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Original Contribution |

Risk of Acute Myocardial Infarction, Stroke, Heart Failure, and Death in Elderly Medicare Patients Treated With Rosiglitazone or Pioglitazone FREE

David J. Graham, MD, MPH; Rita Ouellet-Hellstrom, PhD; Thomas E. MaCurdy, PhD; Farzana Ali, BA; Christopher Sholley, BS; Christopher Worrall, BS; Jeffrey A. Kelman, MD, MMSc
[+] Author Affiliations

Author Affiliations: Office of Surveillance and Epidemiology, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland (Drs Graham and Ouellet-Hellstrom); Stanford University, Stanford, California (Dr MaCurdy); Acumen LLC, Burlingame, California (Dr MaCurdy, Ms Ali, and Mr Sholley); and Centers for Medicare & Medicaid Services, Washington, DC (Mr Worrall and Dr Kelman).


JAMA. 2010;304(4):411-418. doi:10.1001/jama.2010.920.
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Published online

Context Studies have suggested that the use of rosiglitazone may be associated with an increased risk of serious cardiovascular events compared with other treatments for type 2 diabetes.

Objective To determine if the risk of serious cardiovascular harm is increased by rosiglitazone compared with pioglitazone, the other thiazolidinedione marketed in the United States.

Design, Setting, and Patients Nationwide, observational, retrospective, inception cohort of 227 571 Medicare beneficiaries aged 65 years or older (mean age, 74.4 years) who initiated treatment with rosiglitazone or pioglitazone through a Medicare Part D prescription drug plan from July 2006-June 2009 and who underwent follow-up for up to 3 years after thiazolidinedione initiation.

Main Outcome Measures Individual end points of acute myocardial infarction (AMI), stroke, heart failure, and all-cause mortality (death), and composite end point of AMI, stroke, heart failure, or death, assessed using incidence rates by thiazolidinedione, attributable risk, number needed to harm, Kaplan-Meier plots of time to event, and Cox proportional hazard ratios for time to event, adjusted for potential confounding factors, with pioglitazone as reference.

Results A total of 8667 end points were observed during the study period. The adjusted hazard ratio for rosiglitazone compared with pioglitazone was 1.06 (95% confidence interval [CI], 0.96-1.18) for AMI; 1.27 (95% CI, 1.12-1.45) for stroke; 1.25 (95% CI, 1.16-1.34) for heart failure; 1.14 (95% CI, 1.05-1.24) for death; and 1.18 (95% CI, 1.12-1.23) for the composite of AMI, stroke, heart failure, or death. The attributable risk for this composite end point was 1.68 (95% CI, 1.27-2.08) excess events per 100 person-years of treatment with rosiglitazone compared with pioglitazone. The corresponding number needed to harm was 60 (95% CI, 48-79) treated for 1 year.

Conclusion Compared with prescription of pioglitazone, prescription of rosiglitazone was associated with an increased risk of stroke, heart failure, and all-cause mortality and an increased risk of the composite of AMI, stroke, heart failure, or all-cause mortality in patients 65 years or older.

Figures in this Article

Rosiglitazone and pioglitazone are the only thiazolidinediones currently marketed in the United States. In mid-2007, a meta-analysis of 42 randomized controlled trials involving rosiglitazone reported a 1.4-fold increase in risk of acute myocardial infarction (AMI) compared with non-thiazolidinedione therapies.1 Subsequently, a meta-analysis of 19 randomized controlled trials with pioglitazone found a statistically significant reduction in the composite outcome of nonfatal AMI, stroke, and all-cause mortality and a nearly statistically significant reduction in nonfatal AMI alone,2 thereby suggesting a potential difference in cardiovascular risk between the 2 thiazolidinediones.

The cardiovascular risks of rosiglitazone and pioglitazone have been compared with one another in several observational studies.311 Rosiglitazone increased AMI risk in 7 studies,36,810 statistically significantly so in 3.3,9,10 Stroke risk was examined in 2 studies, both of which reported a statistically nonsignificant increase with rosiglitazone compared with pioglitazone.5,7 The risk of heart failure was statistically significantly increased with rosiglitazone compared with pioglitazone in 3 studies,5,7,8 with a nonsignificant increase in one other.11 Lastly, the risk of all-cause mortality was statistically significantly increased with rosiglitazone compared with pioglitazone in 2 studies.5,8

The availability of prescription drug data for Medicare beneficiaries, beginning with introduction of the Part D benefit in January 2006, provided an opportunity to investigate whether rosiglitazone increases cardiovascular and mortality risks using a large, nationally representative population of elderly patients with type 2 diabetes newly treated with a thiazolidinedione.

Medicare Database

Medicare is the largest health insurance program in the United States, providing coverage to persons 65 years or older, as well as to persons younger than 65 years, who have end-stage renal disease or are disabled.12,13 Eligibility for Medicare Part A, which covers hospitalization expenses, begins automatically at age 65 years, whereas coverage for outpatient medical care (Part B) and prescription drugs (Part D) must be purchased.13,14 Computerized data for Parts A and B are available from the 1990s, while data for Part D are available since January 2006, when the Medicare prescription drug benefit took effect.

