Medications And Diabetes Risk - Mechanisms And Approach To Risk Reduction

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Medications and Risk: Mechanisms and Approach to Risk Reduction

Diabetes

Want to Cure Diabetes? Click Here This material is not intended to be, and should not be considered, a substitute for medical or other professional advice. Treatment for the conditions described in this material is highly dependent on the individual circumstances. While this material is designed to off er accurate information with respect to the subject matter covered and to be current as of the time it was written, research and knowledge about medical and health issues is constantly evolving, and dose schedules for medications are being revised continually, with new side eff ects recognized and accounted for regularly. Readers must therefore always check the product information and clinical procedures with the most up-to-date published product information and data sheets provided by the manufacturers and the most recent codes of conduct and safety regulation. Oxford University Press and the authors make no representations or warranties to readers, express or implied, as to the accuracy or completeness of this material, including without limitation that they make no representations or warranties as to the accuracy or effi cacy of the drug dosages mentioned in the material. The authors and the publishers do not accept, and expressly disclaim, any responsibility for any liability, loss, or risk that may be claimed or incurred as a consequence of the use and/ or application of any of the contents of this material. The Publisher is responsible for author selection and the Publisher and the Author(s) make all editorial decisions, including decisions regarding content. The Publisher and the Author(s) are not responsible for any product information

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Medications and Diabetes Risk: Mechanisms and Approach to Risk Reduction

Samuel Dagogo-Jack, MD, FRCP Mullins Professor in Translational Research Professor of Medicine & Chief Division of Endocrinology, Diabetes & Metabolism University of Tennessee Health Science Center Memphis, TN

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DISCLOSURES

MEDICATIONS AND DIABETES RISK

Dr. Dagogo-Jack has served as a consultant for Eli Lilly and GlaxoSmithKline. He has also served on the speaker’s bureaus of Merck and Sanofi -Aventis.

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MEDICATIONS AND DIABETES RISK

PREFACE

More than 23 million Americans currently have diabetes, and approximately 54 million have prediabetes. People with diabetes often also require medications for several comorbid conditions (including hypertension, dyslipidemia, depression, heart disease, and pain syndromes). Yet, a vast literature abounds on the potential adverse eff ects of numerous medications on glucose metabolism. There is, thus, genuine clinical concern that certain medications used for treatment of comorbid conditions and other indications (such as hormone replacement, contraception, infections) might worsen glycemic control in diabetic patients or trigger diabetes in others. These concerns infl uence therapeutic decisions in a manner that sometimes emphasizes avoidance of possible dysglycemia over eff ective control of the comorbid conditions. The same concerns may also weigh against the otherwise appropriate use of necessary medications. The purpose of this concise book is to provide clinicians with actionable knowledge regarding the eff ects of various medications on glucose regulation and diabetes risk. Beginning with a brief overview of diabetes pathophysiology, the diff erent drugs have been organized by class, and the scientifi c evidence for the diabetes risk and possible mechanisms have been presented for each drug. The agents discussed include widely prescribed medication classes: antibiotics, antidepressants, antihypertensives, bronchodilators, estrogens and oral contraceptives, glucocorticoids, lipid-lowering agents, nonsteroidal anti-infl

ammatory drugs (NSAIDs), and thyroid hormone. Although less widely prescribed than the foregoing list, atypical antipsychotics, human immunodefi ciency virus (HIV) antir etrovirals, immunomodulatory agents, and human growth hormone have also been included because of the interest generated by their link to diabetes risk. In addition to medications used in ambulatory practice, this work includes a discussion of total parenteral nutrition (TPN)-induced hyperglycemia, which is associated with increased morbidity and mortality among hospitalized patients. For completeness, an account of the growing link between use of recreational drugs (alcohol, nicotine, cannabinoids, opioids, cocaine) and glucose abnormalities has been included, because of the possible intersection between these OAPN addictive agents and the growing diabetes

epidemic. With some medications, the data presented should help debunk myths, clarify misperceptions, and provide reassurance to the practicing clinicians. Wherever the evidence supports increased diabetes risk, clear suggestions are given on how to reduce the risk. There are also diabetes management guidelines for special situations, including newonset diabetes after transplant (NODAT) and TPN-induced hyperglycemia. The fi nal chapter provides suggestions for a general approach to the prevention or attenuation of diabetes risk, focusing on risk stratifi cation, lifestyle modifi cation, and the emerging concept of diabetes “pharmacoprevention” in high-risk persons receiving treatment with potentially diabetogenic agents.

MEDICATIONS AND This book should serve two DIABETES RISK essential functions—to enable clinicians to confi dently prescribe therapeutic regimens that embody the best risk–benefi t profi le with regard to glycemia, and to equip them with the know-how for preventing and managing druginduced hyperglycemia.

