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Record W2924683704 · doi:10.1007/s10067-019-04496-3

PANLAR consensus statement on biosimilars

2019· article· en· W2924683704 on OpenAlexaff
Sérgio Cândido Kowalski, J. A. Benavides, P. A. B. Roa, Claudio Galarza-Maldonado, Carlo V. Caballero‐Uribe, Enrique R. Soriano, Carlos Pineda, Valderílio Feijó Azevedo, G. Ávila, Alejandra Babini, Antonio Cachafeiro-Vilar, Mayra Elizabeth Cifuentes-Alvarado, Stanley Cohen, P. E. Díaz, Longino Soto, C. Encalada, Boris Garro, I. A. G. Sariego, Marlene Guibert-Toledano, Virginia Jiménez Rodríguez, María Elena López, Andrés Perea Ortega, A. S. Russell, P. Santos-Moreno, Ivana Terán, Alejandro Vargas, Giorgio Vasquez, Ricardo Machado Xavier, D. X. Xibillé Firedman, Eduardo Mysler, Jonathan Kay

Bibliographic record

VenueClinical Rheumatology · 2019
Typearticle
Languageen
FieldImmunology and Microbiology
TopicBiosimilars and Bioanalytical Methods
Canadian institutionsCanadian Rheumatology Association
Fundersnot available
KeywordsBiosimilarMedicinePharmacovigilanceTraceabilityDelphiDelphi methodFamily medicineActuarial scienceAdverse effectPharmacologyBusinessInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: Biologics have improved the treatment of rheumatic diseases, resulting in better outcomes. However, their high cost limits access for many patients in both North America and Latin America. Following patent expiration for biologicals, the availability of biosimilars, which typically are less expensive due to lower development costs, provides additional treatment options for patients with rheumatic diseases. The availability of biosimilars in North American and Latin American countries is evolving, with differing regulations and clinical indications. OBJECTIVE: The objective of the study was to present the consensus statement on biosimilars in rheumatology developed by Pan American League of Associations for Rheumatology (PANLAR). METHODS: Using a modified Delphi process approach, the following topics were addressed: regulation, efficacy and safety, extrapolation of indications, interchangeability, automatic substitution, pharmacovigilance, risk management, naming, traceability, registries, economic aspects, and biomimics. Consensus was achieved when there was agreement among 80% or more of the panel members. Three Delphi rounds were conducted to reach consensus. Questionnaires were sent electronically to panel members and comments about each question were solicited. RESULTS: Eight recommendations were formulated regarding regulation, pharmacovigilance, risk management, naming, traceability, registries, economic aspects, and biomimics. CONCLUSION: The recommendations highlighted that, after receiving regulatory approval, pharmacovigilance is a fundamental strategy to ensure safety of all medications. Registries should be employed to monitor use of biosimilars and to identify potential adverse effects. The price of biosimilars should be significantly lower than that of reference products to enhance patient access. Biomimics are not biosimilars and, if they are to be marketed, they must first be evaluated and approved according to established regulatory pathways for novel biopharmaceuticals. KEY POINTS: • Biologics have improved the treatment of rheumatic diseases. • Their high cost limits access for many patients in both North America and Latin America. • Biosimilars typically are less expensive, providing additional treatment options for patients with rheumatic diseases. • PANLAR presents its consensus on biosimilars in rheumatology.

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)0.069
metaresearch head score (Gemma)0.077
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.069
Threshold uncertainty score0.363

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0690.077
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.006
Bibliometrics0.0050.003
Science and technology studies0.0030.005
Scholarly communication0.0110.005
Open science0.0090.010
Research integrity0.0360.026
Insufficient payload (model declined to judge)0.0100.011

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 head0.052
GPT teacher head0.379
Teacher spread0.326 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations18
Published2019
Admission routes1
Has abstractno

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