Claims for Parts A, B, and D are evaluated for data quality and entered into an analyzable database, where they are linked with the Medicare Enrollment Database. Together, these provide information about demographic and enrollment characteristics, diagnoses, procedures, prescription drugs, and medical equipment use for each beneficiary. Prescription claims include days of supply and quantities dispensed and are mapped against reference databases to identify drug name and strength using the National Drug Code number.

We restricted the Medicare population to persons enrolled in Parts A and B fee-for-service and Part D, because claims from these sources provide the data needed for research purposes. We linked these claims across all settings of care for each beneficiary, using a unique identifier to create a longitudinal record of each patient's health care utilization and related diagnoses.

Design

This study used a new-user inception cohort design. Patients with at least 6 months of continuous Part D enrollment and at least 12 months of continuous Parts A and B enrollment prior to the date of their first thiazolidinedione prescription and who were 65 years or older on that date were identified; those not resident in a hospital or long-term care facility or receiving hospice care formed the rosiglitazone and pioglitazone inception cohorts.

During the year prior to thiazolidinedione initiation, data were collected for each cohort member on the presence of cardiovascular or cerebrovascular disease, diabetes-related complications, lipid disorders, and other chronic medical conditions. The Charlson comorbidity score was calculated using claims from inpatient hospitalizations.15,16 Data on use of medications prescribed for the treatment of cardiovascular disease, diabetes, and other chronic medical conditions were collected for the 6-month period preceding cohort entry. For purposes of analysis, these baseline variables were separated into 2 categories: core (variables frequently included in analyses of cardiovascular end points) (Table 1 and Table 2) and additional (variables more indicative of general health or that represent medical conditions already captured by prescription drug use included as core variables) (Table 3). Data on race/ethnicity were based on self-declaration at the time of Medicare enrollment and were included to provide an additional measure of cohort comparability.

Table Graphic Jump LocationTable 1. Baseline Characteristics of Cohort Members at Initiation of Thiazolidinedione Therapy
Table Graphic Jump LocationTable 2. Core Cardiovascular Medical Conditions and Medications Used Among Cohort Members During the 12-Month (Medical Conditions) or 6-Month (Medications) Period Preceding Initiation of Thiazolidinedione Therapy
Table Graphic Jump LocationTable 3. Additional Medical Conditions and Medications Used Among Cohort Members During the 12-Month (Medical Conditions) and 6-Month (Medications) Period Preceding Initiation of Thiazolidinedione Therapy
Study End Points

Acute myocardial infarction was defined by International Classification of Diseases, Ninth Revision (ICD-9) code 410 in the first or second position of the hospital discharge diagnosis. In recent studies, code 410 had a positive predictive value (PPV) between 89% and 97% in a variety of US and Canadian administrative claims databases.1721 Of note, code 410 in the first or second position had a PPV of 94% in a recent study using Medicare Part A data.20 Out-of-hospital death occurring within 1 day of an emergency department visit for acute ischemic heart disease was also classified as fatal AMI.22

Stroke was identified by ICD-9 hospital discharge diagnosis codes 430, 431, 433.x1, 434.x1, and 436, located in the first position only. When listed as the first discharge diagnosis, these codes have a PPV of 92% to 100%.2325

Heart failure was identified by ICD-9 hospital discharge diagnosis codes 402.x1, 404.x3, and 428 in the first position only. These codes have a PPV of 85% to 96%.2628

All-cause mortality (referred to as “death” herein) was ascertained by linkage to the Social Security Master Beneficiary Record database, which provides the date, but not cause, of death and captures more than 95% of deaths for persons 65 years or older in the United States.29

Because cardiovascular disease accounts for nearly 70% of deaths in patients with diabetes,30 all-cause mortality may be an indicator of cardiovascular mortality in this study. For this reason, in addition to evaluating the time to event for the individual end points of AMI, stroke, heart failure, and death, we also evaluated the time to event for the composite end point of AMI, stroke, heart failure, or death.

Follow-up and Analysis

New users of rosiglitazone and pioglitazone underwent follow-up from cohort entry until the earliest occurrence of a study end point, a gap in continuous thiazolidinedione treatment exceeding 7 days, a prescription fill for a different thiazolidinedione, a non–end-point hospitalization, or end of the study period (June 30, 2009). To guard against bias arising from informative censoring, most importantly by events leading to death, any end point events occurring within 14 days following a gap in continuous treatment or admission to a hospital were counted in the analysis. This 14-day period of extended follow-up was not applied to thiazolidinedione switching, because it would not be possible to distinguish effects attributable to rosiglitazone from those attributable to pioglitazone, nor was it applied to censoring at the end of the study window because no data were collected after that date.

