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New model predicts growth hormone therapy response in children with short stature (opens in a new tab)

news-medical.net · 2026-10-05

Short answerEvidenceSource

Short answer

Mostly not supported

Mostly not supported.

The claims we could check match the study, but some claims were not covered by the evidence reviewed.

  • 2 supported
  • 5 not covered

Checked against the study summary. The full text wasn't available, so some details couldn't be settled either way.

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1
2

NewsLink checks it

Mostly not supported

Every claim we could check holds up. Two of seven claims match the study. This overall rating is based only on the claims we could check. Five claims the study doesn't address.

  • 2 supported
  • 5 not covered
Open claim evidence
3
Source paper

Source layer

The 2 papers the story cites

Source study separated from background citations.

The research anchor for the report.

Then inspect each claim

Evidence layer

Claim by claim

Each claim gets a verdict. Expand it to see the evidence directly below.

7 claims in this story

Showing all 7 claimsChoose a verdict to focus the list.

Claim 1 of 7Not coveredThe retrospective, single-center study analyzed 91 prepubertal Korean children with idiopathic short stature who received recombinant human growth hormone between July 2020 and December 2023.View evidenceHide evidence

As stated91 children

Why this verdict

The abstract profile supports a cohort of 91 prepubertal patients with idiopathic short stature and observational/secondary-data modeling. However, it does not report that the study was retrospective, single-center, Korean, conducted between July 2020 and December 2023, or specifically that recombinant human growth hormone was used, so those details are not verifiable from the abstract-depth profile.

1

Study evidence

A Gompertz-based NLME model characterized the longitudinal dose–response of GH on height percentile in 91 prepubertal ISS patients, estimating a baseline height percentile of 0.63 ± 0.90 and an upper growth limit of 17.2 ± 11.1.baseline 0.63 ± 0.90; upper growth limit 17.2 ± 11.1

“A total of 91 prepubertal patients with ISS were included in this study.”
Claim 2 of 7Not coveredOver a mean treatment period of 619 ± 307 days, the mean height percentile increased from 1.26 at baseline to 9.16 at follow-up.View evidenceHide evidence

As statedfrom 1.26 to 9.16

Why this verdict

The abstract-depth profile does not report mean treatment duration or raw mean height percentile changing from 1.26 to 9.16. It explicitly notes that follow-up duration and measurement timing are not reported in the abstract. The profile instead reports model parameters such as baseline height percentile 0.63 ± 0.90 and upper growth limit 17.2 ± 11.1.

1

Study evidence

A Gompertz-based NLME model characterized the longitudinal dose–response of GH on height percentile in 91 prepubertal ISS patients, estimating a baseline height percentile of 0.63 ± 0.90 and an upper growth limit of 17.2 ± 11.1.baseline 0.63 ± 0.90; upper growth limit 17.2 ± 11.1

“A total of 91 prepubertal patients with ISS were included in this study.”
Claim 3 of 7Not coveredHigher body mass index, lower insulin-like growth factor-binding protein 3 levels, and shorter paternal height were associated with a greater predicted response, with BMI described as the strongest association.View evidenceHide evidence

Why this verdict

The abstract profile supports that BMI, IGFBP-3, and paternal height were significant covariates influencing total growth. It does not provide the direction of effects—higher BMI, lower IGFBP-3, shorter paternal height—or state that BMI had the strongest association. Those added specifics are not verifiable from the supplied abstract-depth profile.

1

Study evidence

Body mass index (BMI), insulin-like growth factor–binding protein 3 (IGFBP-3), and paternal height were reported as significant baseline covariates influencing total growth in the NLME model.

“stepwise covariate modeling identified significant baseline predictors.”
Claim 4 of 7Not coveredThe team developed GrowCast, a web-based tool that generates individualized predicted height and percentile trajectories using age, sex, height, weight, paternal height, IGFBP-3 level, and GH dose.View evidenceHide evidence

Why this verdict

The abstract profile supports that the developed model was integrated into a web-based tool for individualized growth-trajectory prediction and treatment optimization. It does not provide the tool name GrowCast, implementation details, or the exact input list of age, sex, height, weight, paternal height, IGFBP-3, and GH dose, so the full claim is not verifiable at this depth.

1

Study evidence

A Gompertz-based NLME model characterized the longitudinal dose–response of GH on height percentile in 91 prepubertal ISS patients, estimating a baseline height percentile of 0.63 ± 0.90 and an upper growth limit of 17.2 ± 11.1.baseline 0.63 ± 0.90; upper growth limit 17.2 ± 11.1

“A total of 91 prepubertal patients with ISS were included in this study.”
2

Study evidence

Body mass index (BMI), insulin-like growth factor–binding protein 3 (IGFBP-3), and paternal height were reported as significant baseline covariates influencing total growth in the NLME model.

