Resource: ART Drug-Drug Interactions

August 13, 2024

Purpose of This Resource

Date of current publication: August 13, 2024
Lead author: John J. Faragon, PharmD, BCPS, AAHIVP
Writing group: Rona M. Vail, MD; Sanjiv S. Shah, MD, MPH, AAHIVM, AAHIVS; Steven M. Fine, MD, PhD; Joseph P. McGowan, MD, FACP, FIDSA, AAHIVS; Samuel T. Merrick, MD, FIDSA; Asa E. Radix, MD, MPH, PhD, FACP, AAHIVS; Jessica Rodrigues, MPH, MS; Christopher J. Hoffmann, MD, MPH, MSc, FACP; Brianna L. Norton, DO, MPH; Charles J. Gonzalez, MD
Committee: Medical Care Criteria Committee
Date of original publication: April 25, 2019

The New York State Department of Health (NYSDOH) AIDS Institute (AI) developed this reference for clinicians who manage the care of patients with HIV to accomplish the following:

  • Provide a central source of information on drug-drug interactions involving antiretroviral (ARV) medications
  • Assist healthcare providers in preventing or managing drug-drug interactions that could have a negative or dangerous effect on patient health
  • Balance the risks and benefits of reported drug-drug interactions to identify those that should or must be avoided and those that can be managed to alleviate adverse effects

The NYSDOH AI Medical Care Criteria Committee offers guidance on the interactions between ARVs and medications commonly used in the management of coexisting conditions seen in healthcare settings, based on a comprehensive review of available clinical trial data.

This guideline supports the NYSDOH Ending the Epidemic Initiative by providing a tool for clinicians to use in safely prescribing antiretroviral therapy (ART). ART initiation is now recommended for all patients diagnosed with HIV to improve the health of the patient, optimize virologic suppression, and reduce HIV transmission. This resource supports proper management of ART.

Scope: This resource does not provide an exhaustive survey of all possible interactions between ARVs and other medications. The focus is on those interactions most commonly encountered. Several robust free online resources are available to check specific drug-drug interactions, including the following:

Consultation with an experienced HIV care provider is also recommended when assistance is needed in choosing an ART regimen for a patient who has multiple comorbidities and may have multiple drug-drug interactions. For help locating an experienced HIV care provider, contact the Clinical Education Initiative at 866-637-2342.

Note on “experienced” and “expert” HIV care providers: Throughout this guideline, when reference is made to “experienced HIV care provider” or “expert HIV care provider,” those terms are referring to the following 2017 NYSDOH AI definitions:

  • Experienced HIV care provider: Practitioners who have been accorded HIV Experienced Provider status by the American Academy of HIV Medicine or have met the HIV Medicine Association’s definition of an experienced provider are eligible for designation as an HIV Experienced Provider in New York State. Nurse practitioners and licensed midwives who provide clinical care to individuals with HIV in collaboration with a physician may be considered HIV Experienced Providers as long as all other practice agreements are met (8 NYCRR 79-5:1; 10 NYCRR 85.36; 8 NYCRR 139-6900). Physician assistants who provide clinical care to individuals with HIV under the supervision of an HIV Specialist physician may also be considered HIV Experienced Providers (10 NYCRR 94.2)
  • Expert HIV care provider: A provider with extensive experience in the management of complex patients with HIV.

Identifying Drug-Drug Interactions

Individuals with HIV have a greatly increased risk of exposure to polypharmacy, especially as the population ages Edelman, et al. 2013Gleason, et al. 2013. The use of several concomitant medications can have unintended consequences, including increased risk of drug-drug interactions and associated adverse effects such as fatigue, nausea, weight gain or loss, and neurocognitive deficits Paul, et al. 2024. Drug-drug interactions may also decrease virologic control of HIV, increasing the risk of drug resistance and HIV-associated symptoms. The risks of polypharmacy and potential drug-drug interactions are expected to increase to correspond with increased use of medications such as statins to prevent cardiovascular events in people with HIV who have low-to-moderate risk scores and glucagon-like peptide receptor agonists for weight loss Grinspoon, et al. 2024Nguyen, et al. 2024.

Multiple factors may be associated with polypharmacy in patients. Physicians should be mindful of potential drug-drug interactions as a possible mechanism for new symptoms or unexpected medical events Davies and O'Mahony 2015. Drug-drug interactions can occur regardless of age or disease state. Any of the following potential polypharmacy-related risk factors may signal the need to update a patient’s medication list and evaluate the potential for drug-drug interactions:

  • Longstanding illness, chronic conditions, or disability Zingmond, et al. 2017Walckiers, et al. 2015
  • Age older than 50 years:
    • As people age, more diseases develop, which increases the risk of polypharmacy. Comorbidities commonly seen in an aging population, such as hypertension, chronic obstructive pulmonary disease, and diabetes mellitus, are increasingly prevalent in individuals with HIV Gleason, et al. 2013.
    • Age-related physiologic changes may alter drug responses in older individuals Gujjarlamudi 2016.
  • Treatment provided by more than 1 care provider (including specialists)
  • Limited care provider communication
  • Prescriptions filled at multiple pharmacies
  • Recent hospitalization:
    • Hospitalization may be the result of adverse reactions caused by drug-drug interactions, or interactions may result during transitions of care or because of medication changes for formulary decisions Mixon, et al. 2015Walckiers, et al. 2015. In addition, formulary changes for inpatient institutions may result in medication errors upon discharge, leading to omissions, duplications, or combinations that can create significant drug-drug interactions.
KEY POINT
  • People with HIV may experience a greater number of comorbid conditions as they age. Treatment of multiple comorbid conditions increases the risk of polypharmacy and associated drug-drug interactions.

Beneficial Concomitant Drug Use

Drug-drug interactions are most commonly thought of as having a negative effect on a patient’s quality of life, but beneficial drug-drug interactions may also occur. Beneficial concomitant drug use can work in multiple ways Trevor, et al. 2013.

Pharmacodynamic synergy: The most common positive outcome of drug-drug interactions is pharmacodynamic synergy, which is the combination of 2 or more drugs in which the shared effect is greater than the effect of either agent used alone.

Examples of this type of interaction include the combined use of antiretroviral (ARV) agents from multiple classes to manage a patient’s HIV infection. Combining ARVs with multiple mechanisms of action suppresses virus replication to a greater extent and for a longer period than using a single agent and reduces the risk of resistance to any single ARV. The use of multiple pharmaceutical agents to treat 1 medical condition is also beneficial for a number of the comorbidities that people with HIV may develop, including hypertension, diabetes, chronic obstructive pulmonary disease, or some psychological disorders.

Pharmacokinetic boosting: Another positive drug-drug interaction results from using a potent CYP3A4 enzyme inhibitor to allow higher bioavailability of a second agent. This effect is commonly achieved in HIV therapy through pharmacokinetic boosting with ritonavir and cobicistat. Boosting makes possible once-daily dosing or lower dosing of ARVs, which may decrease adverse effects caused by higher or more frequent dosing of the active agent. In turn, adherence may be improved by reducing pill burden. Similarly, using a potent inhibitor of a drug transporter allows for reduced or less frequent dosing of the second active agent. An example is the use of probenecid, an organic anion transporter inhibitor, to decrease the elimination of penicillins, such as penicillin, ampicillin, or nafcillin. This increases the clinical activity and efficacy of these agents. Although ritonavir boosting can be beneficial, it also poses a risk of unwanted drug-drug interactions due to its potent and broad effect on CYP450 enzymes.