Baseline characteristics of the thiazolidinedione cohorts were compared using standardized mean differences, calculated as the difference in means or proportions of a variable divided by a pooled estimate of the standard deviation of the variable.31 This measure is not influenced by sample size and is useful for comparing cohorts in large observational studies. A value of 0.1 SD or less indicates a negligible difference in means between groups.31 Kaplan-Meier cumulative incidence plots were generated showing time to event for all end points. Unadjusted incidence rates and rate differences (attributable risk) with 95% confidence intervals (CIs) were calculated using cumulative cohort follow-up time. Hazard ratios (HRs) with 95% CIs were calculated using Cox proportional hazards models, stratified by prior history of a cardiovascular end point and cancer, with adjustment for all remaining covariates (Tables 1, 2, and 3). The proportional hazards assumption was assessed using a test of weighted Schoenfeld residuals.32 The number needed to harm was estimated using the attributable risk.

Preplanned sensitivity analyses included repetition of the main analysis with zero days of follow-up after a gap in thiazolidinedione therapy or hospitalization to identify evidence of informative censoring and repetition of the main analysis restricted to strata defined by baseline treatment with insulin, metformin, sulfonylureas, nitrates, or statins. Several unplanned, post hoc analyses were performed to evaluate the failure of some Cox proportional hazards models to meet the proportional hazards assumption. These unplanned analyses included those restricted to patients who entered the study before or after publication of a widely publicized meta-analysis of rosiglitazone randomized trials on May 21, 2007,1 and partitioning of follow-up time into intervals of 0 through 2 months, more than 2 through 4 months, and more than 4 months.

This study was performed as part of the SafeRx Project, a joint initiative of the Centers for Medicare & Medicaid Services, the US Food and Drug Administration, and the Office of the Assistant Secretary for Planning and Evaluation. It was approved by the Research in Human Subjects Committee of the Food and Drug Administration's Center for Drug Evaluation and Research. Analyses were performed using Stata version 11 (StataCorp, College Station, Texas).

During the study period, 227 571 patients initiated thiazolidinedione therapy and contributed 101 126 to 101 323 person-years of follow-up, depending on the end point analyzed. The mean age was 74.4 years in both cohorts, with a median follow-up of 105 days (range, 1-1093). The cohorts were similar with respect to background characteristics, with the exception of a slight imbalance in the proportion receiving a prescription co-payment subsidy (Table 1). They were also similar with respect to prior medical conditions and medication use (Tables 2 and 3).

During follow-up, there were 1746 AMIs (21.7% fatal), 1052 strokes (7.3% fatal), 3307 hospitalizations for heart failure (2.6% fatal), and 2562 deaths from all causes among cohort members (Table 4). For the composite of AMI, stroke, heart failure, or death, the attributable risk was 1.68 (95% CI, 1.27-2.08) excess events per 100 person-years of rosiglitazone compared with pioglitazone treatment. The corresponding number needed to harm for this composite end point was 60 (95% CI, 48-79) persons treated for 1 year to generate 1 excess event.

Table Graphic Jump LocationTable 4. Incidence Rates, Attributable Risks (Rate Differences), and Numbers Needed to Harm for AMI, Stroke, Heart Failure, All-Cause Mortality, and a Composite Individual End Point in Elderly Medicare Patients Treated With Rosiglitazone vs Pioglitazone

Kaplan-Meier cumulative incidence plots showed no differences in risk for AMI between rosiglitazone and pioglitazone but did show evidence of increased risk of stroke, heart failure, and death and for the composite of all events with rosiglitazone compared with pioglitazone (Figure 1 and Figure 2).

Place holder to copy figure label and caption
Figure 1. Kaplan-Meier Cumulative Incidence of Time to Event for Acute Myocardial Infarction, Stroke, Heart Failure, and All-Cause Mortality in Elderly Medicare Patients Treated With Rosiglitazone or Pioglitazone
Graphic Jump Location

Segment of y-axes shown in blue indicates the range of 0 to 0.02 cumulative proportion.

Place holder to copy figure label and caption
Figure 2. Kaplan-Meier Cumulative Incidence of Time to Event for the Composite of Acute Myocardial Infarction, Stroke, Heart Failure, and All-Cause Mortality in Elderly Medicare Patients Treated With Rosiglitazone or Pioglitazone
Graphic Jump Location

Segment of y-axis shown in blue indicates the range of 0 to 0.02 cumulative proportion.

The adjusted HRs for stroke, heart failure, death, and the composite of AMI, stroke, heart failure, or death were increased for rosiglitazone compared with pioglitazone (Table 4). The adjusted HR for AMI was not significantly increased. The proportional hazards assumption was met for AMI, stroke, and heart failure but not for death or the composite of AMI, stroke, heart failure, or death.

To evaluate the nature and importance of this nonproportionality, we performed a series of unplanned, post hoc analyses. We restricted the cohorts to the 110 950 patients who entered the study prior to the May 21, 2007, publication of the rosiglitazone meta-analysis by Nissen and Wolski.1 Nearly identical results were obtained for the main analysis (eTable 1), and the proportional hazards assumption was now also met for death. An analysis restricted to patients who entered the study after the May 2007 publication date produced results similar to those for the prepublication period (eTable 1). Of note, there were only 15 009 patients receiving rosiglitazone during this latter period, who contributed 5400 person-years of exposed observation time, compared with 101 612 patients receiving pioglitazone who underwent follow-up for 40 400 person-years.