TABLE OF CONTENTS

1 2

Pathophysiology of Type 1 and Type 2 Diabetes 1 General Mechanisms of Medications and Diabetes Risk 8

3

Steroids and Immunomodulatory Agents 14

4

Antihypertensive Agents 26

5

Catecholamines, -Adrenergic Bronchodilators 33

6

Lipid-lowering Drugs 35

7

Antimicrobial Drugs 40

8 9

Agonists,

Atypical Antipsychotic and Antidepressant Agents 47 Recreational Drugs 56

10 Miscellaneous Agents 59 11 General Approach to Risk Reduction 66 References 70

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Section 1: Pathophysiology of Type 1 and Type 2 Diabetes DIABETES MELLITUS

Diabetes mellitus (DM) refers to a group of metabolic disorders that result in hyperglycemia. These disorders have diff erent underlying processes but their common manifestation is hyperglycemia, regardless of underlying process. More than 20 million Americans have diabetes and approximately 5 million of them are undiagnosed. Diabetes is a major public health problem because of the long-term complications (such as blindness, amputations, kidney failure, heart disease, and stroke) that could occur if the condition is inadequately controlled. Fortunately, as demonstrated in the Diabetes Control and Complications Trial (DCCT) study and other landmark clinical trials, the complications of diabetes can be prevented by maintaining excellent glycemic control using diet, exercise, and medications. Diagnosis of Diabetes The diagnosis of diabetes can be established using any of the following American Diabetes Association criteria: Plasma glucose of 126 mg/dL or greater after an overnight fast. A repeat test on a diff erent day is required to confi rm the diagnosis of diabetes (American Diabetes Association, 2009). Symptoms of diabetes and a random (nonfasting) plasma glucose of 200 mg/dL or greater. A standard Oral Glucose Tolerance Test showing a plasma glucose level of 200 mg/dL or greater at 2 hours after ingestion of a 75 g glucose load, provided all testing protocols are followed. ■

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A hemoglobin A1c level of 6.5% or greater (International Expert Committee, 2009). Diagnosis of Prediabetes The term “prediabetes” is used to describe persons with impaired glucose tolerance (IGT) or impaired fasting glucose (IFG). Impaired glucose tolerance is defi ned by a 2-hour oral glucose tolerance test (OGTT) plasma glucose level greater than 140 mg/dL but less than 200 mg/dL, and IFG is defi ned by a fasting plasma glucose level of 100 mg/dL or greater, but less than 126 mg/dL (ADA, 2009). Approximately 57 million Americans have prediabetes, and studies have shown that people with prediabetes tend to develop type 2 diabetes within 10 years. Lifestyle modifi cations (dietary restriction and exercise) and certain medications can prevent the development of diabetes in persons with prediabetes (Diabetes Prevention Program Research Group, 2002). ■

CLASSIFICATION OF DIABETES

Type 1 diabetes accounts for less than 10% of all cases of DM, occurs in younger persons, and is caused by absolute insulin defi ciency resulting from an immune-mediated destruction of the insulin-producing cells of the pancreas, known as cells. Type 2 diabetes mellitus (T2DM) accounts for more than 90% of all cases of DM. Usually a disease of adults, type 2 DM is being diagnosed increasingly in younger age groups. Obesity, insulin resistance, and relative insulin defi ciency are characteristic fi ndings. The risk factors for T2DM are listed in Table 1. Insulin resistance refers to a decreased ability of insulin to drive the uptake of glucose from the blood into the cells and to produce the other appropriate 2

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metabolic eff ects of insulin. Persons with insulin resistance alone do not develop diabetes, because their pancreatic -cells compensate by increasing Table 1 Risk Factors for Type 2 Diabetes ■

Having a fi rst-degree relative with diabetes mellitus

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Increasing age

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Being overweight (body mass index >25)

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Having dyslipidemia (elevated triglycerides or decreased high-density lipoprotein cholesterol) Having hypertension Belonging to a high-risk ethnic group (African American, Hispanic, Native American, Asian)

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History of gestational diabetes or birth of child weighing ≥9 lbs

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History of polycystic ovary syndrome

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Habitual physical inactivity

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History of vascular disease

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History of impaired fasting glucose or impaired glucose tolerance

From American Diabetes Association. (2009). Standards of Medical Care in Diabetes—2009. Diabetes Care, 32(Suppl 1):S13–S61, with permission of the publisher.

insulin secretion to levels that can maintain normoglycemia. Therefore, a second defect—an inability of the cells to maintain compensatory hyperinsulinemia—is required to precipitate type 2 diabetes. Other specifi c types of diabetes include those due to surgical resection or diseases of the pancreas (that compromise insulin secretion) and glandular disorders (e.g., Cushing 3

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syndrome, acromegaly), and rare syndromes. Gestational diabetes occurs during pregnancy and tends to resolve once the baby and placenta have been delivered (although the mother remains at high risk for future type 2 diabetes).