In the current era of HIV treatment, it is well established that when used as prescribed, antiretroviral therapy (ART) effectively suppresses viral load over the long term. Ongoing research attempts to simplify ART regimens in an effort to reduce the number of ARVs that a patient must take long-term, thus reducing any long-term adverse effects or drug-drug interactions Boswell, et al. 2018Orkin, et al. 2018Wandeler, et al. 2018. However, simplifying a patient’s ART regimen can have unintended or unrecognized consequences. For instance, switching from a boosted ART regimen that includes ritonavir or cobicistat to an unboosted regimen removes a cytochrome P450 (CYP) isoenzyme inhibitor, which may reduce concentrations of drugs that had previously been boosted and reduce the therapeutic effects of any such concomitantly administered agents. Similarly, when switching from an unboosted to a boosted regimen, a CYP inhibitor is added, which may increase the therapeutic effects or toxicities of other medications.

As a result, when new adverse effects occur, a patient or clinician may attribute them to the new ART regimen, even if they are simply the result of a loss or addition of CYP inhibition. It is important to consider the effect of such simplification strategies on concentrations of all of a patient’s concomitantly administered medications. Doing so may prevent the addition of more medications to manage adverse effects that could otherwise have been expected or avoided. For example, if ritonavir-boosted darunavir (which inhibits various CYP enzymes) is replaced with dolutegravir (which is not known to be an inhibitor of CYP enzymes), then a low dose of a psychotropic medication known to be a substrate of any of these enzymes may have to be increased to maintain therapeutic effect.

KEY POINT
  • When simplifying or changing ART regimens, it is important to identify the potential effects that a loss (or gain) of CYP inhibition may have on every drug (not just ARVs) that an individual is taking.

Risks of Concomitant Drug Use

Combining drugs that have multiple mechanisms of action to achieve a similar therapeutic endpoint introduces the risk of additive adverse effects. Although this is not seen when combining ARVs to suppress HIV viral load, it can be seen when combining antihypertensive medicines (which may cause hypotension) or antidiabetic medicines (which may lead to additive hypoglycemia). In addition, an additive effect may result from medications with overlapping adverse effect profiles. A historic example is the use of zidovudine with other drugs that cause bone marrow suppression, including ribavirin or ganciclovir Sim, et al. 1998Aulitzky, et al. 1988.

Potent inhibitors: The use of potent inhibitors of metabolizing enzymes or drug transport proteins, such as protease inhibitors, may also lead to negative clinical outcomes (e.g., toxicities). Pharmacokinetic boosting, described as a potential beneficial drug-drug interaction in the section Beneficial Concomitant Drug Use, above, can have adverse outcomes if boosting leads to an undesired increase in the level of a concomitantly administered drug. When patients experience adverse effects, they are more likely to discontinue medications. Adverse effects also increase the number of patient visits to healthcare providers and may lead to prescription of additional medications to treat the adverse symptoms caused by the original medication, thus perpetuating the cycle of polypharmacy.

Potent inducers: The use of potent inducers of metabolizing enzymes or drug transport proteins, such as efavirenz or nevirapine, also has the potential to result in negative clinical outcomes. By increasing the metabolism or elimination of pharmacotherapeutic agents, reduced concentrations of these drugs are available to exert the expected therapeutic effect. Reducing ARVs to subtherapeutic levels can compromise viral suppression and increase the potential for resistance mutations. When simplifying an ART regimen by removing strong inducers of CYP isoenzymes, clinicians should remember that the loss of CYP induction may also affect all concomitant medications that a patient is taking, not just the ARVs.

For example, if efavirenz (which induces various CYP enzymes) is replaced with dolutegravir (which is not known to be an inhibitor of CYP enzymes) in a patient who was previously taking high doses of methadone (which is a substrate of several CYP enzymes), then the dose of methadone may have to be decreased to maintain the same therapeutic effect that was seen while the patient was taking efavirenz but without precipitating withdrawal.

Long-acting injectable ART: Long-acting injectable ARVs, which have a prolonged half-life, pose a unique drug-drug interaction challenge. For example, residual concentrations of the capsid inhibitor lenacapavir remain in the body for ≥12 months after discontinuation FDA(e) 2024, which may result in significant drug-drug interactions when medications also metabolized by CYP3A, including other HIV medications, are initiated for 9 months following the last dose. While residual concentrations of long-acting injectable cabotegravir/rilpivirine also last ≥12 months, the residual cabotegravir/rilpivirine concentrations are unlikely to have an effect on other primary care or HIV medications. The concurrent use of medications that are strong inducers of uridine diphosphate glucuronosyltransferase (UGT) 1A1 or UGT1A9 can decrease plasma concentrations of cabotegravir; medications that induce or inhibit CYP3A can affect plasma concentrations of rilpivirine. Therefore, clinicians should use caution when adding medications that induce UGT1A1, UGT1A9, or CYP3A since their concurrent use can lead to reduced cabotegravir or rilpivirine drug levels, complicating the timing for re-dosing of long-acting injectable ARVs.

Clinical Considerations and Prevention of Medication-Related Adverse Effects

Box 1: Medication Review and Prescribing Checklist
At each clinical visit, ask patients about the following:
  • Current medication list, including prescription medications, over-the-counter medications, supplements, and herbal preparation (see discussion below)
  • Any changes in medications or dosages since the last visit or medication review
  • Current medical conditions being treated or that require treatment
  • Previous medical conditions that have been resolved to check for medications that should be discontinued
When prescribing new medications or renewing a prescription, always:
  • Identify the new drug’s potential to cause adverse effects and current or future drug-drug interactions
  • Identify any potential interactions between an existing prescription medication and any new medications on the patient’s list
  • Identify and review any previous long-acting injectable medications, which can cause significant drug-drug interactions following discontinuation due to their long half-life
  • Inform patients about the potential for drug-drug interactions or adverse effects when taking ARVs that interact with commonly available over-the-counter medications, including nasal steroids, mineral supplements, antacids, or proton pump inhibitors

In reviewing medications, note all current prescription and over-the-counter medications (i.e., oral, inhalers, eye drops, ear drops, throat lozenges, suppositories, and topical medications), injectable drugs (including biologic agents and vaccines), complementary products (i.e., vitamins, supplements, and herbal products), and social and recreational drug use.

Clinicians can take several additional steps to prevent or alleviate unnecessary adverse effects, such as encouraging patients to avoid seeing multiple prescribers, avoid filling their prescriptions at multiple pharmacies, and keep each of their healthcare providers informed of treatment decisions made by other specialists Lavan, et al. 2016Lehnbom, et al. 2014. Prescribers are encouraged to work closely with clinical pharmacists and, in settings where this is possible, to consider collaborative drug therapy management agreements with these pharmacists McBane, et al. 2015.

Healthcare providers can assist patients in structuring detailed medication lists to be readily available in case of emergencies. This list should include the patient’s:

  • Medication allergies and intolerances
  • Prescription drugs
  • Pharmacy and contact information
  • Over-the-counter drugs and vitamins
  • Herbal or supplemental products

With the help of their care providers, patients can update their medication list at each medical appointment to ensure its accuracy Rose, et al. 2017. For each medication listed, the following information should be included McBane, et al. 2015:

  • Name of medication
  • Appropriate dosing
  • Indication for each medication, including those taken “as needed”
  • How and when each medication should be taken
  • How long each medication will be taken
  • What foods, beverages, or medications to avoid while taking each medication
  • Adverse effects a medication may cause
  • Special monitoring a medication may require

Electronic health records have streamlined the process of prescribing and dispensing medications and may even flag the potential for new therapeutic duplication, adverse drug reactions, or drug-drug interactions. Unfortunately, clinical decision support (CDS) systems, which aim to alert clinicians to therapeutic duplications, inappropriate dosages, or drug-drug interactions, are not without their drawbacks. Busy clinicians who receive more notifications than they can attend to may ignore important alerts Wright, et al. 2018. Such “alert fatigue” can potentially compromise patient safety. Efforts to further refine and/or customize the information detailed in these CDS alerts are ongoing. However, clinicians should be aware of the risks associated with alert fatigue when utilizing electronic health records or prescribing systems.

