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Burden of Exposure to Potential Interactions Between Antiretroviral and Non-Antiretroviral Medications in a Population of HIV-Positive Patients Aged 50 Years or Older

Ranzani, Alice MD*; Oreni, Letizia MS*; Agrò, Massimiliano MD*; van den Bogaart, Lorena MD*; Milazzo, Laura MD*; Giacomelli, Andrea MD*; Cattaneo, Dario PD; Gervasoni, Cristina MD*; Ridolfo, Anna Lisa MD*

Author Information
JAIDS Journal of Acquired Immune Deficiency Syndromes: June 1, 2018 - Volume 78 - Issue 2 - p 193-201
doi: 10.1097/QAI.0000000000001653
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Advances in antiretroviral treatment (ART) over the past 30 years have significantly prolonged the life expectancy of HIV-positive patients, whose median age has progressively increased.1 One study of the ATHENA cohort in the Netherlands has projected that 73% of HIV-positive subjects will be older than 50 years by 2030,2 and there is a growing proportion of newly reported cases of HIV infection involving people aged 50 years or older in various countries.3,4

Patients with HIV may age prematurely,5–7 and it has been shown that those aged 50 years or older (usually known as “older patients” in the HIV literature) are at increased risk of developing a number of age-related comorbidities (ie, diabetes, cardiovascular diseases, osteoporosis, non-AIDS–related cancers, and disorders affecting physical and mental function) in comparison with their uninfected counterparts.5–9 This means that aging HIV-positive patients may require more medications to treat comorbidities in addition to ART, which traditionally consists of combinations of 3 antiretroviral agents (ARVs). The increasing complexity of therapeutic regimens and, particularly, polypharmacy (ie, the simultaneous use of ≥5 medications) may have a negative impact on the quality of life and adherence to treatment of elderly people, and inevitably increases the chance of drug–drug and drug–disease interactions that may lead to unintended adverse events.10 Moreover, when the adverse events related to drug–drug interactions are misunderstood, there may be a “prescribing cascade” in which new and possibly unnecessary drugs are administered with the risk of further adverse outcomes.11

The risk of drug–drug interactions is particularly high in HIV-positive patients because many ARVs and the boosters frequently used to potentiate their activity are substrates and inhibitors or inducers of hepatic CYP450 enzymes and drug transporters.12,13 Previous studies have shown that 27%–63% of HIV-positive patients are exposed to potential drug–drug interactions (PDDIs), and that an older age and higher number of medications significantly increase their likelihood.14–17 However, few studies have specifically examined medication-related problems including potential interactions between ARVs and comedications and the use of potential inappropriate comedications in older HIV-positive patients.

The aim of this study was to characterize the medications used by a population of older HIV-positive patients and investigate all the potential interactions between ARVs and non-ARV medications by examining the contribution of the different ART regimens and non-ARV medication classes to the risk of PDDIs.


This cross-sectional observational study of adult HIV-positive patients attending the outpatient Clinic of Infectious Diseases Unit of L. Sacco Hospital-University of Milan was conducted between January 1, 2016, and June 30, 2016. To be eligible, the patients had to be 50 years or older and receiving ART and at least 1 non-ARV medication. The study protocol was approved by the Ethics Review Board of the Azienda Ospedaliera- Polo Universitario Luigi Sacco, Milan, Italy.

The patients' clinical charts were retrospectively reviewed to extract information concerning their age, sex, and risk factors for HIV infection; the stage of HIV infection using the Centers for Disease Control and Prevention (CDC) classification; hepatitis virus coinfection; current CD4 cell counts and HIV-RNA levels; and ARV and non-ARV medications. All the medications were classified and grouped using the anatomical, therapeutic, and chemical classification system.18 Each drug (including each of those contained in coformulations) was considered 1 medication.

The PDDIs between ARV and non-ARV medications were screened for each patient using the HIV Drug Interaction Checker of the University of Liverpool HIV Pharmacology Group, which uses a “traffic light” system.19 Amber-PDDIs are those requiring close monitoring or an adjustment in the dose or timing of administration to minimize possible clinical consequences, and red-PDDIs are contraindicated combinations. Any unclear PDDI was reviewed and classified by an expert pharmacist on the basis of the Summary of Product Characteristics. All the PDDIs were considered to be present, regardless of any adjustment in dose or timing of administration.

