Increasing evidence has been accumulated for treating rheumatoid arthritis (RA) with TNF-α blocking agents. The formulation and definition of an early indicator of patient's reactivity during therapy may be extremely simplified by a mathematical model of clinical response. We analyzed the most significant clinical and laboratory parameters of response of 35 homogeneous patients (30 women, 5 men mean age ± SD: 52.31 ± 12.30 years) treated with adalimumab 40 mg every 2 weeks associated with methotrexate (MTX) 10-15 mg/week and with a stable dosage of steroids for 30 weeks. The over time trend of the studied parameters showed a linear response, which has allowed the realization of a simple mathematical model. The formula derived from this mathematical model was then applied and therefore validated in a group of 121 patients previously treated with several anti-TNF-alpha agents for at least 6 months. We drafted a mathematical model (early response indicator, ERI) that, by using a simple calculation, allows us to identify a high percentage of responder patients after only 2 weeks of treatment. ERI identified a high percentage (88%) of patients responding after only 2 weeks, as was confirmed at weeks 30; the use of ERI calculation after 6 weeks increases the proportion of responding patients to 92% with a percentage of false negatives of only 12%. ERI could be a useful tool to early differentiate the responder from the non-responder patients.
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http://dx.doi.org/10.1007/s00296-010-1619-7 | DOI Listing |
N Z Med J
January 2025
Executive Dean, Bond Business School, Bond University, Gold Coast, QLD, Australia; Harkness Senior Fellow, Commonwealth Fund of New York.
This article makes the case for taking a model-based management approach, specifically using the Viable System Model (VSM), to embed learning and adaptation into the New Zealand health system so it can function as a learning health system. We draw on a case study of a specialist clinical service where the VSM was used to guide semi-structured interviews and workshops with clinicians and managers and to guide analysis of the findings. The VSM analysis revealed a lack of clarity of organisational functioning, and of the systems, processes and integrated IT infrastructure necessary to support the fundamental requirements of a learning health system.
View Article and Find Full Text PDFAstrobiology
January 2025
Department of Aerospace, Physics and Space Sciences, Florida Institute of Technology, Melbourne, Florida, USA.
Waste heat production represents an inevitable consequence of energy conversion as per the laws of thermodynamics. Based on this fact, by using simple theoretical models, we analyze constraints on the habitability of Earth-like terrestrial planets hosting putative technological species and technospheres characterized by persistent exponential growth of energy consumption and waste heat generation. In particular, we quantify the deleterious effects of rising surface temperature on biospheric processes and the eventual loss of liquid water.
View Article and Find Full Text PDFSoft comput
July 2024
Department of Mathematics, Institute of Numerical Sciences, Gomal University, Dera Ismail Khan, KPK 29050 Pakistan.
[This retracts the article DOI: 10.1007/s00500-021-06133-1.].
View Article and Find Full Text PDFPLoS Comput Biol
January 2025
Deparment of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands.
Systems biology tackles the challenge of understanding the high complexity in the internal regulation of homeostasis in the human body through mathematical modelling. These models can aid in the discovery of disease mechanisms and potential drug targets. However, on one hand the development and validation of knowledge-based mechanistic models is time-consuming and does not scale well with increasing features in medical data.
View Article and Find Full Text PDFPLoS Biol
January 2025
Carney Institute for Brain Science, Department of Cognitive & Psychological Sciences, Brown University, Providence, Rhode Island, United States of America.
The basal ganglia (BG) play a key role in decision-making, preventing impulsive actions in some contexts while facilitating fast adaptations in others. The specific contributions of different BG structures to this nuanced behavior remain unclear, particularly under varying situations of noisy and conflicting information that necessitate ongoing adjustments in the balance between speed and accuracy. Theoretical accounts suggest that dynamic regulation of the amount of evidence required to commit to a decision (a dynamic "decision boundary") may be necessary to meet these competing demands.
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