Electronic health records are not a replacement for direct review of a patient’s current medications or other drugs being taken. Care providers using electronic health records are at risk of missing important drug information if they succumb to alert fatigue Zahabi, et al. 2015.

KEY POINT
  • Clinicians utilizing electronic prescribing systems should be aware of the risks associated with “alert fatigue,” including the potential to miss drug-drug interaction alerts.

Medication therapy management (MTM) model: The MTM model was created in collaboration with 11 national pharmacy organizations and offers a useful approach to assessing and managing patient health concerns when disciplines work separately to care for a single patient. Centers for Medicaid and Medicare Services (CMS) must participate in MTM programs, and the goals of these programs are to optimize therapeutic outcomes through improved medication use, reduce the risk of adverse drug effects and drug-drug interactions, and improve medication adherence. The CMS website provides more information on requirements and services. Core elements of the MTM model include American Pharmacists Association 2021:

  • Medication therapy review: A systematic process of collecting patient-specific information to assess medication therapies in order to identify a prioritized list of medication-related problems and create a plan to resolve them.
  • Personal medication record (PMR) and medication-related action plan: Records created for an individual patient to address possible interventions and make appropriate referrals, including documenting these procedures.
    • The PMR is a comprehensive record of all of a patient’s medications, including herbal products, over-the-counter products, and dietary supplements, and is intended for patients to use in medication self-management.
    • Updated PMRs should be created with any medication change.
    • The medication-related action plan is a patient-centric document containing a list of actions that the patient can take to improve his or her self-management and includes only information that is within the pharmacist’s scope of practice or has been agreed on by other relevant members of the healthcare team.
  • Pharmacotherapy consults: Inclusion of a pharmacist’s expertise for safe, appropriate, and cost-effective use of medications for patients who have already developed or are at high risk of developing medication-related problems.

These strategies have several important benefits, including preventing or managing adverse medication reactions and hypersensitivities. They ensure an adequate diagnosis and indication for each therapy and help determine whether symptoms are caused by a medical condition or are simply effects of a medication the patient is already taking. It also aids in transitions of care, including transitions from primary to specialty care or from ambulatory care to inpatient facilities. Such documents also aid in future treatment decisions and allow for appropriate patient education about drug effects and adherence. They may also reduce polypharmacy and healthcare costs by ensuring a patient is not given medication simply to treat adverse drug reactions or manage drug-drug interactions.

Pharmacist care services and comprehensive medication management are also considered integral components of the patient-centered medical home Patient-Centered Primary Care Collaborative 2012.

KEY POINT
  • An accurate and frequently updated medication history helps to prevent errors with prescription, over-the-counter, and supplement and/or herbal medications.

Therapeutic drug monitoring (TDM): TDM of drug concentrations from plasma, serum, or blood is used to individualize dosing of narrow therapeutic index drugs, allowing drug concentrations to be maintained within a specific target range. Although measurement of drug concentration at the site of action is not always possible, it is believed that with TDM, the concentration of a drug in intracellular fluids is more closely associated with therapeutic and adverse effects than the dose of a medication. TDM is most commonly performed for medications that have a narrow therapeutic window and significant pharmacokinetic variability. Medications that are dosed based on TDM include immunosuppressant drugs used to prevent organ rejection (e.g., cyclosporine, tacrolimus), antiseizure medications (e.g., phenytoin, carbamazepine), and mood stabilizers (e.g., lithium, lamotrigine). Certain antibiotics, including vancomycin or aminoglycosides, are also dosed based on TDM.

The use of TDM with ARV dosing is not currently recommended in the routine management of most patients with HIV. However, limited prospective data suggest that certain clinical scenarios exist in which TDM may be beneficial, such as suspicion of clinically significant drug-drug interactions that result in reduced plasma concentrations of an ARV, which may reduce viral control, or when such interactions result in increased concentrations of an ARV, thereby increasing the risk of adverse drug effects DHHS(a) 2023. The effects may be more pronounced when drug-drug interactions are accompanied by pathophysiologic changes that alter the pharmacokinetics of a drug, including its absorption, distribution, metabolism, or excretion. These changes include, but are not limited to, reduced renal or hepatic function, vomiting or other conditions that reduce absorption, and pregnancy.

Resources

Online and print materials are available to help healthcare professionals and patients with the management of interactions between ARVs and other commonly used medications. Use caution when consulting print resources and/or online resources that are not routinely updated because drug-drug interaction data change consistently with new research, case reports, or approval of new medications by the U.S. Food and Drug Administration.

RESOURCES
For clinicians:
For patients:

Classifications and Mechanisms of Drug-Drug Interactions

Antiretroviral (ARV) medications themselves, though increasingly safe and effective, may cause adverse effects that affect organ systems Gallant, et al. 2018Dharan and Cooper 2017. Tenofovir disoproxil fumarate (TDF) has been shown to reduce bone mineral density and may impair renal function. Tenofovir alafenamide (TAF) does not appear to have a similar effect on bone density or kidney function, and increased bone density and improved renal function have been observed in patients who are switched from TDF to TAF Lampertico, et al. 2020Raffi, et al. 2017. Conflicting data suggest a possible association between abacavir and cardiovascular disease Llibre and Hill 2016. A convincing pathophysiologic mechanism for this association has not yet been described and is likely to be multifactorial Alvarez, et al. 2017. Association should not imply causation, but caution may be warranted when prescribing abacavir to patients with underlying risk factors for cardiovascular disease. Boosted protease inhibitors (PIs) and some non-nucleoside reverse transcriptase inhibitors may exacerbate metabolic disorders by reducing insulin sensitivity or causing lipid abnormalities Aberg, et al. 2012Noor, et al. 2004Carr, et al. 1998. These inherent adverse effects may lead to poor control and the need for additional concurrent medications for management of these metabolic conditions. An unintended consequence of the additional medications is the increased likelihood of drug-drug interactions.

Table 1: Mechanisms of Antiretroviral (ARV) Drug-Drug Interactions, below, shows the influence of specific ARVs on liver enzymes and describes the effect of specific ARVs on these drug transport proteins.

Pharmacodynamic Interactions

Pharmacodynamic interactions are drug-drug interactions that involve the direct effects of the interacting drugs and a change in a patient’s response to the drugs Trevor, et al. 2013. Pharmacodynamic interactions may involve pharmacologic receptors, and drugs may be agonists or antagonists of other drugs.

  • Pure agonists attach to the same binding site receptor as another drug, thus causing the same effect.
  • Partial agonists bind to a different receptor site on the same receptor and may cause the same effect as another drug but to a lower intensity.
  • Antagonists attach to the same receptor site as another drug, but the effect of this binding opposes the effect seen with another drug.

An historic example of a pharmacodynamic interaction is the concomitant use of zidovudine with other drugs that cause bone marrow suppression, including ribavirin or ganciclovir.

To minimize pharmacodynamic interactions, identify and address potential additive or antagonistic physiologic effects when treating a patient with more than 1 medication. Adding or removing a pharmacokinetic booster from a patient’s medication regimen may alter the levels of coadministered drugs and affect the efficacy or safety of these drugs.

