A Review of Long-Term Toxicity of Antiretroviral Treatment Regimens and Implications for an Aging Population

Chawla, Anita; Wang, Christina; Patton, Cody; Murray, Miranda; Punekar, Yogesh Suresh; Ruiter, Annemiek de; Steinhart, Corklin R.

doi:10.1007/s40121-018-0201-6

Cited by 113 publications

(90 citation statements)

References 80 publications

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“…As previously mentioned, seropositive patients surviving to their ICU stay are now at increased hazard of comorbidities associated with aging, chronic HIV infection, and cART-related toxicities [10,105]. This is especially relevant for cardiovascular and liver diseases, COPD, pulmonary hypertension, certain solid and hematological malignancies, and associated psychiatric [98].…”

Section: Long-term Outcomes Following Critical Illnessmentioning

confidence: 99%

Management of HIV-infected patients in the intensive care unit

et al. 2020

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The widespread use of combination antiretroviral therapies (cART) has converted the prognosis of HIV infection from a rapidly progressive and ultimately fatal disease to a chronic condition with limited impact on life expectancy. Yet, HIV-infected patients remain at high risk for critical illness due to the occurrence of severe opportunistic infections in those with advanced immunosuppression (i.e., inaugural admissions or limited access to cART), a pronounced susceptibility to bacterial sepsis and tuberculosis at every stage of HIV infection, and a rising prevalence of underlying comorbidities such as chronic obstructive pulmonary diseases, atherosclerosis or non-AIDS-defining neoplasms in cART-treated patients aging with controlled viral replication. Several patterns of intensive care have markedly evolved in this patient population over the late cART era, including a steady decline in AIDS-related admissions, an opposite trend in admissions for exacerbated comorbidities, the emergence of additional drivers of immunosuppression (e.g., anti-neoplastic chemotherapy or solid organ transplantation), the management of cART in the acute phase of critical illness, and a dramatic progress in short-term survival that mainly results from general advances in intensive care practices. Besides, there is a lack of data regarding other features of ICU and post-ICU care in these patients, especially on the impact of sociological factors on clinical presentation and prognosis, the optimal timing of cART introduction in AIDS-related admissions, determinants of end-of-life decisions, long-term survival, and functional outcomes. In this narrative review, we sought to depict the current evidence regarding the management of HIV-infected patients admitted to the intensive care unit.

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Section: Long-term Outcomes Following Critical Illnessmentioning

confidence: 99%

Management of HIV-infected patients in the intensive care unit

et al. 2020

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“…Efavirenz exhibits prolonged autoinduction leading to sub-therapeutic plasma levels in some patients after long-term treatment 5 . Furthermore metabolic disorders including, maldistribution, hyperlipemia, glucose intolerance and insulin resistance is recognized as long-term cART associated toxicities 6 . Hence long-term efavirenz pharmacokinetics may have implication on susceptibility to metabolic disorders including cardiovascular diseases.…”

Section: Introductionmentioning

confidence: 99%

Long-term efavirenz pharmacokinetics is comparable between Tanzanian HIV and HIV/Tuberculosis patients with the same CYP2B6*6 genotype

Kitabi

Minzi

Mugusi

et al. 2018

Sci Rep

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The impact of anti-tuberculosis co-treatment on efavirenz (EFV) exposure is still uncertain as contradictory reports exist, and the relevance of CYP2B6*6 genetic polymorphism on efavirenz clearance while on-and-off anti-tuberculosis co-treatment is not well investigated. We investigated the determinants of long-term efavirenz pharmacokinetics by enrolling HIV (n = 20) and HIV/Tuberculosis (n = 36) subjects undergoing efavirenz and efavirenz/rifampicin co-treatment respectively. Pharmacokinetic samplings were done 16 weeks after initiation of efavirenz-based anti-retroviral therapy and eight weeks after completion of rifampicin-based anti-tuberculosis treatment. Population pharmacokinetic modeling was used to characterize variabilities and covariates of efavirenz pharmacokinetic parameters. CYP2B6*6 genetic polymorphism but not rifampicin co-treatment was the statistically significant covariate. The estimated typical efavirenz clearance in the HIV only subjects with the CYP2B6*1/*1 genotype was 23.6 L/h/70 kg, while it was 38% and 69% lower in subjects with the CYP2B6*1/*6 and *6/*6 genotypes, respectively. Among subjects with the same CYP2B6 genotypes, efavirenz clearances were comparable between HIV and HIV/Tuberculosis subjects. Typical efavirenz clearances before and after completion of anti-tuberculosis therapy were comparable. In conclusion, after 16 weeks of treatment, efavirenz clearance is comparable between HIV and HIV/Tuberculosis patients with the same CYP2B6 genotype. CYP2B6 genotyping but not anti-tuberculosis co-treatment should guide efavirenz dosing to optimize treatment outcomes.

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“…It was possible to predict virological and immunological therapy failure/effectiveness based on the descriptors generated from a nucleotide sequence in combination with other descriptors, reflecting laboratory data and the clinical status of the patient, such as CD4 + count and viral load. Application of the computational models developed to predict HIV drug resistance, HIV treatment history, and virological and immunological therapy failure/effectiveness could be helpful in the optimization and personalization of antiretroviral therapy, which could be particularly important taking into account the toxicity and adverse effects [34][35][36] of drugs comprising ART schemes.…”

Section: Predicting Treatment Failure and Treatment Effectivenessmentioning

confidence: 99%

A Computational Approach for the Prediction of Treatment History and the Effectiveness or Failure of Antiretroviral Therapy

Tarasova

Biziukova

Kireev

et al. 2020

IJMS

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Human Immunodeficiency Virus Type 1 (HIV-1) infection is associated with high mortality if no therapy is provided. Currently, the treatment of an HIV-1 positive patient requires that several drugs should be taken simultaneously. The resistance of the virus to an antiretroviral drug may lead to treatment failure. Our approach focuses on predicting the exposure of a particular viral variant to an antiretroviral drug or drug combination. It also aims at the prediction of drug treatment success or failure. We utilized nucleotide sequences of HIV-1 encoding protease and reverse transcriptase to perform such types of prediction. The PASS (Prediction of Activity Spectra for Substances) algorithm based on the naive Bayesian classifier was used to make a prediction. We calculated the probability of whether a sequence belonged (P1) or did not belong (P0) to the class associated with exposure of the viral sequence to the set of drugs that can be associated with resistance to the set of drugs. The accuracy calculated as the average Area Under the ROC (Receiver Operating Characteristic) Curve (AUC/ROC) for classifying exposure of the sequence to the HIV-1 protease inhibitors was 0.81 (±0.07), and for HIV-1 reverse transcriptase, it was 0.83 (±0.07). To predict cases of treatment effectiveness or failure, we used P1 and P0 values, obtained in PASS, along with the binary vector constructed based on short nucleotide descriptors and the applied random forest classifier. Average AUC/ROC prediction accuracy for the prediction of treatment effectiveness or failure for the combinations of HIV-1 protease inhibitors was 0.82 (±0.06) and of HIV-1 reverse transcriptase was 0.76 (±0.09).

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A Review of Long-Term Toxicity of Antiretroviral Treatment Regimens and Implications for an Aging Population

Cited by 113 publications

References 80 publications

Management of HIV-infected patients in the intensive care unit

Management of HIV-infected patients in the intensive care unit

Long-term efavirenz pharmacokinetics is comparable between Tanzanian HIV and HIV/Tuberculosis patients with the same CYP2B6*6 genotype

A Computational Approach for the Prediction of Treatment History and the Effectiveness or Failure of Antiretroviral Therapy

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