Abstract
Next-generation sequencing (NGS) is likely to become the new standard method for HIV drug resistance (HIVDR) genotyping. Despite the significant advances in the development of wet-lab protocols and bioinformatic data processing pipelines, one often-missing critical component of an NGS HIVDR assay for clinical use is external quality assessment (EQA). EQA is essential for ensuring assay consistency and laboratory competency in performing routine biomedical assays, and the rollout of NGS HIVDR tests in clinical practice will require an EQA. In September 2019, the 2nd International Symposium on NGS HIVDR was held in Winnipeg, Canada. It convened a multidisciplinary panel of experts, including research scientists, clinicians, bioinformaticians, laboratory biologists, biostatisticians, and EQA experts. A themed discussion was conducted on EQA strategies towards such assays during the symposium. This article describes the logistical challenges identified and summarizes the opinions and recommendations derived from these discussions, which may inform the development of an inaugural EQA program for NGS HIVDR in the near future.
Keywords: HIV, drug resistance, next generation sequencing, external quality assessment
1. Introduction
External quality assessment (EQA), also referred to as an external quality assessment scheme (EQAS), plays a vital role in assuring that a laboratory performs biomedical assays competently [1]. EQA is defined as a system for objectively verifying performance using an external agency or facility [2], relying on interlaboratory or inter-site comparisons. It facilitates the identification of areas that need improvement, the determination of potential training needs, and the evaluation and monitoring of training impact. An EQA is often administered by a third-party agency for ensuring the consistency of a laboratory in performing specific assays of interest or by regulatory agencies for accreditation purposes. For instance, the ISO 15189-accredited medical laboratories and the Clinical Laboratory Improvement Amendments (CLIA)-certified clinical laboratories in the US are all required to participate in relevant EQA programs for consistent test quality and demonstrated laboratory competence [3].
Conventional EQA relies on three main approaches: proficiency testing (PT), rechecking/retesting, and on-site evaluation [2]. By leveraging their unique advantages, each of these approaches plays an important role in EQA for varied biomedical assays. PT is, by all means, the most commonly applied EQA method, especially when established reference materials are readily available [2]. The Clinical and Laboratory Standards Institute (CLSI) defines PT as “A program in which multiple samples are periodically sent to members of a group of laboratories for analysis and/or identification; whereby each laboratory’s results are compared with those of other laboratories in the group and/or with an assigned value, and reported to the participating laboratories and others” [4]. The ISO/IEC uses a different term, proficiency testing schemes (PTS), which is defined as “inter-laboratory comparisons that are organized regularly to assess the performance of analytical laboratories and the competence of the analytical personnel” [5]. While minor difference exists among these terms, PT, PTS, EQA, and EQAS are often used interchangeably [4,6].
2. EQA for Sanger Sequencing-Based HIVDR Testing
For decades, Sanger sequencing (SS) has been applied as the standard HIV drug resistance (HIVDR) genotyping method for research, surveillance, and patient care purposes [7]. Several EQA programs designed for SS HIVDR assays have been applied worldwide by different regulatory agencies or assay quality assessment groups [8,9,10,11,12]. Among them is the Virology Quality Assurance (VQA) program, funded through the US National Institute of Allergy and Infectious Diseases (NIAID) [8]. The VQA program provides comprehensive quality assessment for assays targeting HIV used in NIAID-supported clinical trials under the AIDS Clinical Trials Group (ACTG). Its functionality was expanded later to provide resources and EQA support to any laboratory doing virological testing for any NIH-sponsored study or program. The NIAID VQA program has been in operation since 1988. It plays a vital role in ensuring the validity and inter- and intra-laboratory comparability of HIV virology data generated for NIH-sponsored studies [8,13]. In 2001, the VQA launched its EQA program for SS-based HIVDR assays [13], which was later adopted by the World Health Organization (WHO) Global HIV Resistance Network (HIVResNet) as a mandatory requirement for membership in its HIVDR laboratory network [8].
