New Directions for Biologic Targets in Urothelial Carcinoma – Response
Notice bibliographique
Résumé
We thank Necchi and colleagues for their interest in our article (1). Their comments serve to highlight key challenges that we face in evaluating new treatments in advanced urothelial cancer.Necchi and colleagues presented the results of their phase II study of the angiogenesis inhibitor pazopanib in treatment-refractory urothelial cancer at the 2012 American Society of Oncology annual meeting (2). Their abstract was eloquently discussed by Dr. Feldman from the Memorial Sloan Kettering Cancer Center New York, NY (3). Despite strong preclinical support for the activity of angiogenesis inhibitors in urothelial cancer, clinically they have only had modest but inconsistent activity and cannot be considered standard of care for this disease. Further research is needed to determine whether the angiogenesis inhibitors may have a therapeutic role if used earlier in the course of the disease, whether they should be used in combination with other targeted therapies or chemotherapies, and whether there is a subset of patients who are most likely to derive benefit from these agents.Necchi and colleagues have attempted to address the latter point and should be commended for the biomarker component of their study. They showed that higher levels of IL-8 were associated with progressive disease and worse outcomes. Similar results have also been reported by Bellmunt and colleagues in a first-line study of another angiogenesis inhibitor, sunitinib, in advanced urothelial cancer. More recently, a retrospective analysis of phases II and III trials of pazopanib in metastatic renal cell cancer also showed that higher concentrations of IL-8 were associated with a shorter progression free survival (4, 5). We agree that a better understanding of both prognostic and predictive biomarkers is important and may help us to select the patients who are most likely to benefit from this class of agents. Biomarkers may also help us to identify and overcome de novo or acquired resistance mechanisms used by cancers against targeted therapies. Ultimately, well-designed clinical trials will be critical to move this field forward. Ideally, trials should have clinically meaningful endpoints, with quality of life parameters, and should attempt to incorporate correlative studies and functional imaging wherever feasible and possible.See the original Letter to the Editor, p. 2306No potential conflicts of interest were disclosed.
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 ».