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. 2018 Dec 4;18(1):617.
doi: 10.1186/s12879-018-3536-4.

Validation of CD4+ T-cell and viral load data from the HIV-Brazil Cohort Study using secondary system data

Alex Jones Flores Cassenote  1 , Alexandre Grangeiro  2 , Maria Mercedes Escuder  3 , Jair Minoro Abe  4 , Aluísio Augusto Cotrim Segurado  5   6
Affiliations

Validation of CD4+ T-cell and viral load data from the HIV-Brazil Cohort Study using secondary system data

Alex Jones Flores Cassenote et al. BMC Infect Dis. .

Abstract

Background: The HIV-Brazil Cohort Study (HIV-BCS) is a research primarily based on data collection from medical records of people living with HIV/AIDS in Brazil. The aim of this study was to present the validating design and results for the laboratory biomarkers viral load and CD4+ T-cell count from the HIV-Brazil Cohort Study.

Methods: A total of 8007 patients who were started cART from 2003 to 2013 were considered eligible for this study. Total follow-up time was 32,397 years. The median duration of follow-up was 3.51 years (interquartile range - IQR 1.63-6.13 years; maximum 11.51 years). We used secondary data from the Brazilian Laboratory Tests Control System (SISCEL). Incidence of lab testing rates per 100 person years (100 py) were used to compare the number of laboratory tests carried out among cohort sites considering different databases for CD4+ T-cell counts and HIV viral load assessments. Descriptive statistics including 95% confidence interval, Pearson correlation coefficient, Bland-Altman agreement analysis and kappa coefficient agreement were applied for analysis.

Results: A total of 80,302 CD4+ T-cell counts and 79,997 HIV viral load assessments were observed in HIV-BCS versus 94,083 CD4+ T-cell counts and 84,810 viral loads from the Brazilian Laboratory Tests Control System. The general CD4+ T-cell HIV-BCS testing rate was 247 per 100 py versus 290 per 100 py and the viral load HIV-BCS testing rate was 246 per 100 py versus 261 per 100 py. The general correlation observed for the lowest quantitative CD4+ T-cell count before cART was 0.970 (p < 0.001) and for the log of the highest viral load before cART was 0.971 (p < 0.001). The general agreement coefficient for categorized CD4+ T-cell count was 0.932 (p < 0.001) and for viral load was 0.996 (p < 0.001).

Conclusions: The current study confirms that biomarkers CD4+ T-cell count and viral load from the HIV-BCS have a high correlation and agreement with data from SISCEL, rendering both databases reliable and useful for epidemiological studies on HIV care in Brazil.

Keywords: HIV-Brazilian cohort study; Medical records; TCD4+ − cell; Validation; Viral load.

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Conflict of interest statement

Ethics approval and consent to participate

Ethics Statement: This study was approved by the Ethics in Research Committee of the Medical School of the University of São Paulo (Universidade de São Paulo) (Decision #. #229/13). As this is a retrospective study, the aforementioned IRB has withdrawn the need for the free and informed consent term. Consent and responsibility were at the discretion of the directors of each of the participating sites.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures

Fig. 1
Fig. 1
The structure of the HIV-BCS database with the different databases in different phases of the study (Phase 1 is retrospective and Phase 2 is prospective)
Fig. 2
Fig. 2
SISCEL operating system used by National Network of Laboratories (NNT) to feed the database with costs and laboratory results of T-cell counts (CD4+/CD8+) and HIV VL assessments
Fig. 3
Fig. 3
Final sample size flowchart. (1) no linkage code with National HIV/AIDS register surveillance; (2) no data available for CD4+ T-cell count or HIV viral load assessment during clinical follow-up; or (3) no data available for CD4+ T-cell count or viral load after initiating cART. Analysis 1 refers to descriptive statistics including mean, median, standard deviation (SD) and interquartile range (IQR) and proportions (%) for the ten first quantitative measures of CD4+ T-cell counts and categorized viral loads (above or below assay lower limit) after cART; analysis 2 including Pearson correlation coefficient and Bland-Altman agreement analysis for quantitative measures of lowest CD4+ T-cell count and log of highest viral load before cART; and analysis 3 is a Kappa coefficient agreement for categorized measures of lowest CD4+ T-cell count before cART and highest viral load before cART
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References

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