The VQA HIVDR panels include HIV-positive plasma from donors with HIV or virus stocks derived from the expansion of HIV positive specimens in cell culture, diluted in a plasma matrix. PT specimens are first characterized for viral load (VL) and HIV DR-associated mutations (DRMs) using commercially available assays. The five-specimen panels are then distributed to the designated client laboratories, where they are genotyped for HIVDR using commercial and/or in-house-developed SS assays. All laboratory data derived from such tests are then submitted and compiled. A well-defined scoring algorithm is then used to compare the sequences from different laboratories to a group consensus, and the EQA assessment results are then communicated to the laboratories and relevant requesting agencies directly [8,14]. Similar EQA programs designed for SS HIVDR assays also exist in different regions or countries around the world such as TREAT Asia Quality Assessment Scheme (TAQAS) in Asia, Quality Control for Molecular Diagnostics (QCMD) HIVDR proficiency program in Europe, and Japanese External Quality Assessment Program to Standardize HIV genotyping (JEQS) in Japan [9,11,12]. All such programs played an essential role in establishing SS as the routine method for HIVDR genotyping across the world.
3. EQA, a Challenging but Essential Component in the Generalized Implementation of Next Generation Sequencing HIVDR Testing
While SS has been considered the “gold standard” for HIVDR genotyping, its intrinsic limitations, such as inconsistent detection of minority resistance variants (MRVs), necessitate the development of new HIVDR tests with improved sensitivity [15,16,17]. A next-generation sequencing (NGS)-based HIVDR test enables quantitative, sensitive detection of low abundance nucleotide and amino acid variations. Moreover, it also allows simultaneous analyses of multiple specimens with unprecedented high data throughput in multiplexed runs, rendering improved time-efficiency and cost-effectiveness when conducting batched sample testing [7,18,19,20]. With the increasing affordability of equipment and consumables, NGS HIVDR assays are being adopted by more laboratories worldwide and may soon become the new standard for HIVDR genotyping.
While it is well-appreciated that the generalized adoption of NGS HIVDR assays requires fully validated, standard operating procedures (SOPs) for sample processing and a sophisticated bioinformatics pipeline for effective data analysis, one essential but still missing aspect of ensuring assay consistency and reliability is an EQA program that functions (Figure 1). NGS HIVDR assays are multiprocedural and involve many potential “check-points”, where artificial biases or significant variations may arise and subsequently compromise the accuracy and reliability of the final output. Therefore, an EQA is at least as critical for laboratories performing NGS HIVDR assays, as it is for other clinical laboratory assays. While EQA programs for SS HIVDR have been widely applied, innovative EQA strategies have yet to be established for NGS HIVDR due to the fundamental differences between SS- and NGS-based assays and the data they generate [21,22,23]. For instance, conventional SS assays generate a single sequence per specimen, and DRMs are qualitatively detected and reported as being present (sometimes in mixtures) or absent. The EQA strategies for such tests are based on similarity analysis of the sequences and the concordance of DRM detection from individual laboratories against the consensus from the combined group [13,24] (Table 1). In contrast, NGS HIVDR assays differ from SS in many ways; EQA strategies developed for SS assays may not be applicable for NGS HIVDR assays [21]. With such challenges being recognized, themed discussions were carried out on EQA strategies for NGS HIVDR during the 2nd International Symposium on NGS HIVDR held in Winnipeg, Canada, in September 2019. This article summarizes the proceedings from the discussions specifically on the logistical challenges and considerations for establishing an EQA program for NGS HIVDR assays.
Table 1.
