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      A meta-analysis of the performance of the Pima TM CD4 for point of care testing

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          Abstract

          Background

          The Alere point-of-care (POC) Pima™ CD4 analyzer allows for decentralized testing and expansion to testing antiretroviral therapy (ART) eligibility. A consortium conducted a pooled multi-data technical performance analysis of the Pima CD4.

          Methods

          Primary data (11,803 paired observations) comprised 22 independent studies between 2009–2012 from the Caribbean, Asia, Sub-Saharan Africa, USA and Europe, using 6 laboratory-based reference technologies. Data were analyzed as categorical (including binary) and numerical (absolute) observations using a bivariate and/or univariate random effects model when appropriate.

          Results

          At a median reference CD4 of 383 cells/μl the mean Pima CD4 bias is -23 cells/μl (average bias across all CD4 ranges is 10 % for venous and 15 % for capillary testing). Sensitivity of the Pima CD4 is 93 % (95 % confidence interval [CI] 91.4 % - 94.9 %) at 350 cells/μl and 96 % (CI 95.2 % - 96.9 %) at 500 cells/μl, with no significant difference between venous and capillary testing. Sensitivity reduced to 86 % (CI 82 % - 89 %) at 100 cells/μl (for Cryptococcal antigen (CrAg) screening), with a significant difference between venous (88 %, CI: 85 % - 91 %) and capillary (79 %, CI: 73 % - 84 %) testing. Total CD4 misclassification is 2.3 % cases at 100 cells/μl, 11.0 % at 350 cells/μl and 9.5 % at 500 cells/μl, due to higher false positive rates which resulted in more patients identified for treatment. This increased by 1.2 %, 2.8 % and 1.8 %, respectively, for capillary testing. There was no difference in Pima CD4 misclassification between the meta-analysis data and a population subset of HIV+ ART naïve individuals, nor in misclassification among operator cadres. The Pima CD4 was most similar to Beckman Coulter PanLeucogated CD4, Becton Dickinson FACSCalibur and FACSCount, and less similar to Partec CyFlow reference technologies.

          Conclusions

          The Pima CD4 may be recommended using venous-derived specimens for screening (100 cells/μl) for reflex CrAg screening and for HIV ART eligibility at 350 cells/μl and 500 cells/μl thresholds using both capillary and venous derived specimens. These meta-analysis findings add to the knowledge of acceptance criteria of the Pima CD4 and future POC tests, but implementation and impact will require full costing analysis.

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          Most cited references22

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          Effect of point-of-care CD4 cell count tests on retention of patients and rates of antiretroviral therapy initiation in primary health clinics: an observational cohort study.

          Loss to follow-up of HIV-positive patients before initiation of antiretroviral therapy can exceed 50% in low-income settings and is a challenge to the scale-up of treatment. We implemented point-of-care counting of CD4 cells in Mozambique and assessed the effect on loss to follow-up before immunological staging and treatment initiation. In this observational cohort study, data for enrolment into HIV management and initiation of antiretroviral therapy were extracted retrospectively from patients' records at four primary health clinics providing HIV treatment and point-of-care CD4 services. Loss to follow-up and the duration of each preparatory step before treatment initiation were measured and compared with baseline data from before the introduction of point-of-care CD4 testing. After the introduction of point-of-care CD4 the proportion of patients lost to follow-up before completion of CD4 staging dropped from 57% (278 of 492) to 21% (92 of 437) (adjusted odds ratio [OR] 0·2, 95% CI 0·15-0·27). Total loss to follow-up before initiation of antiretroviral treatment fell from 64% (314 of 492) to 33% (142 of 437) (OR 0·27, 95% CI 0·21-0·36) and the proportion of enrolled patients initiating antiretroviral therapy increased from 12% (57 of 492) to 22% (94 of 437) (OR 2·05, 95% CI 1·42-2·96). The median time from enrolment to antiretroviral therapy initiation reduced from 48 days to 20 days (p<0·0001), primarily because of a reduction in the median time taken to complete CD4 staging, which decreased from 32 days to 3 days (p<0·0001). Loss to follow-up between staging and antiretroviral therapy initiation did not change significantly (OR 0·84, 95% CI 0·49-1·45). Point-of-care CD4 testing enabled clinics to stage patients rapidly on-site after enrolment, which reduced opportunities for pretreatment loss to follow-up. As a result, more patients were identified as eligible for and initiated antiretroviral treatment. Point-of-care testing might therefore be an effective intervention to reduce pretreatment loss to follow-up. Absolute Return for Kids and UNITAID. Copyright © 2011 Elsevier Ltd. All rights reserved.
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            Evaluation of old and new tests of heterogeneity in epidemiologic meta-analysis.

