49 research outputs found
Growth Hormone Research Society perspective on biomarkers of GH action in children and adults
Objective
The Growth Hormone Research Society (GRS) convened a Workshop in 2017 to evaluate clinical endpoints, surrogate endpoints and biomarkers during GH treatment of children and adults and in patients with acromegaly.
Participants
GRS invited 34 international experts including clinicians, basic scientists, a regulatory scientist and physicians from the pharmaceutical industry.
Evidence
Current literature was reviewed and expert opinion was utilized to establish the state of the art and identify current gaps and unmet needs.
Consensus process
Following plenary presentations, breakout groups discussed questions framed by the planning committee. The attendees re-convened after each breakout session to share the group reports. A writing team compiled the breakout session reports into a document that was subsequently discussed and revised by participants. This was edited further and circulated for final review after the meeting. Participants from pharmaceutical companies were not part of the writing process.
Conclusions
The clinical endpoint in paediatric GH treatment is adult height with height velocity as a surrogate endpoint. Increased life expectancy is the ideal but unfeasible clinical endpoint of GH treatment in adult GH-deficient patients (GHDA) and in patients with acromegaly. The pragmatic clinical endpoints in GHDA include normalization of body composition and quality of life, whereas symptom relief and reversal of comorbidities are used in acromegaly. Serum IGF-I is widely used as a biomarker, even though it correlates weakly with clinical endpoints in GH treatment, whereas in acromegaly, normalization of IGF-I may be related to improvement in mortality. There is an unmet need for novel biomarkers that capture the pleiotropic actions of GH in relation to GH treatment and in patients with acromegaly
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Application of MCNP{trademark} to computed tomography in medicine
The MCNP{trademark} code has been used to simulate CT scans of the MIRD human phantom. In addition. an actual CT scan of a patient was used to create an MCNP geometry, and this geometry was computationally ``CT scanned`` using MCNP to reconstruct CT images. The results show that MCNP can be used to model the human body based on data obtained from CT scans and to simulate CT scans that are based on these or other models