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Record W2765883502 · doi:10.1016/j.jaad.2017.10.012

Characterization of disease burden, comorbidities, and treatment use in a large, US-based cohort: Results from the Corrona Psoriasis Registry

2017· article· en· W2765883502 on OpenAlexaff
Bruce Strober, Chitra Karki, Marc A. Mason, Ning Guo, Stacey H. Holmgren, Jeffrey D. Greenberg, Mark Lebwohl

Bibliographic record

VenueJournal of the American Academy of Dermatology · 2017
Typearticle
Languageen
FieldImmunology and Microbiology
TopicPsoriasis: Treatment and Pathogenesis
Canadian institutionsProbity Medical Research
FundersUniversity of ConnecticutAbbVieEli Lilly and Company
KeywordsMedicinePsoriasisCohortDiseaseDermatologyComorbidityIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Psoriasis is an immunodysregulatory inflammatory disease associated with comorbidities affecting quality of life. With the advent of new treatments, there is growing need to assess the long-term safety and efficacy of treatments in a real-world setting. OBJECTIVE: The objective of the Corrona Psoriasis Registry is to study the comparative safety and efficacy of Food and Drug Administration-approved biologic treatments. METHODS: A cross-sectional study of patients enrolled in the registry, who initiated or switched to a systemic therapy at enrollment or previous 12 months. Descriptive characteristics (demographics, clinical and patient-reported outcomes, comorbidities, and treatment history) were examined at registry enrollment. RESULTS: As of October 1, 2016, there were 1942 patients enrolled in the registry: 23% on apremilast, 4% on other nonbiologic systemic medications, 25% on interleukin (IL) 17A inhibitors, 22% on an IL-12/23 inhibitor, and 26% on tumor necrosis factor inhibitors. Overall, mean disease duration was 15.6 years, and 40% had a concurrent psoriatic arthritis diagnosis. About 66% had >3% body surface area involvement and 49% had a moderate or severe Investigator Global Assessment. LIMITATIONS: Selection and channeling bias can result in potential confounding that needs to be addressed in modeled analyses. CONCLUSION: This disease-based registry cohort represents a population exposed to multiple therapies, long disease duration, and multiple comorbidities and can be used to examine comparative safety and efficacy of various therapies.

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)0.000
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 score0.017
Threshold uncertainty score0.398

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.025
GPT teacher head0.271
Teacher spread0.246 · 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".

Quick stats

Citations100
Published2017
Admission routes1
Has abstractyes

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