THE GENETIC BASIS OF TYPE 2 DIABETES

A family history of diabetes in fi rst-degree relatives (parents, siblings, and off spring) is one of the strongest risk factors for the development of diabetes. However, the genetic transmission of diabetes risk from parents to off spring is rather complex. Among monozygotic (identical) twins, the concordance rate of type 2 diabetes (that is, the chances of diabetes occurring in the second twin if one has diabetes) is approximately 80%, and the lifetime risk of developing type 2 diabetes among off spring and siblings of aff ected patients has been estimated at approximately 40% (Granner & O’Brien, 1992). If both parents are aff ected, the risk approaches 80% in off spring (Martin et al., 1992). Current understanding indicates that multiple genes may be involved in this process, and rarely have single genes been discovered that explained the entire processes underlying the development of diabetes. PATHOPHYSIOLOGY OF TYPE 2 DIABETES

In genetically susceptible persons, the development of type 2 diabetes is characterized ultimately by three underlying mechanisms: impaired insulin action (also known as insulin resistance), which is expressed in skeletal muscle and fat cells; impaired insulin secretion by the pancreatic -cells; and increased hepatic (liver) glucose production (HGP) (Dagogo-Jack & Santiago, 1997; Moneva & Dagogo-Jack, 2002). The transition from the normal state to type 2 4

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diabetes is punctuated by a variable interlude (usually lasting several years) in the intermediate state of prediabetes (IGT and IFG). There is general agreement that insulin resistance and impaired insulin secretion are present in most individuals before the onset of diabetes (Dagogo-Jack & Santiago, 1997; Moneva & Dagogo-Jack, 2002). Longitudinal studies in which initially healthy Pima Indians underwent metabolic assessments repeatedly over several years showed that subjects who progressed from the normal state to prediabetes (IGT) had lost approximately 12% of their insulin sensitivity, but 27% of their insulin secretion; the further progression from prediabetes to type 2 diabetes was preceded by a 31% decline in insulin sensitivity and a 78% decline in insulin secretion (Weyer et al., 1999). INSULIN RESISTANCE

The binding of insulin to its receptor triggers a series of phosphorylation reactions in the cytosol. The initial phosphorylation occurs on tyrosine residues within the cytoplasmic tail of the insulin receptor, followed by phosphorylation of multiple other intracellular proteins, including insulin receptor substrates (IRS)-1, 2, 3, and 4. Phosphorylation of the IRS proteins activates the enzyme phosphatidylinositol 3kinase (PI3K), leading to the translocation of an intracellular pool of glucose transporter molecules (GLUT4) to the plasma membrane, where they form vesicles that mediate glucose transport into the cell. Thus, insulin lowers blood glucose by stimulating the transport of glucose across cell membranes through a series of complex chemical reactions. Failure of this mechanism at any level between the binding of insulin to its cell membrane 5

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receptor and the eventual translocation of GLUT4 and internalization of glucose results in insulin resistance. Insulin resistance can be inherited or acquired. Obesity, aging, physical inactivity, overeating, and accumulation of free fatty acids are known causes of insulin resistance. Phosphorylation of serine or threonine residues (instead of tyrosine) interferes with the insulin signaling, and is a common molecular mechanism that leads to insulin resistance. INSULIN SECRETION BY THE - CELLS

Under normal conditions, the pancreatic cells secrete insulin in response to glucose stimulation through a series of transmembrane electrical reactions. Glucose metabolism in cells generates bursts of action potentials that ultimately lead to calcium infl ux. The adenosine triphosphate (ATP)sensitive potassium channel (KATP) normally maintains the cell resting membrane potential, thereby preventing calcium entry. The KATP channel is closed when the ratio of ATP to adenosine diphosphate rises within the cells, as occurs during glucose metabolism. The resultant depolarization (change in electrical charge) of the -cell membrane drives calcium into the cell, which then triggers insulin secretion. Agents that open the KATP channel (e.g., diazoxide) reverse the depolarization and inhibit insulin secretion by the cells. The -cell mass is reduced in type 2 diabetic patients as a result of apoptosis induced by islet amyloid deposition, oxidative stress, infl ammatory cytokines, and other mechanisms (Haataja et al., 2008). HEPATIC GLUCOSE PRODUCTION

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In the prospective study of Pima Indians, hepatic glucose output remained normal during the transition from normal glucose tolerance to IGT, but increased by 15% with further progression to diabetes (Weyer et al., 1999). In patients with established type 2 diabetes, the rate of hepatic gluconeogenesis is not suppressed postprandially (as occurs normally). Thus, the upregulated endogenous glucose production becomes a key determinant of fasting, as well as postprandial glucose excursions in type 2 diabetes. The increased endogenous glucose production is triggered by an increased fl ux of lipolytic products and other glucose precursors, and is due, at least in part, to hepatic insulin resistance. GLUCAGON AND INCRETINS

Glucagon secretion by the pancreatic cells also tends to be elevated in type 2 diabetes subjects, which further stimulates hepatic glucose production. Incretin hormones (GLP-1 and GIP), normally secreted by the enterocytes in response to food, serve to amplify postprandial insulin secretion and suppress glucagon secretion. Emerging data indicate that type 2 diabetes is associated with impaired incretin secretion and relative resistance to the action of incretin hormones. The major pathophysiological defects in T2DM are summarized in Table 2.

