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Zijp TR, Izzah Z, Åberg C, Gan CT, Bakker SJL, Touw DJ, van Boven JFM. Clinical Value of Emerging Bioanalytical Methods for Drug Measurements: A Scoping Review of Their Applicability for Medication Adherence and Therapeutic Drug Monitoring. Drugs 2021; 81:1983-2002. [PMID: 34724175 PMCID: PMC8559140 DOI: 10.1007/s40265-021-01618-7] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/26/2021] [Indexed: 12/05/2022]
Abstract
INTRODUCTION Direct quantification of drug concentrations allows for medication adherence monitoring (MAM) and therapeutic drug monitoring (TDM). Multiple less invasive methods have been developed in recent years: dried blood spots (DBS), saliva, and hair analyses. AIM To provide an overview of emerging drug quantification methods for MAM and TDM, focusing on the clinical validation of methods in patients prescribed chronic drug therapies. METHODS A scoping review was performed using a systematic search in three electronic databases covering the period 2000-2020. Screening and inclusion were performed by two independent reviewers in Rayyan. Data from the articles were aggregated in a REDCap database. The main outcome was clinical validity of methods based on study sample size, means of cross-validation, and method description. Outcomes were reported by matrix, therapeutic area and application (MAM and/or TDM). RESULTS A total of 4590 studies were identified and 175 articles were finally included; 57 on DBS, 66 on saliva and 55 on hair analyses. Most reports were in the fields of neurological diseases (37%), infectious diseases (31%), and transplantation (14%). An overview of clinical validation was generated of all measured drugs. A total of 62 drugs assays were applied for MAM and 131 for TDM. CONCLUSION MAM and TDM are increasingly possible without traditional invasive blood sampling: the strengths and limitations of DBS, saliva, and hair differ, but all have potential for valid and more convenient drug monitoring. To strengthen the quality and comparability of future evidence, standardisation of the clinical validation of the methods is recommended.
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Affiliation(s)
- Tanja R Zijp
- University of Groningen, University Medical Center Groningen, Department of Clinical Pharmacy and Pharmacology, Groningen, The Netherlands
| | - Zamrotul Izzah
- University of Groningen, University Medical Center Groningen, Department of Clinical Pharmacy and Pharmacology, Groningen, The Netherlands
- Department of Pharmacy Practice, Faculty of Pharmacy, Universitas Airlangga, Surabaya, Indonesia
- University of Groningen, Groningen Research Institute of Pharmacy, Department of Pharmaceutical Analysis, Groningen, The Netherlands
| | - Christoffer Åberg
- University of Groningen, Groningen Research Institute of Pharmacy, Department of Pharmaceutical Analysis, Groningen, The Netherlands
| | - C Tji Gan
- University of Groningen, University Medical Center Groningen, Respiratory Diseases and Lung Transplantation, Groningen, The Netherlands
| | - Stephan J L Bakker
- University of Groningen, University Medical Center Groningen, Department of Internal Medicine, Division of Nephrology, Groningen, The Netherlands
| | - Daan J Touw
- University of Groningen, University Medical Center Groningen, Department of Clinical Pharmacy and Pharmacology, Groningen, The Netherlands.
- University of Groningen, Groningen Research Institute of Pharmacy, Department of Pharmaceutical Analysis, Groningen, The Netherlands.
- Medication Adherence Expertise Center of the Northern Netherlands (MAECON), Groningen, The Netherlands.
