NATALIA BARROS CERQUEIRA
Projetos de Pesquisa
Unidades Organizacionais
Instituto Central, Hospital das Clínicas, Faculdade de Medicina
5 resultados
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Agora exibindo 1 - 5 de 5
- Interpreting HIV diagnostic histories into infection time estimates: analytical framework and online tool(2019) GREBE, Eduard; FACENTE, Shelley N.; BINGHAM, Jeremy; PILCHER, Christopher D.; POWRIE, Andrew; GERBER, Jarryd; PRIEDE, Gareth; CHIBAWARA, Trust; BUSCH, Michael P.; MURPHY, Gary; KASSANJEE, Reshma; WELTE, Alex; WELTE, Alex; SEMPA, Joseph; MATTEN, David; BRAND, Hilmarie; CHIBAWARA, Trust; MURPHY, Gary; HALL, Jake; MCKINNEY, Elaine; BUSCH, Michael P.; GREBE, Eduard; FACENTE, Shelley; HAMPTON, Dylan; KEATING, Sheila; LEBEDEVA, Mila; PILCHER, Christopher D.; MARSON, Kara; KASSANJEE, Reshma; LAEYENDECKER, Oliver; QUINN, Thomas; BURNS, David; LITTLE, Susan; SANDS, Anita; HALLETT, Tim; OWEN, Sherry Michele; PAREKH, Bharat; SEXTON, Connie; PRICE, Matthew; KAMALI, Anatoli; LOEB, Lisa; MARTIN, Jeffrey; DEEKS, Steven G.; HOH, Rebecca; BARTOLOMEI, Zelinda; SANTOS, Breno; ZABTOSKI, Kellin; LIRA, Rita de Cassia Alves; SPERHACKE, Rosa Dea; MOTTA, Leonardo R.; PAGANELLA, Machline; KALLAS, Esper; TOMIYAMA, Helena; TOMIYAMA, Claudia; COSTA, Priscilla; NUNES, Maria A.; REIS, Gisele; SAUER, Mariana M.; CERQUEIRA, Natalia; NAKAGAWA, Zelinda; FERRARI, Lilian; AMARAL, Ana P.; MILANI, Karine; KARIM, Salim S. Abdool; KARIM, Quarraisha Abdool; NDUNGU, Thumbi; MAJOLA, Nelisile; SAMSUNDER, Natasha; NANICHE, Denise; MANDOMANDO, Inacio; MACETE, Eusebio V.; SANCHEZ, Jorge; LAMA, Javier; DUERR, Ann; CAPOBIANCHI, Maria R.; SULIGOI, Barbara; STRAMER, Susan; WILLIAMSON, Phillip; VERMEULEN, Marion; SABINO, EsterBackground It is frequently of epidemiological and/or clinical interest to estimate the date of HIV infection or time-since-infection of individuals. Yet, for over 15 years, the only widely-referenced infection dating algorithm that utilises diagnostic testing data to estimate time-since-infection has been the 'Fiebig staging' system. This defines a number of stages of early HIV infection through various standard combinations of contemporaneous discordant diagnostic results using tests of different sensitivity. To develop a new, more nuanced infection dating algorithm, we generalised the Fiebig approach to accommodate positive and negative diagnostic results generated on the same or different dates, and arbitrary current or future tests - as long as the test sensitivity is known. For this purpose, test sensitivity is the probability of a positive result as a function of time since infection. Methods The present work outlines the analytical framework for infection date estimation using subject-level diagnostic testing histories, and data on test sensitivity. We introduce a publicly-available online HIV infection dating tool that implements this estimation method, bringing together 1) curatorship of HIV test performance data, and 2) infection date estimation functionality, to calculate plausible intervals within which infection likely became detectable for each individual. The midpoints of these intervals are interpreted as infection time 'point estimates' and referred to as Estimated Dates of Detectable Infection (EDDIs). The tool is designed for easy bulk processing of information (as may be appropriate for research studies) but can also be used for individual patients (such as in clinical practice). Results In many settings, including most research studies, detailed diagnostic testing data are routinely recorded, and can provide reasonably precise estimates of the timing of HIV infection. We present a simple logic to the interpretation of diagnostic testing histories into infection time estimates, either as a point estimate (EDDI) or an interval (earliest plausible to latest plausible dates of detectable infection), along with a publicly-accessible online tool that supports wide application of this logic. Conclusions This tool, available at , is readily updatable as test technology evolves, given the simple architecture of the system and its nature as an open source project.