We also partitioned follow-up time into 3 periods and repeated the main analysis for death-related end points using the entire (prepublication and postpublication) study population (eTable 2). The HRs for death and for the composite of AMI, stroke, heart failure, or death were increased with rosiglitazone compared with pioglitazone during the first interval (0 through 2 months), somewhat lower but still increased during the second interval (>2 through 4 months), and were increased to a greater degree during the third interval (>4 months) than during the first. The proportional hazards assumption was met during each follow-up interval for both death-related end points, and the HRs for rosiglitazone compared with pioglitazone were statistically significantly increased during the third and final interval (HR for death, 1.21 [95% CI, 1.05-1.39]; HR for the composite of AMI, stroke, heart failure, or death, 1.23 [95% CI, 1.14-1.34]).

Several preplanned sensitivity analyses were performed. We repeated the main analyses on the entire study population without allowing for the 14-day follow-up after hospital admission or a break in thiazolidinedione use. In this analysis, patients dying after hospital admission or experiencing any study end point shortly after stopping thiazolidinedione were not counted. The risk of stroke and heart failure with rosiglitazone compared with pioglitazone remained statistically significantly increased, as did risk for the composite end point of AMI, stroke, heart failure, or death (eTable 3). With no extended follow-up, the HR for all-cause mortality was no longer increased (1.07 [95% CI, 0.95-1.22]).

We also examined the effect of rosiglitazone compared with pioglitazone on risk of study end points within separate subpopulations defined by baseline use or nonuse of insulin, metformin, sulfonylureas, nitrates, and statins. The HRs for each end point were similar in patients with and without baseline use of these agents (eTable 4).

Use of rosiglitazone was associated with an increased risk of stroke, heart failure, and death and the composite of AMI, stroke, heart failure, or death compared with pioglitazone among Medicare beneficiaries 65 years or older. Both thiazolidinediones have been shown to increase the risk of heart failure compared with treatment with placebo or other antidiabetes medications.33,34 Our study found that rosiglitazone was associated with a 1.25-fold (95% CI, 1.16-1.34) increase in risk of heart failure compared with pioglitazone, similar to the risk increase reported in 2 other studies conducted among elderly persons.5,8 Of note, a differentially increased risk of heart failure with rosiglitazone was also suggested by a meta-analysis of randomized trials for both drugs.35 Heart failure is associated with increased 1-year and 4-year mortality, and this mortality effect is greater in patients with diabetes,36 an effect that would not be captured by our study because follow-up did not continue beyond the acute episode.

We were unable to determine whether one or both thiazolidinediones increase or decrease the absolute risk of any outcome, because we did not have a reference group treated with non-thiazolidinedione medications only. However, these data suggest that rosiglitazone was associated with a 1.27-fold (95% CI, 1.12-1.45) increased risk of stroke and a 1.14-fold (95% CI, 1.05-1.24) increased risk of death compared with pioglitazone. Increased mortality in elderly patients treated with rosiglitazone compared with pioglitazone, of a magnitude similar to that described here, has also been reported in other studies.5,8

The risk of AMI was not different between the 2 thiazolidinediones in this study of elderly Medicare patients. Two other studies conducted in elderly persons (mean age, 72-76 years) also found no difference in AMI risk between the 2 thiazolidinediones.5,8 In contrast, most studies that have reported an increased risk of AMI with rosiglitazone were conducted in younger populations (mean age, 54-65 years), and most required that patients survive to hospitalization to be counted.1,3,4,9,10 There may be no difference in AMI risk between the 2 drugs in elderly persons. However, it is also possible that the pattern of cardiovascular outcomes for rosiglitazone compared with pioglitazone changes with advancing age. The incidence of sudden cardiac death increases nearly 6-fold between the sixth and eighth decades of life,37 perhaps contributing to a shift toward fatal AMI that does not reach hospital to be counted. In an older population of patients with diabetes, in which nearly 70% of deaths have an underlying cardiovascular cause,30 the effect of an increase in sudden cardiac death might be even greater. While the reason for the increased risk of death with rosiglitazone compared with pioglitazone seen in the elderly patients in our study and others is not known,5,8 it is plausibly attributable to an increase in a specific cause rather than to a diffuse increase in all causes of death. We believe that this specific cause is most likely cardiovascular.

The incidence rates of AMI, stroke, heart failure, and death observed for the pioglitazone cohort in our study were similar to those that can be calculated for the pioglitazone group of the PROactive trial, a large cardiovascular end point trial that compared pioglitazone with other diabetes therapies (calculated incidence rates from PROactive, per 100 person-years, were 1.6 for AMI; 1.2 for stroke; 2.8 for heart failure; and 2.4 for death).38 Although the mean age of patients in PROactive was younger than in our cohort (61.1 years vs 74.4 years), the PROactive cohort was rich in patients with established macrovascular disease, thereby making it more similar to an older population with longer-standing diabetes. This similarity in rates suggests that event capture in our study was relatively complete. The event rates in our study were also similar to those obtained by Juurlink et al8 in a study of elderly patients with diabetes from Ontario, Canada.

