Abstract
Background: The increased risk of cardio-metabolic disorders associated with people living with human immunodeficiency virus (HIV) is of growing importance. Given the broad adoption of integrase strand-transfer inhibitor (INSTI)-based antiretroviral therapy (ART) as first-line therapy for HIV, additional data are needed regarding the metabolic effects of these regimens. Objective: The purpose of this study is to assess glycemic control in patients started on INSTI-based 3-drug regimens over a 2-year period. Methods: A retrospective study was conducted on patients seen in the Brooklyn Hospital Center. Men and nonpregnant, nonlactating women aged 18 years or older with a diagnosis of HIV who were initiated on or switched to an ART consisting of 2 nucleoside reverse transcriptase inhibitors (NRTIs) plus an INSTI were included in the analysis. The primary endpoint is change in A1C from baseline (pre-INSTI initiation) to 2 years after initiation. Results: Two hundred fifty-one patients were eligible based on specified inclusion and exclusion criteria. Overall, a statistically significant increase in A1C was seen in all patients started on INSTI-based regimen (95% CI, 0.10-0.36; P < 0.001). Primarily patients on both elvitegravir-based and bictegravir-based regimens saw the most significant increase in A1C: 0.16% (95% CI, 0.04-0.27; P = 0.006) and 0.39% (95% CI, 0.02-0.76; P = 0.038), respectively. Conclusion and Relevance: Integrase strand-transfer inhibitor-based 3-drug ART was associated with a small but statistically significant increase in A1C over a 2-year period, requiring additional monitoring by clinicians.
Keywords: diabetes mellitus, integrase inhibitors, antiretroviral therapy, glycemic control, human immunodeficiency virus
Introduction
Diabetes mellitus (DM) is a chronic metabolic condition characterized by hyperglycemia resulting from defects in insulin secretion or sensitivity. Long-term hyperglycemia has been associated with significant damage, especially to the eyes, kidneys, heart, nerves, and blood vessels. 1 As of 2018, it is estimated that up to 34.2 million Americans (10.5% of the population) will have diabetes, with 1.5 million new cases diagnosed each year. 2 Classic risk factors, such as poor diet, limited physical activity, and family history cannot exclusively explain the increasing trend in diabetic cases yearly. This suggests other novel risk factors, such as chronic infections, inflammation, and medication, may be linked to the development of DM. Of these risk factors, human immunodeficiency virus (HIV) and antiretrovirals (ARVs) have been shown to cause an increase in metabolic alterations that are associated with the progression of DM. 3 The decrease in HIV-related mortality may also contribute to the increased burden of chronic disease conditions, specifically cardiovascular disease and DM, in this patient population. It is suggested that people living with HIV (PLWH) are at greater risk of developing DM than the general population due to the natural progression of the disease, related coinfections, and medications, specifically antiretroviral therapy (ART). 4
In the multicenter AIDS Cohort Study, the incidence of type 2 diabetes (T2D) was 4 times greater in PLWH receiving ART than in the HIV-seronegative control participants. 5 Certain older ARTs, such as protease inhibitors (PIs) and nucleoside reverse transcriptase inhibitors (NRTIs), have been shown to reversibly induce insulin resistance and increase the risk of developing T2D. 6 However, our modern NRTI backbones have failed to show a significant increase in insulin resistance, indicating that the escalation may due to the third active agent in a traditional 3-drug regimen. In healthy men, short-term use of tenofovir alafenamide (TAF)/emtricitabine plus either rilpivirine or elvitegravir/cobicistat did not increase insulin resistance. 7 Similarly, the use of tenofovir disoproxil fumarate (TDF)/emtricitabine plus either elvitegravir/cobicistat or darunavir/ritonavir did not increase insulin resistance in PLWH. However, there was a significant uptick in insulin resistance in those using TDF/emtricitabine plus lopinavir/ritonavir. 8
Integrase strand-transfer inhibitors (INSTIs) in combination with NRTIs are recommended as first-line therapy for PLWH by the US National Institute of Health (NIH). 9 Though they are well tolerated, long-term toxicities of this class are still unknown. Weight gain in particular is an adverse effect that has been seen in recent studies. A study conducted by Bourgi et al 10 looked at 1152 ART-naïve HIV-positive individuals who were initiated on either INSTI-based, PI-based, or non-nucleoside reverse transcriptase inhibitors (NNRTI)-based ART. The majority of the participants in this study identified as male, and 42% were black. At 18 months postinitiation, weight gain amounts among those starting INSTI-based regimens with dolutegravir, elvitegravir, or raltegravir were 6.0, 0.5, and 3.4 kg, respectively. Dolutegravir-based regimens also showed more weight gain than either NNRTI-based regimen or PI-based regimens, with 2.6 and 4.1 kg increases over 18 months. 10 Weight gain while on ART may contribute to an increased risk of several comorbidities, but the incidence of DM, and its relationship with weight gain, among persons being initiated on an INSTI is not well defined. Findings of increased fibrosis in adipose tissue and reduced insulin sensitivity in adipocytes in individuals exposed to INSTIs have hypothesized that incidence of diabetes may be independent from weight gain. 11
Given the increased cardiometabolic disease risks associated with PLWH, attention to glucose abnormalities is of growing importance. The effect of INSTI-based 3-drug ART on A1C levels in PLWH is an area still requiring study. These changes in A1C levels may vary depending on different ART regimens and baseline glycemic control. The coexistence of diabetes and HIV presents a unique challenge for healthcare professionals when managing patients on ART and antiglycemic agents due to the opposing effects on A1C.