Table 2 Pathophysiological Defects in Type 2 Diabetes

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Insulin resistance

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Impaired insulin secretion

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Increased glucagon secretion

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Incretin defi ciency/resistance

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Impaired glucagon suppression

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Increased hepatic glucose production

Section 2: General Mechanisms of Medications and Diabetes Risk

To Cure Diabetes Naturally Click Here Diabetes has been reported in association with exposure to a wide variety of medications. As summarized in Table 3, in many cases, the mechanism relating the particular drug to hyperglycemia is explainable, whereas the mechanism of the association is less clear with regard to several other medications (Comi, 2000). Hyperglycemia can result from drugs that induce hypoinsulinemia through destruction of the pancreatic cells (e.g., pentamidine, Vacor), or by inhibiting insulin secretion (e.g., diazoxide). Hypokalemia impairs insulin secretion and also desensitizes the insulin receptor, and it is one mechanism underlying the dysglycemia associated with thiazides, loop diuretics, and hyperaldosteronism (Zillich et al., 2006). Induction of insulin resistance is a classic mechanism for steroid-induced diabetes, but the underlying processes are complex (with contributions from hyperglucagonemia, glycogenolysis, lipolysis, and gluconeogenesis). It has been suggested that drugs that restrict blood flow could impair the normal 8

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delivery of substrates to insulin-sensitive tissues (especially skeletal muscle) and, by that mechanism, reduce glucose disposal (McCullen & Ahmed, 2007). Theoretically, vasoconstrictors and -blockers (unopposed -adrenergic activity) could induce dysglycemia through this mechanism. In many instances, multiple mechanisms appear to mediate the drug effect. It is important to recognize drug-induced diabetes promptly, because withdrawal of the offending drug should result in resolution of the diabetes, in the absence of permanent cellular damage to the insulinsecreting cells. Table 3 Mechanisms and Examples of Iatrogenic Hyperglycemia Mechanism

Examples

A. I nterference with insulin secretion

Diazoxide, -blockers Diuretics Pentamidine, Vacor

• Pancreatotoxic B. I nterference with insulin action

Diuretics (via hypokalemia) Glucocorticoids, antiretrovirals - agonists, growth hormone

C. I mpaired insulin secretion and action

Thiazide diuretics cyclosporin, tacrolimus

D. I ncreased nutrient fl ux and gluconeogenesis

Nicotinic acid total parenteral nutrition - interferon

E. Unknown mechanism

Nonsteroidal anti-infl ammatory drugs antipsychotics antidepressants

RISK FACTOR VERSUS CAUSATION: THE BRADFORD HILL’S CRITERIA 9

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Originally established by Sir Austin Bradford Hill (Hill, 1965) and later elaborated by others, Hill’s criteria form the basis for establishing scientifi cally valid causal connections between potential disease agents and the many diseases that affl ict humankind. The criteria are (a) temporal relationship, an essential requirement that exposure to the agent must necessarily always precede the occurrence of the disease; (b) strength of association; (c) dose–response, a requirement that exposure to increasing amounts of the agent should result in increasing severity of disease; (d) consistency; (e) biological plausibility, with regard to currently accepted understanding of disease mechanisms; (f) consideration of alternate explanations; (g) experimental insight, a requirement that the observed association be reproducible and modifi able through deliberate experimentation; (h) specifi city of the association; and (i) coherence, which requires that the association be compatible with existing theory and knowledge. Applying the Hill’s criteria, only a few exceptions (e.g., pancreatic toxins and steroid-induced diabetes) among the myriad medications that have been reported to alter blood glucose levels meet the scientifi c threshold for establishing direct causality. For the majority of medications, the occurrence of diabetes is observed only in a minority of patients exposed, and the reported link to diabetes suff ers from paucity of randomized control data, weak association, inconsistent pattern, indeterminate temporal relationship (due to lack of baseline glucose data in many cases), unclear mechanism(s), and uncertain dose–response relationship. Apart from a direct causal eff ect, treatment-emergent diabetes could arise from preexisting undiagnosed diabetes; 10

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increased susceptibility to diabetes from underlying genetic or environmental risk factors; an indirect eff ect mediated by known risk factors, such as weight gain; a coincidental fi nding; or an idiosyncratic reaction in susceptible persons that is inherently unpredictable. DRUGS ASSOCIATED WITH TYPE 1 DIABETES

Type 1 diabetes is a disease of absolute or severe insulin defi ciency. The vast majority of patients with type 1 diabetes have autoimmune destruction of the pancreatic islet -cells as the underlying mechanism for the insulin defi ciency. In a small minority of patients with type 1 diabetes, evidence for autoimmunity is lacking and the etiology of islet destruction is unclear. Drug-induced type 1 diabetes is rare in clinical practice. Experimental insulin-defi cient diabetes can be induced by treating rodents with the pancreatic toxins streptozotocin or alloxan. Ingestion of the rat poison Vacor (N-3 pyridylmethyl-N’ 4 nitrophenol urea), which is structurally related to alloxan and streptozotocin, has been associated with human cases of diabetes (Miller et al., 1978; Pont et al., 1979). The diabetes induced by Vacor poisoning can have a delayed onset (≥1 week), but is usually severe and often presents with ketoacidosis. Prophylactic treatment with the antidote nicotinamide should be started as soon as possible following ingestion of Vacor, even in euglycemic persons (Miller et al., 1978; LeWitt, 1980). The antiprotozoal drug pentamidine, widely used for the treatment of refractory Pneumocystis carnii pneumonia (PCP) in human immunodefi ciency virus (HIV)infected patients, can induce acute insulinopenic diabetes in some patients through destruction of the pancreatic cells (Liegl et al., 1994; Coyle et al., 1996). An initial phase of hypoglycemia 11