EQA Tasks | Logistical Issues | Sanger Experiences (VQA as an Example) |
NGS HIVDR EQA Considerations and Recommendations |
---|---|---|---|
Organization and Administration | Who organizes/operates? |
|
|
Who participates? |
|
|
|
Who funds? |
|
|
|
Laboratory Recruitment | Recruitment strategies |
|
|
Basic infrastructure requirements |
|
|
|
Sample processing capacity requirement |
|
|
|
Bioinformatics capacity requirement |
|
|
|
Reference Materials prep and distribution: Wet Panels [21] | Panel design | VQA panels contain five specimens, designed with the following factors:
|
|
Panel specimen types |
|
* Initial VP panels may focus on plasma specimens at viral loads of ≥1,000 copies/mL. |
|
Panel characterization strategies |
|
|
|
Panel size |
|
|
|
Panel distribution |
|
|
|
HIV gene targets |
|
|
|
HIV DRM MRV frequency range |
|
|
|
Different VLs/mutation loads |
|
|
|
Reference Materials prep and distribution: Dry Panels [25] | Genuine raw sequencing data |
|
|
Synthetic/in silico datasets |
|
Such data may complement datasets derived from real specimens for covering:
|
|
Panel size |
|
|
|
Data access |
|
|
|
Potential application |
|
Such panels involve no sample processing in the laboratory and may serve the needs for
|
|
Data Collection | Data submission requirement |
|
|
Consensus sequence |
|
|
|
HIV DRM / Variation reports |
|
|
|
Raw sequencing data |
|
|
|
Information on the protocols applied |
|
|
|
Data collection approach |
|
|
|
Data Assessment | Guidelines/SOPs |
|
|
Data assessment parameters [24] |
|
||
Scoring strategies |
|
|
|
Assessment Reporting | Files & contents | Report files:
|
|
Assessment, data distribution and retention/archival |
|
|
|
Other Challenges | Incentives for participation |
|
|
Program sustainability |
|
|
|
Strategies to facilitate SS to NGS transitioning |
|
|
Abbreviations (in alphabetical order): AAVF: Amino Acid Variation File; ACTG: the AIDS Clinical Trials Group; ANRS: the HIV genotypic interpretation system from the Agence Nationale de Recherches Sur le SIDA), France; AP: Assessment Panel; CLSI: Clinical and Laboratory Standards Institute; DNA: Deoxyribonucleic Acid; DRM: Drug Resistance Mutation; EQA: External Quality Assessment; HIV: Human Immunodeficiency Virus; HIVdb: the HIV resistance interpretation system from the HIV Drug Resistance Database, Stanford University, The United States; HIVDR: HIV Drug Resistance testing; HIVResNet: Global HIV Drug Resistance Network; IAS-USA: the International Antiviral Society-USA; IN: Integrase; MRV: Minority Resistance Variant; NGS: Next-Generation Sequencing; NIAID: National Institute of Allergy and Infectious Diseases, the United States; NIH: National Health Institutes, the United States; PAHO: Pan America Health Organization; PHAC: Public Health Agency of Canada; PR: Protease; PT: Proficiency Test; QA: Quality Assurance; REGA: the HIV genotypic interpretation system from Rega Institute for Medical Research, Belgium; RM: Reference materials; RNA: Ribonucleic Acid; RT: Reverse Transcriptase; SOP: Standard Operating Procedure; SS: Sanger sequencing; UMI: Unique molecular identifier; VL: Viral load; VP: Validation Panel; VQA: Virology Quality Assurance program supported by NIAID; WHO: World Health Organization.
4. EQA Strategies for NGS HIVDR Assays: Logistic Challenges and Considerations
Recognizably, EQA for NGS HIVDR testing is a new field for which limited knowledge and experience are available currently, and extensive research and development efforts are still required. An operational EQAP that executes such EQA functionalities has yet to be established. Most of the research efforts in this regard have been devoted to the development of effective data assessment and scoring criteria for the evaluation of laboratory competence in performing such assays [21,22,24]. However, the establishment of such an EQAP requires a comprehensive effort of administerial management, financial operation, PT support, data management, and subsequent reporting and follow-up actions.
Like EQAPs for other biomedical assays, the operation of an EQAP for NGS HIVDR testing may be divided into six main task areas, including (1) organization and administration, (2) laboratory recruitment, (3) reference material preparation and distribution, (4) data collection, (5) data assessment, and (6) EQA reporting (Figure 1). Accordingly, Table 1 summarizes the major logistical challenges one may encounter within each of these areas and some general issues applicable for any operational program (listed as “other challenges”), the successful experiences from EQA for SS HIVDR testing in addressing such challenges (taking the NIAID VQA program as an example), and the suggested considerations and recommendations for the establishment and operation of an EQAP for laboratories conducting NGS HIVDR assays. Based on the experiences from a pilot study that evaluated the potential of using existing VQA PT specimens for NGS HIVDR EQA [23,29], and comparing the performance of different bioinformatics pipelines [22], some strategies that may facilitate a smooth transition from a SS- to a NGS-based HIVDR testing era are also advised (Table 1).
