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Record W4387405939 · doi:10.1210/jendso/bvad114.1151

THU071 Key Device Attributes For Injectable SRL Therapy In Acromegaly And NETs To Aid Clinical Decision Making

2023· article· en· W4387405939 on OpenAlexaboutno aff
Wouter W. de Herder, Шломо Мелмед, Cecilia Follin, Wanda Geilvoet, Jens Otto Lunde Jørgensen, Teodora Kolarova, Muriël Marks, Wendy Martin, Kim Geerlings-Grootscholten

Bibliographic record

VenueJournal of the Endocrine Society · 2023
Typearticle
Languageen
FieldMedicine
TopicPituitary Gland Disorders and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsAcromegalyMedicineFamily medicineInternal medicineClinical PracticeGrowth hormoneHormone

Abstract

fetched live from OpenAlex

Abstract Disclosure: W.W. de Herder: Research Investigator; Self; Novartis Pharmaceuticals. Speaker; Self; Novartis Pharmaceuticals, Ipsen. S. Melmed: Consulting Fee; Self; Ionis Pharmaceuticals Inc., Ipsen, Novo Nordisk. Grant Recipient; Self; Pfizer Global R&D. C. Follin: None. W. Geilvoet: None. J.O. Jorgensen: Consulting Fee; Self; Novo Nordisk, Pfizer Global R&D. T. Kolarova: Grant Recipient; Self; Ipsen, ITM, AAA, Novartis Pharmaceuticals. M. Marks: None. W. Martin: Speaker; Self; Ipsen, AAA. K. Geerlings-Grootscholten: None. Background: Adherence, effectiveness and safety of SRL injections are similar for self- vs healthcare setting administration but patient preferences and device satisfaction vary. Device ease of use is associated with more favourable outcomes for other injectable hormones. Aim: To define key injectable SRL device attributes associated with optimal injection experience by people living with NETs/acromegaly and HCPs, identifying differences at 95% confidence. Methods: The survey (Jun-Nov ‘22) included active current users (≥6 months) of an SRL device for NETs/acromegaly, and for HCPs currently treating patients with NETs/acromegaly. There were 263 respondents from Australia, Canada, Chile, Denmark, Ireland, Mexico, Norway, Spain, UK, and USA: 201 patients (P), 10 caregivers (C) and 52 HCPs. In the P/C group (n=211), 157 people lived with NET and 54 with acromegaly; 74% were female. The HCP group (n=52) comprised 29 physicians, 20 nurses and 3 others (research nurse, clinical manager, patient leader) treating acromegaly (n=22), NET (n=15), or both (n=15). Results: P/C treatment duration ranged from 0.5->15y (≥3y in 61%); 49% had experience with >1 SRL device type. Most HCPs (62%) were prescribers, 48% administered SRL injections, 83% had experience with >1 SRL device type. In the P/C group, NET patients were significantly more likely to have injections administered by an HCP in a hospital setting (54% vs 26% with acromegaly, p=0.05). Home administration was more common among acromegaly P/C (57%; 26% self-injected, 22% by caregiver, 9% by HCP) vs NET P/C (30%; 10%, 9% and 11%, respectively). Top 3 key device attributes preferred by the P/C group were: 1) confidence that the correct amount of drug is delivered (76%); 2) quick administration with minimal pain/discomfort (68%); 3) device safety (needle-safety system, low risk of contamination; 53%).The top 3 in the HCP group was: 1) quick administration with minimal pain/discomfort (69%); 2) correct use is easy to learn, confidence in handling the device (63%); 3) confidence that the correct amount of drug is delivered (62%). Ease of learning and confidence on correct use was significantly more likely to be selected as important by HCPs than P/C (63% vs 44%, p=0.05); ‘shorter/finer needles’ was significantly more likely to be selected by P/C than HCPs (48% vs 25%; p=0.05). ‘Easy to store and transport’ was significantly more likely to be selected by people living with acromegaly vs NET (59% vs 35%, p=0.05). Conclusions: Patient opinions are important to define key device attributes impacting the injection experience. Home administration is more common in acromegaly vs NET, as reflected in P/C device attribute preferences. Identified differences in key device attributes preferred by patients and HCPs inform the decision on which SRL device best fits individual patient needs. Developed with COR2ED, supported by an independent educational grant from Ipsen. Presentation: Thursday, June 15, 2023

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.256

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.054
GPT teacher head0.393
Teacher spread0.339 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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