The 'RCT augmentation': a novel simulation method to add patient heterogeneity into phase III trials.

BACKGROUND: Phase III randomized controlled trials (RCT) typically exclude certain patient subgroups, thereby potentially jeopardizing estimation of a drug's effects when prescribed to wider populations and under routine care ('effectiveness'). Conversely, enrolling heterogeneous populations in RCTs can increase endpoint variability and compromise detection of a drug's effect. We developed the 'RCT augmentation' method to quantitatively support RCT design in the identification of exclusion criteria to relax to address both of these considerations. In the present manuscript, we describe the method and a case study in schizophrenia. METHODS: We applied typical RCT exclusion criteria in a real-world dataset (cohort) of schizophrenia patients to define the 'RCT population' subgroup, and assessed the impact of re-including each of the following patient subgroups: (1) illness duration 1-3 years; (2) suicide attempt; (3) alcohol abuse; (4) substance abuse; and (5) private practice management. Predictive models were built using data from different 'augmented RCT populations' (i.e., subgroups where patients with one or two of such characteristics were re-included) to estimate the absolute effectiveness of the two most prevalent antipsychotics against real-world results from the entire cohort. Concurrently, the impact on RCT results of relaxing exclusion criteria was evaluated by calculating the comparative efficacy of those two antipsychotics in virtual RCTs drawing on different 'augmented RCT populations'. RESULTS: Data from the 'RCT population', which was defined with typical exclusion criteria, allowed for a prediction of effectiveness with a bias < 2% and mean squared error (MSE) = 5.8-6.8%. Compared to this typical RCT, RCTs using augmented populations provided improved effectiveness predictions (bias < 2%, MSE = 5.3-6.7%), while returning more variable comparative effects. The impact of augmentation depended on the exclusion criterion relaxed. Furthermore, half of the benefit of relaxing each criterion was gained from re-including the first 10-20% of patients with the corresponding real-world characteristic. CONCLUSIONS: Simulating the inclusion of real-world subpopulations into an RCT before running it allows for quantification of the impact of each re-inclusion upon effect detection (statistical power) and generalizability of trial results, thereby explicating this trade-off and enabling a controlled increase in population heterogeneity in the RCT design

Assessment of Community Event-Based Surveillance for Ebola Virus Disease, Sierra Leone, 2015.

In 2015, community event-based surveillance (CEBS) was implemented in Sierra Leone to assist with the detection of Ebola virus disease (EVD) cases. We assessed the sensitivity of CEBS for finding EVD cases during a 7-month period, and in a 6-week subanalysis, we assessed the timeliness of reporting cases with no known epidemiologic links at time of detection. Of the 12,126 CEBS reports, 287 (2%) met the suspected case definition, and 16 were confirmed positive. CEBS detected 30% (16/53) of the EVD cases identified during the study period. During the subanalysis, CEBS staff identified 4 of 6 cases with no epidemiologic links. These CEBS-detected cases were identified more rapidly than those detected by the national surveillance system; however, too few cases were detected to determine system timeliness. Although CEBS detected EVD cases, it largely generated false alerts. Future versions of community-based surveillance could improve case detection through increased staff training and community engagement

Whole-exome resequencing distinguishes cystic kidney diseases from phenocopies in renal ciliopathies

Rare single-gene disorders cause chronic disease. However, half of the 6,000 recessive single gene causes of disease are still unknown. Because recessive disease genes can illuminate, at least in part, disease pathomechanism, their identification offers direct opportunities for improved clinical management and potentially treatment. Rare diseases comprise the majority of chronic kidney disease (CKD) in children but are notoriously difficult to diagnose. Whole exome resequencing facilitates identification of recessive disease genes. However, its utility is impeded by the large number of genetic variants detected. We here overcome this limitation by combining homozygosity mapping with whole exome resequencing in 10 sib pairs with a nephronophthisis-related ciliopathy, which represents the most frequent genetic cause of CKD in the first three decades of life. In 7 of 10 sib-ships with a histologic or ultrasonographic diagnosis of nephronophthisis-related ciliopathy we detect the causative gene. In six sib-ships we identify mutations of known nephronophthisis-related ciliopathy genes, while in two additional sib-ships we found mutations in the known CKD-causing genes SLC4A1 and AGXT as phenocopies of nephronophthisis-related ciliopathy. Thus whole exome resequencing establishes an efficient, non-invasive approach towards early detection and causation-based diagnosis of rare kidney diseases. This approach can be extended to other rare recessive disorders, thereby providing accurate diagnosis and facilitating the study of disease mechanisms