The North American AIDS Cohort Collaboration on Research and Design (NA-ACCORD) analysis looked at the impact of different ART classes in ART treatment-naïve patients and the development of diabetes. 12 Among the 21,516 participants in the trial, 23% were started on an INSTI-based ARV regimen, with a median follow-up of 1.6 years. Overall, the incidence of developing diabetes in patients taking INSTIs was 12.03 per 1000 person years. Incidence rates were higher in patients taking raltegravir-based regimens compared with other INSTIs, such as elvitegravir and dolutegravir. 12 Integrase strand-transfer inhibitors had a higher incidence of diabetes compared with other ARVs in the trial. Given the broad adoption of INSTI-based ART as first-line therapy for HIV, additional data are needed regarding the metabolic effects of these regimens.
Methods
This study includes participants who were seen as outpatients in the Brooklyn Hospital Center (TBHC) Program for AIDS Treatment and Health (PATH) center. Patients were identified through a query extracted from the outpatient medication database in EPIC and filtered by INSTI name, such as bictegravir, dolutegravir, elvitegravir, and raltegravir, including all brand name and combination products containing these agents. Men and nonpregnant, nonlactating women aged 18 years or older with a diagnosis of HIV who were initiated on or switched to an ART consisting of 2 NRTIs and an INSTI were included in the analysis. Patients must have been started on a 3-drug INSTI-based regimen between January 2017 and November 2018. Patients were excluded if they were initiated or switched to a 2-drug or 4-drug INSTI-based regimen, or if a 3-drug INSTI-based regimen was discontinued prior to a 2-year duration. A 2-year snapshot of data, including A1C and weight, was collected directly prior to INSTI-based ART initiation through 2 years after initiation. Pre-INSTI baseline data collection included age, sex, race, height, comorbid conditions, T2D medication history, serum creatinine, CD4, and HIV RNA. Paired t tests using Prism GraphPad statistics software v9.1 were used to compare continuous variables. This study received an expedited review and was approved by the Institutional Review Board at the Brooklyn Hospital Center.
The objective of this retrospective study is to assess glycemic control in patients started on INSTI-based 3-drug regimens over a 2-year period. The primary endpoint is change in A1C from baseline (pre-INSTI initiation) to 2 years postinitiation. Secondary endpoints include change in weight, change in A1C for each individual INSTI, and change in weight for each individual INSTI from baseline to 2 years post-INSTI initiation. Postdata collection, patients were stratified into 3 groups according to baseline A1C. Groups include baseline A1C < 5.7%, baseline A1C 5.7% to 6.5%, and baseline A1C > 6.5%. The purpose of this stratification was to compare the percentage of patients within diabetes classifications who had a change in A1C from before the 2 years after initiation of INSTI.
Results
A total of 1424 patients who were initiated on an INSTI-based 3-drug regimen between January 2017 and November 2018 were screened. Two hundred fifty-one patients were eligible based on specified inclusion and exclusion criteria. Of these patients, 114 (45.4%) were started on elvitegravir/cobicistat/emtricitabine/TAF; 70 (27.9%), on bictegravir/emtricitabine/TAF; 40 (15.9%), on dolutegravir/abacavir/lamivudine; and 20 (8.0%), on dolutegravir plus emtricitabine/TAF. Seven patients (2.8%) were started on raltegravir-based regimens; these patients were not included in overall analysis of data because of the small sample size (Table 1).
Table 1.
