Activity

This study seeks to (1) demonstrate how machine learning (ML) can be used for prediction modeling by predicting the treatment patients with T1-2, N0-N1 oropharyngeal squamous cell carcinoma (OPSCC) receive and (2) assess the impact patient, socioeconomic, regional, and institutional factors have in the treatment of this population.

A retrospective cohort of adults diagnosed with T1-2, N0-N1 OPSCC from 2004 to 2013 was obtained using the National Cancer Database. The data was split into 80/20 distribution for training and testing, respectively. Various ML algorithms were explored for development. Area under the curve (AUC), accuracy, precision, and recall were calculated for the final model.

Among the 19,111 patients in the study, the mean (standard deviation) age was 61.3 (10.8) years, 14,034 (73%) were male, and 17,292 (91%) were white. RO4987655 manufacturer Surgery was the primary treatment in 9,533 (50%) cases and radiation in 9,578 (50%) cases. The model heavily utilized T-stage, primary site, N-stage, grade, and type of treatment facility to predict the primary treatment modality. The final model yielded an AUC of 78% (95% CI, 77-79%), accuracy of 71%, precision of 72%, and recall of 71%.

This study created a ML model utilizing clinical variables to predict primary treatment modality for T1-2, N0-N1 OPSCC. This study demonstrates how ML can be used for prediction modeling while also highlighting that tumor and facility realted variables impact the decision making process on a national level.

This study created a ML model utilizing clinical variables to predict primary treatment modality for T1-2, N0-N1 OPSCC. This study demonstrates how ML can be used for prediction modeling while also highlighting that tumor and facility realted variables impact the decision making process on a national level.

Mechanical shunt malfunction may lead to significant morbidity and mortality. Shunt series assessments help evaluate shunt integrity; however, they are of limited value in the area of the skull due to skull curvature, thickness, and air sinuses. We describe the role of 3D bone reconstruction CT (3DCT) in demonstrating the shunt integrity over the skull, comparing this technique to skull X-rays (SXR).

Data were collected retrospectively for shunted patients with concurrent SXR and 3DCT and for patients presenting with shunt failures at the region of the skull, including clinical course and radiological findings. We compared the SXR and 3DCT findings. The 3DCT was reconstructed from standard diagnostic CT protocols performed during evaluation of suspected shunt malfunction and not thin-slice CT protocols.

Forty-eight patients with 57 shunts underwent SXR and 3DCT. Interobserver agreement was high for most variables. Both SXR and 3DCT had a high sensitivity, specificity, and accuracy identifying tubing disconnections (between 0.83 and 1). Full valve type and setting were significantly more accurate based on SXR versus 3DCT (>90 vs. <20%), and valve integrity was significantly more readily verified on 3DCT versus SXR (100 vs. 52%).

3DCT and SXR complement each other in diagnosing mechanical shunt malfunctions over the skull. The main limitation of 3DCT is identification of valve type and settings, which are clearer on SXR, while the main limitation of SXR is a less ability to evaluate valve integrity. 3DCT also enables an intuitive 3D understanding of the shunt tubing over the skull.

3DCT and SXR complement each other in diagnosing mechanical shunt malfunctions over the skull. The main limitation of 3DCT is identification of valve type and settings, which are clearer on SXR, while the main limitation of SXR is a less ability to evaluate valve integrity. 3DCT also enables an intuitive 3D understanding of the shunt tubing over the skull.

Environmental exposure to mites and fungi has been proposed to critically contribute to the development of IgE-mediated asthma. A common denominator of such organisms is chitin. Human chitinases have been reported to be upregulated by interleukin-13 secreted in the context of Th2-type immune responses and to induce asthma. We assessed whether chitin-containing components induced chitinases in an innate immune-dependent way and whether this results in bronchial hyperresponsiveness.

Monocyte/macrophage cell lines were stimulated with chitin-containing or bacterial components in vitro. Chitinase activity in the supernatant and the expression of the chitotriosidase gene were measured by enzyme assay and quantitative PCR, respectively. Non-sensitized mice were stimulated with chitin-containing components intranasally, and a chitinase inhibitor was administered intraperitoneally. As markers for inflammation leukocytes were counted in the bronchoalveolar lavage (BAL) fluid, and airway hyperresponsiveness was assessed via methacholine challenge.

We found both whole chitin-containing dust mites as well as the fungal cell wall component zymosan A but not endotoxin-induced chitinase activity and chitotriosidase gene expression in vitro. The intranasal application of zymosan A into mice led to the induction of chitinase activity in the BAL fluid and to bronchial hyperresponsiveness, which could be reduced by applying the chitinase inhibitor allosamidin.

We propose that environmental exposure to mites and fungi leads to the induction of chitinase, which in turn favors the development of bronchial hyperreactivity in an IgE-independent manner.

We propose that environmental exposure to mites and fungi leads to the induction of chitinase, which in turn favors the development of bronchial hyperreactivity in an IgE-independent manner.

The aim of the study was to evaluate impact of the systemic immune-inflammation index (SII) on prognosis and survival within the International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) score groups.

The records of 187 patients with metastatic renal cell carcinoma (RCC) were reviewed retrospectively. The SII was calculated as follows SII = Neutrophil × Platelet/Lymphocyte. The patients were categorized into 2 groups based on a median SII of 730 (×109 per 1 L) as SII low (<730) and SII high (≥730). The Kaplan-Meier method was used for survival analysis and a Cox regression model was utilized to determine independent predictors of survival.

The median age was 61 years (range 34-86 years). Kaplan-Meier tests revealed significant differences in survival between the SII-low and SII-high levels (27.0 vs. 12.0 months, respectively, p < 0.001). The Cox regression model revealed that SII was an independent prognostic factor. The implementation of the log-rank test in the IMDC groups according to the SII level provided the distinction of survival in the favorable group (SII low 49.