It is noteworthy that, while the NIAID VQA program is taken as an exemplar EQAP for SS-based HIVDR assays in Table 1, most of the NGS HIVDR considerations and recommendations based on the VQA experience should be applicable or adaptable for other alike EQAPs such as TAQAS, QCMD, JEQS, or existing similar programs.
5. Conclusions
As an exemplar “disruptive” technology, NGS can revolutionize the conventional SS-based HIVDR genotyping practice and can enable sensitive and quantitative MRV detection. Many commercial and in-house-developed NGS HIVDR assays have been developed together with sophisticated bioinformatics pipelines. Meanwhile, the gradual cost reductions for both NGS instruments and related consumables have converted NGS from a high-end research tool into an affordable and accessible technology for general HIVDR laboratories. NGS may soon become the new standard for HIVDR testing in research and surveillance, as well as clinical monitoring purposes. Therefore, appropriate EQAPs will become imperative for ensuring the quality of data from the laboratories performing such assays. Due to the uniqueness of NGS HIVDR assays and the complexity of data derived from such tests, the existing EQA strategies and EQAPs targeting SS-based HIVDR genotyping are not optimal for these new assays. Technical and logistical challenges involved in the development and implementation of NGS-specific EQAPs remain to be resolved and require additional research.
Acknowledgments
We appreciate the generous in-kind support from all participating parties and institutes for the symposium series and the related research and development efforts. The funders played no role in the study design, data collection and analyses, manuscript preparation, and the decision-making for the publication of this work.
Author Contributions
H.J., N.P., and R.K. led the themed discussions on EQA logistics during the 2nd international symposium on NGS HIVDR. H.J. drafted the manuscript, and N.P., F.G., C.J., R.K., and P.S. all contributed significantly to the revisions of this manuscript. All authors gave consent to the publication of this work. All authors have read and agreed to the published version of the manuscript.
Funding
This study was generously supported by the Public health Agency of Canada and the Federal Initiative to Address HIV/AIDS in Canada (H.J., P.S.). This study was also supported by the National Institute of Allergy and Infectious Diseases for Virology Quality Assurance (75N93019C00015, T.D., F.G., and C.J.) and External Quality Assurance Program Oversight Laboratory (HHSN272201700061C, F.G. and T.D.). RK was supported in part by R01AI147333, R01AI136058, R01AI120792, K24AI134359 and P30AI042853. The APC was funded by the Public Health Agency of Canada, Canada.
Conflicts of Interest
The authors declare no conflict of Interest.
References
- 1.Sciacovelli L., Secchiero S., Zardo L., Zaninotto M., Plebani M. External Quality Assessment: An effective tool for Clinical Governance in laboratory medicine. Clin. Chem. Lab. Med. 2006;44:740–749. doi: 10.1515/CCLM.2006.133. [DOI] [PubMed] [Google Scholar]
- 2.WHO . Laboratory Quality Management System Training Toolkit. WHO Lyon Office; Lyon, France: 2005. [Google Scholar]
- 3.Schneider F., Maurer C., Friedberg R.C. International Organization for Standardization (ISO) 15189. Ann. Lab. Med. 2017;37:365–370. doi: 10.3343/alm.2017.37.5.365. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.CLSI Harmonized Terminology Database. [(accessed on 20 April 2020)];2019 Available online: https://clsi.org/
- 5.ISO/IEC . ISO/IEC Guideline 43-1: Proficiency Testing by Interlaboratory Comparisons-Part 1: Development and Operation of Proficiency Testing Schemes. ISO/IEC; Genève, Switzerland: 1997. [Google Scholar]