To further characterize the risk profile of medications used by our patients, we applied the American Geriatrics Society 2015 Beers Criteria20 to screen the patients' medication lists for potentially inappropriate medications (PIMs: ie, medications whose use in the elderly pose more risk than benefit when safer alternatives exist). Medications included in the Beers Criteria list independent of specific clinical condition were analyzed, and PIM use was identified when a patient used 1 or more of them. We also assessed the burden of medications with anticholinergic effects using the Anticholinergic Cognitive Burden (ACB) scale.21 This scale classifies anticholinergic medications as possible anticholinergics (score 1) or definite anticholinergics (score 2 or 3), and the scores of each anticholinergic medication are added together to give a patient's total ACB score. An ACB score of ≥3 has been associated with a significantly increased risk of adverse events, including cognitive impairment, falls, and blurred vision.21

Information concerning all the identified medication-related problems was given to the patient's attending physician for medication review.

Statistical Analyses

The demographic, clinical, and therapeutic characteristics of the study population are given as absolute numbers and percentages or median values with their interquartile ranges (IQRs).

Univariate and multivariate logistic regression models were used to examine the factors associated with the presence of PDDIs, with age, sex, HIV stage, hepatitis B virus (HBV)/hepatitis C virus (HCV) coinfection, current CD4 cell count and HIV-RNA level, and the type of ART regimen and comedication class being used as independent variables.

The strength of the associations was measured as odds ratios (ORs) and adjusted ORs (aORs) with 95% confidence intervals (95% CIs). All the statistical analyses were made using SPSS version 11.0, and differences with P values of <0.05 were considered statistically significant.


Study Population

Nine hundred forty (47.1%) of the 1994 HIV-positive patients attending our outpatient clinic during the period of the study were aged 50 years or older; of these, the 744 (79.1%) who were receiving ART and at least 1 non-ARV medication were included in the analysis. The patients aged 50 years or older who were only receiving ART were significantly younger, less frequently had an AIDS diagnosis, and had a shorter history of ART treatment.

Table 1 shows the main characteristics of the study population. Most of the patients were white (96.3%) and males (74.2%). They had a median age of 56.1 years (IQR: 53.2–61.7), and 137 (18.4%) were aged 65 years or older. Most of the patients (66.1%) had acquired HIV as a result of sexual intercourses, whereas 28.6% had a history of drug addiction. Two hundred and eighteen patients (29.3%) had a previous diagnosis of AIDS, and 267 (35.9%) were coinfected with HBV and/or HCV. The median duration of ART was 17.6 years (IQR: 11.4–21.0), and 94.5% of the patients were virologically suppressed at the time of the study (HIV-RNA levels <37 copies/mL) with a median CD4 cell count of 679 cells/mm3 (IQR: 502–890 cells/mm3).

Characteristics of the Study Population

Five hundred twelve patients were receiving conventional ART regimens: 2 nucleoside reverse transcriptase inhibitors (NRTI) + 1 non-NRTI (NNRTI, 29.4%), or 1 protease inhibitor (PI, 22.6%), or 1 integrase strand transfer inhibitors (INSTIs, 16.8%); other mixed regimens with or without INSTIs were being received by, respectively, 24% and 7.1% of the patients.

The median number of non-ARV medications was 2 (IQR: 1–4) and 509 patients (68.4%) were on ≥5 ARV/non-ARV medications.

Characteristics of Prescribed Medications and Prevalence of PDDIs by ARV and Non-ARV Drug Classes

Table 2 shows that 573 (77%) of the patients were receiving NRTIs, most frequently tenofovir/emtricitabine (34.8%) and abacavir/lamivudine (27.1%); 364 (48.9%) PIs, most frequently atazanavir (26.7%) and darunavir (16.5%) boosted with ritonavir or cobicistat; 288 (38.7%) NNRTIs, efavirenz (15.0%), and nevirapine (11.8%); 304 (40.8%) INSTIs, raltegravir (25.1%) and dolutegravir (13.0%); and 21 (2.8%) maraviroc.

