Sumudinie Fernando

SANKOFA: a multisite collaboration on paediatric HIV disclosure in Ghana.

With the scale-up of effective antiretroviral therapy in resource-limited settings, many HIV-infected children are now able to survive into adulthood. To achieve this potential, children must navigate normative developmental processes and challenges while living with an unusually complex, stigmatizing, potentially fatal chronic illness and meeting the demands of treatment.Yet many of these children, especially preadolescents, do not know they are HIV-infected. Despite compelling evidence supporting the merits of informing children of their HIV status, there has been little emphasis on equipping the childs caregiver with information and skills to promote disclosure, particularly, when the caregiver faces a variety of sociocultural barriers and is reluctant to do so. In this study, we present the background, process and methods for a first of its kind collaboration that is examining the efficacy of an intervention developed to facilitate the engagement of caregivers in the process of disclosure in a manner suitable to the sociocultural context and developmental age and needs of the child in Ghana. We also report preliminary data that supported the design of the intervention approach and currently available domains of the data system. Finally, we discuss challenges and implications for future research.

Sankofa pediatric HIV disclosure intervention cyber data management: building capacity in a resource-limited setting and ensuring data quality

Prevalence of pediatric HIV disclosure is low in resource-limited settings. Innovative, culturally sensitive, and patient-centered disclosure approaches are needed. Conducting such studies in resource-limited settings is not trivial considering the challenges of capturing, cleaning, and storing clinical research data. To overcome some of these challenges, the Sankofa pediatric disclosure intervention adopted an interactive cyber infrastructure for data capture and analysis. The Sankofa Project database system is built on the HUBzero cyber infrastructure (https://hubzero.org), an open source software platform. The hub database components support: (1) data management – the “databases” component creates, configures, and manages database access, backup, repositories, applications, and access control; (2) data collection – the “forms” component is used to build customized web case report forms that incorporate common data elements and include tailored form submit processing to handle error checking, data validation, and data linkage as the data are stored to the database; and (3) data exploration – the “dataviewer” component provides powerful methods for users to view, search, sort, navigate, explore, map, graph, visualize, aggregate, drill-down, compute, and export data from the database. The Sankofa cyber data management tool supports a user-friendly, secure, and systematic collection of all data. We have screened more than 400 child–caregiver dyads and enrolled nearly 300 dyads, with tens of thousands of data elements. The dataviews have successfully supported all data exploration and analysis needs of the Sankofa Project. Moreover, the ability of the sites to query and view data summaries has proven to be an incentive for collecting complete and accurate data. The data system has all the desirable attributes of an electronic data capture tool. It also provides an added advantage of building data management capacity in resource-limited settings due to its innovative data query and summary views and availability of real-time support by the data management team.

Positron Emission Tomography in Thymic Tumors: Analysis Using a Prospective Research Database

BACKGROUND Positron emission tomography may have a role in the pretreatment workup of patients with thymic malignancies. This study was undertaken to determine the utility of the maximum standardized uptake value (SUVmax) in predicting histologic type and tumor stage in a large cohort of thymic epithelial tumors. METHODS The large, multiinstitutional, prospective database of The International Thymic Malignancy Interest Group (ITMIG) was queried for the use of positron emission tomography in the pretreatment workup of patients with thymic tumors. Data analyzed included demographics, SUVmax, histologic tumor type, and tumor stage. The distribution of SUVmax according to histologic type and Masaoka-Koga pathologic stage was determined, and the ability of SUVmax to predict these two variables was calculated using analysis of receiver operating characteristic curves. RESULTS Since 2012, data from 926 patients with thymic malignancies were entered into the ITMIG prospective database, of which 154 had a reported value for SUVmax. The area under the receiver operating characteristic curve for SUVmax in predicting histologic type and pathologic stage was 0.79 (95% confidence interval, 0.70 to 0.88; p < 0.001) and 0.81 (95% confidence interval, 0.73 to 0.88; p < 0.001), respectively. In addition, there was a significant relationship between SUVmax and histologic type (p < 0.001) as well as Masaoka-Koga pathologic stage (p < 0.001). CONCLUSIONS Positron emission tomography has utility in predicting clinicopathologic features of thymic malignancies. These results may have clinical application in the pretreatment workup of patients with these rare tumors.