| | - Job F M van Boven
- University of Groningen, University Medical Center Groningen, Department of Clinical Pharmacy and Pharmacology, Groningen, The Netherlands
- Medication Adherence Expertise Center of the Northern Netherlands (MAECON), Groningen, The Netherlands
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Scherrer AU, Traytel A, Braun DL, Calmy A, Battegay M, Cavassini M, Furrer H, Schmid P, Bernasconi E, Stoeckle M, Kahlert C, Trkola A, Kouyos RD, Tarr P, Marzolini C, Wandeler G, Fellay J, Bucher H, Yerly S, Suter F, Hirsch H, Huber M, Dollenmaier G, Perreau M, Martinetti G, Rauch A, Günthard HF. Cohort Profile Update: The Swiss HIV Cohort Study (SHCS). Int J Epidemiol 2021; 51:33-34j. [PMID: 34363666 DOI: 10.1093/ije/dyab141] [Citation(s) in RCA: 65] [Impact Index Per Article: 21.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/30/2021] [Indexed: 11/13/2022] Open
Affiliation(s)
- Alexandra U Scherrer
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Anna Traytel
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Dominique L Braun
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Alexandra Calmy
- Division of Infectious Diseases, University Hospital Geneva, University of Geneva, Geneva, Switzerland
| | - Manuel Battegay
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Matthias Cavassini
- Division of Infectious Diseases, University Hospital Lausanne, University of Lausanne, Lausanne, Switzerland
| | - Hansjakob Furrer
- Department of Infectious Diseases, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Patrick Schmid
- Division of Infectious Diseases, Cantonal Hospital St Gallen, St Gallen, Switzerland
| | - Enos Bernasconi
- Division of Infectious Diseases, Regional Hospital Lugano, Lugano, Switzerland
| | - Marcel Stoeckle
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Christian Kahlert
- Division of Infectious Diseases and Hospital Epidemiology, Cantonal Hospital St Gallen, St Gallen, Switzerland.,Division of Infectious Diseases and Hospital Epidemiology, Children's Hospital of Eastern Switzerland, St Gallen, Switzerland
| | - Alexandra Trkola
- Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Roger D Kouyos
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Philip Tarr
- University Department of Medicine, Kantonsspital Bruderholz, University of Basel, Bruderholz, Switzerland
| | - Catia Marzolini
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Gilles Wandeler
- Department of Infectious Diseases, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Jacques Fellay
- Precision Medicine Unit, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Heiner Bucher
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Sabine Yerly
- Division of Infectious Diseases and Laboratory of Virology, University Hospital Geneva, University of Geneva, Geneva, Switzerland
| | - Franziska Suter
- Department of Infectious Diseases, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Hans Hirsch
- Department of Biomedicine, University of Basel, Basel, Switzerland
| | - Michael Huber
- Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | | | - Matthieu Perreau
- Division of Immunology and Allergy, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Lausanne, Switzerland
| | - Gladys Martinetti
- Department of Microbiology, Ente Ospedaliero Cantonale, Bellinzona, Switzerland
| | - Andri Rauch
- Department of Infectious Diseases, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Huldrych F Günthard
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
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Zhang Q, Li X, Qiao S, Shen Z, Zhou Y. Comparing self-reported medication adherence measures with hair antiretroviral concentration among people living with HIV in Guangxi, China. AIDS Res Ther 2020; 17:8. [PMID: 32122394 PMCID: PMC7053048 DOI: 10.1186/s12981-020-00265-4] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2019] [Accepted: 02/21/2020] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND Antiretroviral adherence is essential to HIV treatment efficacy. Various self-reported measures are commonly used for assessing antiretroviral adherence. Limited data are available regarding the validity of those self-reported measures in comparison with long-term objective biomarkers of adherence measures such as hair measures. METHODS Self-reported adherence (frequency, percentage, and visual analog scale [VAS]) and hair tenofovir concentration were evaluated at a single time point from 268 people living with HIV in China. The responses to each of three self-reported measures were converted into percentage and then dichotomized as "optimal" (100%) vs. "suboptimal" (less than 100%) adherence. Two composite adherence scores (CAS) were created from the three self-reported measures: (1) an overall adherence was the average percentage of the three self-reported measures; (2) responses were termed optimal adherence if participants reporting optimal adherence in all three self-reported measures, while were termed suboptimal adherence. Hair tenofovir concentration was also dichotomized as "optimal" (above the limit of quantitation, 36 pg/mg) vs. "suboptimal" adherence (blow 36 pg/mg). Spearman correlation, kappa statistics, and logistic regression analysis were used to calculate the correlations, agreements, and predictions of self-reported measures with hair measure, respectively. RESULTS Overall adherence, but any of the three self-reported adherence, was correlated with hair tenofovir concentration (r = 0.13, p < 0.05). Self-reported optimal adherence in VAS and CAS measures were agreed with and predicted optimal adherence assessed by hair measure (Kappa = 0.107, adjusted OR = 1.88, 95% CI 1.03-3.45; Kappa = 0.109, adjusted OR = 1.80, 95% CI 1.02-3.18; all p < 0.05, respectively). CONCLUSION VAS may be a good individual self-reported measure for antiretroviral adherence, and CAS may be a good composite self-reported measure for antiretroviral adherence.
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Affiliation(s)
- Quan Zhang
- South Carolina SmartState Center for Healthcare Quality (CHQ), Arnold School of Public Health, University of South Carolina, Discovery I, 915 Greene Street, Columbia, SC, 29028, USA.
- Institute of Pedagogy and Applied Psychology, School of Public Administration, Hohai University, Nanjing, Jiangsu, China.
| | - Xiaoming Li
- South Carolina SmartState Center for Healthcare Quality (CHQ), Arnold School of Public Health, University of South Carolina, Discovery I, 915 Greene Street, Columbia, SC, 29028, USA
| | - Shan Qiao
- South Carolina SmartState Center for Healthcare Quality (CHQ), Arnold School of Public Health, University of South Carolina, Discovery I, 915 Greene Street, Columbia, SC, 29028, USA
| | - Zhiyong Shen
- Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, Guangxi, China
| | - Yuejiao Zhou
- Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, Guangxi, China
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