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Constructing an Insulin-Like Growth Factor-based Prediction Model

This study has been terminated.
(Insufficient recruitment)
Information provided by (Responsible Party):
Pinchas Cohen, University of California, Los Angeles Identifier:
First received: December 7, 2005
Last updated: December 1, 2014
Last verified: December 2014

Serum insulin-like growth factor-I (IGF-I) measurements have been shown to correlate well with growth hormone action and effect, and recent data show that serum IGF-I may be related to safety and efficacy of growth hormone (GH) treatment in patients. Some studies indicate that high IGF-I levels are associated with increased cancer risk, and low IGF-I levels are associated with increased risk for cardiovascular disease. Studies in children also show that the serum IGF-I level is correlated with the change in height score achieved (that is, the higher the IGF-I level, the greater the gain in height). Pediatric endocrinologists have therefore begun to use serum IGF-I levels, in addition to growth rate and weight gain, to adjust the GH dose in treated children.

Although monitoring of serum IGF-I levels is becoming standard of care in patients begin treated with GH, there are few guidelines regarding the actual logistics of adjusting GH dose. As serum IGF-I level has been linked to both safety and efficacy of GH treatment, the ideal practice would be to maintain serum IGF-I levels within a certain target range. The overall goal of our study is to construct a mathematical model which predicts the change in GH dose necessary to achieve a desired change in IGF-I level.

Hypotheses to be tested by our study include the following: IGF-I measurement has a role in optimization of GH therapy; GH dose change to achieve IGF-I changes are predictable; and gender and puberty affect the relationship between dose change and target IGF-I changes.

Condition Phase
Growth Hormone Deficiency
Idiopathic Short Stature
Small for Gestational Age
Phase 1
Phase 2

Study Type: Observational
Study Design: Observational Model: Case-Only
Time Perspective: Retrospective
Official Title: Constructing an Insulin-Like Growth Factor-based Prediction Model

Resource links provided by NLM:

Further study details as provided by University of California, Los Angeles:

Primary Outcome Measures:
  • Delta IGF-I SDS [ Time Frame: 3-months ]
    1 SDS change per 20% dose change

Enrollment: 30
Study Start Date: August 2004
Study Completion Date: July 2012
Primary Completion Date: July 2012 (Final data collection date for primary outcome measure)
Detailed Description:

The first phase of our study, previously approved by the UCLA IRB in August 2004, involved a retrospective chart review and collection of preexisting data. We analyzed charts of patients who underwent non-weight-based GH dose adjustments preceded and followed by a serum IGF-I level. Data collected included patient's age, gender, height, weight, linear height velocity, pubertal status, GH dose, IGF-I levels, disease condition (i.e., growth hormone deficiency, idiopathic short stature, small-for-gestational age) and recording of any adverse effects. Based on this data collected, we performed statistical analysis of the relationship between GH dose change and change in IGF-I level achieved, and have found that in prepubertal children, there is a significant relationship between the GH dose change and change in corresponding IGF-I level. We have subsequently constructed a mathematical prediction model that allows us to determine the GH dose change necessary to achieve a desired IGF-I level, and in this second phase of our study, we plan to apply this mathematical prediction model prospectively for guiding GH dose adjustments in prepubertal children being treated with GH therapy.

Children being treated with GH are typically followed in the outpatient Endocrinology clinic every 3-4 months, and our practitioners have routinely been obtaining serum IGF-I levels (via venipuncture in the outpatient laboratory) for monitoring purposes. Validation of our GH dose change/IGF-I change prediction model will require assessment of sequential serum IGF-I level measurements immediately preceding a GH dose change, and again within 1-4 months following the GH dose change. We plan to continue our retrospective and ongoing analysis of patients who have paired values of GH dose adjustments preceded and followed by a serum IGF-I level, in order that we may continue to fine-tune our prediction model for optimizing GH dose adjustments.


Ages Eligible for Study:   3 Years to 14 Years   (Child)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No
Sampling Method:   Non-Probability Sample
Study Population
GH-treated chlidren

Inclusion Criteria:

  • Prepubertal patients,
  • Male/female,
  • Ages 3-14 yrs,
  • Being treated with growth hormone for the conditions of growth hormone deficiency, idiopathic short stature, and small-for-gestational age with failure to catch up to the normal growth curve by age 2 years.

Exclusion Criteria:

  • Patients being treated with growth hormone for other conditions such as Turner syndrome, chronic renal failure, or Prader-Willi syndrome
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Please refer to this study by its identifier: NCT00263445

United States, California
UCLA Pediatric Endocrinology
Los Angeles, California, United States, 90095
Sponsors and Collaborators
University of California, Los Angeles
Principal Investigator: Pinchas Cohen, MD University of California, Los Angeles
  More Information

Responsible Party: Pinchas Cohen, Proffessor and Chief, Peds Endo, University of California, Los Angeles Identifier: NCT00263445     History of Changes
Other Study ID Numbers: 04-07-052-02
304-F02/X3270n (Genentech)
Study First Received: December 7, 2005
Last Updated: December 1, 2014

Keywords provided by University of California, Los Angeles:
Growth hormone dosing

Additional relevant MeSH terms:
Dwarfism, Pituitary
Bone Diseases, Developmental
Bone Diseases
Musculoskeletal Diseases
Bone Diseases, Endocrine
Pituitary Diseases
Hypothalamic Diseases
Brain Diseases
Central Nervous System Diseases
Nervous System Diseases
Endocrine System Diseases
Genetic Diseases, Inborn
Mitosis Modulators
Molecular Mechanisms of Pharmacological Action processed this record on May 22, 2017