MétaCan
Menu
Back to cohort
Record W3021798477 · doi:10.1210/jendso/bvaa046.504

OR10-04 Interpretation of Insulin-like Growth Factor-1 (IGF-1) Levels Following Administration of Somatrogon (a Long-acting Human Growth Hormone - hGH-CTP)

2020· article· en· W3021798477 on OpenAlexaff
Dennis M. Fisher, Aleksandra Pastrak, John Choe, Michael P. Wajnrajch, José Cara

Bibliographic record

VenueJournal of the Endocrine Society · 2020
Typearticle
Languageen
FieldMedicine
TopicGrowth Hormone and Insulin-like Growth Factors
Canadian institutionsOPKO Health (Canada)
Fundersnot available
KeywordsDosingMedicineInternal medicineInsulin-like growth factorGrowth hormoneBiomarkerEndocrinologyGrowth factorHormoneChemistryReceptorBiochemistry

Abstract

fetched live from OpenAlex

Abstract IGF-1 is often used as a biomarker to evaluate the efficacy and safety of hGH replacement therapy. Typically, the mean IGF-1 SDS level during the dosing interval, rather than the peak value, guides clinical decision-making: sustained mean values > +2 may require hGH dose modifications. With long-acting formulations (administered weekly), the IGF-1 evaluation paradigm needs to take into account when the sample was obtained relative to the last administered dose. Previous studies with OPKO’s once weekly Somatrogon (hGH-CTP), demonstrated that IGF-1 SDS peaked ~ 48 hours post-dose and that values at ~ 96 hours best approximated the mean IGF-1 SDS throughout the dosing interval [1]. Data from the pivotal Phase 3 non-inferiority study comparing treatment with Somatrogon to Genotropin allowed further evaluation of the IGF-1 SDS analysis paradigm. Enrolled subjects were randomized to receive treatment with either once weekly Somatrogon (0.66 mg/kg; N=109) or once daily Genotropin (0.034 mg/kg; N=115). IGF1 was sampled ~ five times during 52 weeks of treatment with Somatrogon, providing a total of 557 samples obtained after the first dose of Somatrogon. IGF-1 SDS values were calculated using Bidlingmaier’s equations [2]. Analysis of IGF-I SDS data from the Phase 3 study showed that the previously-developed model, with adjustments to two parameters (baseline IGF-1, EC50) and adapted to fit IGF-1 values in the absence of Somatrogon concentration data, fit the IGF-1 data for Somatrogon with minimal bias. This allowed prediction of IGF-1 SDS values at timepoints throughout the dosing interval as well as calculation of the mean value during a dosing interval. Of the samples obtained between 48–72 hours post-dose (representing peak IGF-1 SDS), approximately 17% had an IGF1 SDS > +2. At 96 hours (corresponding to mean IFG-1 SDS), fewer than 2% of modeled values were > +2. Mean IGF-1 SDS over the dosing interval was between -1 and +1 for all subjects. These findings indicate that IGF-1 SDS values need to be interpreted in the context of when the sample was obtained relative to the last dose of Somatrogon. Our results indicate that samples obtained 96 hours post-dose best represent mean IGF-1 levels and that values obtained between 48–72 hours post-dose represent values closer to peak IGF-1 concentrations. In our Phase 3 study, of the 557 samples collected from 114 patients during the 12-month Somatrogon treatment period, fewer than 2% of the corresponding values at 96 hours postdose (estimated from a pharmacokinetic/pharmacodynamic model) had IGF-1 SDS levels > +2. 1. Fisher DM, et al. Horm Res Paediatr 2017;87:324. 2. Bidlingmaier M, et al. J Clin Endocrinol Metab 2014;99:1712

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.249
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.031
GPT teacher head0.293
Teacher spread0.261 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the Endocrine SocietySame topicGrowth Hormone and Insulin-like Growth FactorsFrench-language works237,207