            The identification of heterogeneity in effects between studies is a key issue in meta-analyses of observational studies, since it is critical for determining whether it is appropriate to pool the individual results into one summary measure. The result of a hypothesis test is often used as the decision criterion. In this paper, the authors use a large simulation study patterned from the key features of five published epidemiologic meta-analyses to investigate the type I error and statistical power of five previously proposed asymptotic homogeneity tests, a parametric bootstrap version of each of the tests, and tau2-bootstrap, a test proposed by the authors. The results show that the asymptotic DerSimonian and Laird Q statistic and the bootstrap versions of the other tests give the correct type I error under the null hypothesis but that all of the tests considered have low statistical power, especially when the number of studies included in the meta-analysis is small (<20). From the point of view of validity, power, and computational ease, the Q statistic is clearly the best choice. The authors found that the performance of all of the tests considered did not depend appreciably upon the value of the pooled odds ratio, both for size and for power. Because tests for heterogeneity will often be underpowered, random effects models can be used routinely, and heterogeneity can be quantified by means of R(I), the proportion of the total variance of the pooled effect measure due to between-study variance, and CV(B), the between-study coefficient of variation.
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              Evaluation of the PIMA point-of-care CD4 analyzer in VCT clinics in Zimbabwe.

              Point-of-care (POC) CD4 testing was implemented at a stand-alone HIV voluntary testing and counseling centre in Harare, Zimbabwe. To validate the use of this new technology, paired blood samples were collected from 165 patients either by a nurse or a laboratory technician and tested using POC and conventional laboratory CD4 machines. Finger prick (capillary) blood was collected directly into the PIMA POC CD4 Analyzer cartridges and tested immediately, whereas venous blood collected into evacuated tubes was used for CD4 enumeration on a Becton Dickinson FACSCalibur. There was no significant difference in mean absolute CD4 counts between the POC PIMA and Becton Dickinson FACSCalibur platforms (+7.6 cells/microL; P = 0.72). Additionally, there was no significant difference in CD4 counts between the platforms when run by either a nurse (+18.0 cells/microL; P = 0.49), or a laboratory technicians (-3.1 cells/microL; P = 0.93). This study demonstrates that POC CD4 testing can be conducted in a voluntary testing and counseling setting for staging HIV-positive clients. Both nurses and laboratory technicians performed the test accurately, thereby increasing the human resources available for POC CD4 testing. By producing same-day results, POC CD4 facilitates immediate decision-making, patient management and referral and may help improve patient care and retention. POC CD4 may also alleviate testing burdens at traditional central CD4 laboratories, hence improving test access in both rural and urban environments.
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                Author and article information

                Contributors
                lesley.scott@nhls.ac.za
                jcampbell@clintonhealthaccess.org
                lew2@cdc.gov
                LKestens@itg.be
                lvojnov@clintonHealthAccess.org
                iee2@cdc.gov
                jcn5@cdc.gov
                tpeter@clintonhealthaccess.org
                wendy.stevens@nhls.ac.za
                Journal
                BMC Med
                BMC Med
                BMC Medicine
                BioMed Central (London )
                1741-7015
                25 July 2015
                25 July 2015
                2015
                : 13
                : 168
                Affiliations
                [ ]Department of Molecular Medicine and Haematology, Faculty of Health Science, School of Pathology, University of the Witwatersrand, 7 York Road Parktown, Johannesburg, South Africa
                [ ]Clinton Health Access Initiative, Boston, MA USA
                [ ]US Centers for Disease Control, Atlanta, GA USA
                [ ]Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
                [ ]Laboratory of Immunology, Department of Biomedical Sciences, Institute of Tropical Medicine, Antwerp, Belgium
                [ ]National Health Laboratory Service, Johannesburg, South Africa
                Article
                396
                10.1186/s12916-015-0396-2
                4515022
                26208867
                547d8143-7cda-4477-b6f7-ca68a9493262
                © Scott et al. 2015

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 10 March 2015
                : 11 June 2015
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2015

                Medicine
                pima cd4,point of care testing,meta-analysis,cd4 misclassification
                Medicine
                pima cd4, point of care testing, meta-analysis, cd4 misclassification

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