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Abstract

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Appendix 1
  7. References

We examined the association of hepatitis C virus (HCV) infection with diabetes in veterans infected with human immunodeficiency virus (HIV) before and after the institution of highly active antiretroviral therapy (HAART). The role of age, race, liver disease, alcohol, and drug diagnoses upon the risk of diabetes was also determined. Male veterans with HIV who entered care between 1992 and 2001 were identified from the Veterans Affairs (VA) administrative database. Demographic and disease data were extracted. Kaplan-Meier curves were plotted to determine the incidence of diabetes. Unadjusted and adjusted hazards ratios for diabetes were determined using Cox regression method. A total of 26,988 veterans were studied. In multivariate Cox regression analysis, factors associated with a diagnosis of diabetes included increasing age (HR, 1.44 per 10-year increase in age; 95% CI, 1.39–1.49), minority race (African American: HR, 1.35; 95% CI, 1.24–1.48; Hispanic: HR, 1.63; 95% CI, 1.43–1.86), and care in the HAART era (HR, 2.35; 95% CI, 2.01–2.75). There was a significant interaction between care in the HAART era and HCV infection, with HCV infection being associated with a significant risk of diabetes in the HAART era (HR, 1.39; 95% CI, 1.27–1.53) but not in the pre-HAART era (HR, 1.01; 95% CI, 0.75–1.36). In conclusion, HIV-infected veterans in the HAART era are at a higher risk for diabetes compared with those in the pre-HAART era. HCV coinfection is associated with a significantly higher risk of diabetes in the HAART era, but not in the pre-HAART era. HCV-HIV coinfected patients should be aggressively screened for diabetes. (HEPATOLOGY 2004;40:115–119.)

About 1.8% of the U.S. population is infected with the hepatitis C virus (HCV). This translates to over 4 million Americans' being HCV antibody–positive. Of these, over 2.7 million are estimated to be chronically infected, as determined by persistent HCV viremia, making this the most common chronic blood-borne viral infection.1 Because of shared routes of transmission and similarity in demographics of infected patients, a large number of patients infected with human immunodeficiency virus (HIV) are coinfected with HCV.

An association between HCV infection and diabetes mellitus (diabetes) has been reported by various authors.2, 3 Persons with HCV who are 40 years of age or older are greater than 3 times more likely to have diabetes than those of the same age without HCV infection.2 In a study of 1,117 patients with chronic viral hepatitis, 21% of HCV-infected patients had a diagnosis of diabetes, compared with 12% of patients infected with hepatitis B virus.4 Among HIV-infected injection-drug users, receipt of highly active antiretroviral therapy (HAART) for more than 1 year, with or without a protease inhibitor, has been associated with a higher risk for diabetes.5 Other studies have also demonstrated an association between protease inhibitor use and diabetes in HIV-infected patients.6, 7

We undertook this study to determine whether care in the HAART era increased the risk for diabetes in HIV-infected veterans. We also sought to quantify the association of HCV with diabetes in these veterans, and to understand the role of age, race, and alcohol and drug use upon the risk for diabetes. Since both HCV- and HIV-infected patients appear to have an increased risk of diabetes, either directly or because of the treatment prescribed, we hypothesized that HCV-HIV coinfected patients in the HAART era will have a higher risk of diabetes than those with HIV infection alone. Veterans receiving care in the Veterans Health Administration provide a unique study population due to the availability of administrative data on all patients in the Veterans Health Administration and a higher prevalence of infections with HCV, HIV or both than the general population.8–10

Methods

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Appendix 1
  7. References

We adapted an algorithm used by Fasciano et al.11 to identify HIV positive patients using Veterans Affairs (VA) electronic medical record inpatient and outpatient diagnosis codes from fiscal years (FY) 1992 through 2001. Our program searched for the International Classification of Diseases, 9th Revision (ICD-9), Clinical Modification diagnosis codes for AIDS (042-044), asymptomatic HIV (044.9 and V08), inconclusive HIV test results (795.8), and related Diagnostic Related Group codes (488-490). The VA began keeping national files in FY 1970. Our study utilized the inpatient diagnostic codes from FY 1992 to FY 1997 and inpatient and outpatient diagnostic codes from FY 1997 onward, when outpatient diagnostic codes became available. For this study, the HAART era was defined as period after October 1, 1996. To account for the effect of crossing over from the pre-HAART to the HAART era, multiple records were created for veterans who received care in both time periods, with first record being right censored September 30, 1996, and second record beginning October 1, 1996.