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(refl ecting -cell degranulation and transient hyperinsulinemia) may precede the development of pentamidine-induced diabetes (Bouchard et al., 1982). The risk factors and exact mechanisms for cell destruction by pentamidine are unknown, and the resultant diabetes tends to persist after withdrawal of pentamidine (Liegl et al., 1994). Although pentamidine-induced hypoglycemia can be reversed by treatment with oral diazoxide (Fitzgerald & Young, 1984), it is not known whether such therapy would alter the course of progressive -cell destruction by pentamidine. Alcoholism and chronic pancreatitis have been associated with the development of insulin-defi cient diabetes (Ito et al., 2007). It is possible that other as yet unidentifi ed environmental toxins may be involved in the pathogenesis of the rare nonautoimmune cases of type 1 diabetes. DRUGS ASSOCIATED WITH TYPE 2 DIABETES

In contrast to the rarity of drug-associated typical type 1 diabetes, numerous medications in common use have been associated with the development of what can best be classifi ed as type 2 diabetes. The latter classifi cation is based loosely on the absence of absolute insulinopenia together with evidence for insulin resistance or related mechanisms for the disruption of glucoregulation. However, depending on the severity and acuteness of the perturbation, some patients with drug-related diabetes may present with diabetic ketoacidosis (DKA). The fact that DKA is more characteristic of type 1 than type 2 diabetes may lead physicians to classify such presentations as type 1 diabetes. However, it should be noted that approximately 25% of type 2 diabetes patients in the general population present with 12

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DKA (Johnson et al., 1980). After initial stabilization with insulin therapy and fl uid repletion, the majority of such patients respond to oral antidiabetic agents, as is typical of type 2 diabetes. Therefore, it is more important to stabilize the patient with drug-related hyperglycemic crisis than to be distracted by a quest for an exact classifi cation in the acute setting. In fact, in many instances, the exact mechanism of the medication-related hyperglycemia remains obscure, and the condition is best assigned to the “Other” category. Approximately 50% of patients with diabetes have hypertension; other chronic comorbidities include dyslipidemia, degenerative joint disease, chronic obstructive pulmonary disease (COPD), sleep apnea, congestive heart failure, aff ective disorders, and peptic ulcer disease. Persons with diabetes also are at risk for infections. These various conditions often require chronic or recurrent treatment with a wide array of medications, some of which could aff ect insulin sensitivity, cell function, or other aspects of glucoregulation. Whenever feasible, preference should be given to those agents that are either neutral or benefi cial in their eff ects on carbohydrate and lipid metabolism. In the sections that follow, diff erent classes of medications will be discussed with regard to their impact on diabetes risk. These medication classes were selected for discussion based either on (a) their historical association with dysglycemia in clinical practice, (b) extensive utilization for the management of comorbid conditions (e.g., hypertension, dyslipidemia) in diabetic patients, or (c) existing or emerging reports of possible association with dysglycemia. Section 3: Steroids and Immunomodulatory Agents GLUCOCORTICOID STEROIDS 13

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In persons with diabetes, systemic glucocorticoid steroid therapy impairs glycemic control by multiple mechanisms. Glucocorticoids induce insulin resistance, inhibit peripheral glucose utilization, stimulate lipolysis, and increase hepatic glucose production (Chan & Cockram, 1991; Andrews et al., 2002). In addition, these steroids inhibit insulin secretion and stimulate glucagon release (Chan & Cockram, 1991; Fallo et al., 2006). For persons with prediabetes and those at high risk for type 2 diabetes, prolonged steroid therapy could worsen glucose tolerance and induce diabetes. The diabetes risk is dependent on the dose and duration of glucocorticoid therapy, but even single doses of potent agents, such as dexamethasone, can induce transient hyperglycemia (Dagogo-Jack et al., 1997). Genetic factors play a prominent role in determining susceptibility: In one study, a family history of diabetes increased the risk of steroid-induced diabetes tenfold (Fajans & Conn, 1954). Other risk factors for steroid-induced diabetes include the potency of steroid preparation, age, weight, decreased -cell capacity, and a history of gestational diabetes ( Heazell et al., 2005; McCullen & Ahmed, 2007) (Table 4). Compared with systemic therapy, inhaled corticosteroids are far less likely to produce adverse eff ects on glucoregulation. However, high doses of topical steroids can induce hyperglycemia (Heazell et al., 2005). Approach to Risk Reduction When systemic glucocorticoid therapy is unavoidable, as in patients with acute severe asthma or transplant recipients, blood glucose levels should be monitored frequently and the antidiabetic regimen should be optimized. Insulin sensitizer drugs and insulin augmentation, alone or in combination, can 14

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help restore glycemic control in most patients with steroidinduced diabetes. Because the metabolic eff ects of glucocorticoids are dose-related, use of the minimum eff ective dose for treatment of the primary condition is recommended. For persons with prediabetes and those at high risk for type 2 diabetes, lifestyle modifi cation (Table 5) has been shown to be eff ective in preventing diabetes, and should be advocated empirically, although there are no specifi c data for the steroid-treated population. In experimental animals,

Table 4 Risk Factors for Steroid-induced Diabetes ■

Family history of diabetes

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Type, dose, and duration of steroid therapy

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History of gestational diabetes

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Overweight/obesity

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Older age

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Decreased insulin secretory capacity

Table 5 Approach to Prevention of Steroid-induced Diabetes ■

Identify risk factors for diabetes (family history, body mass index, etc.)

