Optimizing the parameters of a physical exercise dose-response model

Author(s):  
Mark Connor ◽  
Michael O'Neill
2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Irina Kapitanova ◽  
Sharmi Biswas ◽  
Sabrina Divekar ◽  
Eric J. Kemmerer ◽  
Robert A. Rostock ◽  
...  

Abstract Background Brachial plexopathy is a potentially serious complication from stereotactic body radiation therapy (SBRT) that has not been widely studied. Therefore, we compared datasets from two different institutions and generated a brachial plexus dose–response model, to quantify what dose constraints would be needed to minimize the effect on normal tissue while still enabling potent therapy for the tumor. Methods Two published SBRT datasets were pooled and modeled from patients at Indiana University and the Richard L. Roudebush Veterans Administration Medical Center from 1998 to 2007, as well as the Karolinska Institute from 2008 to 2013. All patients in both studies were treated with SBRT for apically located lung tumors localized superior to the aortic arch. Toxicities were graded according to Common Terminology Criteria for Adverse Events, and a probit dose response model was created with maximum likelihood parameter fitting. Results This analysis includes a total of 89 brachial plexus maximum point dose (Dmax) values from both institutions. Among the 14 patients who developed brachial plexopathy, the most common complications were grade 2, comprising 7 patients. The median follow-up was 30 months (range 6.1–72.2) in the Karolinska dataset, and the Indiana dataset had a median of 13 months (range 1–71). Both studies had a median range of 3 fractions, but in the Indiana dataset, 9 patients were treated in 4 fractions, and the paper did not differentiate between the two, so our analysis is considered to be in 3–4 fractions, one of the main limitations. The probit model showed that the risk of brachial plexopathy with Dmax of 26 Gy in 3–4 fractions is 10%, and 50% with Dmax of 70 Gy in 3–4 fractions. Conclusions This analysis is only a preliminary result because more details are needed as well as additional comprehensive datasets from a much broader cross-section of clinical practices. When more institutions join the QUANTEC and HyTEC methodology of reporting sufficient details to enable data pooling, our field will finally reach an improved understanding of human dose tolerance.


2010 ◽  
Vol 25 (1) ◽  
pp. 38-41 ◽  
Author(s):  
Menachem Ben-Ezra ◽  
Yuval Palgi ◽  
Amit Shrira ◽  
Dina Sternberg ◽  
Nir Essar

AbstractIntroduction:Exposure to prolonged war stress is understudied. While there is debate regarding the empirical data of the dose-response model for post-traumatic stress disorder (PTSD), little is known about how weekly changes in external stress influences the level of PTSD symptoms. The purpose of this study was to measure the relation between objective external stress and PTSD symptoms across time, and thus, gain a deeper understating of the dose-response model.Hypothesis:The study hypothesis postulates that the more severe the external stressor, the more severe the exhibition of traumatic symptoms.Methods:Thirteen special army administrative staff (SAAS) members from the Rambam Medical Center in Haifa attended seven intervention meetings during the war. These personnel answered a battery of questionnaires regarding demographics and PTSD symptoms during each session. A non-parametric test was used in order to measure the changes in PTSD symptoms between sessions. Pearson correlations were used in order to study the relationship between the magnitude of external stressors and the severity of PTSD symptoms.Results:The results suggested that there was a significant relationship between the magnitude of external stressors and the severity of PTSD symptoms. These results are in line with the dose-response model.Conclusions:The results suggest that a pattern of decline in PTSD symptoms confirm the dose-response model for PTSD.


2007 ◽  
Vol 48 (2) ◽  
pp. 135-147 ◽  
Author(s):  
Daniela K. Nitcheva ◽  
Walter W. Piegorsch ◽  
R.Webster West

2017 ◽  
Vol 50 (2) ◽  
pp. 31-36 ◽  
Author(s):  
Duayne Strydom ◽  
Ralf R. Küsel ◽  
Ian K. Craig
Keyword(s):  

Author(s):  
Faten S. Alamri ◽  
Edward L. Boone ◽  
David J. Edwards
Keyword(s):  

Author(s):  
Elharith Ahmed ◽  
Edward Early ◽  
Paul Kennedy ◽  
Robert Thomas
Keyword(s):  

Pathogens ◽  
2019 ◽  
Vol 8 (4) ◽  
pp. 253 ◽  
Author(s):  
Esfahanian ◽  
Adhikari ◽  
Dolan ◽  
Mitchell

. In order to determine the relationship between an exposure dose of Staphylococcus aureus (S. aureus) on the skin and the risk of infection, an understanding of the bacterial growth and decay kinetics is very important. Models are essential tools for understanding and predicting bacterial kinetics and are necessary to predict the dose of organisms post-exposure that results in a skin infection. One of the challenges in modeling bacterial kinetics is the estimation of model parameters, which can be addressed using an inverse problem approach. The objective of this study is to construct a microbial kinetic model of S. aureus on human skin and use the model to predict concentrations of S. aureus that result in human infection. In order to model the growth and decay of S. aureus on skin, a Gompertz inactivation model was coupled with a Gompertz growth model. A series of analyses, including ordinary least squares regression, scaled sensitivity coefficient analysis, residual analysis, and parameter correlation analysis were conducted to estimate the parameters and to describe the model uncertainty. Based on these analyses, the proposed model parameters were estimated with high accuracy. The model was then used to develop a new dose-response model for S. aureus using the exponential dose–response model. The new S. aureus model has an optimized k parameter equivalent to 8.05 × 10−8 with 95th percentile confidence intervals between 6.46 × 10−8 and 1.00 × 10−7.


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