Modelling study of the ability to diagnose acute rheumatic fever at different levels of the Ugandan healthcare system.

OBJECTIVE: To determine the ability to accurately diagnose acute rheumatic fever (ARF) given the resources available at three levels of the Ugandan healthcare system. METHODS: Using data obtained from a large epidemiological database on ARF conducted in three districts of Uganda, we selected variables that might positively or negatively predict rheumatic fever based on diagnostic capacity at three levels/tiers of the Ugandan healthcare system. Variables were put into three statistical models that were built sequentially. Multiple logistic regression was used to estimate ORs and 95% CI of predictors of ARF. Performance of the models was determined using Akaike information criterion, adjusted R2, concordance C statistic, Brier score and adequacy index. RESULTS: A model with clinical predictor variables available at a lower-level health centre (tier 1) predicted ARF with an optimism corrected area under the curve (AUC) (c-statistic) of 0.69. Adding tests available at the district level (tier 2, ECG, complete blood count and malaria testing) increased the AUC to 0.76. A model that additionally included diagnostic tests available at the national referral hospital (tier 3, echocardiography, anti-streptolysin O titres, erythrocyte sedimentation rate/C-reactive protein) had the best performance with an AUC of 0.91. CONCLUSIONS: Reducing the burden of rheumatic heart disease in low and middle-income countries requires overcoming challenges of ARF diagnosis. Ensuring that possible cases can be evaluated using electrocardiography and relatively simple blood tests will improve diagnostic accuracy somewhat, but access to echocardiography and tests to confirm recent streptococcal infection will have the greatest impact

Active case finding for rheumatic fever in an endemic country

Background: Despite the high burden of rheumatic heart disease in sub‐Saharan Africa, diagnosis with acute rheumatic fever (ARF) is exceedingly rare. Here, we report the results of the first prospective epidemiologic survey to diagnose and characterize ARF at the community level in Africa. Methods and Results: A cross‐sectional study was conducted in Lira, Uganda, to inform the design of a broader epidemiologic survey. Key messages were distributed in the community, and children aged 3 to 17 years were included if they had either (1) fever and joint pain, (2) suspicion of carditis, or (3) suspicion of chorea, with ARF diagnoses made by the 2015 Jones Criteria. Over 6 months, 201 children met criteria for participation, with a median age of 11 years (interquartile range, 6.5) and 103 (51%) female. At final diagnosis, 51 children (25%) had definite ARF, 11 (6%) had possible ARF, 2 (1%) had rheumatic heart disease without evidence of ARF, 78 (39%) had a known alternative diagnosis (10 influenza, 62 malaria, 2 sickle cell crises, 2 typhoid fever, 2 congenital heart disease), and 59 (30%) had an unknown alternative diagnosis. Conclusions: ARF persists within rheumatic heart disease–endemic communities in Africa, despite the low rates reported in the literature. Early data collection has enabled refinement of our study design to best capture the incidence of ARF and to answer important questions on community sensitization, healthcare worker and teacher education, and simplified diagnostics for low‐resource areas. This study also generated data to support further exploration of the relationship between malaria and ARF diagnosis in rheumatic heart disease/malaria‐endemic countries

Evaluating the Cellular Targets of Anti-4-1BB Agonist Antibody during Immunotherapy of a Pre-Established Tumor in Mice

Manipulation of the immune system represents a promising avenue for cancer therapy. Rational advances in immunotherapy of cancer will require an understanding of the precise correlates of protection. Agonistic antibodies against the tumor necrosis factor receptor family member 4-1BB are emerging as a promising tool in cancer therapy, with evidence that these antibodies expand both T cells as well as innate immune cells. Depletion studies have suggested that several cell types can play a role in these immunotherapeutic regimens, but do not reveal which cells must directly receive the 4-1BB signals for effective therapy.We show that re-activated memory T cells are superior to resting memory T cells in control of an 8-day pre-established E.G7 tumor in mice. We find that ex vivo activation of the memory T cells allows the activated effectors to continue to divide and enter the tumor, regardless of antigen-specificity; however, only antigen-specific reactivated memory T cells show any efficacy in tumor control. When agonistic anti-4-1BB antibody is combined with this optimized adoptive T cell therapy, 80% of mice survive and are fully protected from tumor rechallenge. Using 4-1BB-deficient mice and mixed bone marrow chimeras, we find that it is sufficient to have 4-1BB only on the endogenous host alphabeta T cells or only on the transferred T cells for the effects of anti-4-1BB to be realized. Conversely, although multiple immune cell types express 4-1BB and both T cells and APC expand during anti-4-1BB therapy, 4-1BB on cells other than alphabeta T cells is neither necessary nor sufficient for the effect of anti-4-1BB in this adoptive immunotherapy model.This study establishes alphabeta T cells rather than innate immune cells as the critical target in anti-4-1BB therapy of a pre-established tumor. The study also demonstrates that ex vivo activation of memory T cells prior to infusion allows antigen-specific tumor control without the need for reactivation of the memory T cells in the tumor