Drug name abbreviations: 3TC, lamivudine; ABC, abacavir; ATV, atazanavir; BIC, bictegravir; CAB, cabotegravir; COBI, cobicistat; DRV, darunavir; DOR, doravirine; DTG, dolutegravir; EFV, efavirenz; ETR, etravirine; EVG, elvitegravir; FTC, emtricitabine; FTR, fostemsavir; IBA, ibalizumab; LEN, lenacapavir; MVC, maraviroc; RAL, raltegravir; RPV, rilpivirine; RTV, ritonavir; TAF, tenofovir alafenamide; TDF, tenofovir disoproxil fumarate.

Other abbreviations: BCRP, breast cancer resistance protein; CYP, cytochrome P450; GI, gastrointestinal; MATE, multidrug and toxin extrusion; MRP, multidrug resistance protein; OATP, organic anion transporting polypeptide; OCT, organic cation transporter; P-gP, P-glycoprotein; UGT, uridine diphosphate glucuronosyltransferase.

Note:

  1. Based on the IBA mechanism of action and target-mediated drug disposition, drug-drug interactions are not expected.

Sources: DHHS(b) 2023Tseng, et al. 2017Marzolini, et al. 2016Taneva, et al. 2015Kiser, et al. 2008; 1. Markham 2018; 2. FDA(d) 2023; 3. McCormack 2014; 4. Deeks(c) 2014Perry 2014; 5. Deeks 2017; 6. Deeks(a) 2014; 7. Tseng, et al. 2017Deeks(b) 2014Croom, et al. 2009; 8. Croom, et al. 2009; 9. Deeks(b) 2014; 10. Deeks 2018Yee, et al. 2017; 11. Ogburn, et al. 2010; 12. Deeks and Keating 2008; 13. Deeks(d) 2014; 14. Barbarino, et al. 2014; 15. Reznicek, et al. 2017; 16. Muller, et al. 2013; 17. Scott and Chan 2017; 18. Kohler, et al. 2011Kearney, et al. 2004; 19. FDA(d) 2024; 20. FDA(c) 2023; 21. Perry 2010; 22. FDA(e) 2024.

Table 1: Mechanisms of Antiretroviral (ARV) Drug-Drug Interactions
Cited references are listed at bottom of table; also see drug package inserts.
ARV CYP Substrate CYP Inhibitor CYP Inducer UGT1A1 Drug Transport Protein Other
Integrase Strand Inhibitors (INSTIs)
BIC [1] 3A4 (minor) Substrate Inhibitor of MATE1, OCT2 Chelation
CAB [2] Substrate P-gP substrate; OATP1 inhibitor
DTG [3] 3A4 (minor) Substrate P-gP substrate; Inhibitor of MATE2, OCT2 Chelation
EVG [4] 3A4 2C9 Substrate Chelation
RAL [5] Substrate Chelation
Pharmacokinetic Boosters
COBI [6] 3A4, 2D6 (minor) 3A4, 2D6 (minor) Inhibitor of P-gP, BCRP, OATP, OCT, MATE1
RTV [7] 3A4, 2D6 (minor) 3A4, 2C8, 2C9, 2C19, 2D6 1A2, 2B6, 2C9, 2C19 Inducer Inhibitor of P-gP, BCRP, OATP, OCT, MATE1
Protease Inhibitors (PIs)
ATV [8] 3A4 3A4, 2C8 (minor) Inhibitor P-gP substrate, inhibitor, inducer; OATP inhibitor GI absorption (pH-dependent)
DRV [9] 3A4 3A4 2C9 P-gP substrate; OATP inhibitor
Non-Nucleoside Reverse Transcriptase Inhibitors (NNRTIs)
DOR [10] 3A4, 3A5
EFV [11] 2B6 (primary), 2A6, 3A4 3A4 3A4, 2B6
ETR [12] 3A4, 2C9, 2C19 2C9, 2C19 3A4 P-gP inducer
RPV [13] 3A4 GI absorption (pH-dependent)
Nucleoside Reverse Transcriptase Inhibitors (NRTIs)
ABC [14] Alcohol dehydrogenase substrate
FTC [15] MATE1 substrate
3TC [16] Substrate of MATE1/2, OCT2
TAF [17] 3A4 (minor) Substrate of P-gP, BCRP, OATP
TDF [18] Substrate of P-gP, OATP, MRP
Entry Inhibitors (EIs)
FTR [19] 3A4 Substrate of P-gP, BCRP; Inhibitor of OATP, BCRP
IBA [a] [20]
MVC [21] 3A4 P-gP substrate
Capsid Inhibitor
LEN [22] 3A4 (minor) 3A4 (moderate) Substrate (minor) P-gP substrate
Abbreviations: BCRP, breast cancer resistance protein; CYP, cytochrome P450; MATE, multidrug and toxin extrusion; OAT, organic anion transporter; OATP, organic anion transporting protein; OCT, organic cation transporter; P-gP, P-glycoprotein; UGT, uridine diphosphate glucuronosyltransferase.

Note:

  1. The information above is expected when ritonavir is given at doses used to boost other protease inhibitors. Effects may change at higher doses of ritonavir because this drug has a mixed effect (both induction and inhibition) on several CYP isoenzymes when studied at higher doses.

Sources: Tseng, et al. 2017Marzolini, et al. 2016Foisy, et al. 2008

Table 2: Induction Potential of Ritonavir [a] and Cobicistat Used as Boosters
Ritonavir Cobicistat
Cytochrome
CYP1A2 Moderate inducer Clinically negligible effect
CYP2B6 Moderate inducer Clinically negligible effect
CYP2C8 Moderate inhibitor Clinically negligible effect
CYP2C9 Moderate inducer Clinically negligible effect
CYP2C19 Strong inducer Clinically negligible effect
CYP2D6 Moderate inhibitor Mild inhibitor
CYP3A4 Strong inhibitor Strong inhibitor
Transporter
P-gP Moderate inhibitor Moderate inhibitor
UGT Moderate inducer Clinically negligible effect
BCRP Moderate inhibitor Moderate inhibitor
OATP1B1 Moderate inhibitor Moderate inhibitor
OATP1B3 Moderate inhibitor Moderate inhibitor
MATE1 Moderate inhibitor Moderate inhibitor
MATE2-K Clinically negligible effect Clinically negligible effect
OAT1 Clinically negligible effect Clinically negligible effect
OAT3 Weak inducer Clinically negligible effect
OCT2 Clinically negligible effect Clinically negligible effect

Pharmacokinetic Interactions

Pharmacokinetic interactions involve the modification of drug absorption, distribution, metabolism, and excretion Trevor, et al. 2013.

Absorption: Modification of gastric pH will influence the absorption of drugs that require the acidity of the stomach (e.g., the absorption of both rilpivirine and atazanavir are reduced when these drugs are given concomitantly with proton pump inhibitors such as omeprazole Schafer and Short 2012Klein, et al. 2008). Some substances will form insoluble complexes with other drugs in a process known as chelation (e.g., using integrase inhibitors such as raltegravir with divalent or trivalent cations such as aluminum and magnesium Wallace, et al. 2003). Medications that influence the motility of the gastrointestinal tract may also affect absorption of other drugs.

Distribution: When 2 heavily protein-bound medications are given at the same time, competition for protein binding sites leads to an increase in free drug concentrations, which are available to exert therapeutic effects or increase toxicity of the medications. In most cases, a rapid equilibrium is reached between the free and bound drugs, and these drug-drug interactions are rarely clinically significant Benet and Hoener 2002. An exception is when a drug has a narrow therapeutic index (e.g., warfarin, digoxin, lithium, aminoglycoside antibiotics); displacement of such a drug may have a dramatic effect on the level of activity of the agent Zaccara and Perucca 2014.