Based on commercially available drug usage data purchased by the US Food and Drug Administration (SDI, Vector One [VONA]. US national prescription use of rosiglitazone and pioglitazone, 1999-2009. Provided to the Food and Drug Administration under contract), there were an estimated 2.84 million person-years of rosiglitazone use in patients 65 years or older in the United States from 1999-2009. With a number needed to harm of 60 persons treated for 1 year to produce 1 excess event of the composite of AMI, stroke, heart failure, or death attributable to use of rosiglitazone rather than pioglitazone, the negative population effect of rosiglitazone may have been great.

Our study had a number of limitations. This was an observational study, not a randomized trial, and so could be subject to biases arising from confounding. To guard against this, we collected data on a wide array of variables known or suspected to be associated with the outcomes under study, as well as many variables related to general health. The 2 cohorts were virtually indistinguishable with respect to these numerous baseline characteristics. In this regard, other observational studies that directly compared rosiglitazone with pioglitazone also noted a marked similarity between drug groups with respect to baseline characteristics and risk factors,39 suggesting that the thiazolidinediones are probably prescribed to comparable types of patients. Misclassification of exposure or outcome is another potential limitation of observational studies but usually acts to reduce the strength of associations. We did not independently validate the diagnoses of AMI, stroke, or heart failure. There is currently no mechanism in place under the SafeRx Project to obtain medical record data. However, the ICD-9 diagnosis–coded case definitions that we adhered to in this study have been consistently well-validated in previous studies using the same or similar hospitalization claims data.1728 Lastly, because prescription drug data from Medicare Part D have not been used extensively for purposes of comparative safety, issues related to data quality must be considered. The Medicare Part D data are collected and processed by the Centers for Medicare & Medicaid Services in exactly the same manner as prescription data from Medicaid, which have been shown to be complete and of high quality.39

In conclusion, in a population of more than 227 000 patients 65 years or older who initiated treatment with a thiazolidinedione, we found that, compared with pioglitazone, rosiglitazone was associated with an increased risk of stroke, heart failure, and death and an increased risk of the composite of AMI, stroke, heart failure, or death.

Corresponding Author: David J. Graham, MD, MPH, Office of Surveillance and Epidemiology, Center for Drug Evaluation and Research, US Food and Drug Administration, 10903 New Hampshire Ave, Bldg 22, Room 4314, Silver Spring, MD 20993-0002 (david.graham1@fda.hhs.gov).

Published Online: June 28, 2010. doi:10.1001/jama.2010.920

Author Contributions: Dr MaCurdy had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Graham, Ouellet-Hellstrom, Kelman.

Acquisition of data: Worrall.

Analysis and interpretation of data: Graham, Ouellet-Hellstrom, MaCurdy, Ali, Sholley, Kelman.

Drafting of the manuscript: Graham, Ouellet-Hellstrom.

Critical revision of the manuscript for important intellectual content: Graham, Ouellet-Hellstrom, MaCurdy, Ali, Sholley, Worrall, Kelman.

Statistical analysis: Graham, Ouellet-Hellstrom, MaCurdy, Ali, Sholley.

Obtained funding: Graham, Worrall, Kelman.

Administrative, technical, or material support: Ouellet-Hellstrom, Worrall, Kelman.

Study supervision: Graham, MaCurdy.

Financial Disclosures: None reported.

Funding/Support: This study was funded by the Office of the Assistant Secretary for Planning and Evaluation (ASPE), the Centers for Medicare & Medicaid Services (CMS), and the US Food and Drug Administration (FDA).

Role of Sponsors: The authors are employees or contractors of the CMS or the FDA; however, other officials at the ASPE, the CMS, and the FDA had no role in the design and conduct of the study; the collection, analysis, and interpretation of the data; or the preparation, review, or approval of the manuscript. The manuscript was subject to administrative review prior to submission, but the content was not altered by this review.

Disclaimer: The views expressed are those of the authors and not necessarily those of the US Department of Health and Human Services, the CMS, or the FDA.

Additional Contributions: We thank the Office of the Assistant Secretary for Planning and Evaluation in the Department of Health and Human Services for scientific contributions and financial support of this study and the SafeRx Project. We also extend special thanks to Mark Levenson, PhD, and Stephine Keeton, PhD (both with the FDA Office of Biostatistics), for providing statistical advice and to Pallavi Mukherji, MSc, Richard Domurat, BS, Jonathan Gibbs, BA, and Konrad Turski, MSc (all with Acumen LLC), for assistance with programming and data analysis. These individuals are salaried employees of their respective organizations and received no additional compensation related to their contributions to this study.