“stepwise covariate modeling identified significant baseline predictors.”
Claim 5 of 7Not coveredThe article says the platform may support clinician-family discussions and treatment planning, but it is not yet a validated dosing-prescription tool and larger prospective multicenter studies are needed before routine use.View evidenceHide evidence

Why this verdict

The profile supports only that the authors proposed a web-based tool for individualized prediction and GH treatment optimization, while noting lack of abstract-level validation and implementation details. The specific caveats that it may support clinician-family discussions, is not a validated dosing-prescription tool, and requires larger prospective multicenter studies before routine use are plausible limitations but are not directly reported in the supplied abstract-depth profile.

1

Study evidence

The developed model was integrated into a web-based tool, allowing clinicians to predict individualized growth trajectories and optimize GH treatment strategies.

“The developed model was integrated into a web-based tool, allowing clinicians to predict individualized growth trajectories and optimize GH treatment strategies”
Claim 6 of 7SupportedResearchers led by Professor Jung-woo Chae investigated changes in height percentile over time among children with idiopathic short stature receiving growth hormone therapy.View evidenceHide evidence

Why this verdict

The abstract profile supports that the study modeled longitudinal changes in age- and sex-adjusted height percentile among prepubertal children with idiopathic short stature receiving growth hormone. The supplied profile does not verify the named lead investigator, but the scientific substance of the claim is supported.

1

Study evidence

A Gompertz-based NLME model characterized the longitudinal dose–response of GH on height percentile in 91 prepubertal ISS patients, estimating a baseline height percentile of 0.63 ± 0.90 and an upper growth limit of 17.2 ± 11.1.baseline 0.63 ± 0.90; upper growth limit 17.2 ± 11.1

“A total of 91 prepubertal patients with ISS were included in this study.”
Claim 7 of 7SupportedThe model estimated a total growth-response parameter of approximately 17.2 percentile points, and responses differed substantially among patients.View evidenceHide evidence

As statedapproximately 17.2 percentile points

Why this verdict

The profile reports a finalized Gompertz-based NLME model with an upper growth limit of 17.2 ± 11.1 and identifies inter-individual variability through covariate modeling. The story’s phrasing of an approximately 17.2 percentile-point total growth-response parameter and heterogeneous responses is consistent with the abstract-level evidence.

1

Study evidence

A Gompertz-based NLME model characterized the longitudinal dose–response of GH on height percentile in 91 prepubertal ISS patients, estimating a baseline height percentile of 0.63 ± 0.90 and an upper growth limit of 17.2 ± 11.1.baseline 0.63 ± 0.90; upper growth limit 17.2 ± 11.1

“A total of 91 prepubertal patients with ISS were included in this study.”
2

Study evidence

Body mass index (BMI), insulin-like growth factor–binding protein 3 (IGFBP-3), and paternal height were reported as significant baseline covariates influencing total growth in the NLME model.

“stepwise covariate modeling identified significant baseline predictors.”
Then look for missing context

Context layer

What the story left out

Important study details the story did not include.

  • Stepwise covariate modeling identified BMI, IGFBP-3, and paternal height as significant covariates influencing total growth, but the abstract does not provide coefficients, effect sizes, confidence intervals, p-values, or effect directions.

    The story covers the three covariates, but presents directions and a strongest association for BMI without noting that the abstract-level evidence lacks effect magnitudes, uncertainty, and directionality. This is an interpretation-relevant limitation at abstract depth.

    From Secondary-data NLME with stepwise covariate selection

  • Model performance was assessed using visual predictive checks and goodness-of-fit plots, but the abstract does not provide quantitative diagnostic results or conclusions about fit quality.

    The story does not mention the reported VPC/GOF diagnostic assessment or the abstract-level limitation that diagnostic outcomes are not available.

    From secondary_data: NLME model diagnostics (VPC, GOF)

  • The abstract does not report duration of follow-up, timing or number of longitudinal measurements, missing-data handling, sensitivity analyses, or detailed estimation methods/software.

    These abstract-level reporting limitations are not acknowledged in the story; one of them is particularly relevant because the story states a specific mean treatment duration that is not available in the abstract-depth profile.

    From Gompertz-based NLME longitudinal dose–response model

4 things the story did carry across
  • The paper’s central contribution is a Gompertz-based nonlinear mixed-effects longitudinal dose–response model using age- and sex-adjusted height percentile as outcome and cumulative GH dose as exposure in 91 prepubertal ISS patients.
  • The abstract reports model parameters including baseline height percentile 0.63 ± 0.90 and upper growth limit 17.2 ± 11.1.
  • The finalized model was integrated into a web-based tool intended for individualized growth-trajectory prediction and GH treatment optimization.
  • The abstract lacks tool implementation, availability, usability, and external/prospective validation details.
Then read the study layer

Study layer

Study at a glance

Scan the study first. Expand only the parts you want to inspect.