Prevalence of PDDIs Between ARV and Non-ARV Drug Classes Used by 744 HIV-Positive Patients Aged 50 Years or Older

Comedications belonged to large variety of classes and subclasses, but the most frequently used were cardiovascular agents, mainly lipid-lowering agents (38.5%) and renin-angiotensin-aldosterone system inhibitors (34.4%); anticoagulant/antiplatelet agents (21.9%); alimentary tract/metabolism agents, mainly vitamins and minerals (19.2%), antacids/acid-lowering agents (18.3%), and anti-diabetics (11.1%); and nervous system agents, mainly hypnotics/sedatives (13.7%) and antidepressants (9.5%). Systemic hormones (mainly thyroid hormones), genitourinary agents [mainly to treat benign prostatic hypertrophy (BPH), and erectile dysfunction], musculoskeletal system agents (mainly antiosteoporosis medications), antimicrobials, antineoplastic/immunomodulators, and antihistamines were less frequently used (Table 2).

Screening for PDDIs between ARV and non-ARV medications yielded a total of 694 amber-PDDIs and 43 red-PDDIs; 353 patients (47.4%) had ≥1 amber-PDDI, and 42 (5.6%) had ≥1 red-PDDI. The presence of ≥1 PDDI and ≥1 red-PDDI was more frequent in the patients aged 65 years or older than in those aged younger than 65 years: 62% versus 51.1%, and 8.7% versus 4.9%. Moreover, the proportion of patients with ≥1 amber-PDDI was higher among those receiving PIs (61.5%) than among those receiving NNRTIs (38.9%), INSTIs (14.8%), or NRTIs (11.9%); the presence of ≥1 red-PDDI was also more frequent among the patients receiving PIs (10.4%) than those receiving NNRTIs (1.0%) or INSTIs (0.3%) (Table 2).

Almost all the non-ARV medications had potential for interactions with ARVs, with the proportion of patients with ≥1 amber-PDDI ranging from 3.6% of those receiving blood supplements (ie, iron and/or folinic acid) to 88.5% of those receiving antiosteroporotic agents (Table 2). The prevalence of red-PDDIs was highest among the patients receiving anti-BPH agents (20.4%), antacids/acid-lowering agents (17.6%), and antipsychotics (13.6%) (Table 2). The red-PDDIs were between atazanavir (22 patients) or rilpivirine (2 patients) and proton-pump inhibitors, and between the various PIs and alfuzosin (9 cases), simvastatin (3), or quetiapine (3). In 4 single cases, red-PDDIs were between rilpivirine and oxcarbazepine, atazanavir and ticagrelor, saquinavir and nebivolol, and elvitegravir/cobicistat and triazolam.

Most of the patients with PDDIs were exposed to the potential adverse effects caused by increased blood levels of non-ARV medications, but 24 patients with ≥1 amber-PDDI (6.7%) and 26 with ≥1 red–PDDI (61.9%) were potentially exposed to a viral breakthrough caused by a decrease in blood ARV levels: these specifically involved atazanavir, rilpivirine, raltegravir or dolutegravir, and antacids/acid-lowering agents (n = 32); raltegravir or dolutegravir and supplements containing calcium or iron (n = 15); and atazanavir, efavirenz, or elvitegravir/cobicistat and antiepileptic drugs (n = 7). Therapeutic drug monitoring results were available for 9 of the 50 patients with PDDIs capable of reducing ARV concentrations: 2 patients receiving atazanavir/ritonavir + proton-pump inhibitors and 1 receiving rilpivirine + oxcarbazepine had ARV values below the therapeutic range.