Data on age, race, history of and first date of HIV, HCV and diabetes diagnoses in the VA Healthcare System, and history of alcohol- and drug-related diagnoses were extracted from the VA administrative database. Data on the presence of end-stage liver disease within 6 months of entering the cohort were also retrieved. The disease data was also based on ICD-9 codes. The ICD-9 codes for HIV and HCV have been prospectively validated in the Veterans Aging Cohort Study 3-site (VACS-3). We validated the ICD-9 codes used against laboratory tests for HCV infection (HCV antibody test positive); agreement was 78% (kappa 0.42). Positive predictive value was 94%. We also validated the ICD-9 codes used for a diagnosis of diabetes against manual chart abstraction; agreement was 91.1% (kappa 0.54). Positive predictive value was 88.9%. The outcome variable was time to first diagnosis of diabetes from the time of entry into the VA system. We excluded veterans who had a first diagnosis of diabetes on or before the first observation date in the database (to exclude prevalent diabetes). The ICD-9 codes used are listed in the Appendix.

The time to development of diabetes was examined using the Kaplan-Meier method between veterans who received care in the pre-HAART and the HAART era, between HCV coinfected and HCV uninfected veterans, and by age group. Log rank test was used to detect differences between the above groups. Univariate and multivariate Cox proportional hazards regression analysis was used to determine the hazard ratios for the predictor variables. All analyses were performed using the Stata version 7.0 (Stata Corporation, College Station, TX).

Results

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Appendix 1
  7. References

A total of 30,174 veterans were identified. Of these, 3,186 had a diagnosis of diabetes at or before entry into study period and were dropped from further analysis. Of the 26,988 veterans in the final analysis, 9.5% had a diagnosis of diabetes during the study period (incident diabetes) and 22.8% had a diagnosis of HCV infection. End-stage liver disease diagnoses were recoded within 90 days of entering the cohort in 7.8%. Diagnoses of alcohol abuse or dependence were recorded in 39.7%, and diagnoses of drug abuse or dependence were recorded in 40.6% during the study period (Table 1).

Table 1. Baseline Characteristics of the Veterans Studied
 % of Veterans (n = 26,988)
  • *

    Excludes patients with prevalent diabetes at entry into the cohort.

Age 
 <4035.1
 40–6055.1
 >609.8
Race 
 White42.9
 African American48.2
 Hispanic8.9
Hepatitis C22.8
Incident diabetes9.5*
End-stage liver disease7.8
Diagnosis of alcohol abuse or dependence39.7
Diagnosis of drug abuse or dependence40.6

Veterans cared for in the HAART era had a significantly higher rate of diabetes than those cared for entirely in the pre-HAART era (P < .0005, Fig. 1). Follow-up time is from the date of first HIV diagnosis. Subjects in care on September 30, 1996, crossed over to the HAART era. HCV coinfection was associated with a significantly higher rate of diabetes during the period of follow up (P < .0005, Fig. 2). The rate of diabetes increased significantly with increasing age (P < .0005, Fig. 3). There was an interaction between HCV and care in the HAART era, with HCV being associated with a significantly higher risk of diabetes in the HAART era (P < .0005) but not in the pre-HAART era (P = .24) (Fig. 4).

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Figure 1. Kaplan-Meier estimates of diabetes in veterans followed in the pre-HAART and HAART eras. P < .0005 by log rank test.

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Figure 2. Kaplan-Meier estimates of diabetes by HCV diagnosis. P < .0005 by log rank test. HCV, hepatitis C virus.

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Figure 3. Kaplan-Meier estimates of diabetes by age category. P < .0005 by log rank test.

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Figure 4. Kaplan-Meier estimates of diabetes by HCV diagnosis in the pre-HAART vs the HAART era. P < .0005 for the HAART era, P < .24 for the pre-HAART era, by log rank test.

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In univariate Cox proportional hazards analyses, the following factors were positively associated with a diagnosis of diabetes: increasing age (hazard ratio [HR], 1.50 for each 10-year increase in age; 95% CI, 1.45–1.54); minority race (African American: HR, 1.18; 95% CI, 1.08–1.28; Hispanic: HR, 1.51; 95% CI, 1.33–1.73); HCV coinfection (HR, 1.23; 95% CI, 1.13–1.33); and care in the HAART era (HR, 3.25; 95% CI, 2.85–3.71). Diagnoses of alcohol abuse or dependence and diagnoses of drug abuse or dependence were negatively associated with a diagnosis of diabetes (Table 2). In multivariate Cox regression analysis, factors positively associated with a diagnosis of diabetes included increasing age (HR, 1.44 for each 10-year increase in age; 95% CI 1.39–1.49), minority race (African American: HR, 1.35; 95% CI, 1.24–1.48; Hispanic: HR 1.63; 95% CI, 1.43–1.86) and care in the HAART era (HR, 2.35; 95% CI, 2.01–2.75). Drug-related diagnosis was negatively associated with a risk of diabetes (HR, 0.88; 95% CI, 0.79–0.98) Having a diagnosis of end-stage liver disease within 90 days of entering care was not associated with a higher risk of diabetes in univariate or multivariate analysis.

