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Record W2749018374 · doi:10.1093/ofid/ofx163.392

Patients Followed in an Addiction Medicine Clinic Are Less Likely to Be Eligible to Hepatitis C Drug Studies Regardless of Drug Use

2017· article· en· W2749018374 on OpenAlexaff
Gabrielle Doré, Julie Bruneau, Valérie Martel‐Laferrière

Bibliographic record

VenueOpen Forum Infectious Diseases · 2017
Typearticle
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsCentre Hospitalier de l’Université de MontréalUniversité Laval
FundersJanssen Pharmaceuticals
KeywordsMedicineHepatitis CPopulationDrugInclusion and exclusion criteriaInternal medicineRetrospective cohort studyClinical trialPediatricsAlternative medicinePsychiatry

Abstract

fetched live from OpenAlex

Phase 3 trials evaluating direct-acting antivirals (DAA) consistently report high sustained virologic responses (SVR). The strict eligibility criteria applied to these studies may affect the reproducibility in clinical practice. It has been demonstrated that drug use generally does not affect SVR. This retrospective cohort study sought to estimate the proportion of patients followed in a tertiary addiction clinic that would meet eligibility criteria for clinical trials, if drug use was not considered as a rejection criteria. The sample population consists of patients with active HCV genotypes (GT) 1-3, seen at the clinic between 01/2013 and 09/2015. Information from clinical charts was retrieved to examine how participants would meet the eligibility criteria of 14 studies. Individual patient’s data were compared with the studies’ eligibility criteria. A total of 234 patients met the inclusion criteria (GT 1: 58.1%; GT 2: 8.5%, GT 3: 34.2%; experienced: 16.2%; cirrhotic: 14.5%) and 53% (124/234) of patients could have been included in at least one study. Table shows individual study results. The most inclusive study was COSMOS (31/49; 63%). The most frequent exclusion criteria were the presence of significant diseases (cardiac, pulmonary, hepatic, porphyria or other), contraindicated medication and haemoglobin level. Even without considering drug use, only half of the patients of the addiction clinic would have been eligible for at least one study. This under-representation stems from strict eligibility criteria that promote a healthier population. Our study suggests that the DAA might prove less effective when administered to infected populations followed in specialized clinics for drug. J. Bruneau, Gilead: Consultant, Consulting fee. Merck: Consultant, Consulting fee. V. Martel-Laferrière, Gilead Inc.: Consultant and Grant Investigator, Consulting fee and Research grant. Abbvie: Grant Investigator, Research grant Merck: Consultant, Consulting fee

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)0.001
metaresearch head score (Gemma)0.007
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 score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.099
GPT teacher head0.424
Teacher spread0.325 · 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".

Quick stats

Citations0
Published2017
Admission routes1
Has abstractyes

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