Factors Associated With the Risk of PDDIs Between ARV and Non-ARV Medications

Table 3 shows the results of the univariate and multivariate logistic regression analyses of the risk factors associated with having ≥1 PDDI. The use of ≥5 ARV/non-ARV medications was independently associated with an increased risk of PDDIs (P < 0.001). The other factors that were independently associated with an increased risk were the use of anticoagulant/antiplatelet agents (P = 0.006), calcium channel blockers (P < 0.001), anti-BPH agents (P < 0.001), antiosteoporotic agents (P < 0.001), and hypnotics/sedatives (P = 0.022), whereas the factors associated with a reduced risk were male sex (P = 0.004), and the use of NRTI + NNRTI (P < 0.001) and NRTI + INSTI regimens (P < 0.001) rather than PI-based regimens (Table 3). NRTI + NNRTI and NRTI + INSTI regimens were also independently associated with reduced risk of red-PDDIs (P < 0.001), whereas the use of antacids, anti-BPH agents, and antipsychotics was independently associated with a significant increase of the risk (P < 0.001, <0.001, and 0.023, respectively) (Table 4).

Univariate and Multivariate Analyses of Risk Factors Associated With the Presence of at Least One PDDI Between ARV and Non-ARV Medications
Univariate and Multivariate Analyses of Risk Factors Associated With the Presence of at Least One PDDI Between ARV and Non-ARV Medications
Univariate and Multivariate Analyses of Risk Factors Associated With the Presence of at Least One Red-PDDI Between ARV and Non-ARV Medications
Univariate and Multivariate Analyses of Risk Factors Associated With the Presence of at Least One Red-PDDI Between ARV and Non-ARV Medications

PIMs and Anticholinergic Burden

PIMs were detected in a total of 119 (16.0%) patients, with central nervous system–active agents (mainly hypnotics/sedatives) being those most frequent (64.7%). Of these patients, 49 (41.2%) had ≥1 PDDI able to increase the blood levels of PIMs. PIMs were used by 16.1% (98/137) of patients aged 65 years or older and 15.3% (21/607) of those younger than 65 years. Overall, a total of 51 (6.8%) patients showed an ACB score ≥3: 8 (5.8%) of patients aged 65 years or older and 43 (7.1%) of those younger than 65 years. Antipsycotics, antidepressants, and hypnotic/sedatives were medications that contributed the most to anticholinergic burden.


More than one-half of our older HIV-positive patients receiving ART with different types of comedications were exposed to at least 1 PDDI: 5% to ≥1 red-PDDIs and 47% to ≥1 amber-PDDIs. These percentages are quite similar to those reported in recent studies.17,22,23

As expected, patients receiving ≥5 medications were more exposed to PDDIs, but the increased risk we observed in women, which suggests that they make more frequent use of ARV/non-ARV medications with PDDIs, warrants further evaluation.

Our findings confirm previous evidence that the risk of PDDIs is significantly lower in patients receiving NRTI + NNRTI regimens than in those receiving NRTI + PI regimens.14–17 We also found that regimens based on NRTI + INSTI combinations were independently associated with the lowest risk of experiencing PDDIs, and a similar figure has been reported in 2 previous studies of patients with HIV of all ages.17,24 It is worth noting that raltegravir and dolutegravir accounted for most of the INSTIs prescribed to our patients, and that the albeit very small number of patients receiving elvitegravir/cobicistat may have led to an overestimate of the risk of PDDIs attributed to NRTI+ INSTI regimens: raltegravir and dolutegravir have a reasonably benign drug interaction profile, but elvitegravir, which requires coadministration with cobicistat, has an interaction profile similar to that of boosted PIs.25,26

Almost all the non-ARV medication classes used by our patients may interact with ARVs, but the likelihood of red-PDDIs was significantly higher among the patients using antiacids/acid-lowering agents, anti-BPH agents, and antipsychotics. The coadministration of gastric acid–reducing medications with atazanavir and rilpivirine (which accounted for most of our red-PDDIs) is generally contraindicated because the bioavailability (and hence the efficacy) of ARVs may be affected by gastric pH.27,28 However, such combinations can be safely managed by adequately separating the times of administration.29 Moreover, the coadministration of PIs may significantly increase blood concentrations of atypical antipsychotics (such as quetiapine)30 and lead to the risk of cognitive alterations.31 For this reason, a dose reduction or the use of an alternative agent are recommended.29 Similarly, PIs may increase blood concentrations of alfuzosin, an alpha-adrenergic blocker used to treat BPH that has a narrow therapeutic window, and increased concentrations may lead to severe hypotension.32

Overall, the magnitude of PDDIs in our study population supports previously expressed concerns regarding the possible harm of polypharmacy in aging HIV-positive subjects.33,34 However, the prevalence of PDDIs leading to clinically significant adverse events is probable substantially less than the percentage of exposed patients.35 None of the 737 PDDIs had high quality evidence indicating its seriousness, and only 40 (5.4%) had moderate evidence, thus suggesting that the remaining PDDIs are unlikely to induce clinically adverse outcomes.

