Vitiligo-Like Depigmentation Induced by Anti–Programmed Death 1 Antibody
Notice bibliographique
Résumé
To the Editor, A 50-year-old woman presented to the dermatology clinic with a 3-month history of asymptomatic depigmented macules and patches on the face, neck, and chest (Fig. 1). Ten months ago, she started treatment with an anti–programmed death (PD)-1 antibody (toripalimab) for metastatic melanoma. One year ago, she was diagnosed with acral lentiginous melanoma with lymph node metastasis and received surgical treatment and high-dose interferon. Both the patient and her family had no history of vitiligo. The patient refused additional treatment for vitiligo-like depigmentation (VLD), which only affected esthetic appearance.Figure 1: Multiple depigmented macules and patches on the face and neck.Vitiligo-like depigmentation is a common cutaneous adverse effect in patients with melanoma receiving checkpoint inhibitors, and the incidence is approximately 10% to 28%, which is much more frequent than spontaneously occurring vitiligo.1 The development of VLD during treatment with checkpoint inhibitors can represent a longer survival and a higher response rate.1 Vitiligo-like depigmentation is different from vitiligo in clinical characteristics and mechanisms. Vitiligo-like depigmentation is characterized by flecked depigmented macules appearing on photoexposed areas without the Koebner phenomenon.2 In contrast to vitiligo, the patients with VLD did not report any personal or family histories of vitiligo, thyroiditis, or other autoimmune disorders.2 The level of serum CXCL10, expression of CXCR3 in skin CD8 T cells, and the levels of lesional interferon γ and tumor necrosis factor α were significantly elevated in patients with VLD.2 Their specific clinical and histological patterns on previous sun-exposed areas with a possible link between microphthalmia-associated transcription factor and the immune response reinforced by anti–PD-1.3 We herein described the first case of VLD induced by toripalimab. Toripalimab, the first domestic anti–PD-1 antibody in China, has received approval to treat melanoma in 2018 as well as nasopharyngeal carcinoma and urothelial carcinoma in 2021 and has shown preliminary efficacy in other tumors with acceptable safety profiles.4 It has different crystal structures and interactions with immune checkpoint proteins compared with other anti–PD-1 antibodies.5 Toripalimab mainly binds to the FG loop of PD-1 with an unconventionally long complementarity-determining region 3 loop of the heavy chain; the light chain complementarity-determining regions of toripalimab participate mainly in recognizing the epitopes on PD-1.4,6 Comparatively, nivolumab mainly binds to the N-terminal loop of PD-1, whereas the binding of pembrolizumab primarily involves the C′ D loop.4 Although VLD occurring in patients receiving anti–PD-1 is not life-threatening, the management of VLD deserves concern because it could dramatically impact the quality of life and social interactions. At present, there is a lack of effective treatment for VLD. Cosmetic camouflage with educational sessions may be a viable choice. Li-Wen ZhangLi-Xin FuWen-Ju WangYong-Hong LuTao Chen Department of Dermatovenereology Chengdu Second People's Hospital China [email protected]
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 | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,005 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
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 ».