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Monitor blood glucose frequently in high-risk subjects

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Recommend lifestyle modifi cation for high-risk persons

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Use minimum eff ective dose of glucocorticoid steroid

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Consider alternative-day regimen, if feasible

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Consider metformin for persons with prediabetes (impaired fasting glucose, impaired glucose tolerance)

15

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treatment with etomoxir (an inhibitor of fatty acid oxidation) improves insulin sensitivity and reverses glucocorticoidinduced insulin resistance (Guillaume-Gentil et al., 1993). Theoretically, prophylactic use of insulin sensitizers (e.g., thiazolidinediones [TZDs] and metformin) to prevent diabetes during prolonged steroid therapy is appealing (Willi et al., 2002). However, that would be an “off -label” use of metformin and TZDs; besides, the number needed to treat is unknown, and the merit of such an approach over that of careful monitoring and lifestyle modifi cation is unproven. Nonetheless, for high-risk patients who show evidence of prediabetes (IFG and IGT) before or during prolonged steroid therapy, metformin can be added to lifestyle modifi cation to prevent progression to diabetes (Nathan et al., 2007). ORAL CONTRACEPTIVES AND ESTROGEN REPLACEMENT

Oral contraceptive (OC) drugs containing estrogen and progesterone combinations have been reported to cause glucose intolerance, with elevations in plasma glucose and insulin levels. Depending on the dose and formulation, mild to moderate fl uctuations in blood glucose can occur following initiation of OC therapy (Gaspard, 1987). In one large study, OGTTs were performed in 1,060 women taking one of nine types of oral contraceptives for at least 3 months and 418 women who took none. Two of the formulations were progestin-only agents, and seven were combinations of progestin (150–1,000 μ g) and ethinyl estradiol (30–40 μ g). The combination OCs were associated with a worsening of glucose tolerance. Compared to the control group, women taking OCs had an approximately 50% 16

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increase in the OGTT plasma glucose and an approximately 30% increase in insulin and C-peptide levels, which indicates that exposure to OCs had induced insulin resistance (Godsland et al., 1990). In another report (Nader et al., 1997), 16 hyperandrogenic women tested before and 6 months after receiving desogestrel-containing OC showed deterioration of glucose tolerance (two of them developed diabetes). Progestincontaining formulations are believed to be more liable to induce hyperglycemia, whereas low-dose triphasic OCs appear to be less so (Xiang et al., 2006; Spellacy et al., 1991). However, there are confl icting reports regarding whether a dose–response relationship exists between progestins and glycemia (Godsland et al., 1990; Rosenthal et al., 2004). In general, the OC-induced insulin resistance usually is mild and reversible; it is most likely a steroid eff ect, and can be minimized by selecting preparations with low estrogen and progesterone content. Estrogen replacement therapy in menopausal women has the same potential eff ects on carbohydrate metabolism. In practice, however, diabetes patients on oral contraceptives or estrogen replacement therapy rarely develop signifi cant perturbations in glycemic control. Approach to Risk Reduction Antidiabetic drug doses should be optimized in women with diabetes who experience blood glucose fl uctuations during treatment with OCs (Shawe & Lawrenson, 2003). Other women receiving OCs should be advised to undergo blood glucose testing if they develop symptoms suggestive of diabetes. The prevalence of diabetes in women treated with OCs is unknown, and causality has not been established. Therefore, diabetes (or the risk for diabetes) would not be a 17

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rational contraindication to the appropriate use of OCs. Use of low-dose triphasic formulations may be associated with less metabolic perturbations than higher- dose OCs. FLORINEF

The mineralocorticoid agent, 9--fl uorohydrocortisone (Florinef), is widely prescribed for a variety of indications, including primary adrenal insuffi ciency, orthostatic hypotension, type IV renal tubular acidosis, and other conditions associated with aldosterone defi ciency and hyperkalemia. To date, the clinical use of Florinef has not been associated with diabetes risk in published reports. However, glucose intolerance is a feature of primary hyperaldosteronism, in which the mechanism appears to be mediated by hypokalemia (Fallo et al., 2006). IMMUNOMODULATORY AGENTS

Calcineurin Inhibitors and Posttransplant Diabetes Organ transplantation is an expanding area of modern medical practice, and diabetes is being increasingly diagnosed in organ recipients. Posttransplant diabetes (also known as new-onset diabetes after transplantation, NODAT) refers to the occurrence of diabetes in previously nondiabetic subjects following transplantation. The development of NODAT is associated with adverse clinical outcomes, including renal allograft loss, posttransplant infections, cardiovascular disease, and increased mortality (Cosio et al., 2002; Chapman et al., 2005; Hjelmesaeth et al., 2006). Variable incidence rates of NODAT have been reported over variable intervals among recipients of diff erent organ transplants. The estimated rates of NODAT at 12 months or longer 18