INSTI-Based Antiretroviral Therapy (n = 251).
| Elvitegravir/cobicistat/emtricitabine/tenofovir alafenamide | 114 (45.4%) |
| Bictegravir/emtricitabine/tenofovir alafenamide | 70 (27.9%) |
| Dolutegravir/abacavir/lamivudine | 40 (15.9%) |
| Dolutegravir + emtricitabine/tenofovir alafenamide | 20 (8.0%) |
| Raltegravir + emtricitabine/tenofovir alafenamide | 4 (1.6%) |
| Raltegravir + emtricitabine/tenofovir disoproxil fumarate | 3 (1.2%) |
Values are given as no. (%).
Abbreviation: INSTI, integrase strand-transfer inhibitor.
Baseline demographics and clinical characteristics at the initiation of INSTI-based regimens are shown in Table 2. The majority of patients identified as male and had a median age of 54. A large portion of patients were black or African American; black or African American women represented 31% of the study population. This number is representative of the community in which the hospital is located. Only a small subset of patients were diabetic, with 48 (19.1%) having an A1C greater than 6.5% prior to initiation of INSTI-based regimen. The average baseline weight for these patients was 86.2 kg. Prediabetic patients (n = 31; 12.4%) had an A1C between 5.7% and 6.5% prior to INSTI-based regimen initiation, with an average baseline weight of 88.4 kg. The average weight for patients with an A1C < 5.7% was 80.4 kg. The average A1C for all patients included in the trial was 5.71%, with an average weight of 82.5 kg. Metformin was the most common antiglycemic drug used among either prediabetic or diabetic patients, consisting of 12.4% of the study population. Other antiglycemic regimens are listed in Table 3. The majority of patients, 218 (86.5%), had undetectable HIV-RNA prior to initiation of INSTI-based therapy. Undetectable HIV-RNA was defined as a viral load of less than 40 viral copies/mL. Comorbid conditions included hypertension, hyperlipidemia, heart failure, and previous atherosclerotic cardiovascular disease (ASCVD) events: 144 (57.4%), 118 (47.0%), 7 (2.8%), and 32 (12.7%), respectively.
Table 2.
Demographics (n = 251).
| Age (years), mean (range) | 54 (18-80) |
| Male sex, no. (%) | 141 (55.9%) |
| Race | |
| White, no. (%) | 34 (13.5%) |
| Black/African American, no. (%) | 190 (75.7%) |
| Hispanic, no. (%) | 14 (5.6%) |
| Other, no. (%) | 13 (5.2%) |
| Baseline weight (kg), mean (range) | 82.5 (42.7-151.8) |
| Baseline SCr (mg/dL), mean (range) | 1.05 (0.6-1.8) |
| A1C (%), mean (range) | 5.71 (4.5-14) |
| CD4 (copies/mL), mean | 658 |
| Viral load | |
| Undetectable, no. (%) | 218 (86.5%) |
| Undetectable-100, no. (%) | 9 (3.6%) |
| 100-1000, no. (%) | 9 (3.6%) |
| >1000, no. (%) | 15 (5.9%) |
| Hypertension, no. (%) | 144 (57.4%) |
| Hyperlipidemia, no. (%) | 118 (47.0%) |
| Heart failure, no. (%) | 7 (2.8%) |
| Previous ASCVD event, no. (%) | 32 (12.7%) |
| Prediabetes, no. (%) | 31 (12.4%) |
| Diabetes, no. (%) | 48 (19.1%) |
Abbreviation: ASCVD, atherosclerotic cardiovascular disease.
Table 3.
Antiglycemic Agents (n = 251).
| Metformin | 31 (12.4%) |
| GLP-1RA | 13 (5.2%) |
| SGLT2 inhibitors | 11 (4.4%) |
| DPP4 inhibitors | 14 (5.6%) |
| SU | 13 (5.2%) |
| Insulin | 21 (8.3%) |
| Other | 3 (1.2%) |
Values are given as no. (%).
Abbreviations: DDP4, dipeptidyl peptidase 4; GLP-1RA, glucagon-like peptide 1 receptor agonist; SGLT2, sodium-glucose cotransporter 2; SU, sulfonylureas.
