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Early Prediction of Treatment Efficacy in Second-Stage Gambiense Human African Trypanosomiasis

BACKGROUND: Human African trypanosomiasis is fatal without treatment. The long post-treatment follow-up (24 months) required to assess cure complicates patient management and is a major obstacle in the development of new therapies. We analyzed individual patient data from 12 programs conducted by Mé...

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Detalles Bibliográficos
Autores principales: Priotto, Gerardo, Chappuis, François, Bastard, Mathieu, Flevaud, Laurence, Etard, Jean-François
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3367996/
https://www.ncbi.nlm.nih.gov/pubmed/22701752
http://dx.doi.org/10.1371/journal.pntd.0001662
Descripción
Sumario:BACKGROUND: Human African trypanosomiasis is fatal without treatment. The long post-treatment follow-up (24 months) required to assess cure complicates patient management and is a major obstacle in the development of new therapies. We analyzed individual patient data from 12 programs conducted by Médecins Sans Frontières in Uganda, Sudan, Angola, Central African Republic, Republic of Congo and Democratic Republic of Congo searching for early efficacy indicators. METHODOLOGY/PRINCIPAL FINDINGS: Patients analyzed had confirmed second-stage disease with complete follow-up and confirmed outcome (cure or relapse), and had CSF leucocytes counts (CSFLC) performed at 6 months post-treatment. We excluded patients with uncertain efficacy outcome: incomplete follow-up, death, relapse diagnosed with CSFLC below 50/µL and no trypanosomes. We analyzed the 6-month CSFLC via receiver-operator-characteristic curves. For each cut-off value we calculated sensitivity, specificity and likelihood ratios (LR+ and LR−). We assessed the association of the optimal cut-off with the probability of relapsing via random-intercept logistic regression. We also explored two-step (6 and 12 months) composite algorithms using the CSFLC. The most accurate cut-off to predict outcome was 10 leucocytes/µL (n = 1822, 76.2% sensitivity, 80.4% specificity, 3.89 LR+, 0.29 LR−). Multivariate analysis confirmed its association with outcome (odds ratio = 17.2). The best algorithm established cure at 6 months with < = 5 leucocytes/µL and relapse with > = 50 leucocytes/µL; patients between these values were discriminated at 12 months by a 20 leucocytes/µL cut-off (n = 2190, 87.4% sensitivity, 97.7% specificity, 37.84 LR+, 0.13 LR−). CONCLUSIONS/SIGNIFICANCE: The 6-month CSFLC can predict outcome with some limitations. Two-step algorithms enhance the accuracy but impose 12-month follow-up for some patients. For early estimation of efficacy in clinical trials and for individual patients in the field, several options exist that can be used according to priorities.