MEDICATIONS AND DIABETES RISK

posttransplant are approximately 20% for kidney transplants, 9%–21% for liver transplants, and approximately 20% for lung transplants (Kasiske et al., 2003; Chadban, 2008; Bonato et al., 2009). Most of the data in this fi eld are derived from analysis of renal transplants, as there is limited information on other types of transplants. The peak incidence of NODAT appears to occur around 3 months posttransplant, but the risk of diabetes persists for much longer. Mechanisms The clinical presentation of NODAT is consistent with type 2 diabetes, and studies have identifi ed insulin-resistance and impaired -cell function as the underlying mechanisms (Hjelmesaeth et al., 2001). The insulin resistance can be induced in previously normoglycemic subjects and aggravated in prediabetic subjects, following organ transplantation. Medications used for posttransplant immunosuppression have been implicated in the pathogenesis of NODAT. The calcineurin inhibitors (tacrolimus and cyclosporine) and steroids have been the most documented drugs associated with the induction of NODAT. However, these agents also are the most widely used immunosuppressive agents in the transplant population, and many other risk factors appear to infl uence the development of NODAT (Table 6) (Vesco et al., 1996; Kasiske et al., 2003). The mechanisms for steroid-induced insulin resistance are well-known and have been discussed in the preceding section; the mechanism whereby calcineurin inhibitors induce insulin resistance is unclear, but these agents are known to inhibit insulin gene transcription and decrease insulin secretion by the cells (Oetjen et al., 2003). 19

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The reported approximately 20% incidence of NODAT for kidney transplant recipients at 1 Table 6 Risk Factors for Posttransplant Diabetes Mellitus Nonmodifi able

Modifi able

Age Race Ethnicity Family history of T2DM

Immunosuppressive regimen Tacrolimus Glucocorticoid steroids; dose and duration Concurrent use of tacrolimus and steroid ■

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■

Acute rejection Obesity Source of organ (cadaver vs. living) Hepatitis-C infection

year means that about 80% of graft recipients can expect to be free from diabetes (Kasiske et al., 2003; Chadban, 2008; Bonato et al., 2009). Thus, immunosuppressive agents induce NODAT in a substantial minority of posttransplant patients, whereas a sizeable majority of such patients escape the diabetes risk, which underscores the contributory roles of other risk factors (Table 6). Notably, the risk of NODAT does not appear to be a class eff ect for the calcineurin inhibitors: In one study, treatment with tacrolimus was associated with a two fold higher incidence of NODAT

20

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(16.8% vs. 8.9%) than cyclosporine (Vincenti et al., 2007). Prediabetes events also were more frequent with tacrolimus. Approach to Management and Risk Reduction The occurrence of NODAT provides opportunity for developing evidence-based strategies for diabetes prevention, yet randomized controlled studies are lacking. Pretransplant lifestyle counseling would be most appropriate for high-risk patients, including those who are overweight or obese, and Table 7 Approach to Prevention of Posttransplant Diabetes Pretransplant Period ■

Document baseline FPG

■

Identify high-risk subjects

■

Initiate lifestyle intervention • Dietary counseling • Exercise counseling

Posttransplant Period ■

Immunosuppressive regimen

■

Minimize steroid dose

persons with a family history of T2DM (Table 1). A screening fasting plasma glucose level or OGTT would help identify subjects with prediabetes (IFG or IGT) during the pretransplant period, so that diabetes prevention counseling could be better targeted (Table 7). The goal of glycemic control in patients with NODAT is similar to the target (A1c 11) and 5.7% were taking antidepressants (Diabetes Prevention Program [DPP] Research Group, 2008). Subjects with elevated BDI scores at baseline and those who ever had elevated BDI scores during the DPP were identifi ed. Cox proportional hazard models were then used to evaluate whether elevated depression symptoms or use of antidepressants predicted progression from prediabetes to type 2 diabetes. After controlling for multiple predictors of diabetes risk (age, gender, fasting glucose, weight change, and ethnicity), elevated BDI scores at baseline or during the DPP study did not predict diabetes risk in any treatment arm. By contrast, use of antidepressant at baseline more than doubled the risk of incident diabetes among participants in the placebo (hazard ratio 2.25 [95% confi dence interval (CI) 1.38– 3.66]) and lifestyle (3.48 [1.93–6.28]) arms (DPP Research Group, 2008). Continuous antidepressant use during the study (vs. never users) also signifi cantly predicted a similar magnitude of diabetes risk in the same subgroups of DPP subjects. Interestingly, subjects in the metformin arm did not show a relationship between antidepressant use and diabetes risk. The association between antidepressant use and diabetes risk in the DPP was seen across all drug classes, including SSRIs and selective norepinephrine reuptake inhibitors (SNRIs). The DPP fi ndings are consistent with recent data from a nested case-control study in a cohort of 165,958 patients with depression in the United Kingdom General Practice Research Database (Andersohn et al., 2009). The U.K. data showed increased diabetes rates for persons receiving longterm (>24 months) treatment with moderate to high daily 53