Metabolism: The liver is the major site of drug metabolism, which occurs in 2 phases. Medications that alter phase I metabolism affect the oxidation, reduction, or hydrolysis of another medication. This typically involves the cytochrome P450 (CYP) isoenzymes, and drugs are classified as substrates, inducers, or inhibitors of specific enzymes. One of the most commonly described CYP enzymes is 3A4, which is responsible for the metabolism of many commonly used medications. However, other enzymes exist, and many play important roles in interactions related to ARVs. Each enzyme has a specific action; some drugs may be substrates, inhibitors, or inducers of more than 1 enzyme, and may even be substrates of one while inhibiting or inducing others. This creates complex interaction possibilities, and the therapeutic effects of these interactions may be unknown.

A drug is defined as a substrate if a certain enzyme metabolizes it. Rilpivirine and maraviroc are substrates of CYP3A4 Deeks(d) 2014Perry 2010. Enzyme inducers increase the numbers of specific enzyme subtypes inside the body, thus increasing the metabolism of substrates of that enzyme or reducing the drug’s bioavailability. Examples of strong CYP3A inducers include efavirenz and rifampin Ogburn, et al. 2010. Moderate inducers of CYP3A include etravirine Deeks and Keating 2008. Some drugs, including nevirapine, are autoinducers of their own metabolism, causing the lead-in period seen when dosing those drugs Cammett, et al. 2009. Inhibitors block metabolism of substrate drugs by directly binding to enzymes, increasing the bioavailability of substrate drugs. The most common examples of CYP3A inhibitors are the pharmacokinetic enhancers ritonavir and cobicistat and other PIs Tseng, et al. 2017Deeks(a) 2014.

Drugs that alter phase II metabolism affect glucuronidation, methylation, sulfation, or other forms of conjugation. Careful monitoring for therapeutic efficacy and safety is required in these circumstances. Examples of this type of enzyme include uridine diphosphate glucuronosyltransferase (UGT), which also plays a role in the glucuronidation of some drugs, including integrase strand transfer inhibitors (INSTIs) Adams, et al. 2012. Other agents, such as atazanavir, can inhibit UGT enzymes Gammal, et al. 2016. The interaction between raltegravir and atazanavir is of limited clinical significance. However, rifampin also induces UGT enzymes, and concomitant administration of rifampin and INSTIs greatly reduces bioavailability of these drugs, often necessitating dose adjustments Miller, et al. 2017.

Long-acting injectable ARVs, such as lenacapavir and cabotegravir/rilpivirine, result in residual concentrations that last ≥12 months following the last injection of medication. Drug-drug interaction risk may continue as long as 9 months after the last dose FDA(e) 2024. As a moderate CYP3A4 inhibitor, lenacapavir is of greater concern than cabotegravir/rilpivirine for potential drug-drug interactions even after discontinuation.

Excretion: Renal elimination involves both passive and active processes. Tubular secretion is a drug transport protein-mediated process, and competitive inhibition of tubular secretion is a common mechanism of drug-drug interactions in the kidney. Other drugs are more rapidly eliminated in acidic or alkaline urine, and alterations in the urine pH will influence rate of elimination.

To minimize pharmacokinetic interactions, identify and address a drug’s effect on metabolizing enzymes or drug transport proteins when treating a patient with more than 1 medication Trevor, et al. 2013. Consider Table 1: Mechanisms of Antiretroviral (ARV) Drug-Drug Interactions, above, as a helpful starting point, but be aware that the chart is not meant to be a finite resource on the pharmacokinetic effects of the listed ARVs.

Other Drug-Drug Interactions

Drug-drug interactions may also result from modification of drug transport proteins, which exist throughout the body (e.g., kidney, liver, small intestine, and blood-brain barrier). As their name suggests, these drugs are important in the transfer of a drug or other endogenous substance from one body compartment to another Ivanyuk, et al. 2017Yoshida, et al. 2017. P-glycoprotein (P-gP) is a well-known example of a drug transport protein, and this efflux transporter attempts to keep foreign substances, including some drugs, out of a cell Lund, et al. 2017. Inducing P-gP may decrease the amount of drug inside a cell, reducing its therapeutic efficacy. Inhibiting P-gP may increase the amount of drug inside a cell, increasing its efficacy, or leading to adverse effects.

Several other drug transport proteins have been discovered, and families of these proteins include multidrug and toxin extrusion, organic cation transporter Yin, et al. 2016, organic anion transporter, breast cancer resistance protein Mao and Unadkat 2015, and organic anion transporting polypeptide (OATP) enzymes Kovacsics, et al. 2017Yu, et al. 2017. The clinical significance of these proteins or the influence of drugs on the activity of these proteins is incompletely understood, but this area of pharmacotherapeutic research is rapidly evolving. An example of such an interaction is TDF with diclofenac Morelle, et al. 2009, which are both substrates of OATP1B3 and compete for renal secretion. This increases the levels of these agents and may increase the risk of tubular toxicity due to prolonged tenofovir availability inside the tubular cells.

Drug-Drug Interactions by Antiretroviral Medication Class

RECOMMENDATION
  • Clinicians should consult an experienced HIV care provider for assistance in managing drug-drug interactions between antiretroviral (ARV) agents and less common medications. (A3)

Caveats: Many of the formal interaction studies involving ARVs are carried out in small samples of participants who do not have HIV or other known comorbid conditions. Although the results of such studies may be extrapolated to larger populations of individuals with HIV, several important considerations should be kept in mind. The U.S. Food and Drug Administration has issued draft guidance on the design, analysis, and clinical implications of drug-drug interaction studies to aid in the interpretation of future interactions FDA(b) 2024.

Given the limited financial and clinical resources available to researchers, it is impossible to design and run randomized controlled trials to determine the effects of every possible drug-drug interaction. Therefore, many drug-drug interactions are theoretical—based not on evidence or data but instead on what is known about the pharmacokinetic properties of the various individual agents. As a result, an incomplete correlation often exists between predicted drug-drug interactions and in vivo pharmacokinetics. Significant person-to-person variability also exists in drug-drug interactions, and small sample sizes may not be adequate to identify the effects such an interaction may have on a specific patient.

Patients with HIV may be at greater risk of pharmacokinetic variability due to the nature of the infection itself or the drugs taken for antiretroviral therapy (ART). At the same time, both the medications and HIV itself may alter the physiologic processes of the liver, kidney, brain, gastrointestinal system, or other organ systems, which may affect absorption, distribution, metabolism, or elimination of pharmacologically active agents. Additionally, patients with HIV are at a greater risk of the effects of polypharmacy, and the effects of multiple drugs on the pharmacokinetic pathways or pharmacodynamic effects of a single agent are not well documented. Therefore, when treating patients who are taking several medications for multiple comorbid conditions, expert advice may be necessary and is often recommended to ensure appropriate management of drug-drug interactions.

ARVs can have complex interactions with other medications commonly used by patients with HIV. When questions arise regarding the management of drug-drug interactions not described here, a clinician cannot assume that no interaction exists. Several theoretical drug-drug interactions may exist given the unique nature of the pharmacokinetic and pharmacodynamic effects seen with each medication, and the clinical significance of these interactions is not always known. The interactions described here reflect medications used to treat comorbid conditions commonly seen in primary care or family health clinics.

Prescribers should become familiar with the potential for adverse effects and drug-drug interactions with all coadministered drugs they prescribe. Clinicians who manage the care of only a few patients with HIV may find it difficult to remember the potential mechanisms or effects of interactions between ARVs and other medications commonly prescribed in primary care, and drug-drug interactions may lead to symptoms attributed to ARVs rather than the physiologic effect of interaction. Consultation with a pharmacist or healthcare provider experienced in prescribing ART may assist in determining the true cause of symptoms and/or adverse effects. Adverse drug-drug interactions can be prevented when patients receive anticipatory guidance regarding possible interactions between prescribed medications and commonly available over-the-counter medications or supplements.