- A generalizable method for estimating duration of HIV infections using clinical testing history and HIV test results(2019) PILCHER, Christopher D.; PORCO, Travis C.; FACENTE, Shelley N.; GREBE, Eduard; DELANEY, Kevin P.; MASCIOTRA, Silvina; KASSANJEE, Reshma; BUSCH, Michael P.; MURPHY, Gary; OWEN, S. Michele; WELTE, Alex; MATTEN, David; BRAND, Hilmarie; CHIBAWARA, Trust; MCKINNEY, Elaine; HALL, Jake; BUSCH, Michael; KEATING, Sheila; LEBEDEVA, Mila; HAMPTON, Dylan; PILCHER, Christopher; FACENTE, Shelley; MARSON, Kara; LAEYENDECKER, Oliver; QUINN, Thomas; BURNS, David; LITTLE, Susan; SANDS, Anita; HALLETT, Tim; OWEN, Sherry Michele; PAREKH, Bharat; SEXTON, Connie; PRICE, Matthew; KAMALI, Anatoli; LOEB, Lisa; MARTIN, Jeffrey; DEEKS, Steven G.; HOH, Rebecca; BARTOLOMEI, Zelinda; CERQUEIRA, Natalia; SANTOS, Breno; ZABTOSKI, Kellin; LIRA, Rita de Cassia Alves; SPERHACKE, Rosa Dea; MOTTA, Leonardo R.; PAGANELLA, Machline; KALLAS, Esper; TOMIYAMA, Helena; TOMIYAMA, Claudia; COSTA, Priscilla; NUNES, Maria A.; REIS, Gisele; SAUER, Mariana M.; NAKAGAWA, Zelinda; FERRARI, Lilian; AMARAL, Ana P.; MILANI, Karine; KARIM, Salim S. Abdool; KARIM, Quarraisha Abdool; NDUNGU, Thumbi; MAJOLA, Nelisile; SAMSUNDER, Natasha; NANICHE, Denise; MANDOMANDO, Inicio; V, Eusebio Macete; SANCHEZ, Jorge; LAMA, Javier; DUERR, Ann; CAPOBIANCHI, Maria R.; SULIGOI, Barbara; STRAMER, Susan; WILLIAMSON, Phillip; VERMEULEN, Marion; SABINO, EsterObjective: To determine the precision of new and established methods for estimating duration of HIV infection. Design: A retrospective analysis of HIV testing results from serial samples in commercially available panels, taking advantage of extensive testing previously conducted on 53 seroconverters. Methods: We initially investigated four methods for estimating infection timing: method 1, 'Fiebig stages' based on test results from a single specimen; method 2, an updated '4th gen' method similar to Fiebig stages but using antigen/antibody tests in place of the p24 antigen test; method 3, modeling of 'viral ramp-up' dynamics using quantitative HIV-1 viral load data from antibody-negative specimens; and method 4, using detailed clinical testing history to define a plausible interval and best estimate of infection time. We then investigated a 'two-step method' using data from both methods 3 and 4, allowing for test results to have come from specimens collected on different days. Results: Fiebig and '4th gen' staging method estimates of time since detectable viremia had similar and modest correlation with observed data. Correlation of estimates from both new methods (3 and 4), and from a combination of these two ('two-step method') was markedly improved and variability significantly reduced when compared with Fiebig estimates on the same specimens. Conclusion: The new 'two-step' method more accurately estimates timing of infection and is intended to be generalizable to more situations in clinical medicine, research, and surveillance than previous methods. An online tool is now available that enables researchers/clinicians to input data related to method 4, and generate estimated dates of detectable infection.