- 6.Miller W.G., Jones G.R., Horowitz G.L., Weykamp C. Proficiency testing/external quality assessment: Current challenges and future directions. Clin. Chem. 2011;57:1670–1680. doi: 10.1373/clinchem.2011.168641. [DOI] [PubMed] [Google Scholar]
- 7.Clutter D.S., Jordan M.R., Bertagnolio S., Shafer R.W. HIV-1 drug resistance and resistance testing. Infect. Genet. Evol. 2016;46:292–307. doi: 10.1016/j.meegid.2016.08.031. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Parkin N., Bremer J., Bertagnolio S. Genotyping external quality assurance in the World Health Organization HIV drug resistance laboratory network during 2007–2010. Clin. Infect. Dis. 2012;54(Suppl. S4):S266–S272. doi: 10.1093/cid/cir992. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Pandit A., Mackay W.G., Steel C., van Loon A.M., Schuurman R. HIV-1 drug resistance genotyping quality assessment: Results of the ENVA7 Genotyping Proficiency Programme. J. Clin. Virol. 2008;43:401–406. doi: 10.1016/j.jcv.2008.08.021. [DOI] [PubMed] [Google Scholar]
- 10.Saeng-Aroon S., Saipradit N., Loket R., Klamkhai N., Boonmuang R., Kaewprommal P., Prommajan K., Takeda N., Sungkanuparph S., Shioda T., et al. External Quality Assessment Scheme for HIV-1 Drug-Resistance Genotyping in Thailand. AIDS Res. Hum. Retrovir. 2018;34:1028–1035. doi: 10.1089/aid.2017.0299. [DOI] [PubMed] [Google Scholar]
- 11.Yoshida S., Hattori J., Matsuda M., Okada K., Kazuyama Y., Hashimoto O., Ibe S., Fujisawa S., Chiba H., Tatsumi M., et al. Japanese external quality assessment program to standardize HIV-1 drug-resistance testing (JEQS2010 program) using in vitro transcribed RNA as reference material. AIDS Res. Hum. Retrovir. 2015;31:318–325. doi: 10.1089/aid.2014.0059. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Land S., Cunningham P., Zhou J., Frost K., Katzenstein D., Kantor R., Chen Y.M., Oka S., DeLong A., Sayer D., et al. TREAT Asia Quality Assessment Scheme (TAQAS) to standardize the outcome of HIV genotypic resistance testing in a group of Asian laboratories. J. Virol. Methods. 2009;159:185–193. doi: 10.1016/j.jviromet.2009.03.016. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Huang D.D., Bremer J.W., Brambilla D.J., Palumbo P.E., Aldrovandi G., Eshleman S., Brown C., Fiscus S., Frenkel L., Hamdan H., et al. Model for assessment of proficiency of human immunodeficiency virus type 1 sequencing-based genotypic antiretroviral assays. J. Clin. Microbiol. 2005;43:3963–3970. doi: 10.1128/JCM.43.8.3963-3970.2005. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.WHO . WHO/HIVResNet HIV Drug Resistance Laboratory Operational Framework. World Health Organization; Geneva, Switzerland: 2017. [Google Scholar]
- 15.Johnson J.A., Li J.F., Wei X., Lipscomb J., Irlbeck D., Craig C., Smith A., Bennett D.E., Monsour M., Sandstrom P., et al. Minority HIV-1 drug resistance mutations are present in antiretroviral treatment-naive populations and associate with reduced treatment efficacy. PLoS Med. 2008;5:e158. doi: 10.1371/journal.pmed.0050158. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Korn K., Reil H., Walter H., Schmidt B. Quality control trial for human immunodeficiency virus type 1 drug resistance testing using clinical samples reveals problems with detecting minority species and interpretation of test results. J. Clin. Microbiol. 2003;41:3559–3565. doi: 10.1128/JCM.41.8.3559-3565.2003. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Simen B.B., Simons J.F., Hullsiek K.H., Novak R.M., Macarthur R.D., Baxter J.D., Huang C., Lubeski C., Turenchalk G.S., Braverman M.S., et al. Low-abundance drug-resistant viral variants in chronically HIV-infected, antiretroviral treatment-naive patients significantly impact treatment outcomes. J. Infect. Dis. 2009;199:693–701. doi: 10.1086/596736. [DOI] [PubMed] [Google Scholar]