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Choma NN, Griffin MR, Huang RL,  et al.  An algorithm to identify incident myocardial infarction using Medicaid data.  Pharmacoepidemiol Drug Saf. 2009;18(11):1064-1071
PubMed   |  Link to Article
Chung CP, Murry KT, Stein CM, Hall K, Ray WA. A computer case definition for sudden cardiac death [published online ahead of print December 22, 2009].  Pharmacoepidemiol Drug Saf. 2009;19(6):563-572
PubMed  |  Link to Article   |  Link to Article
Tirschwell DL, Longstreth WT Jr. Validating administrative data in stroke research.  Stroke. 2002;33(10):2465-2470
PubMed   |  Link to Article
Roumie CL, Mitchel E, Gideon PS, Varas-Lorenzo C, Castellsague J, Griffin MR. Validation of ICD-9 codes with a high positive predictive value for incident stroke resulting in hospitalization using Medicaid health data.  Pharmacoepidemiol Drug Saf. 2008;17(1):20-26
PubMed   |  Link to Article
Kokotailo RA, Hill MD. Coding of stroke and stroke risk factors using International Classification of Diseases, revisions 9 and 10.  Stroke. 2005;36(8):1776-1781
PubMed   |  Link to Article
Birman-Deych E, Waterman AD, Yan Y, Nilasena DS, Radford MJ, Gage BF. Accuracy of ICD-9-CM codes for identifying cardiovascular and stroke risk factors.  Med Care. 2005;43(5):480-485
PubMed   |  Link to Article
Goff DC Jr, Pandey DK, Chan FA, Ortiz C, Nichaman MZ. Congestive heart failure in the United States: is there more than meets the I(CD code)? the Corpus Christi Heart Project.  Arch Intern Med. 2000;160(2):197-202
PubMed   |  Link to Article
Jong P, Gong Y, Liu PP, Austin PC, Lee DS, Tu JV. Care and outcomes of patients newly hospitalized for heart failure in the community treated by cardiologists compared with other specialists.  Circulation. 2003;108(2):184-191
PubMed   |  Link to Article
Hill ME, Rosenwaike I. The Social Security Administration's Death Master File: the completeness of death reporting at older ages.  Soc Secur Bull. 2001-2002;64(1):45-51
PubMed
Centers for Disease Control and Prevention.  National Diabetes Fact Sheet, 2007: general information and national estimates on diabetes in the United States, 2007. Centers for Disease Control and Prevention Web site. http://www.cdc.gov/diabetes/pubs/pdf/ndfs_2007.pdf. 2008. Accessed April 20, 2010
Mamdani M, Sykora K, Li P,  et al.  Reader's guide to critical appraisal of cohort studies, 2: Assessing potential for confounding.  BMJ. 2005;330(7497):960-962
PubMed   |  Link to Article
Grambsch PM, Therneau TM. Proportional hazards tests and diagnostics based on weighted residuals.  Biometrika. 1994;81:515-526
Link to Article
 Actos (pioglitazone hydrochloride) [product label]. Deerfield, IL: Takeda Pharmaceuticals America Inc; 2008
 Avandia (rosiglitazone) [product label]. Research Triangle Park, NC: GlaxoSmithKline; 2008
Lago RM, Singh PP, Nesto RW. Congestive heart failure and cardiovascular death in patients with prediabetes and type 2 diabetes given thiazolidinediones: a meta-analysis of randomised clinical trials.  Lancet. 2007;370(9593):1129-1136
PubMed   |  Link to Article
Barsheshet A, Shotan A, Cohen E,  et al.  Predictors of long-term (4-year) mortality in elderly and young patients with acute heart failure [published online ahead of print May 21, 2010].  Eur J Heart FailLink to Article
Zheng ZJ, Croft JB, Giles WH, Mensah GA. Sudden cardiac death in the United States, 1989 to 1998.  Circulation. 2001;104(18):2158-2163
PubMed   |  Link to Article
Dormandy JA, Charbonnel B, Eckland DJA,  et al; PROactive Investigators.  Secondary prevention of macrovascular events in patients with type 2 diabetes in the PROactive Study (PROspective pioglitAzone Clinical Trial In macroVascular Events): a randomised controlled trial.  Lancet. 2005;366(9493):1279-1289
PubMed   |  Link to Article
Hennessy S, Leonard CE, Palumbo CM, Newcomb C, Bilker WB. Quality of Medicaid and Medicare data obtained through Centers for Medicare and Medicaid Services (CMS).  Med Care. 2007;45(12):1216-1220
PubMed   |  Link to Article

Figures

Place holder to copy figure label and caption
Figure 1. Kaplan-Meier Cumulative Incidence of Time to Event for Acute Myocardial Infarction, Stroke, Heart Failure, and All-Cause Mortality in Elderly Medicare Patients Treated With Rosiglitazone or Pioglitazone
Graphic Jump Location

Segment of y-axes shown in blue indicates the range of 0 to 0.02 cumulative proportion.

Place holder to copy figure label and caption
Figure 2. Kaplan-Meier Cumulative Incidence of Time to Event for the Composite of Acute Myocardial Infarction, Stroke, Heart Failure, and All-Cause Mortality in Elderly Medicare Patients Treated With Rosiglitazone or Pioglitazone
Graphic Jump Location

Segment of y-axis shown in blue indicates the range of 0 to 0.02 cumulative proportion.

