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Record W2989858130 · doi:10.3389/fphar.2019.01372

The Clinical Implications of Nocebo Effects for Biosimilar Therapy

2019· review· en· W2989858130 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

VenueFrontiers in Pharmacology · 2019
Typereview
Languageen
FieldImmunology and Microbiology
TopicBiosimilars and Bioanalytical Methods
Canadian institutionsUniversity of Calgary
FundersPfizer
KeywordsNocebo EffectBiosimilarNoceboMedicineIntensive care medicinePsychosocialAdverse effectDiseasePsychological interventionRheumatoid arthritisAlternative medicinePharmacologyPsychiatryImmunologyPlaceboInternal medicine

Abstract

fetched live from OpenAlex

Nocebo effects encompass negative responses to inert interventions in the research setting and negative outcomes with active treatments in the clinical research or practice settings, including new or worsening symptoms and adverse events, stemming from patients' negative expectations and not the pharmacologic action of the treatment itself. Numerous personality, psychosocial, neurobiological, and contextual/environmental factors contribute to the development of nocebo effects, which can impair quality of life and reduce adherence to treatment. Biologics are effective agents widely used in autoimmune disease, but their high cost may limit access for patients. Biosimilar products have gained regulatory approval based on quality, safety, and efficacy comparable to that of originator biologics in rigorous study programs. In this review, we identified gaps in patients' and healthcare professionals' awareness, understanding, and perceptions of biosimilars that may result in negative expectations and nocebo effects, and may diminish their acceptance and clinical benefits. We also examined features of nocebo effects with biosimilar treatment that inform research and clinical practices. Namely, when biosimilars are introduced to patients as possible treatment options, we recommend adoption of nocebo-reducing strategies to avoid negative expectations, including delivery of balanced information on risk-benefit profiles, framing information to focus on positive attributes, and promoting shared decision-making processes along with patient empowerment. Healthcare professionals confident in their knowledge of biosimilars and aware of bias-inducing factors may help reduce the risk of nocebo effects and improve patients' adherence in proposing biosimilars as treatment for autoimmune diseases such as rheumatoid arthritis and inflammatory bowel disease.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.751
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.128
GPT teacher head0.477
Teacher spread0.349 · 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