ArticleEJNMMI research2016
Article in EJNMMI research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.
- Systematic Review: Targeted Molecular Imaging of Angiogenesis and Its Mediators in Rheumatoid Arthritis.International journal of molecular sciences · 2022Pooled it
- A Review of Advances in Molecular Imaging of Rheumatoid Arthritis: From In Vitro to Clinic Applications Using Radiolabeled Targeting Vectors with Technetium-99m.Life (Basel, Switzerland) · 2024Review
- Biomarkers and Predictive Factors for Treatment Response to Tumor Necrosis Factor-α Inhibitors in Patients with Psoriasis.Journal of clinical medicine · 2023Article
- Use of Imaging in Axial Spondyloarthritis for Diagnosis and Assessment of Disease Remission in the Year 2022.Current rheumatology reports · 2022Review
- Certolizumab pegol treatment for leg ulcers due to rheumatoid vasculitis.JAAD case reports · 2021Article
- PET/CT Imaging of Human TNFα Using [Molecular imaging and biology · 2020Article
- Immuno-Imaging to Predict Treatment Response in Infection, Inflammation and Oncology.Journal of clinical medicine · 2019Review
- Properties of Fluorescent Far-Red Anti-TNF Nanobodies.Antibodies (Basel, Switzerland) · 2018Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundBiologicals directed against tumour necrosis factor (TNF) have proven their efficacy in the treatment of spondyloarthritis and rheumatoid arthritis. We present a radiolabelling method for certolizumab pegol (CZP), a commercially available humanized Fab'-fragment directed against TNF. A biodistribution and dosimetry study was conducted. Tc-S-HYNIC CZP was synthesized. The in vitro TNF neutralizing activity was tested by exposing L929s-cells to various concentrations 99mTc-S-HYNIC CZP and measuring TNF-induced cytotoxicity. For biodistribution and dosimetry, WB images and blood and urine sampling were performed up to 24 h pi. Cumulative activities were estimated using mono-exponential fitting, and organ doses were estimated using OLINDA/EXM. The effective dose was calculated using the International Commission on Radiological Protection 103 recommendations. The uptake of the tracer in the peripheral joints was assessed visually and semiquantitatively.
resultsIn vitro tests showed blocking of TNF cytotoxicity by the
conclusionsWe present a radiolabelling technique for CZP, a Fab'-fragment directed against TNF and currently used as a therapeutic agent in rheumatology. An effective dose of 6.1 mSv (SD 0.9) was estimated. We confirmed the uptake of this new radiopharmaceutical in clinically affected peripheral joints.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.