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Record W2060221163 · doi:10.1007/s12325-012-0037-5

Treatment Patterns in the First Year After Initiating Tumor Necrosis Factor Blockers in Real-World Settings

2012· article· en· W2060221163 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAdvances in Therapy · 2012
Typearticle
Languageen
FieldMedicine
TopicRheumatoid Arthritis Research and Therapies
Canadian institutionsThomson Reuters (Canada)
FundersPfizerAmgen
KeywordsEtanerceptMedicineAdalimumabInfliximabGolimumabPsoriatic arthritisRheumatoid arthritisInternal medicineAbataceptAnkylosing spondylitisPsoriasisUstekinumabTumor necrosis factor alphaRituximabDermatologyLymphoma

Abstract

fetched live from OpenAlex

BACKGROUND: Tumor necrosis factor (TNF)-blockers are approved for use in several immune-related conditions, but treatment patterns, such as switching between TNF blockers or restarting treatment after a gap in therapy, are not clearly established. This analysis examined TNF blocker treatment patterns within the first year after initiating treatment with etanercept, adalimumab, or infliximab in patients with rheumatoid arthritis, psoriasis, psoriatic arthritis, or ankylosing spondylitis. METHODS: Administrative claims data from the MarketScan® Commercial Claims and Encounters Database (Thomson Reuters, Ann Arbor, MI, USA) were analyzed for patients with rheumatoid arthritis, psoriasis, psoriatic arthritis, or ankylosing spondylitis who were continuously enrolled and newly initiated etanercept, adalimumab, or infliximab treatment between January 1, 2005 and July 1, 2009. Persistence (no treatment gap ≥45 days), restarting index therapy (after a ≥45-day treatment gap), switching to a different biologic of interest (certolizumab, golimumab, ustekinumab, alefacept, abatacept, rituximab, or tocilizumab), and stopping (≥45-day treatment gap with no restart or switch) were analyzed for the first year after the index date. RESULTS: A total of 8,454 patients had an index claim for etanercept (n = 4,224), adalimumab (n = 2,941), or infliximab (n = 1,289). Treatment patterns in the first year across all four conditions combined for etanercept, adalimumab, or infliximab, respectively, were: persistence, 42%, 47%, and 56%; restarting, 25%, 19%, and 12%; switching, 13%, 12%, and 13%; and stopping, 20%, 22%, and 19%. The combined rates of either persistence or restarting initial therapy after a treatment gap were 67%, 66%, and 68%, for etanercept, adalimumab, and infliximab, respectively. Most switches (66-92%) were between the three TNF blockers. CONCLUSION: In the first year after initiating TNF blocker therapy, patients often have a ≥45-day treatment gap; however, approximately two-thirds of patients are either persistent with or restart their index therapy in the year following TNF blocker initiation.

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.

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 score0.067
Threshold uncertainty score0.447

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.020
GPT teacher head0.322
Teacher spread0.302 · 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