The following tables are available as individual PDF downloads.

Boosted Protease Inhibitors (PIs)

Integrase Strand Transfer Inhibitors (INSTIs)

Non-Nucleoside Reverse Transcriptase Inhibitors (NNRTIs)

Nucleoside Reverse Transcriptase Inhibitors (NRTIs)

Entry Inhibitors (EIs)

Capsid Inhibitor

Drug-Drug Interactions by Common Medication Class

The following tables are not meant to serve as a definitive resource on all possible drug-drug interactions between common antiretroviral (ARV) and non-ARV medications. Instead, they offer a brief introduction to the management of interactions between medications used to treat HIV and comorbidities commonly seen in primary care settings. The tables are organized by common disease states and prioritized by those most commonly seen in primary care. Within each table, the medications are prioritized according to the preference the NYSDOH AI and U.S. Department of Health and Human Services give each class of medications in the initial management of HIV. Appropriate HIV management should be individualized according to patient-specific factors, and not all ARVs may be suitable for all patients.

In the event that an ARV does not have a clinically significant interaction with the class of medications described, it is still listed in the table. If an interaction is theoretical but its significance is unknown, the recommendation to monitor for safety and efficacy is provided. Drugs within a class that may have a significant interaction are described within the table. Other drugs that do not have clinically significant drug-drug interactions with ARVs but were reviewed are described in the footnotes of the individual tables. If a drug does not appear in the table or the footnotes, exercise extra caution when prescribing this medication to patients with HIV or AIDS. The resources provided here might be valuable for clinicians who seek more guidance on drug-drug interactions related to ARVs.

The informational material found within these tables is based on previously referenced primary, secondary, and tertiary literature, as well as the various publicly available databases described in the Resources section. Further information may be found in the literature, including the U.S. Food and Drug Administration’s reports or manufacturer’s prescribing information (drug package inserts), which are also available online for each of the listed pharmacologic agents. Healthcare providers are encouraged to utilize these resources if they are interested in learning more about specific drug-drug interactions or seek further information about the methodology of the research or the mechanisms and management of these interactions.

Consultation with an experienced HIV care provider is also recommended when assistance is needed in choosing an antiretroviral therapy (ART) regimen for a patient who has multiple comorbidities and may have multiple drug-drug interactions. For help locating an experienced HIV care provider, contact the Clinical Education Initiative at 866-637-2342.

KEY POINT
  • Medications used to treat epilepsy, various types of malignancies, and tuberculosis and to prevent graft-versus-host disease following solid organ transplants are known to interact with several ARVs. Because of the serious nature of these conditions and the complexity of their treatment, many details of the specific interactions of these drugs have not been reviewed here. Clinicians should consult with the appropriate specialty service when questions arise pertaining to the management of these conditions.

Shared Decision-Making

Download Printable PDF of Shared Decision-Making Statement

Date of current publication: August 8, 2023
Lead authors:
Jessica Rodrigues, MS; Jessica M. Atrio, MD, MSc; and Johanna L. Gribble, MA
Writing group: Steven M. Fine, MD, PhD; Rona M. Vail, MD; Samuel T. Merrick, MD; Asa E. Radix, MD, MPH, PhD; Christopher J. Hoffmann, MD, MPH; Charles J. Gonzalez, MD
Committee: Medical Care Criteria Committee
Date of original publication: August 8, 2023

Rationale

Throughout its guidelines, the New York State Department of Health (NYSDOH) AIDS Institute (AI) Clinical Guidelines Program recommends “shared decision-making,” an individualized process central to patient-centered care. With shared decision-making, clinicians and patients engage in meaningful dialogue to arrive at an informed, collaborative decision about a patient’s health, care, and treatment planning. The approach to shared decision-making described here applies to recommendations included in all program guidelines. The included elements are drawn from a comprehensive review of multiple sources and similar  attempts to define shared decision-making, including the Institute of Medicine’s original description [Institute of Medicine 2001]. For more information, a variety of informative resources and suggested readings are included at the end of the discussion.

Benefits

The benefits to patients that have been associated with a shared decision-making approach include:

  • Decreased anxiety [Niburski, et al. 2020; Stalnikowicz and Brezis 2020]
  • Increased trust in clinicians [Acree, et al. 2020; Groot, et al. 2020; Stalnikowicz and Brezis 2020]
  • Improved engagement in preventive care [McNulty, et al. 2022; Scalia, et al. 2022; Bertakis and Azari 2011]
  • Improved treatment adherence, clinical outcomes, and satisfaction with care [Crawford, et al. 2021; Bertakis and Azari 2011; Robinson, et al. 2008]
  • Increased knowledge, confidence, empowerment, and self-efficacy [Chen, et al. 2021; Coronado-Vázquez, et al. 2020; Niburski, et al. 2020]

Approach

Collaborative care: Shared decision-making is an approach to healthcare delivery that respects a patient’s autonomy in responding to a clinician’s recommendations and facilitates dynamic, personalized, and collaborative care. Through this process, a clinician engages a patient in an open and respectful dialogue to elicit the patient’s knowledge, experience, healthcare goals, daily routine, lifestyle, support system, cultural and personal identity, and attitudes toward behavior, treatment, and risk. With this information and the clinician’s clinical expertise, the patient and clinician can collaborate to identify, evaluate, and choose from among available healthcare options [Coulter and Collins 2011]. This process emphasizes the importance of a patient’s values, preferences, needs, social context, and lived experience in evaluating the known benefits, risks, and limitations of a clinician’s recommendations for screening, prevention, treatment, and follow-up. As a result, shared decision-making also respects a patient’s autonomy, agency, and capacity in defining and managing their healthcare goals. Building a clinician-patient relationship rooted in shared decision-making can help clinicians engage in productive discussions with patients whose decisions may not align with optimal health outcomes. Fostering open and honest dialogue to understand a patient’s motivations while suspending judgment to reduce harm and explore alternatives is particularly vital when a patient chooses to engage in practices that may exacerbate or complicate health conditions [Halperin, et al. 2007].

Options: Implicit in the shared decision-making process is the recognition that the “right” healthcare decisions are those made by informed patients and clinicians working toward patient-centered and defined healthcare goals. When multiple options are available, shared decision-making encourages thoughtful discussion of the potential benefits and potential harms of all options, which may include doing nothing or waiting. This approach also acknowledges that efficacy may not be the most important factor in a patient’s preferences and choices [Sewell, et al. 2021].

Clinician awareness: The collaborative process of shared decision-making is enhanced by a clinician’s ability to demonstrate empathic interest in the patient, avoid stigmatizing language, employ cultural humility, recognize systemic barriers to equitable outcomes, and practice strategies of self-awareness and mitigation against implicit personal biases [Parish, et al. 2019].

Caveats: It is important for clinicians to recognize and be sensitive to the inherent power and influence they maintain throughout their interactions with patients. A clinician’s identity and community affiliations may influence their ability to navigate the shared decision-making process and develop a therapeutic alliance with the patient and may affect the treatment plan [KFF 2023; Greenwood, et al. 2020]. Furthermore, institutional policy and regional legislation, such as requirements for parental consent for gender-affirming care for transgender people or insurance coverage for sexual health care, may infringe upon a patient’s ability to access preventive- or treatment-related care [Sewell, et al. 2021].

