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Record W4206393627 · doi:10.1093/brain/awab422

Randomized trial of three IVIg doses for treating chronic inflammatory demyelinating polyneuropathy

2021· article· en· W4206393627 on OpenAlexaff
David R. Cornblath, Pieter A. van Doorn, Hans‐Peter Hartung, Ingemar S. J. Merkies, Hans Katzberg, Doris Hinterberger, Elisabeth Clodi, Sasho Hristov Kastrev, V. Rizova, Rami Massie, Radomír Taláb, Martin M. Bednar, Petr Ridzoň, J Schmidt, Jana Zschüntzsch, Csilla Rózsa, László Vécsei, Konrad Rejdak, Magdalena Koszewicz, Sławomir Budrewićz, Adriana Octaviana Dulămea, Monica Marian, A. Kádár, L. Zecheru-Lapusneanu, В. А. Михайлов, D Zakharov, Н. А. Супонева, М. А. Пирадов, N. M. Smolko, D. G. Smolko

Bibliographic record

VenueBrain · 2021
Typearticle
Languageen
FieldMedicine
TopicPeripheral Neuropathies and Disorders
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsChronic inflammatory demyelinating polyneuropathyMedicineRandomized controlled trialClinical endpointPolyneuropathyPolyradiculoneuropathyInternal medicineAdverse effectGastroenterologyMultifocal motor neuropathyConfidence intervalAntibodySurgeryGuillain-Barre syndromeImmunology

Abstract

fetched live from OpenAlex

Intravenous immunoglobulin treatment for chronic inflammatory demyelinating polyneuropathy usually starts with a 2.0 g/kg induction dose followed by 1.0 g/kg maintenance doses every 3 weeks. No dose-ranging studies with intravenous immunoglobulin maintenance therapy have been published. The Progress in Chronic Inflammatory Demyelinating polyneuropathy (ProCID) study was a prospective, double-blind, randomized, parallel-group, multicentre, phase III study investigating the efficacy and safety of 10% liquid intravenous immunoglobulin (Panzyga®) in patients with active chronic inflammatory demyelinating polyneuropathy. Patients were randomized 1:2:1 to receive the standard intravenous immunoglobulin induction dose and then either 0.5, 1.0 or 2.0 g/kg maintenance doses every 3 weeks. The primary end point was the response rate in the 1.0 g/kg group, defined as an improvement ≥1 point in adjusted Inflammatory Neuropathy Cause and Treatment score at Week 6 versus baseline and maintained at Week 24. Secondary end points included dose response and safety. This trial was registered with EudraCT (Number 2015-005443-14) and clinicaltrials.gov (NCT02638207). Between August 2017 and September 2019, the study enrolled 142 patients. All 142 were included in the safety analyses. As no post-infusion data were available for three patients, 139 were included in the efficacy analyses, of whom 121 were previously on corticosteroids. The response rate was 80% (55/69 patients) [95% confidence interval (CI): 69-88%] in the 1.0 g/kg group, 65% (22/34; CI: 48-79%) in the 0.5 g/kg group, and 92% (33/36; CI: 78-97%) in the 2.0 g/kg group. While the proportion of responders was higher with higher maintenance doses, logistic regression analysis showed that the effect on response rate was driven by a significant difference between the 0.5 and 2.0 g/kg groups, whereas the response rates in the 0.5 and 2.0 g/kg groups did not differ significantly from the 1.0 g/kg group. Fifty-six per cent of all patients had an adjusted Inflammatory Neuropathy Cause and Treatment score improvement 3 weeks after the induction dose alone. Treatment-related adverse events were reported in 16 (45.7%), 32 (46.4%) and 20 (52.6%) patients in the 0.5, 1.0 and 2.0 g/kg dose groups, respectively. The most common adverse reaction was headache. There were no treatment-related deaths. Intravenous immunoglobulin (1.0 g/kg) was efficacious and well tolerated as maintenance treatment for patients with chronic inflammatory demyelinating polyneuropathy. Further studies of different maintenance doses of intravenous immunoglobulin in chronic inflammatory demyelinating polyneuropathy are warranted.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0100.001

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 head0.019
GPT teacher head0.282
Teacher spread0.263 · 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 designRandomized trial
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

Citations41
Published2021
Admission routes1
Has abstractyes

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