Changes in A1C
Overall, a statistically significant increase of 0.23% in A1C was seen in all patients included in the analysis (95% CI, 0.10-0.36; P < 0.001). Primarily patients on both elvitegravir-based and bictegravir-based regimens saw the most significant increase in A1C: 0.16% (95% CI, 0.04-0.27; P = 0.006) and 0.39% (95% CI, 0.02-0.76; P = 0.038), respectively. Dolutegravir-based regimens did not show a statistically significant change in A1C regardless of the NRTI-backbone used, abacavir/lamivudine, or emtricitabine/tenofovir alafenamide: 0.26% (95% CI, –0.05 to 0.57; P = 0.098) and 0.16% (95% CI, –0.14 to 0.46; P = 0.284), respectively (Figure 1). With regard to DM status, the most significant change in A1C was seen in patients whose A1C was below 5.7% prior to initiation of an INSTI-based regimen. These patients saw an A1C increase of 0.16% (95% CI, 0.43-0.28; P = 0.008), and the majority of these patients were on elvitegravir-based regimens. Change in A1C per baseline diabetic status can be seen in Table 4. Thirty-two patients (18.6%) whose A1C was below 5.7% developed prediabetes within the 2-year period, and 11 patients (35.5%) with A1Cs between 5.7% and 6.5% progressed into diabetic status.
Figure 1.
Change in A1C Per INSTI-based Antiretroviral Regimen.
Abbreviation: INSTI, integrase strand-transfer inhibitor.
Table 4.
Change in A1C Per Baseline Diabetic Status.
| A1C (%), mean (range) | Difference (95% CI) | P value | |
|---|---|---|---|
| Total | 5.71 (4.5-14) | 0.23 (0.10-0.36) | < 0.001 |
| A1C > 6.5% | 7.69 (6.5-14) | 0.35 (–0.05 to 0.76) | 0.083 |
| A1C between 5.7% and 6.5% | 5.87 (5.7-6.4) | 0.41 (–0.15 to 0.97) | 0.142 |
| A1C < 5.7% | 5.19 (4.5-5.6) | 0.16 (0.43-0.28) | 0.008 |
Changes in Weight
An average increase in weight of 1.52 kg (95% CI, 0.64-2.40; P < 0.001) was seen in patients started on INSTI-based regimens. Significant increases were seen in patients started on elvitegravir/cobicistat/emtricitabine/TAF of 1.52 kg (95% CI, 0.64-2.40; P <0.001) and dolutegravir/emtricitabine/TAF of 4.16 kg (95% CI, 0.96-7.34 P = 0.013). Those taking bictegravir-based ART additionally saw a nonsignificant increase of approximately 1.74 kg (95% CI, –0.08 to 3.55; P = 0.061), while those on dolutegravir/abacavir/lamivudine saw a nonsignificant decrease in weight of approximately 0.22 kg (95% CI, –2.58 to 2.14; P = 0.850) (Figure 2). Weight gain was primarily seen in patients who had an A1C below 5.7% and between 5.7% and 6.5% (1.73 and 2.03 kg, respectively). Patients with a baseline A1C above 6.5% also had a nonsignificant increase of approximately 0.44 kg (Table 5).
Figure 2.
Change in Weight Per INSTI-based Antiretroviral Regimen.
Abbreviation: INSTI, integrase strand-transfer inhibitor.
Table 5.
Change in Weight Per Baseline Diabetic Status.
| Baseline weight (kg), mean (range) | Difference (95% CI) | P value | |
|---|---|---|---|
| Total | 82.5 (42.7-151.8) | 1.52 (0.64-2.40) | <0.001 |
| A1C > 6.5% | 86.2 (43.0-131.1) | 0.44 (–1.73 to 2.61) | 0.688 |
| A1C between 5.7% and 6.5% | 88.4 (55.5-136.4) | 2.03 (0.08-3.97) | 0.041 |
| A1C < 5.7% | 80.4 (42.7-151.8) | 1.73 (0.65-2.82) | 0.002 |
Discussion
Though A1C changes were not clinically significant (defined as a change in A1C ≥ 0.5%), 13 this study demonstrated that, over a 2-year period, INSTI-based regimens were associated with a statistically significant increase in both A1C and weight in PLWH. The most significant change in A1C occurred in patients whose baseline A1C was below 5.7%, and the greatest weight gain occurred in those with a baseline A1C below 6.5%. Moreover, this study highlights that those regimens containing elvitegravir or bictegravir were associated with significantly higher increases in A1C compared with regimens containing dolutegravir. In addition, dolutegravir weight gain was mainly seen when used with a TAF-based regimen and not with the abacavir-based regimen.
