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Record W2948262001 · doi:10.2337/db19-1199-p

1199-P: Analysis of Patient Preferences for Adjunct Therapy to Insulin in T1D

2019· article· en· W2948262001 on OpenAlexaboutno aff
Bruce A. Perkins, Julio Rosenstock, Jay S. Skyler, Lori M. Laffel, David Z.I. Cherney, Chantal Mathieu, Christianne Pang, Richard Wood, Ona Kinduryte, Jyothis T. George, Jan Marquard, Nima Soleymanlou

Bibliographic record

VenueDiabetes · 2019
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAdjunctHypoglycemiaInsulinGlycemicInternal medicineIntensive care medicine

Abstract

fetched live from OpenAlex

Recent ADA/EASD recommendations emphasize the importance of the patient role in therapy decisions. Adjunct to insulin SGLT inhibitor (SGLTi) therapy for T1D has been evaluated in RCTs but patient reaction to the benefit-risk profile of these agents is unknown. We aimed to objectively evaluate patient preferences for different therapy options, using a Discrete Choice Experiment (DCE) form of conjoint analysis, a validated methodology. The DCE used an online survey, completed by 701 respondents with T1D (231 U.S., 242 Canada, 228 Germany), to present 6 hypothetical, masked pair-wise drug profile comparison choices composed of different benefit-risk attributes and clinical effect ranges (levels). Attributes and levels were derived from different combinations of phase 3 trial data for a low dose SGLTi (comparable to empagliflozin 2.5mg); a high dose SGLTi (comparable to sotagliflozin 400mg); and an available adjunct to insulin therapy (pramlintide 60µg TID). Based upon respondents’ choices, DCE calculated, in %, the relative importance of one attribute to another and the overall predicted therapy preferences. DKA risk was the most important attribute with a relative importance of 23% (z-test, p<0.05). Second and similarly important were HbA1c reduction (14%), risk of hypoglycemia (13%), oral vs. injection treatment (13%), and risk of genital infection (12%). Next was risk of nausea (11%); weight reduction (8%) and risk of diarrhea (7%) were least important. The predicted therapy preference share was highest for low dose SGLTi, ranked first by 83% (z-test, p<0.05), compared with 8% for high dose SGLTi and 9% for pramlintide. In a separate question, respondents were asked to explicitly choose (masked to drug profile name and dose) among the clinical trial profiles of low dose SGLTi (chosen by 69%), high dose SGLTi (17%), pramlintide (6%), and ‘none of the above’ (9%). In conclusion, the DCE and head-to-head explicit choice identified low dose SGLTi as the favored patient preference for adjunct therapy to insulin in T1D. Disclosure B.A. Perkins: Advisory Panel; Self; Abbott, Boehringer Ingelheim International GmbH, Boehringer Ingelheim International GmbH, Insulet Corporation. Research Support; Self; Boehringer Ingelheim International GmbH. Other Relationship; Self; Abbott, Boehringer Ingelheim International GmbH, Lilly Diabetes, Medtronic, Novo Nordisk Inc., Sanofi. J. Rosenstock: Research Support; Self; AstraZeneca, Bristol-Myers Squibb Company, Genentech, Inc., GlaxoSmithKline plc., Lexicon Pharmaceuticals, Inc., Melior Pharmaceuticals, Inc., Bukwang Pharm. Co., Ltd., Merck & Co., Inc., Oramed Pharmaceuticals, PegBio Co., Ltd., Pfizer Inc. Other Relationship; Self; Boehringer Ingelheim International GmbH, Eli Lilly and Company, Intarcia Therapeutics, Inc., Janssen Pharmaceuticals, Inc., Novo Nordisk Inc., Sanofi. J.S. Skyler: Advisory Panel; Self; ADOCIA, Applied Therapeutics, Dance Biopharm Holdings Inc., Orgenesis Ltd., Tolerion, Inc., Viacyte, Inc. Board Member; Self; Dexcom, Inc., Intarcia Therapeutics, Inc., Moerae Matrix, Inc. Consultant; Self; AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Dalcor, Dialogics, Elcelyx Therapeutics, Inc., Esperion, GeNeuro Innovation, Ideal Life, Immunomolecular Therapeutics, Intrexon, Kamada, Nestlé, Sanofi, Valeritas, Inc., Zafgen, Inc. Stock/Shareholder; Self; Dexcom, Inc., Ideal Life, Intarcia Therapeutics, Inc., Intrexon, Moerae Matrix, Inc. L.M. Laffel: Advisory Panel; Self; Lilly Diabetes, Novo Nordisk A/S, Roche Diabetes Care, Sanofi. Consultant; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Dexcom, Inc., Janssen Pharmaceuticals, Inc., UpToDate. D. Cherney: Other Relationship; Self; AbbVie Inc., AstraZeneca, Bayer AG, Boehringer Ingelheim International GmbH, Janssen Pharmaceuticals, Inc., Merck & Co., Inc., Mitsubishi Tanabe Pharma Corporation, Prometic Life Sciences Inc., Sanofi. C. Mathieu: Advisory Panel; Self; Boehringer Ingelheim International GmbH, Eli Lilly and Company, Merck & Co., Inc., Novo Nordisk A/S, Roche Diabetes Care, Sanofi. Speaker's Bureau; Self; AstraZeneca, Novartis AG, Novo Nordisk A/S, Sanofi. C. Pang: Consultant; Self; dQ&A Market Research, Inc. R. Wood: Other Relationship; Self; Multiple companies in the diabetes field (>10 companies). O. Kinduryte: Employee; Self; Boehringer Ingelheim International GmbH. Stock/Shareholder; Self; Novo Nordisk A/S, Zealand Pharma A/S. J. George: Employee; Self; Boehringer Ingelheim International GmbH. J. Marquard: Employee; Self; Boehringer Ingelheim International GmbH. N. Soleymanlou: Employee; Self; Boehringer Ingelheim Canada Ltd. Funding Boehringer Ingelheim; Eli Lilly and Company

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)0.004
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.016
GPT teacher head0.257
Teacher spread0.241 · 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 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
Published2019
Admission routes1
Has abstractyes

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