LB778 Intravenous administration of allogeneic Mesenchymal Stromal Cells as a treatment for patients with severe generalized Recessive Dystrophic Epidermolysis Bullosa
Notice bibliographique
Résumé
LB774 Male gender is a significant risk factor for the development of multiple basal cell cancers P Batra, K Kuo, HS Chahal, K Rieger, AE Oro, AS Chang, S Li, J Tang and K SarinDermatology, Stanford University, Redwood City, CA Basal cell carcinoma (BCC) is the most common cancer in the United States. Known risk factors for BCC include age, male sex, fair skin, ultraviolet exposure, and family history. However, little is known about the risk factors for patients with multiple BCCs. We sought to investigate the relationship between the incidence of single and multiple BCCs in males and females. We performed a retrospective cohort study of BCCs biopsied between 2005 and 2015 at Stanford Hospital and Clinics. Clinical reports of BCC biopsies were obtained from electronic medical records and were parsed to obtain information on histologic subtypes, age, gender, and anatomical location. Consistent with previous studies, 60.8% of the BCCs were nodular, 21.2% were superficial, and 15.4% were infiltrative. Of 2407 individuals biopsied, 65.6% (1578 individuals) had a single BCC during this time frame, 29.6% (712 individuals) had 2-5 BCCs, 3.6% (86 individuals) had 6-10 BCCs, 0.83% (20 individuals) had 11-15 BCCs, and 0.46% (11 individuals) had 16 or more BCCs. The male to female ratio was 1.4 for single BCCs, consistent with previous studies. Interestingly, the male to female ratio significantly increased with multiple BCCs: 1.8 in individuals with 2-5 BCCs, 3.8 in individuals with 6-10 BCCs, 5.7 in individuals with 11-15 BCCs and 10.0 in those with 16 or more BCCs. Male gender was associated with a 1.36-fold increase in number of BCCs and a 1.57-fold higher likelihood of multiple BCCs based on a generalized linear model with Poisson and multinomial distributions (p < 0.0001 in both cases). Our results indicate that males are more prone to developing multiple BCCs. LB775 Fertility risk of FDA-approved systemic therapies for melanoma: Call for action for dermatologists S Xu, J Walter, AS Paller, J Choi and T Woodruff 1 Dermatology, Northwestern University, Chicago, IL and 2 Obstetrics and Gynecology, Northwestern University, Chicago, IL Melanoma disproportionately affects the young and represents the most common cancer diagnosed in patients ages 25-29 years, the age group with the highest birth rates in the United States. Oncofertility is a new interdisciplinary field addressing the reproductive needs of cancer patients facing potentially fertility-threatening treatment. Currently, there is limited available evidence for assessing fertility risk of FDA-approved melanoma therapies. We conducted a retrospective review of the FDA package insert, the European Union’s public assessment reports, the product monograph of the Health Products and Food Branch of Health Canada, and previously published reports to grade the fertility risk of FDA-approved systemic treatments for melanoma. The proposed fertility risk category system is analogous to the FDA’s A/B/C/D/X/N pregnancy risk system. For female fertility risk, 58% of the systemic treatments represent a fertility risk (Category C and D), 33% have unknown risk (Category N), and only one therapy, vemurafenib, did not show ovarian toxicity in animal studies (Category B). For males, 50% of the FDA-approved therapies had unknown fertility risk (Category N), 33% represented a fertility risk (Category C and D), and two therapies (17%) did not show testicular toxicity in animal studies (Category B). Among the eight new therapies approved after 2009, preclinical animal studies remain the only source of data on fertility risk. The additive fertility risk for combination therapies (e.g. nivoliumab/ipilimumab, vemurafenib/cobimetinib) is unknown. As cancer survivorship continues to increase, comprehensive care addressing fertility preservation, and long-term endocrine health, has become paramount. Dermatologists have an opportunity to facilitate fertility preservation discussions and referrals, and steward prospective registries with reproductive outcomes following melanoma treatments.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».