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Record W4214632635 · doi:10.3389/fendo.2022.795224

Treatment Adherence to Injectable Treatments in Pediatric Growth Hormone Deficiency Compared With Injectable Treatments in Other Chronic Pediatric Conditions: A Systematic Literature Review

2022· review· en· W4214632635 on OpenAlexaboutno aff
Roy Gomez, S. Faisal Ahmed, Mohamad Maghnie, Dejun Li, Toshiaki Tanaka, Bradley S. Miller

Bibliographic record

VenueFrontiers in Endocrinology · 2022
Typereview
Languageen
FieldMedicine
TopicGrowth Hormone and Insulin-like Growth Factors
Canadian institutionsnot available
FundersPfizer
KeywordsMedicineObservational studyMEDLINEPediatricsGrowth hormone deficiencySystematic reviewInternal medicineGrowth hormoneHormone

Abstract

fetched live from OpenAlex

Background: Pediatric patients with growth hormone deficiency (GHD) are currently treated with daily injections of recombinant human growth hormone (rhGH) to promote linear growth and enable attainment of normal adult height. One of the main reasons for suboptimal growth during rhGH therapy is non-adherence to treatment. The objective of this systematic literature review was to examine the recent literature on pediatric adherence to injectable treatments for chronic conditions (focusing on rhGH) to characterize levels of adherence and identify the factors/barriers associated with adherence. Methods: The Embase and MEDLINE databases (January 2015-October 2020) were searched to identify publications describing studies of pediatric patients (aged ≤17 years) with GHD and other chronic conditions requiring daily or weekly injectable treatments; a similar targeted search of Chinese literature was also performed. Adherence data were extracted from the included studies and summarized. Risk of bias was determined using the Cochrane Risk of Bias tool 2 or the Newcastle-Ottawa Scale. Results: A total of 23 publications were included, with all publications except for one (multiple sclerosis) focused on pediatric GHD studies: there were two clinical trials, 18 observational studies and three survey studies. Study sample sizes ranged from 30 to 13,553 patients (median: 95 patients). The definition of adherence varied between studies and included mean adherence rate, median adherence rate, and the percentage of patients within pre-specified adherence categories. Of the publications assessing adherence to daily rhGH, 11 studies reported 12-month mean adherence rate (range: 73.3%- 95.3%) and eight studies reported median adherence (range: 91%- 99.2%). The barriers to treatment adherence identified included self-administration, increased administration frequency, age (adolescence), longer treatment duration, device design, and insufficient family education, awareness, and/or engagement. Recommendations for increasing adherence included using adherence reminder tools, increasing patient engagement/education, and improving injection device design and drug product. Conclusions: Adherence to rhGH treatment was high (>80%) for many studies, though comparability between studies was limited given the substantial heterogeneity in the way adherence was defined, measured, and reported. To address this heterogeneity, we recommend standardizing how adherence is defined and reported and encourage the use of standardized study designs and outcome measures.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.048
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.010
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.048
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.007
Bibliometrics0.0100.012
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.305
Teacher spread0.274 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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

Citations28
Published2022
Admission routes1
Has abstractyes

Explore more

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