We acknowledge that the websites and apps offered to the community by expert teams are reliable sources that can facilitate clinicians in managing complex therapeutic regimens. However, the many PDDI warnings contained in these systems can lead to alert fatigue in clinical practice, and the consequent risk of overlooking combinations that are truly potentially harmful for patients.36

The HIV interaction team of the University of Liverpool has recently extended its classification system by introducing a new “yellow light” code that falls between “no drug-drug interaction expected” and an amber-PDDI alert [ (accessed 9 November, 2017)]. Yellow-PDDIs are probably not very intense and therefore unlikely to require specific interventions, although their significance may vary between individual patients. Notably, 143 (20.6%) of the 694 amber-PDDIs identified in our study population are reclassificable as yellow-PDDIs, and it is therefore important to continue discerning specific PDDIs that can be downgraded from clinical support alerting tools, as this may enable clinicians to concentrate on most critical PDDIs.

Moreover, prescribing quality assessment tools may help clinicians to focus on medications that are known to be especially risky for elderly.37 Using the Beers criteria,20 we found that 16% of our patients were receiving PIMs (mainly hypnotics/sedatives), a percentage that is much lower than the 52% and 63% found in 2 American studies in which the patients were older and more exposed to non-ARV polypharmacy than our patients.22,23 Of note, 42% of our patients who were receiving PIMs had ≥1 PDDI capable to increase the blood levels of these drugs, with consequent additional risk of adverse events. Moreover, using the Anticholinergic Cognitive Burden scale,21 we estimated that about 7% of our patients were at significantly increased risk of adverse outcomes, including falls and cognitive alterations (ACB scores of ≥3).38 Overall, these findings suggest that the real risk of adverse events due to polypharmacy and drug–drug interactions is not negligible, and that it is necessary to promote the more appropriate use of medications in older HIV-positive patients.

Our study has a number of limitations. First of all, we only considered PDDIs between ARV and non-ARV medications, and not those between ARVs or between non-ARV medications, which means that our findings may significantly underestimate the global burden of PDDIs. Second, it is possible that over-the-counter (OTC) medications may have been underreported or not recorded by clinicians in the patients' medical charts. OTC drugs are often self-managed by patients and may therefore escape the attention and/or approval of clinicians, but considering them (as well as complementary and alternative medicines) on a par with prescription medications is important because they may significantly interact with ARVs.39,40 Finally, it should be mentioned that our findings may not be generalizable to other subgroups or patients in other geographical regions, but they do provide valuable information concerning a population whose demographic characteristics, HIV risk factors, duration of HIV infection, and access to medications are quite similar to common groups of patients enrolled in European and North American HIV cohorts.

In conclusion, exposure to PDDIs between ARV and non-ARV medications can be expected in a considerable proportion of older HIV-positive patients using ART together with treatment for comorbidities. The knowledge of their complete medication regimens (including OTCs) and the screening for PDDIs is therefore crucial to prevent possible toxicities and viral breakthroughs,41 particularly in the case of patients affected by multiple comorbidities who often face transitions of care between providers of different disciplines. Integrating geriatric prescribing principles in HIV clinical practice will be useful to minimize the risk of adverse outcomes resulting from polypharmacy in the aging HIV-infected population.

Future research should continue to investigate the actual harm caused by polypharmacy in the HIV-infected population, and develop optimal strategies to facilitate and promote the effective and safe use of medications.


The authors are grateful to all the patients, doctors, and nurses of our clinic, and thank Chiara Resnati, Bianca Ghisi, and Tiziana Formenti for their support during the preparation of this article.


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older HIV-positive patients; comorbidities; polypharmacy; drug–drug interactions; inappropriate medications

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