Tables

Table Graphic Jump LocationTable 1. Baseline Characteristics of Cohort Members at Initiation of Thiazolidinedione Therapy
Table Graphic Jump LocationTable 2. Core Cardiovascular Medical Conditions and Medications Used Among Cohort Members During the 12-Month (Medical Conditions) or 6-Month (Medications) Period Preceding Initiation of Thiazolidinedione Therapy
Table Graphic Jump LocationTable 3. Additional Medical Conditions and Medications Used Among Cohort Members During the 12-Month (Medical Conditions) and 6-Month (Medications) Period Preceding Initiation of Thiazolidinedione Therapy
Table Graphic Jump LocationTable 4. Incidence Rates, Attributable Risks (Rate Differences), and Numbers Needed to Harm for AMI, Stroke, Heart Failure, All-Cause Mortality, and a Composite Individual End Point in Elderly Medicare Patients Treated With Rosiglitazone vs Pioglitazone

References

Nissen SE, Wolski K. Effect of rosiglitazone on the risk of myocardial infarction and death from cardiovascular causes.  N Engl J Med. 2007;356(24):2457-2471
PubMed   |  Link to Article
Lincoff AM, Wolski K, Nicholls SJ, Nissen SE. Pioglitazone and risk of cardiovascular events in patients with type 2 diabetes mellitus: a meta-analysis of randomized trials.  JAMA. 2007;298(10):1180-1188
PubMed   |  Link to Article
Gerrits CM, Bhattacharya M, Manthena S, Baran R, Perez A, Kupfer S. A comparison of pioglitazone and rosiglitazone for hospitalization for acute myocardial infarction in type 2 diabetes.  Pharmacoepidemiol Drug Saf. 2007;16(10):1065-1071
PubMed   |  Link to Article
Walker AM, Koro CE, Landon J. Coronary heart disease outcomes in patients receiving antidiabetic agents in the PharMetrics database 2000-2007.  Pharmacoepidemiol Drug Saf. 2008;17(8):760-768
PubMed   |  Link to Article
Winkelmayer WC, Setoguchi S, Levin R, Solomon DH. Comparison of cardiovascular outcomes in elderly patients with diabetes who initiated rosiglitazone vs pioglitazone therapy.  Arch Intern Med. 2008;168(21):2368-2375
PubMed   |  Link to Article
Dormuth CR, Maclure M, Carney G, Schneeweiss S, Bassett K, Wright JM. Rosiglitazone and myocardial infarction in patients previously prescribed metformin.  PLoS One. 2009;4(6):e6080
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Habib ZA, Tzogias L, Havstad SL,  et al.  Relationship between thiazolidinedione use and cardiovascular outcomes and all-cause mortality among patients with diabetes: a time-updated propensity analysis.  Pharmacoepidemiol Drug Saf. 2009;18(6):437-447
PubMed   |  Link to Article
Juurlink DN, Gomes T, Lipscombe LL, Austin PC, Hux JE, Mamdani MM. Adverse cardiovascular events during treatment with pioglitazone and rosiglitazone: population based cohort study.  BMJ. 2009;339:b2942
PubMed   |  Link to Article
Ziyadeh N, McAfee AT, Koro C, Landon J, Arnold Chan K. The thiazolidinediones rosiglitazone and pioglitazone and the risk of coronary heart disease: a retrospective cohort study using a US health insurance database.  Clin Ther. 2009;31(11):2665-2677
PubMed   |  Link to Article
Brownstein JS, Murphy SN, Goldfine AB,  et al.  Rapid identification of myocardial infarction risk associated with diabetes medications using electronic medical records.  Diabetes Care. 2010;33(3):526-531
PubMed   |  Link to Article
Pantalone KM, Kattan MW, Yu C,  et al.  The risk of developing coronary artery disease or congestive heart failure, and overall mortality, in type 2 diabetic patients receiving rosiglitazone, pioglitazone, metformin, or sulfonylureas: a retrospective analysis.  Acta Diabetol. 2009;46(2):145-154
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Office of the Assistant Secretary for Planning and Evaluation, Department of Health and Human Services.  Overview of the uninsured in the United States: an analysis of the 2005 Current Population Survey. Dept of Health and Human Services Web site. http://aspe.hhs.gov/health/reports/05/uninsured-cps/ib.pdf. 2005. Accessed April 21, 2006
Centers for Medicare & Medicaid Services.  Medicare program-general information: overview. Centers for Medicare & Medicaid Services Web site. http://www.cms.gov/MedicareGenInfo/. Accessed April 6, 2009
Centers for Medicare & Medicaid Services.  Prescription drug coverage-general information: overview. Centers for Medicare & Medicaid Services Web site. http://www.cms.gov/PrescriptionDrugCovGenIn/. Accessed April 6, 2009
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Deyo RA, Cherkin DC, Ciol MA. Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases.  J Clin Epidemiol. 1992;45(6):613-619
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Petersen LA, Wright S, Normand SL, Daley J. Positive predictive value of the diagnosis of acute myocardial infarction in an administrative database.  J Gen Intern Med. 1999;14(9):555-558