Table 2. Factors Associated With the Risk of Diabetes
 Hazards Ratio
Univariate*Multivariate*
  • *

    Cox proportional hazards model.

Age (10-year increments)1.50 (1.45–1.54)1.44 (1.39–1.49)
Race (compared with white)  
 African American1.18 (1.08–1.28)1.35 (1.24–1.48)
 Hispanic1.51 (1.33–1.73)1.63 (1.43–1.86)
Hepatitis C1.23 (1.13–1.33)0.93 (0.71–1.23)
End-stage liver disease1.16 (0.99–1.35)1.11 (0.95–1.30)
Care in HAART era3.25 (2.85–3.71)2.35 (2.01–2.75)
Alcohol diagnosis0.84 (0.77–0.90)0.95 (0.86–1.05)
Drug diagnosis0.76 (0.71–0.83)0.88 (0.79–0.98)
HCV-HAART era interaction1.61 (1.48–1.76)1.51 (1.13–2.01)

There was a significant interaction between HCV coinfection and care in the HAART era indicating a differential effect of HCV upon the risk of diabetes in the pre-HAART versus the HAART era. We examined this finding further by repeating our analysis in the pre-HAART versus the HAART era (Table 3). The hazard associated with HCV in the pre-HAART era was not significant (HR, 1.01; 95% CI, 0.75–1.36), while HCV was associated with a significantly increased hazard of diabetes in the HAART era (HR, 1.39; 95% CI, 1.27–1.53). There was also an interaction between care in the HAART era and a drug-related diagnosis, with a lower hazard in the pre-HAART era (HR, 0.56; 95% CI, 0.40–0.77), but no significant association in the HAART era (HR, 0.92; 95% CI, 0.82–1.03). No other interaction terms with the HAART era were found to be significant in the multivariate analysis.

Table 3. Hazards of Diabetes in the Pre-HAART and HAART Eras
 Hazards Ratio*
Pre-HAART EraHAART Era
  • *

    Multivariate Cox proportional hazards model.

Age (10-year increments)1.36 (1.20–1.54)1.45 (1.40–1.50)
Race (compared with white)  
 African American1.73 (1.30–2.31)1.32 (1.20–1.45)
 Hispanic2.12 (1.41–3.20)1.59 (1.38–1.83)
Hepatitis C1.01 (0.75–1.36)1.39 (1.27–1.53)
End-stage liver disease1.03 (0.65–1.63)1.12 (0.95–1.33)
Alcohol diagnosis1.02 (0.75–1.38)0.93 (0.84–1.04)
Drug diagnosis0.56 (0.40–0.77)0.92 (0.82–1.03)

Discussion

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Appendix 1
  7. References

We found that receiving care in the HAART era is associated with a significantly higher risk of diabetes in veterans with HIV infection. HCV coinfection was also associated with a higher risk in the HAART era but not in the pre-HAART era. There are three possible explanations for this finding. First, patients are living much longer in the HAART era, resulting in a longer period in which HCV infection may exert its effect. Second, increasing age is one of the strongest risk factors for diabetes, and this increased risk may be due to the longevity of life seen in the HIV-infected veterans in the HAART era. Third, there may be an interaction between HCV and medications in the HAART regimen that may lead to an increased risk of diabetes.

Veterans in the HAART era were more likely to be diagnosed with HCV and diabetes. Other investigators have also reported an increased risk of diabetes among patients on HAART.6, 7 This increase may be partially attributable to enhanced testing in recent years. Another factor contributing to a higher risk of diabetes in the HAART era may be increasing age with improved antiretroviral therapy and survival. Increasing age and care in the HAART era were independently associated with a higher risk of diabetes after adjusting for other factors. These results point to the multifactorial etiology of the association of diabetes in HIV-infected veterans. Hepatitis C virus infection was also independently associated with an increased risk of diabetes, after adjusting for age and minority race, in the HAART era.

