: Dr Gionfriddo is currently supported by Clinical and Translational Science Award grant TL1 TR000137 from the National Center for Advancing Translational Science. Role of the Sponsor: The sponsor had no role in the preparation, review, or approval of the manuscript or the decision to submit the manuscript for publication. Disclaimer: The contents of this letter are solely the responsibility of the authors and do not necessarily represent the official views of the National Institutes of Health.

2. Garber AJ, Abrahamson MJ, Barzilay JI, et al. American Association of Clinical Endocrinologists’ comprehensive diabetes management algorithm 2013 consensus statement—executive summary. Endocr Pract. 2013;19(3):536-557. 3. Institute of Medicine. Clinical Practice Guidelines We Can Trust. Washington, DC: The National Academies Press; 2011. 4. Shippee ND, Shah ND, May CR, Mair FS, Montori VM. Cumulative complexity: a functional, patient-centered model of patient complexity can improve research and practice. J Clin Epidemiol. 2012;65(10):1041-1051. 5. Piette JD, Kerr EA. The impact of comorbid chronic conditions on diabetes care. Diabetes Care. 2006;29(3):725-731.

CORRECTION Missing Conflict of Interest Disclosures: In the Original Investigation titled “Overdiagnosis in Low-Dose Computed Tomography Screening for Lung Cancer” published in the February 2014 issue of JAMA Internal Medicine (2014;174[2]:269274. doi:10.1001/jamainternmed.2013.12738), incorrect information appeared. The Conflict of Interest statement, which read “Conflict of Interest Disclosures: None reported.” should be replaced with the following: “Conflict of Interest Disclosures: Dr Patz conducted a research project on serum protein biomarkers and indeterminate pulmonary nodules funded by Laboratory Corporation of America through a sponsored research agreement with Duke University. Dr Gatsonis is a consultant/member of the scientific advisory board for Wilex AG and a board member for Frontier Science & Technology Research Foundation and has served as a consultant to Endocyte Inc and Genentech.” This article was corrected online.

1. Gionfriddo MR, McCoy RG, Lipska KJ. The 2013 American Association of Clinical Endocrinologists’ diabetes mellitus management recommendations: improvements needed. JAMA Intern Med. 2014;174(2):179-180.

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AACE Response to viewpoint of December 9, 2013.

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