Figure 1: Elements of Shared Decision-Making

Figure 1: Elements of Shared Decision-Making

Download figure: Elements of Shared Decision-Making

Health equity: Adapting a shared decision-making approach that supports diverse populations is necessary to achieve more equitable and inclusive health outcomes [Castaneda-Guarderas, et al. 2016]. For instance, clinicians may need to incorporate cultural- and community-specific considerations into discussions with women, gender-diverse individuals, and young people concerning their sexual behaviors, fertility intentions, and pregnancy or lactation status. Shared decision-making offers an opportunity to build trust among marginalized and disenfranchised communities by validating their symptoms, values, and lived experience. Furthermore, it can allow for improved consistency in patient screening and assessment of prevention options and treatment plans, which can reduce the influence of social constructs and implicit bias [Castaneda-Guarderas, et al. 2016].

Clinician bias has been associated with health disparities and can have profoundly negative effects [FitzGerald and Hurst 2017; Hall, et al. 2015]. It is often challenging for clinicians to recognize and set aside personal biases and to address biases with peers and colleagues. Consciously or unconsciously, negative or stigmatizing assumptions are often made about patient characteristics, such as race, ethnicity, gender, sexual orientation, mental health, and substance use [Avery, et al. 2019; van Boekel, et al. 2013; Livingston, et al. 2012]. With its emphasis on eliciting patient information, a shared decision-making approach encourages clinicians to inquire about patients’ lived experiences rather than making assumptions and to recognize the influence of that experience in healthcare decision-making.

Stigma: Stigma may prevent individuals from seeking or receiving treatment and harm reduction services [Tsai, et al. 2019]. Among people with HIV, stigma and medical mistrust remain significant barriers to healthcare utilization, HIV diagnosis, and medication adherence and can affect disease outcomes [Turan, et al. 2017; Chambers, et al. 2015], and stigma among clinicians against people who use substances has been well-documented [Stone, et al. 2021; Tsai, et al. 2019; van Boekel, et al. 2013]. Sexual and reproductive health, including strategies to prevent HIV transmission, acquisition, and progression, may be subject to stigma, bias, social influence, and violence.

SHARED DECISION-MAKING IN HIV CARE
  • As prevention and treatment modalities in HIV care expand (i.e., vaccines, barriers, injectables, implants, on-demand therapies), it is important for clinicians to ask patients about their goals for prevention and treatment rather than assume that efficacy is the primary factor in patient preference [Sewell, et al. 2021].
  • The shared decision-making approach to clinical care enhances patient knowledge and uptake of new technologies and behavioral practices that align with the patient’s unique preferences and identity [Sewell, et al. 2021], ensures that the selection of a care plan is mutually agreed upon, and considers the patient’s ability to effectively use and adhere to the selected course of prevention or treatment.

Resources and Suggested Reading

In addition to the references cited below, the following resources and suggested reading may be useful to clinicians.

RESOURCES
References

Acree ME, McNulty M, Blocker O, et al. Shared decision-making around anal cancer screening among black bisexual and gay men in the USA. Cult Health Sex 2020;22(2):201-16. [PMID: 30931831]

Avery JD, Taylor KE, Kast KA, et al. Attitudes toward individuals with mental illness and substance use disorders among resident physicians. Prim Care Companion CNS Disord 2019;21(1):18m02382. [PMID: 30620451]

Bertakis KD, Azari R. Patient-centered care is associated with decreased health care utilization. J Am Board Fam Med 2011;24(3):229-39. [PMID: 21551394]

Castaneda-Guarderas A, Glassberg J, Grudzen CR, et al. Shared decision making with vulnerable populations in the emergency department. Acad Emerg Med 2016;23(12):1410-16. [PMID: 27860022]

Chambers LA, Rueda S, Baker DN, et al. Stigma, HIV and health: a qualitative synthesis. BMC Public Health 2015;15:848. [PMID: 26334626]

Chen CH, Kang YN, Chiu PY, et al. Effectiveness of shared decision-making intervention in patients with lumbar degenerative diseases: a randomized controlled trial. Patient Educ Couns 2021;104(10):2498-2504. [PMID: 33741234]

Coronado-Vázquez V, Canet-Fajas C, Delgado-Marroquín MT, et al. Interventions to facilitate shared decision-making using decision aids with patients in primary health care: a systematic review. Medicine (Baltimore) 2020;99(32):e21389. [PMID: 32769870]

Coulter A, Collins A. Making shared decision-making a reality: no decision about me, without me. 2011. https://www.kingsfund.org.uk/sites/default/files/Making-shared-decision-making-a-reality-paper-Angela-Coulter-Alf-Collins-July-2011_0.pdf

Crawford J, Petrie K, Harvey SB. Shared decision-making and the implementation of treatment recommendations for depression. Patient Educ Couns 2021;104(8):2119-21. [PMID: 33563500]

FitzGerald C, Hurst S. Implicit bias in healthcare professionals: a systematic review. BMC Med Ethics 2017;18(1):19. [PMID: 28249596]

Greenwood BN, Hardeman RR, Huang L, et al. Physician-patient racial concordance and disparities in birthing mortality for newborns. Proc Natl Acad Sci U S A 2020;117(35):21194-21200. [PMID: 32817561]

Groot G, Waldron T, Barreno L, et al. Trust and world view in shared decision making with indigenous patients: a realist synthesis. J Eval Clin Pract 2020;26(2):503-14. [PMID: 31750600]

Hall WJ, Chapman MV, Lee KM, et al. Implicit racial/ethnic bias among health care professionals and its influence on health care outcomes: a systematic review. Am J Public Health 2015;105(12):e60-76. [PMID: 26469668]

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Institute of Medicine. Crossing the quality chasm: a new health system for the 21st century. 2001. https://www.ncbi.nlm.nih.gov/books/NBK222274/

KFF. Key data on health and health care by race and ethnicity. 2023 Mar 15. https://www.kff.org/racial-equity-and-health-policy/report/key-data-on-health-and-health-care-by-race-and-ethnicity/ [accessed 2023 May 19]

Livingston JD, Milne T, Fang ML, et al. The effectiveness of interventions for reducing stigma related to substance use disorders: a systematic review. Addiction 2012;107(1):39-50. [PMID: 21815959]

McNulty MC, Acree ME, Kerman J, et al. Shared decision making for HIV pre-exposure prophylaxis (PrEP) with black transgender women. Cult Health Sex 2022;24(8):1033-46. [PMID: 33983866]

Niburski K, Guadagno E, Abbasgholizadeh-Rahimi S, et al. Shared decision making in surgery: a meta-analysis of existing literature. Patient 2020;13(6):667-81. [PMID: 32880820]

Parish SJ, Hahn SR, Goldstein SW, et al. The International Society for the Study of Women’s Sexual Health process of care for the identification of sexual concerns and problems in women. Mayo Clin Proc 2019;94(5):842-56. [PMID: 30954288]

Robinson JH, Callister LC, Berry JA, et al. Patient-centered care and adherence: definitions and applications to improve outcomes. J Am Acad Nurse Pract 2008;20(12):600-607. [PMID: 19120591]

Scalia P, Durand MA, Elwyn G. Shared decision-making interventions: an overview and a meta-analysis of their impact on vaccine uptake. J Intern Med 2022;291(4):408-25. [PMID: 34700363]

Sewell WC, Solleveld P, Seidman D, et al. Patient-led decision-making for HIV preexposure prophylaxis. Curr HIV/AIDS Rep 2021;18(1):48-56. [PMID: 33417201]

Stalnikowicz R, Brezis M. Meaningful shared decision-making: complex process demanding cognitive and emotional skills. J Eval Clin Pract 2020;26(2):431-38. [PMID: 31989727]