Discutindo a educação ambiental no cotidiano escolar: desenvolvimento de projetos na escola formação inicial e continuada de professores

A presente pesquisa buscou discutir como a Educação Ambiental (EA) vem sendo trabalhada, no Ensino Fundamental e como os docentes desta escola compreendem e vem inserindo a EA no cotidiano escolar., em uma escola estadual do município de Tangará da Serra/MT, Brasil. Para tanto, realizou-se entrevistas com os professores que fazem parte de um projeto interdisciplinar de EA na escola pesquisada. Verificou-se que o projeto da escola não vem conseguindo alcançar os objetivos propostos por: desconhecimento do mesmo, pelos professores; formação deficiente dos professores, não entendimento da EA como processo de ensino-aprendizagem, falta de recursos didáticos, planejamento inadequado das atividades. A partir dessa constatação, procurou-se debater a impossibilidade de tratar do tema fora do trabalho interdisciplinar, bem como, e principalmente, a importância de um estudo mais aprofundado de EA, vinculando teoria e prática, tanto na formação docente, como em projetos escolares, a fim de fugir do tradicional vínculo “EA e ecologia, lixo e horta”.Facultad de Humanidades y Ciencias de la Educació

The “RCT augmentation”: a novel simulation method to add patient heterogeneity into phase III trials

Abstract Background Phase III randomized controlled trials (RCT) typically exclude certain patient subgroups, thereby potentially jeopardizing estimation of a drug’s effects when prescribed to wider populations and under routine care (“effectiveness”). Conversely, enrolling heterogeneous populations in RCTs can increase endpoint variability and compromise detection of a drug’s effect. We developed the “RCT augmentation” method to quantitatively support RCT design in the identification of exclusion criteria to relax to address both of these considerations. In the present manuscript, we describe the method and a case study in schizophrenia. Methods We applied typical RCT exclusion criteria in a real-world dataset (cohort) of schizophrenia patients to define the “RCT population” subgroup, and assessed the impact of re-including each of the following patient subgroups: (1) illness duration 1–3 years; (2) suicide attempt; (3) alcohol abuse; (4) substance abuse; and (5) private practice management. Predictive models were built using data from different “augmented RCT populations” (i.e., subgroups where patients with one or two of such characteristics were re-included) to estimate the absolute effectiveness of the two most prevalent antipsychotics against real-world results from the entire cohort. Concurrently, the impact on RCT results of relaxing exclusion criteria was evaluated by calculating the comparative efficacy of those two antipsychotics in virtual RCTs drawing on different “augmented RCT populations”. Results Data from the “RCT population”, which was defined with typical exclusion criteria, allowed for a prediction of effectiveness with a bias < 2% and mean squared error (MSE) = 5.8–6.8%. Compared to this typical RCT, RCTs using augmented populations provided improved effectiveness predictions (bias < 2%, MSE = 5.3–6.7%), while returning more variable comparative effects. The impact of augmentation depended on the exclusion criterion relaxed. Furthermore, half of the benefit of relaxing each criterion was gained from re-including the first 10–20% of patients with the corresponding real-world characteristic. Conclusions Simulating the inclusion of real-world subpopulations into an RCT before running it allows for quantification of the impact of each re-inclusion upon effect detection (statistical power) and generalizability of trial results, thereby explicating this trade-off and enabling a controlled increase in population heterogeneity in the RCT design

The 'RCT augmentation': a novel simulation method to add patient heterogeneity into phase III trials.

