Notice bibliographique
Résumé
This editorial refers to the article ‘Enthesitis in patients with psoriatic arthritis treated with secukinumab or adalimumab: a post hoc analysis of the EXCEED study’, published by Kaeley et al., 2023; https://doi.org/10.1093/rheumatology/kead181. Enthesis is a remarkable tissue that is differentiated to transmit the tensile load from the muscle to the bone. The inflammatory changes within the entheses, enthesitis, is a key feature of PsA and likely the initial event during the disease course. In this issue, Kaeley et al. [1] published the post hoc analysis of the EXCEED trial (NCT02745080), where the focus has been enthesitis, distribution of enthesitis according to different indices, differential efficacy of secukinumab and adalimumab according to the anatomical sites of enthesitis and time to resolution. We would like to congratulate the authors for looking at the enthesitis data with such a detailed approach. With the lack of histological information due to the potential risk of rupture with entheseal biopsies, our understanding of the course of enthesitis at different sites is severely limited. Therefore, responsiveness data from clinical trials give us a rare opportunity to examine entheses at discrete locations. Most clinical trials identify PsA patients for inclusion based on their articular disease, mostly polyarticular, with other domains being represented only by chance [2]. In the Efficacy of Secukinumab Compared to Adalimumab in Patients With Psoriatic Arthritis (EXCEED) trial, the prevalence of enthesitis is reported to be 58.5% with the Leeds Enthesitis Index (LEI) and 74.1% with the Spondyloarthritis Research Consortium of Canada (SPARCC) index [1]. A feature that is not frequently reported in the literature is the site distribution of enthesitis. In the EXCEED trial, all SPARCC sites had enthesitis with similar rates, ranging from 24 to 39%. These anatomical sites responded to both secukinumab and adalimumab to a similar extent, with complete resolution of enthesitis being in the range of 68–88.7% at week 12. The highest response was seen in the plantar fascia and the lowest being in the medial femoral condyle entheses. How can we explain the placebo response in enthesitis and at the same time non-response to secukinumab and adalimumab? The elephant in the room is the way we assess enthesitis. Unlike synovitis, enthesitis is a physical examination feature that is judged fully based on the patients’ pain response to the applied pressure. There is little to no objectivity to the examination. How pain is triggered in entheseal sites is not fully understood. Some possible mechanisms have elegantly been discussed in a review by De Lorenzis et al. [3]. Immune-mediated inflammation is one mechanism leading to pain, and peripheral pain sensitization is another key mechanism. The assessment of enthesitis requires a good knowledge of anatomy and ensuring that the pressure is applied exactly at the tendon or ligament insertion. The proximity of the fibromyalgia points and the entheses sites is a concern that impacts the accuracy of enthesitis assessment [4, 5]. Reflecting that, a study by Sapsford et al. [6] examined the SPARCC and LEI enthesitis sites in PsA patients with ultrasound. When analyses were restricted to PsA cases without concurrent fibromyalgia (n = 78), ultrasound inflammation correlated closely with both LEI (r = 0.48) and SPARCC (r = 0.62) (P < 0.0001 for both). However, for patients with PsA and fibromyalgia, there was no correlation between the clinical enthesitis indices and ultrasound (LEI: r = 0.01; SPARCC: r = 0.13). These observations support that if there is more than one pain mechanisms involved, the physical examination loses the accuracy of detecting enthesitis. This would be applicable to both the standard practice and clinical trials. Patients who are non-responders may be the ones that do not really have inflammatory enthesitis. The anatomical location of the entheses also impacts the accuracy of the physical examination. In a study where the aim was to investigate the relationship between physical examination and sonographic features of enthesitis in 2298 entheses, we found that patients with clinical enthesitis of the Achilles and patellar tendon origin had more corresponding abnormalities on ultrasound [7]. In contrast, the physical examination of the distal patellar tendon insertion and plantar aponeurosis were uncoupled from the ultrasound findings. This would suggest that the response rates for enthesitis reported in clinical trials may be more accurate for some sites (such as the Achilles) than others (plantar aponeurosis). Until our assessment for enthesitis gets better, seeing the response data separately for each of the entheses, as done by Kaeley et al. [1], helps us consider the limitations of our assessment for individual sites. The enthesitis scoring methods focus on only a small portion of existing entheses for understandable reasons. Specifically, as healthcare providers we tend to focus on large entheses, as we feel more confident about our own assessment skills. Should we be ignoring the entheses that are not included in the scoring methods? Are all entheses the same? How about the small entheses? The hands and feet are the most frequently involved anatomical sites in PsA for the ‘peripheral joints’ domain. The anatomy of the hands and feet is quite complex. In addition to the three joints in a single digit, there are multiple anatomical entheses (two for each extensor tendon, two for each flexor tendon, origins and insertions of two collateral ligaments for each joint, joint capsule insertions) in addition to the functional entheses, the pulleys (Fig. 1). These and some other adjacent structures work harmoniously to maintain fine motor skills. Our group has previously looked at whether physical examination can differentiate joint, tendon and entheseal abnormalities in PsA patients with a painful hand, using ultrasound as the gold standard [8]. We found that there was no agreement between the physical examination and ultrasound to differentiate the lesions of each of these. This suggests that the lack of response in a PIP joint with advanced therapy may be due to the real pathology being enthesitis of the extensor tendon insertion and not PIP joint inflammation (enthesitis domain vs synovitis domain of PsA). The representation of the small entheses of the hands. The insertions of the tendons and the collateral ligaments are shown as large green dots and joint capsule insertions are represented by small green dots. FDp: flexor digitorum profundus; FDs: flexor digitorum superficialis; ET-cb: extensor digitorum tendon central band; ET-lb: extensor digitorum tendon lateral band; CL: collateral ligament; *pulleys (functional entheses); **joint capsule In a disease as heterogeneous as PsA, the devil is in the details. Harmonizing the assessment tools and accurate evaluation of the underlying pathologies at baseline will give us an opportunity to understand the response of each of these lesions to treatments with different mechanisms of action. Detailed analysis from a head-to-head randomized clinical trial as published in this issue helps to improve our understanding of PsA pathogenesis. No new data were generated or analysed in support of this article. Data from the article by Kaeley et al. [1] are available within the manuscript and its supplementary material. Dr Aydin drafted the article and Dr Deodhar revised it critically for important intellectual content. Both authors approved the version to be published. No specific funding was received from any bodies in the public, commercial or not-for-profit sectors to carry out the work described in this article. Disclosure statement: S.Z.A. has received consulting and advisory boards fees and research grants from AbbVie, Eli Lilly, Janssen, Novartis, Pfizer and UCB. A.D. has received consulting and advisory board fees from AbbVie, Amgen, Aurinia, Bristol Myers Squibb, Eli Lilly, Janssen, MoonLake Immunotherapeutics, Novartis, Pfizer and UCB and research grants from AbbVie, Bristol Myers Squibb, Celgene, Eli Lilly, Galvani, Janssen, MoonLake, Novartis, Pfizer and UCB.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,009 | 0,033 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,005 | 0,016 |
| Communication savante | 0,009 | 0,019 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,006 | 0,011 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,019 | 0,006 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».