Pieces of work

4

Evidence read

study summary

Lead result

secondary data

1Lead resultsecondary dataDevelop and fit a Gompertz-based nonlinear mixed-effects (NLME) longitudinal dose–response model to quantify growth hormone (GH) treatment effects on height percentile trajectories in prepubertal children with idiopathic short stature (ISS).Gompertz-based NLME longitudinal dose–response modelExpand

In plain English

A Gompertz-based nonlinear mixed-effects (NLME) longitudinal dose–response model was developed and fitted to repeated measures of height percentile (age- and sex-adjusted) from 91 prepubertal children with idiopathic short stature (ISS), using cumulative growth hormone (GH) dose (mg/kg) as the exposure metric. Stepwise covariate modeling identified body mass index (BMI), insulin-like growth factor–binding protein 3 (IGFBP3), and paternal height as significant predictors of total growth. Model performance was assessed with visual predictive checks and goodness-of-fit plots. The final model reported a baseline height percentile of 0.63 ± 0.90 and an upper growth limit of 17.2 ± 11.1 and was implemented in a web-based tool for individualized prediction.

Key findings

  • A Gompertz-based NLME model characterized the longitudinal dose–response of GH on height percentile in 91 prepubertal ISS patients, estimating a baseline height percentile of 0.63 ± 0.90 and an upper growth limit of 17.2 ± 11.1.baseline 0.63 ± 0.90; upper growth limit 17.2 ± 11.1
  • Body mass index (BMI), insulin-like growth factor–binding protein 3 (IGFBP3), and paternal height were identified as significant covariates influencing total growth in the model.
“A total of 91 prepubertal patients with ISS were included in this study.”
What this piece can’t prove
  • Abstract does not report duration of follow-up, timing/number of longitudinal measurements, or estimation algorithm/software.

3 further details could not be confirmed from the summary.

2secondary dataIdentify baseline predictors/covariates (eg, BMI, IGFBP-3, paternal height) that explain inter-individual variability in growth response within the NLME framework to support personalized dosing/response prediction.Secondary-data NLME with stepwise covariate selectionExpand

In plain English

Within a Gompertz-based nonlinear mixed-effects model of height-percentile response to cumulative GH dose in 91 prepubertal children with idiopathic short stature, stepwise covariate modeling identified body mass index (BMI), insulin-like growth factor–binding protein 3 (IGFBP-3), and paternal height as significant baseline predictors of total growth.

Key findings

  • Body mass index (BMI), insulin-like growth factor–binding protein 3 (IGFBP-3), and paternal height were reported as significant baseline covariates influencing total growth in the NLME model.
“stepwise covariate modeling identified significant baseline predictors.”
What this piece can’t prove

2 further details could not be confirmed from the summary.

3secondary dataAssess model adequacy/performance (eg, visual predictive checks and goodness-of-fit) for the finalized NLME model.secondary data: NLME model diagnostics (VPC, GOF)Expand

In plain English

The abstract reports that the finalized Gompertz-based NLME model was evaluated using visual predictive checks (VPCs) and goodness-of-fit (GOF) plots to assess model performance/adequacy, but it does not provide numeric results or diagnostic conclusions in the abstract.

Key findings

  • The study reports that visual predictive checks and goodness-of-fit plots were used to assess the finalized NLME model's performance/adequacy.
“The model performance was assessed using visual predictive checks and goodness-of-fit plots.”
What this piece can’t prove
  • Assessment is based solely on the abstract, which only states the use of VPCs and GOF plots without reporting diagnostic outcomes or implementation details.

2 further details could not be confirmed from the summary.

4otherTranslate the finalized predictive model into a web-based clinical tool for individualized growth-trajectory prediction and treatment optimization.Expand

In plain English

The authors report that the finalized NLME model was integrated into a web-based tool intended to allow clinicians to predict individualized growth trajectories and optimize GH treatment strategies for children with idiopathic short stature; the abstract does not provide implementation, availability, or validation details.

Key findings

  • The developed model was integrated into a web-based tool, allowing clinicians to predict individualized growth trajectories and optimize GH treatment strategies.
“The developed model was integrated into a web-based tool, allowing clinicians to predict individualized growth trajectories and optimize GH treatment strategies”
What this piece can’t prove

3 further details could not be confirmed from the summary.

Finally, the search trail

Method layer

NewsLink found the paper. Tessa takes you deeper.

NewsLink checks the story. Tessa is where you inspect the paper, authors, evidence, and research context.

Open the paper in Tessa

Longitudinal Modeling and Simulation of Growth Hormone Efficacy in Children With Idiopathic Short Stature

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research · 2026

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Why this one

Near certain

NewsLink found the paper. Tessa is where you inspect it deeply.

Papers considered

The selected paper, plus nearby candidates.

PubMed, Europe PMC, Crossref · 29 candidate papers

Selected

Longitudinal Modeling and Simulation of Growth Hormone Efficacy in Children With Idiopathic Short Stature

Value in Health : the Journal of the International Society for Pharmacoeconomics and Outcomes Research · 2026 · PubMed, Europe PMC, Crossref

Tessa (opens in a new tab)Source (opens in a new tab)
Candidate

Unintended Consequences of Expanded Magnetic Resonance Imaging Reimbursement: A Nationwide Analysis Revealing Low Clinical Efficiency.

Value in Health : the Journal of the International Society for Pharmacoeconomics and Outcomes Research · 2026 · PubMed

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And 23 more candidates considered.