A major strength of our study is the large number of patients studied, conferring more precise estimates of risk and enhancing our ability to compare rates of diabetes among HIV-infected individuals in care both before and after the advent of HAART. Using period of care as a surrogate for HAART use, the same factors (minority race, increasing age) strongly predicted diabetes in the pre-HAART as well as the HAART era. Additionally, we have fair estimates of the dates of diagnoses for diabetes, enabling us to study the incidence as opposed to the mere prevalence of diabetes, thus giving us a measure of the risk associated with the factors studied. Most previous studies have reported on the prevalence of diabetes in these groups with the limitation of not knowing which event (diabetes, HCV, or HIV) occurred first.

There are several limitations to our study. It is an analysis of administrative data that relied upon clinical diagnoses made during the course of routine care; patients were not prospectively screened for diabetes. Thus our incidence estimates are likely to be low. Since data is gathered from many centers nationally, there may be local variations in reporting of diagnoses. However, the ICD-9 diagnostic codes for HCV, HIV, and diabetes have been prospectively validated in the Veterans Aging 3-site Cohort Study using laboratory data and chart review, and there is good correlation between these diagnoses and ICD-9 codes. An important limitation in the administrative data is the lack of body mass index and family history of diabetes, two important risk factors for the development of diabetes.

We used October 1,1996, as a cutoff for the introduction of HAART. Specific drugs of the HAART regimen were not analyzed to determine whether a specific drug or class of drugs is associated with a higher risk for diabetes, since information on specific drug regimens is not available in administrative database. Other studies using administrative data of veterans in care with HIV infection have shown that a large number of patients in the HAART era did indeed receive HAART regimens.12 While we adjusted the results for the presence of liver disease in this study, a limitation of this variable was that this diagnosis was extracted only if it was recorded within 90 days of entering the cohort. We have previously shown that only a small number of HCV-HIV coinfected veterans undergo liver biopsy,13 which makes adjusting for this variable particularly difficult. Some authors have shown a correlation between the severity of liver disease and prevalent diabetes in HCV-infected patients,14–16 while others have shown no association between the degree of cirrhosis and diabetes.17 Whether diabetes predisposes these patients to cirrhosis or vice versa is not entirely clear, although preexisting HCV infection increases the risk of diabetes in patients already at a higher risk for diabetes.18 HCV infection remains independently associated with a higher risk for diabetes, regardless of the severity of liver injury, in case control studies, and this risk is higher than in those with hepatitis B virus–related cirrhosis.15, 16 Our database did not have HCV RNA levels. Whether patients with chronic HCV infection, defined as persistent HCV viremia, behave differently than those who clear the viremia, either spontaneously or with treatment, could not be studied in the current database.

In conclusion, HIV-infected veterans who receive care in the HAART era are at a higher risk for developing diabetes compared with those who received care in the pre-HAART era. Increasing age and minority race are strong predictors of diabetes in veterans in the pre-HAART as well as in the HAART era. The effect of HCV coinfection is significant in the HAART era, but not in the pre-HAART era, suggesting that improved survival and HAART regimens may have a role in the development of diabetes in this group. HIV-infected veterans should be screened regularly for diabetes, especially those who are older, are from a minority race, or have HCV coinfection. Because a large proportion of HIV-infected patients are coinfected with HCV, and because patients on HAART are living long enough to develop age-related diabetes, providers of HIV care will need to be more attentive to the early diagnosis and management of this comorbid condition. The applicability of these findings to all HIV-infected patients and the role of specific drugs of the HAART regimen in the development of diabetes requires further investigation.

Appendix 1

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Appendix 1
  7. References
Table  . The International Classification of Diseases, 9th Revision (ICD-9) Codes Used in Data Extraction for This Study
Hepatitis C infection070.41, 070.44, 070.51, 070.54, V02.62;
Diabetes250.xx, 357.2, 790.2, 791.5, 791.6;
Liver disease070.6, 070.9, 155.0, 456.0, 456.1, 456.2, 456.21, 789.5, 567.xx, 570.xx, 571.xx, 572.2x, 572.3x, 572.4x, 572.8x, 571.0x 571.1x 571.3x, 571.4x, 572.xx, 573.xx, 578.xx
Diagnosis of alcohol abuse or dependence291.xx, 303.xx, 305.99, 305.01, 305.02, 305.03, 980.0, 980.8, 980.9, E860, E8601, E8608, E8609, 790.3x
Diagnosis of drug abuse or dependence292.xx, 304.xx, 305.2-306.

References

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Appendix 1
  7. References
  • 1
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