PubMed   |  Link to Article
Levy AR, Tamblyn RM, Fitchett D, McLeod PJ, Hanley JA. Coding accuracy of hospital discharge data for elderly survivors of myocardial infarction.  Can J Cardiol. 1999;15(11):1277-1282
PubMed
Austin PC, Daly PA, Tu JV. A multicenter study of the coding accuracy of hospital discharge administrative data for patients admitted to cardiac care units in Ontario.  Am Heart J. 2002;144(2):290-296
PubMed   |  Link to Article
Kiyota Y, Schneeweiss S, Glynn RJ, Cannuscio CC, Avorn J, Solomon DH. Accuracy of Medicare claims-based diagnosis of acute myocardial infarction: estimating positive predictive value on the basis of review of hospital records.  Am Heart J. 2004;148(1):99-104
PubMed   |  Link to Article
Choma NN, Griffin MR, Huang RL,  et al.  An algorithm to identify incident myocardial infarction using Medicaid data.  Pharmacoepidemiol Drug Saf. 2009;18(11):1064-1071
PubMed   |  Link to Article
Chung CP, Murry KT, Stein CM, Hall K, Ray WA. A computer case definition for sudden cardiac death [published online ahead of print December 22, 2009].  Pharmacoepidemiol Drug Saf. 2009;19(6):563-572
PubMed  |  Link to Article   |  Link to Article
Tirschwell DL, Longstreth WT Jr. Validating administrative data in stroke research.  Stroke. 2002;33(10):2465-2470
PubMed   |  Link to Article
Roumie CL, Mitchel E, Gideon PS, Varas-Lorenzo C, Castellsague J, Griffin MR. Validation of ICD-9 codes with a high positive predictive value for incident stroke resulting in hospitalization using Medicaid health data.  Pharmacoepidemiol Drug Saf. 2008;17(1):20-26
PubMed   |  Link to Article
Kokotailo RA, Hill MD. Coding of stroke and stroke risk factors using International Classification of Diseases, revisions 9 and 10.  Stroke. 2005;36(8):1776-1781
PubMed   |  Link to Article
Birman-Deych E, Waterman AD, Yan Y, Nilasena DS, Radford MJ, Gage BF. Accuracy of ICD-9-CM codes for identifying cardiovascular and stroke risk factors.  Med Care. 2005;43(5):480-485
PubMed   |  Link to Article
Goff DC Jr, Pandey DK, Chan FA, Ortiz C, Nichaman MZ. Congestive heart failure in the United States: is there more than meets the I(CD code)? the Corpus Christi Heart Project.  Arch Intern Med. 2000;160(2):197-202
PubMed   |  Link to Article
Jong P, Gong Y, Liu PP, Austin PC, Lee DS, Tu JV. Care and outcomes of patients newly hospitalized for heart failure in the community treated by cardiologists compared with other specialists.  Circulation. 2003;108(2):184-191
PubMed   |  Link to Article
Hill ME, Rosenwaike I. The Social Security Administration's Death Master File: the completeness of death reporting at older ages.  Soc Secur Bull. 2001-2002;64(1):45-51
PubMed
Centers for Disease Control and Prevention.  National Diabetes Fact Sheet, 2007: general information and national estimates on diabetes in the United States, 2007. Centers for Disease Control and Prevention Web site. http://www.cdc.gov/diabetes/pubs/pdf/ndfs_2007.pdf. 2008. Accessed April 20, 2010
Mamdani M, Sykora K, Li P,  et al.  Reader's guide to critical appraisal of cohort studies, 2: Assessing potential for confounding.  BMJ. 2005;330(7497):960-962
PubMed   |  Link to Article
Grambsch PM, Therneau TM. Proportional hazards tests and diagnostics based on weighted residuals.  Biometrika. 1994;81:515-526
Link to Article
 Actos (pioglitazone hydrochloride) [product label]. Deerfield, IL: Takeda Pharmaceuticals America Inc; 2008
 Avandia (rosiglitazone) [product label]. Research Triangle Park, NC: GlaxoSmithKline; 2008
Lago RM, Singh PP, Nesto RW. Congestive heart failure and cardiovascular death in patients with prediabetes and type 2 diabetes given thiazolidinediones: a meta-analysis of randomised clinical trials.  Lancet. 2007;370(9593):1129-1136
PubMed   |  Link to Article
Barsheshet A, Shotan A, Cohen E,  et al.  Predictors of long-term (4-year) mortality in elderly and young patients with acute heart failure [published online ahead of print May 21, 2010].  Eur J Heart FailLink to Article
Zheng ZJ, Croft JB, Giles WH, Mensah GA. Sudden cardiac death in the United States, 1989 to 1998.  Circulation. 2001;104(18):2158-2163
PubMed   |  Link to Article
Dormandy JA, Charbonnel B, Eckland DJA,  et al; PROactive Investigators.  Secondary prevention of macrovascular events in patients with type 2 diabetes in the PROactive Study (PROspective pioglitAzone Clinical Trial In macroVascular Events): a randomised controlled trial.  Lancet. 2005;366(9493):1279-1289
PubMed   |  Link to Article
Hennessy S, Leonard CE, Palumbo CM, Newcomb C, Bilker WB. Quality of Medicaid and Medicare data obtained through Centers for Medicare and Medicaid Services (CMS).  Med Care. 2007;45(12):1216-1220
PubMed   |  Link to Article
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