BACKGROUND: Phase III randomized controlled trials (RCT) typically exclude certain patient subgroups, thereby potentially jeopardizing estimation of a drug's effects when prescribed to wider populations and under routine care ('effectiveness'). Conversely, enrolling heterogeneous populations in RCTs can increase endpoint variability and compromise detection of a drug's effect. We developed the 'RCT augmentation' method to quantitatively support RCT design in the identification of exclusion criteria to relax to address both of these considerations. In the present manuscript, we describe the method and a case study in schizophrenia. METHODS: We applied typical RCT exclusion criteria in a real-world dataset (cohort) of schizophrenia patients to define the 'RCT population' subgroup, and assessed the impact of re-including each of the following patient subgroups: (1) illness duration 1-3 years; (2) suicide attempt; (3) alcohol abuse; (4) substance abuse; and (5) private practice management. Predictive models were built using data from different 'augmented RCT populations' (i.e., subgroups where patients with one or two of such characteristics were re-included) to estimate the absolute effectiveness of the two most prevalent antipsychotics against real-world results from the entire cohort. Concurrently, the impact on RCT results of relaxing exclusion criteria was evaluated by calculating the comparative efficacy of those two antipsychotics in virtual RCTs drawing on different 'augmented RCT populations'. RESULTS: Data from the 'RCT population', which was defined with typical exclusion criteria, allowed for a prediction of effectiveness with a bias < 2% and mean squared error (MSE) = 5.8-6.8%. Compared to this typical RCT, RCTs using augmented populations provided improved effectiveness predictions (bias < 2%, MSE = 5.3-6.7%), while returning more variable comparative effects. The impact of augmentation depended on the exclusion criterion relaxed. Furthermore, half of the benefit of relaxing each criterion was gained from re-including the first 10-20% of patients with the corresponding real-world characteristic. CONCLUSIONS: Simulating the inclusion of real-world subpopulations into an RCT before running it allows for quantification of the impact of each re-inclusion upon effect detection (statistical power) and generalizability of trial results, thereby explicating this trade-off and enabling a controlled increase in population heterogeneity in the RCT design

Additional file 1: of The “RCT augmentation”: a novel simulation method to add patient heterogeneity into phase III trials

1. Details on methods, 2. details on results, 3. comparison of the study results and the data from literature, 4. codes used for the analysis, modeling and simulation, and 5. references used in the Additional file 1. (DOCX 2465 kb

Diagnosis patterns of sickle cell disease in Ghana: a secondary analysis.

BACKGROUND: Despite having the highest prevalence of sickle cell disease (SCD) in the world, no country in Sub-Saharan Africa has a universal screening program for the disease. We sought to capture the diagnosis patterns of SCD (age at SCD diagnosis, method of SCD diagnosis, and age of first pain crisis) in Accra, Ghana. METHODS: We administered an in-person, voluntary survey to parents of offspring with SCD between 2009 and 2013 in Accra as a part of a larger study and conducted a secondary data analysis to determine diagnosis patterns. This was conducted at a single site: a large academic medical center in the region. Univariate analyses were performed on diagnosis patterns; bivariate analyses were conducted to determine whether patterns differed by participant’s age (children: those  = 18 years old whose parents completed a survey about them), or their disease severity based on SCD genotype. Pearson’s chi-squared were calculated. RESULTS: Data was collected on 354 unique participants from parents. Few were diagnosed via SCD testing in the newborn period. Only 44% were diagnosed with SCD by age four; 46% had experienced a pain crisis by the same age. Most (66%) were diagnosed during pain crisis, either in acute (49%) or primary care (17%) settings. Children were diagnosed with SCD at an earlier age (74% by four years old); among the adults, parents reflected that 30% were diagnosed by four years old (p < 0.001). Half with severe forms of SCD were diagnosed by age four, compared to 31% with mild forms of the disease (p = 0.009). CONCLUSIONS: The lack of a robust newborn screening program for SCD in Accra, Ghana, leaves children at risk for disease complications and death. People in our sample were diagnosed with SCD in the acute care setting, and in their toddler or school-age years or thereafter, meaning they are likely being excluded from important preventive care. Understanding current SCD diagnosis patterns in the region can inform efforts to improve the timeliness of SCD diagnosis, and improve the mortality and morbidity caused by the disease in this high prevalence population