conferenceObject Attitudes and Knowledge About HIV PrEP Among Infectious Diseases Physicians in Brazil(2018) CERQUEIRA, Natalia; VASCONCELOS, Ricardo; HOJILLA, Carlo; KALLAS, Esper; AVELINO-SILVA, Vivian- Performance comparison of the Maxim and Sedia Limiting Antigen Avidity assays for HIV incidence surveillance(2019) SEMPA, Joseph B.; WELTE, Alex; BUSCH, Michael P.; HALL, Jake; HAMPTON, Dylan; FACENTE, Shelley N.; KEATING, Sheila M.; MARSON, Kara; PARKIN, Neil; PILCHER, Christopher D.; MURPHY, Gary; GREBE, Eduard; SEMP, Joseph; MATTEN, David; BRAND, Hilmarie; CHIBAWARA, Trust; MCKINNEY, Elaine; FACENTE, Shelley; KEATING, Sheila; LEBEDEVA, Mila; KASSANJEE, Reshma; LAEYENDECKER, Oliver; QUINN, Thomas; BURNS, David; LITTLE, Susan; SANDS, Anita; HALLETT, Tim; OWEN, Sherry Michele; PAREKH, Bharat; SEXTON, Connie; PRICE, Matthew; KAMALI, Anatoli; LOEB, Lisa; MARTIN, Jeffrey; DEEKS, Steven G.; HOH, Rebecca; BARTOLOMEI, Zelinda; CERQUEIRA, Natalia; SANTOS, Breno; ZABTOSKI, Kellin; LIRA, Rita de Cassia Alves; SPERHACKE, Rosa Dea; MOTTA, Leonardo R.; PAGANELLA, Machline; KALLAS, Esper; TOMIYAMA, Helena; TOMIYAMA, Claudia; COSTA, Priscilla; NUNES, Maria A.; REIS, Gisele; SAUER, Mariana M.; NAKAGAWA, Zelinda; FERRARI, Lilian; AMARAL, Ana P.; MILANI, Karine; KARIM, Salim S. Abdool; KARIM, Quarraisha Abdool; NDUNGU, Thumbi; MAJOLA, Nelisile; SAMSUNDER, Natasha; NANICHE, Denise; MANDOMANDO, Inacio; V, Eusebio Macete; SANCHEZ, Jorge; LAMA, Javier; DUERR, Ann; CAPOBIANCHI, Maria R.; SULIGOI, Barbara; STRAMER, Susan; WILLIAMSON, Phillip; VERMEULEN, Marion; SABINO, EsterBackground Two manufacturers, Maxim Biomedical and Sedia Biosciences Corporation, supply CDC-approved versions of the HIV-1 Limiting Antigen Avidity EIA (LAg) for detecting 'recent' HIV infection in cross-sectional incidence estimation. This study assesses and compares the performance of the two assays for incidence surveillance. Methods We ran both assays on a panel of 2,500 well-characterized HIV-1-infected specimens. We analysed concordance of assay results, assessed reproducibility using repeat testing and estimated mean durations of recent infection (MDRIs) and false-recent rates (FRRs) for a range of normalized optical density (ODn) thresholds, alone and in combination with viral load thresholds. We defined three hypothetical surveillance scenarios, similar to the Kenyan and South African epidemics, and a concentrated epidemic. These scenarios allowed us to evaluate the precision of incidence estimates obtained by means of various recent infection testing algorithms (RITAs) based on each of the two assays. Results The Maxim assay produced lower ODn values than the Sedia assay on average, largely as a result of higher calibrator readings (mean OD of 0.749 vs. 0.643), with correlation of normalized readings lower (R-2 = 0.908 vs. R-2 = 0.938). Reproducibility on blinded control specimens was slightly better for Maxim. The MDRI of a Maxim-based algorithm at the 'standard' threshold (ODn <= 1.5 & VL > 1,000) was 201 days (95% CI: 180,223) and for Sedia 171 (152,191). The difference Differences in MDRI were estimated at 32.7 (22.9,42.8) and 30.9 days (21.7,40.7) for the two algorithms, respectively. Commensurately, the Maxim algorithm had a higher FRR in treatment-naive subjects (1.7% vs. 1.1%). The two assays produced similar precision of incidence estimates in the three surveillance scenarios. Conclusions Differences between the assays can be primarily attributed to the calibrators supplied by the manufacturers. Performance for surveillance was extremely similar, although different thresholds were optimal (i.e. produced the lowest variance of incidence estimates) and at any given ODn threshold, different estimates of MDRI and FRR were obtained. The two assays cannot be treated as interchangeable: assay and algorithm-specific performance characteristic estimates must be used for survey planning and incidence estimation.
- HLA-C DOWNREGULATION BY HIV ADAPTS TO HOST HLA GENOTYPE(2018) APPS, Richard; BACHTEL, Nathaniel; UMVILIGIHOZO, Gisele; PICKERING, Suzanne; MOTA, Talia; LIANG, Hua; PRETE, Gregory Del; CHATTERJEE, Pramita; LEE, Guinevere; THOMAS, Rasmi; BROCKMAN, Mark; NEIL, Stuart; CARRINGTON, Mary; BWANA, Bosco; BANGSBERG, David; MARTIN, Jeffrey; KALLAS, Esper; DONINI, Camila; CERQUEIRA, Natalia; O'DOHERTY, Una; HAHN, Beatrice; JONES, Brad; BRUMME, Zabrina; NIXON, Douglas