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doses of tricyclic antidepressants (TCAs) (incidence rate ratio = 1.77, 95% CI = 1.21–2.59) and SSRIs (incidence rate ratio = 2.06, 95% CI = 1.20–3.52). No increase in diabetes risk was observed for shorter courses or lower daily doses of antidepressants. Another study reported higher risk of diabetes for persons receiving combined treatment with SSRIs and TCAs than those treated with TCAs alone (Brown et al., 2008). The exact mechanism(s) for the reported increased risk of diabetes from antidepressants are unclear; the weight gain sometimes associated with TCA use is not suffi cient explanation for the development of diabetes. (In the DPP, use of antidepressants predicted increased diabetes risk after controlling for weight gain.) Moreover, in the DPP, the predominant antidepressants used were SSRIs and related agents, medications generally considered to be weightneutral or even associated with weight loss. One plausible explanation is that antidepressant use probably refl ects severe or chronic of depression, which has a stronger association with diabetes risk than mild depression (Palinkas et al., 1991; Wing et al., 1990). Approach to Risk Reduction Until the exact mechanisms are elucidated, it is prudent to screen for diabetes at baseline and monitor blood glucose levels at reasonable intervals during treatment with all antidepressants. The emerging data also suggest that treatment with lower doses of antidepressants and for shorter durations (24 kg/m2) and fasting plasma glucose in the range of 96–125 mg/dL. The BMI cut-off was lowered to greater than 22 kg/m2 for Asians. 2. Exercise intervention. The DPP exercise goal was 30 minutes of moderate-intensity aerobic activity (equivalent to brisk walking) for 5 days each week (total 150 min/week). 3. Dietary intervention. The participants were coached by dietitians to decrease fat calories to less than 30% and total calories by 500–700 kcals/day by selectively reducing the intake of saturated fats and excessive carbohydrates. 4. Self-monitoring. The participants recorded their food intake and minutes spent performing physical activity each day. Self-monitoring behavior has been shown to predict long-term maintenance of weight loss, and could well have been an important adjunct to the excellent results obtained in the DPP. MEDICATIONS FOR PREVENTION OF DRUG-INDUCED DIABETES

In the DPP, prediabetic subjects assigned to metformin treatment experienced a 31% reduction in the rate of 68

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progression to diabetes (DPP Research Group, 2002). Acarbose and orlistat also have been reported to signifi cantly reduce progression to diabetes, but, like metformin, the effi cacy of these medications was weaker than that of lifestyle intervention. In contrast, thiazolidinediones (TZDs) have been reported to reduce progression by more than 60%, which approximates to the eff ect of lifestyle modifi cation alone (DREAM Investigators, 2006). Also, as already discussed, fi brates have been reported to decrease diabetes risk, and colesevelam improves glycemic control in diabetic patients. However, none of these medications has been approved for prevention of diabetes. The question often arises as to whether high-risk patients receiving chronic treatment with potentially diabetogenic agents (e.g., steroids) should receive prophylactic therapy with medications that have been shown to prevent diabetes. Unfortunately, there is limited specifi c information from randomized controlled trials to inform such a practice. Clearly, randomized controlled studies are needed to demonstrate whether diabetes “pharmacoprophylaxis” is a rational strategy in high-risk persons receiving treatment with potentially diabetogenic drugs. Obvious candidates for such a trial would be metformin, TZDs, acarbose, fi brates, or colesevelam (all of which have pertinent preliminary data), but the newer dipeptidylpeptidase (DPP)-IV inhibitors (sitagliptin and saxagliptin) would also be attractive candidates because of their low risk for iatrogenic hypoglycemia. Although no drug has been approved for diabetes prevention, in subjects with documented prediabetes (impaired fasting glucose or impaired glucose tolerance), an Expert Panel of the American Diabetes Association (ADA) has 69

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recommended that treatment with metformin be considered as an adjunct to diet and exercise for the prevention of type 2 diabetes (Nathan et al., 2007). The ADA recommendation was directed at the general population, but there is no reason why it should not apply to prediabetic patients at risk for drug-induced diabetes, although its effi cacy in preventing drug-induced diabetes has not been tested specifi cally. REFERENCES Abraham MR, Khardori R. (1999). Hyperglycemic hyperosmolar nonketotic syndrome as initial presentation of type 2 diabetes in a young cocaine abuser. Diabetes Care, 22:1380–1381. Adithan C, Srinivas B, Indhiresan J, et al. (1991). Infl uence of type I and type II diabetes mellitus on phenytoin steady-state levels. Int J Clin Pharmacol Ther Toxicol, 29:310–313. Alderman MH. (1992). Which antihypertensive agent fi rst—and why! JAMA, 267:2786–2787. Ambrose PG, Bhavnani SM, Cirincione BB, et al. (2003). Gatifl oxacin and the elderly: pharmacokinetic-pharmacodynamic rationale for a potential age-related dose reduction. J Antimicrob Chemother, S2:434–444. Ames RP. (1986). The effects of antihypertensive drugs on serum lipids and lipoproteins II. Non-diuretic drugs. Drugs, 32: 335– 357. American Diabetes Association. (2004). Consensus Development Conference on antipsychotic drugs and obesity and diabetes. Diabetes Care, 27:596–601. American Diabetes Association. (2009). Standards of Medical Care in Diabetes—2009. Diabetes Care, 32( Suppl 1):S13–S 61. Andersohn F, Schade R, Suissa S, Garbe E. (2009). Long-term use of antidepressants for depressive disorders and the risk of diabetes mellitus. Am J Psychiatry, 166:591–598. 70

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