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Record W91234465 · doi:10.1002/hep.27255

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2014· letter· en· W91234465 on OpenAlexaff
Jacinta A. Holmes, Gail Matthews, Alexander Thompson

Bibliographic record

VenueHepatology · 2014
Typeletter
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsInstitute of Infection and Immunity
FundersRoche
KeywordsMedicineInternal medicineGastroenterologyRibavirinDosingCohortITPAAnemiaHemoglobinImmunology

Abstract

fetched live from OpenAlex

We thank Dai et al. for their interest in our work. We found in the CHARIOT cohort that inosine triphosphatase (ITPase) deficiency protects against ribavirin (RBV)-induced anemia, but is not associated with sustained virological response (SVR).1 They ask whether rapid virological response (RVR), achieved in 32.8%, had any effect on the result of the association between SVR and the hemoglobin (Hb) decline or upon RBV pharmacokinetics. Patients in the CHARIOT study were randomized to standard (180 μg weekly) versus induction (360 μg weekly) dosing of pegylated interferon (IFN) for the first 12 weeks of the 48-week treatment course.2 In the substudy analyzed in our article, RVR rates were higher in those who were randomized to the induction-dosing arm (37.9% vs. 27.5%; P = 0.011), although this did not translate into higher week 12 response or SVR rates. RVR was strongly associated with SVR on univariable analysis (P < 0.0001). RBV levels at weeks 4 and 8 were not associated with RVR, and ITPA genotype did not predict RVR. We then added RVR into the two multivariable models presented in the original analyses. The first model included fibrosis stage, nadir Hb, and baseline predictors of SVR. Although nadir Hb was still an independent predictor of SVR, RVR was the strongest predictor of SVR (odds ratio: 9.85; P < 0.001). When week 8 RBV levels were added into the model together with RVR, the relationship between nadir Hb and SVR was attenuated, similar to that observed in the original model (data not shown). When the analysis was stratified according to week 4 viral response, nadir Hb was only associated with SVR in patients who attained an RVR, but not in those who did not achieve an RVR (109 vs. 115 for SVR and no SVR, respectively, in RVR patients [P = 0.0142] and 114 vs. 113 for SVR and no SVR, respectively, in non-RVR patients [P = 0.1094]). This suggested that there may be an interaction between RVR and nadir Hb. We formally tested this using interaction testing in the models. However, when the interaction term for RVR and nadir Hb was included, either with or without RBV levels, this was not statistically significant. Therefore, the data are inconclusive; although this is a small substudy, it raises the interesting question of whether RBV-induced anemia/pharmacokinetics might preferentially benefit patients with greater IFN responsiveness, perhaps by modulation of intrahepatic IFN-stimulated genes, as previously suggested.3 Analysis of IL28B genotype would indeed be relevant, and this analysis is ongoing. Jacinta A. Holmes, MBBS, FRACP1,2 Gail V. Matthews, M.B.Ch.B., MRCP (UK), FRACP, Ph.D.3 Alexander J. Thompson, MBBS, FRACP, Ph.D.1,2,4,5 on behalf of the CHARIOT Study Group 1St Vincent's Hospital University of Melbourne Melbourne, VIC, Australia 2Department of Medicine University of Melbourne Melbourne, VIC, Australia 3Kirby Institute for Infection and Immunity in Society University of New South Wales Sydney, NSW, Australia 4Victorian Infectious Diseases Reference Laboratory North Melbourne, VIC, Australia 5Duke University Medical Center Durham, NC

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)0.004
metaresearch head score (Gemma)0.065
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.035
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.065
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0040.005
Open science0.0020.003
Research integrity0.0130.024
Insufficient payload (model declined to judge)0.0350.030

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 head0.063
GPT teacher head0.347
Teacher spread0.284 · 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
GenreCommentary

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".

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Citations0
Published2014
Admission routes1
Has abstractyes

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