ABSTRACT
Purpose: Pseudoprogression mimicking recurrent glioblastoma remains a diagnostic challenge that may adversely confound or delay appropriate treatment or clinical trial enrollment. We sought to build a radiomic classifier to predict pseudoprogression in patients with primary isocitrate dehydrogenase wild type glioblastoma. Methods and Materials: We retrospectively examined a training cohort of 74 patients with isocitrate dehydrogenase wild type glioblastomas with brain magnetic resonance imaging including dynamic contrast enhanced T1 perfusion before resection of an enhancing lesion indeterminate for recurrent tumor or pseudoprogression. A recursive feature elimination random forest classifier was built using nested cross-validation without and with O6-methylguanine-DNA methyltransferase status to predict pseudoprogression. Results: A classifier constructed with cross-validation on the training cohort achieved an area under the receiver operating curve of 81% for predicting pseudoprogression. This was further improved to 89% with the addition of O6-methylguanine-DNA methyltransferase status into the classifier. Conclusions: Our results suggest that radiomic analysis of contrast T1-weighted images and magnetic resonance imaging perfusion images can assist the prompt diagnosis of pseudoprogression. Validation on external and independent data sets is necessary to verify these advanced analyses, which can be performed on routinely acquired clinical images and may help inform clinical treatment decisions.
ABSTRACT
BACKGROUND: Donor financing for malaria has declined since 2010 and this trend is projected to continue for the foreseeable future. These reductions have a significant impact on lower burden countries actively pursuing elimination, which are usually a lesser priority for donors. While domestic spending on malaria has been growing, it varies substantially in speed and magnitude across countries. A clear understanding of spending patterns and trends in donor and domestic financing is needed to uncover critical investment gaps and opportunities. METHODS: Building on the Institute for Health Metrics and Evaluation's annual Financing Global Health research, data were collected from organizations that channel development assistance for health to the 35 countries actively pursuing malaria elimination. Where possible, development assistance for health (DAH) was categorized by spend on malaria intervention. A diverse set of data points were used to estimate government health budgets expenditure on malaria, including World Malaria Reports and government reports when available. Projections were done using regression analyses taking recipient country averages and earmarked funding into account. RESULTS: Since 2010, DAH for malaria has been declining for the 35 countries actively pursuing malaria elimination (from $176 million in 2010 to $62 million in 2013). The Global Fund is the largest external financier for malaria, providing 96% of the total external funding for malaria in 2013, with vector control interventions being the highest cost driver in all regions. Government expenditure on malaria, while increasing, has not kept pace with diminishing DAH or rising national GDP rates, leading to a potential gap in service delivery needed to attain elimination. CONCLUSION: Despite past gains, total financing available for malaria in elimination settings is declining. Health financing trends suggest that substantive policy interventions will be needed to ensure that malaria elimination is adequately financed and that available financing is effectively targeted to interventions that provide the best value for money.