- 18.Ji H., Li Y., Graham M., Liang B.B., Pilon R., Tyson S., Peters G., Tyler S., Merks H., Bertagnolio S., et al. Next-generation sequencing of dried blood spot specimens: A novel approach to HIV drug-resistance surveillance. Antivir. Ther. 2011;16:871–878. doi: 10.3851/IMP1839. [DOI] [PubMed] [Google Scholar]
- 19.Lapointe H.R., Dong W., Lee G.Q., Bangsberg D.R., Martin J.N., Mocello A.R., Boum Y., Karakas A., Kirkby D., Poon A.F., et al. HIV drug resistance testing by high-multiplex “wide” sequencing on the MiSeq instrument. Antimicrob. Agents Chemother. 2015;59:6824–6833. doi: 10.1128/AAC.01490-15. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Inzaule S.C., Ondoa P., Peter T., Mugyenyi P.N., Stevens W.S., de Wit T.F.R., Hamers R.L. Affordable HIV drug-resistance testing for monitoring of antiretroviral therapy in sub-Saharan Africa. Lancet Infect. Dis. 2016;16:e267–e275. doi: 10.1016/S1473-3099(16)30118-9. [DOI] [PubMed] [Google Scholar]
- 21.Lee E.R., Gao F., Sandstrom P., Ji H. External quality assessment for next-generation sequencing-based HIV drug resistance testing: Unique requirements and challenges. Viruses. 2020;12:550. doi: 10.3390/v12050550. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Lee E.R., Parkin N., Jennings C., Brumme C.J., Enns E., Casadella M., Howison M., Coetzer M., Avila-Rios S., Capina R., et al. Performance comparison of next generation sequencing analysis pipelines for HIV-1 drug resistance testing. Sci. Rep. 2020;10:1634. doi: 10.1038/s41598-020-58544-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Lee E.R., Enns E., Parkin N., Brumme C.J., Casadella M., Howison M., Avila Rios S., Jennings R., Capina R., Marinier E., et al. Characterization and data assessment of next generation sequencing-based genotyping using existing HIV-1 drug resistance proficiency panels; Proceedings of the XXVII International HIV Drug Resistance and Treatment Strategies Workshop; Johannesburg, South Africa. 22–23 October 2018. [Google Scholar]
- 24.VQA VQA HIV Gene Sequencing Proficiency Testing Scoring Criteria and Policies. [(accessed on 20 April 2020)];2014 Available online: https://www.hanc.info/labs/labresources/vqaResources/Pages/default.aspx.
- 25.Noguera-Julian M., Lee E.R., Travers S., Shafer R.W., Kantor R., Ji H. Dry panel for next generation sequencing-based HIV DRT EQA. Viruses. 2020 doi: 10.3390/v12060666. submitted. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Vandamme A.M., Camacho R.J., Ceccherini-Silberstein F., De L.A., Palmisano L., Paraskevis D., Paredes R., Poljak M., Schmit J.C., Soriano V., et al. European recommendations for the clinical use of HIV drug resistance testing: 2011 update. AIDS Rev. 2011;13:77–108. [PubMed] [Google Scholar]
- 27.Ji H., Enns E., Brumme C.J., Parkin N., Howison M., Lee E.R., Capina R., Marinier E., Avila-Rios S., Sandstrom P., et al. Bioinformatic data processing pipelines in support of next-generation sequencing-based HIV drug resistance testing: The Winnipeg Consensus. J. Int. AIDS Soc. 2018;21:e25193. doi: 10.1002/jia2.25193. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Wensing A.M., Calvez V., Gunthard H.F., Johnson V.A., Paredes R., Pillay D., Shafer R.W., Richman D.D. 2017 Update of the Drug Resistance Mutations in HIV-1. Top. Antivir. Med. 2016;24:132–133. [PMC free article] [PubMed] [Google Scholar]
- 29.Parkin N., Zaccaro D., Avila-Rios S., Brumme C., Hunt G., Ji H., Kantor R., Mbisa J.L., Predes R., Rivera-Amill V., et al. Multi-Laboratory comparison of next-generation to Sanger-based sequencing for HIV-1 drug resistance genotyping; Proceedings of the XXVII International HIV Drug Resistance and Treatment Strategies Workshop; Johannesburg, South Africa. 22–23 October 2018. [Google Scholar]