Stone EM, Kennedy-Hendricks A, Barry CL, et al. The role of stigma in U.S. primary care physicians’ treatment of opioid use disorder. Drug Alcohol Depend 2021;221:108627. [PMID: 33621805]

Tsai AC, Kiang MV, Barnett ML, et al. Stigma as a fundamental hindrance to the United States opioid overdose crisis response. PLoS Med 2019;16(11):e1002969. [PMID: 31770387]

Turan B, Budhwani H, Fazeli PL, et al. How does stigma affect people living with HIV? The mediating roles of internalized and anticipated HIV stigma in the effects of perceived community stigma on health and psychosocial outcomes. AIDS Behav 2017;21(1):283-91. [PMID: 27272742]

van Boekel LC, Brouwers EP, van Weeghel J, et al. Stigma among health professionals towards patients with substance use disorders and its consequences for healthcare delivery: systematic review. Drug Alcohol Depend 2013;131(1-2):23-35. [PMID: 23490450]

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Updates, Authorship, and Related Guidelines

Updates, Authorship, and Related Guidelines
Date of original publication April 25, 2019
Date of current publication August 13, 2024
Highlights of changes, additions, and updates in the August 13, 2024 edition
  • Added information on long-acting injectable antiretroviral therapy to Identifying Drug-Drug Interactions and Classifications and Mechanisms of Drug-Drug Interactions sections
  • Updated antidiabetic medication and gender-affirming hormones interactions information and added ADHD medications interactions information throughout Drug-Drug Interactions by Antiretroviral Medication Class section
  • Updated Table 25: Antidiabetic Medications and Table 48: Gender-Affirming Hormones in Drug-Drug Interactions by Common Medication Class section
  • Added Table 49: ADHD Medications and Lithium to Drug-Drug Interactions by Common Medication Class section
Intended users New York State clinicians who prescribe and manage antiretroviral therapy for patients with HIV
Lead author

John J. Faragon, PharmD, BCPS, AAHIVP

Writing group

Rona M. Vail, MD; Sanjiv S. Shah, MD, MPH, AAHIVM, AAHIVS; Steven M. Fine, MD, PhD; Joseph P. McGowan, MD, FACP, FIDSA, AAHIVS; Samuel T. Merrick, MD, FIDSA; Asa E. Radix, MD, MPH, PhD, FACP, AAHIVS; Jessica Rodriguez, MPH, MS; Christopher J. Hoffmann, MD, MPH, MSc, FACP; Brianna L. Norton, DO, MPH; Charles J. Gonzalez, MD

Author and writing group conflict of interest disclosures

John J. Faragon, PharmD, BCPS, AAHIVP: Speakers bureau: Gilead Sciences; honorarium recipient: ViiV Healthcare

Committee

Medical Care Criteria Committee

Developer and funder

New York State Department of Health AIDS Institute (NYSDOH AI)

Development process

See Guideline Development and Recommendation Ratings Scheme, below.

Guideline Development and Recommendation Ratings

Guideline Development: New York State Department of Health AIDS Institute Clinical Guidelines Program
Program manager Clinical Guidelines Program, Johns Hopkins University School of Medicine, Division of Infectious Diseases. See Program Leadership and Staff.
Mission To produce and disseminate evidence-based, state-of-the-art clinical practice guidelines that establish uniform standards of care for practitioners who provide prevention or treatment of HIV, viral hepatitis, other sexually transmitted infections, and substance use disorders for adults throughout New York State in the wide array of settings in which those services are delivered.
Expert committees The NYSDOH AI Medical Director invites and appoints committees of clinical and public health experts from throughout New York State to ensure that the guidelines are practical, immediately applicable, and meet the needs of care providers and stakeholders in all major regions of New York State, all relevant clinical practice settings, key New York State agencies, and community service organizations.
Committee structure
  • Leadership: AI-appointed chair, vice chair(s), chair emeritus, clinical specialist(s), JHU Guidelines Program Director, AI Medical Director, AI Clinical Consultant, AVAC community advisor
  • Contributing members
  • Guideline writing groups: Lead author, coauthors if applicable, and all committee leaders
Disclosure and management of conflicts of interest
  • Annual disclosure of financial relationships with commercial entities for the 12 months prior and upcoming is required of all individuals who work with the guidelines program, and includes disclosure for partners or spouses and primary professional affiliation.
  • The NYSDOH AI assesses all reported financial relationships to determine the potential for undue influence on guideline recommendations and, when indicated, denies participation in the program or formulates a plan to manage potential conflicts. Disclosures are listed for each committee member.
Evidence collection and review
  • Literature search and review strategy is defined by the guideline lead author based on the defined scope of a new guideline or update.
  • A comprehensive literature search and review is conducted for a new guideline or an extensive update using PubMed, other pertinent databases of peer-reviewed literature, and relevant conference abstracts to establish the evidence base for guideline recommendations.
  • A targeted search and review to identify recently published evidence is conducted for guidelines published within the previous 3 years.
  • Title, abstract, and article reviews are performed by the lead author. The JHU editorial team collates evidence and creates and maintains an evidence table for each guideline.
Recommendation development
  • The lead author drafts recommendations to address the defined scope of the guideline based on available published data.
  • Writing group members review the draft recommendations and evidence and deliberate to revise, refine, and reach consensus on all recommendations.
  • When published data are not available, support for a recommendation may be based on the committee’s expert opinion.
  • The writing group assigns a 2-part rating to each recommendation to indicate the strength of the recommendation and quality of the supporting evidence. The group reviews the evidence, deliberates, and may revise recommendations when required to reach consensus.
Review and approval process
  • Following writing group approval, draft guidelines are reviewed by all contributors, program liaisons, and a volunteer reviewer from the AI Community Advisory Committee.
  • Recommendations must be approved by two-thirds of the full committee. If necessary to achieve consensus, the full committee is invited to deliberate, review the evidence, and revise recommendations.
  • Final approval by the committee chair and the NYSDOH AI Medical Director is required for publication.
External reviews
  • External review of each guideline is invited at the developer’s discretion.
  • External reviewers recognized for their experience and expertise review guidelines for accuracy, balance, clarity, and practicality and provide feedback.
Update process
  • JHU editorial staff ensure that each guideline is reviewed and determined to be current upon the 3-year anniversary of publication; guidelines that provide clinical recommendations in rapidly changing areas of practice may be reviewed annually. Published literature is surveilled to identify new evidence that may prompt changes to existing recommendations or development of new recommendations.
  • If changes in the standard of care, newly published studies, new drug approval, new drug-related warning, or a public health emergency indicate the need for immediate change to published guidelines, committee leadership will make recommendations and immediate updates and will invite full committee review as indicated.
Recommendation Ratings Scheme
Strength Quality of Evidence
Rating Definition Rating Definition
A Strong 1 Based on published results of at least 1 randomized clinical trial with clinical outcomes or validated laboratory endpoints.
B Moderate * Based on either a self-evident conclusion; conclusive, published, in vitro data; or well-established practice that cannot be tested because ethics would preclude a clinical trial.
C Optional 2 Based on published results of at least 1 well-designed, nonrandomized clinical trial or observational cohort study with long-term clinical outcomes.
2† Extrapolated from published results of well-designed studies (including nonrandomized clinical trials) conducted in populations other than those specifically addressed by a recommendation. The source(s) of the extrapolated evidence and the rationale for the extrapolation are provided in the guideline text. One example would be results of studies conducted predominantly in a subpopulation (e.g., one gender) that the committee determines to be generalizable to the population under consideration in the guideline.
3 Based on committee expert opinion, with rationale provided in the guideline text.

Last updated on August 13, 2024