The mechanism to explain these changes remains unknown and is likely multifactorial. This may be a result of reduced inflammation-related catabolism, lower basal energy expenditure, or modifications in lifestyle and diet.14,15 Recent studies suggest that INSTIs may adversely affect metabolic health through changes in adipose tissue. The NEAT022 study, looking at PLWH switched from PI-containing regimens to dolutegravir-containing regimens, had an 11% lower concentration of adiponectin, an insulin-sensitizing hormone, after 48 weeks. 16 Similarly, a study done on macaques who were given INSTIs saw higher incidences of subcutaneous adipose tissue fibrosis and lower adiponectin expression compared with those who did not receive INSTI. 11 These findings are suggestive that INSTIs may be associated with insulin resistance, possibly due to their adverse effects on adipose tissue, and reduced adiponectin production. There is very limited human data to suggest this causation. A study conducted in Uganda showed that dolutegravir-based regimens increased hyperglycemic events at a rate of 0.47%. 17 In addition, in a recently published case series of 3 patients with A1C < 7% who were switched to bictegravir/emtricitabine/TAF, all developed diabetic ketoacidosis (DKA) within weeks to months of transition. 18 A1C at time of hospitalization for hyperglycemia ranged from 12.4% to 17%. After the INSTI-based regimen was removed, the A1C levels returned to around baseline. 18 Patients in our trial did not show similar immediate spikes in A1C.
With regard to weight gain, findings of our study are similar to other studies showing that INSTI-based regimen may have an independent effect on body mass. The AIDS Clinical Trials Group (ACTG) study A5257 saw greater increases in waist circumference at 96 weeks in patients using raltegravir-based regimens compared with PI-based regimens. 19 In addition, a 96-week randomized trial in South Africa comparing efavirenz-based ART versus dolutegravir-based ART reported greater increases in weight and truncal fat among participants receiving dolutegravir. 20 This is consistent with our data, which showed that patients initiated on dolutegravir-based regimens, particularly those including TAF, had the greatest increases in weight.
In our study, the majority of patients who had increases in weight were on INSTI-based regimens that included TAF (64.4%), which is consistent with other available data. The use of TAF has rapidly increased since its approval in 2015 due to its favorable adverse effect profile compared with TDF. 21 Though TAF has been seen as a preferred alternative to TDF due to its renal-sparing properties, studies have shown that TAF has been associated with more weight gain. The ADVANCE trial demonstrated a higher incidence of weight gain for the TAF group compared with TDF over a 96-week period. 20 In addition, a retrospective cohort trial conducted by Mallon et al 22 found that TAF-containing ARTs were associated with early, pronounced weight gain when patients were switched from a TDF containing ART. The overwhelming majority of patients receiving ART regimens containing TAF in our study may have contributed to the observed increases in weight. In addition, patients in our study receiving dolutegravir-based regimens saw an increase in weight when the regimen was combined with TAF and a decrease when it was combined with other agents, such as abacavir.
Caution is warranted when interpreting our findings, as the study was a retrospective analysis of a predominantly African American/black male cohort from a single center in an urban community hospital, raising concern on its external validity. This study looked at a snapshot of patients from initiation of INSTI-based regimen to 2 years after initiation. As such, ART regimen prior to INSTI initiation could have influenced baseline data and confounded the changes observed in this study. It remains unclear if effects of INSTI-based regimen may change over a longer period of time. Also, patients who come to the TBHC PATH Center are often seen by a variety of specialists to manage various comorbid conditions. Patients who are overweight or diabetic are often referred to specialists, including clinical pharmacists and nutritionists who initiate and modify diet, exercise, and medications. True increases in weight and A1C may not be reflective, as specialists are actively working to prevent worsening outcomes. It should be noted that the American Diabetes Association (ADA) guidelines mentions HIV as a condition that has been associated with an altered relationship between A1C and glycemia and recommends that only plasma blood glucose criteria be used to diagnose diabetes. 23 As our study was a retrospective chart review, it is unclear if the plasma blood glucose in patients’ medical records was fasting or postprandial; thus, A1C was used to assess upward or downward lab trends. This approach, however, does pose a limitation that should be evaluated with future studies.
Conclusion and Relevance
In conclusion, INSTI-based 3-drug ART regimens were associated with a small but statistically significant increase in A1C over a 2-year period, with patients taking elvitegravir-based or bictegravir-based regimens showing the most significant change. In addition, elvitegravir and dolutegravir combined with emtricitabine and TAF showed significant increases in weight compared with other INSTI-based regimens. Findings from our study indicate that these agents carry a greater adverse effect profile and suggest that, when managing patients with HIV, providers need to closely monitor for negative metabolic effects. However, additional data are needed to assess the effects of INSTI-based regimens on glycemic control over a longer period of time.
Footnotes
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding: The author(s) received no financial support for the research, authorship, and/or publication of this article.
ORCID iDs: Anthony Gerber 
https://orcid.org/0000-0003-0559-2175
Briann Fischetti
https://orcid.org/0000-0003-3758-0590
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