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Enregistrement W4402513318 · doi:10.1097/io9.0000000000000085

Pembrolizumab: a beacon of hope for clear-cell renal-cell carcinoma patients post-nephrectomy

2024· article· en· W4402513318 sur OpenAlexaff
Ayush Anand, Godfrey T. Banda, Prakasini Satapathy, Rakesh Kumar Sharma, Divya Sharma, Mithhil Arora, Mahalaqua Nazli Khatib, Shilpa Gaidhane, Quazi Syed Zahiruddin, Sarvesh Rustagi

Notice bibliographique

RevueInternational Journal of Surgery Open · 2024
Typearticle
Langueen
DomaineMedicine
ThématiqueRenal cell carcinoma treatment
Établissements canadiensImpact
Organismes subventionnairesnon disponible
Mots-clésMedicineRenal cell carcinomaNephrectomyPembrolizumabInternal medicineOncologyUrologyKidneyCancerImmunotherapy

Résumé

récupéré en direct d'OpenAlex

Dear Editor, Clear-cell renal-cell carcinoma (ccRCC) is the most common type of renal cancer1,2. In ccRCC, there is a high risk of metastasis and recurrence1,3. Extensive research is being done to develop novel therapies for ccRCC. A shining example of such progress is the development and subsequent approval of adjuvant pembrolizumab (Fig. 1) for the adjuvant treatment of clear-cell renal-cell carcinoma4. This innovative therapy, as demonstrated in the pivotal KEYNOTE-564 trial, offers not just a lifeline but a tangible improvement in survival outcomes for patients who have undergone surgery for this aggressive cancer5.Figure 1: Prescribing information of adjuvant pembrolizumab. [Created with BioRender.com].Pembrolizumab, an immune checkpoint inhibitor that promotes the body’s immune response against cancer cells, has shown promising results in the recent phase 3, double-blind, randomized, placebo-controlled trial involving 994 participants at increased risk of recurrence post-surgery4. Those treated with 200 mg pembrolizumab for up to 17 cycles experienced a significant improvement in both disease-free and overall survival compared to those who received a placebo4. Specifically, the estimated overall survival rate at 48 months was an impressive 91.2% in the pembrolizumab group versus 86.0% in the placebo group. The success of pembrolizumab in extending survival in renal-cell carcinoma patients post-surgery signifies a notable advancement in oncology. It represents the ongoing shift towards precision medicine, where treatments are increasingly based on individual patient characteristics and the genetic makeup of their tumors. Furthermore, the trial’s findings could potentially set the stage for exploring the efficacy of pembrolizumab in other types of cancer, thereby broadening its applicability and benefit to a larger cohort of patients. While the efficacy of pembrolizumab paints a hopeful picture, it is accompanied by an increased incidence of serious adverse events. About one in five patients treated with pembrolizumab experienced serious side effects compared to approximately one in ten receiving the placebo4. These figures highlight a considerable trade-off between the benefits of extended survival and the risk of severe side effects. This underscores the necessity for oncologists and patients to engage in thorough discussions about the potential risks and benefits of this treatment, ensuring that the decision to proceed with pembrolizumab is well-informed and tailored to the individual patient’s health status and treatment preferences. In conclusion, pembrolizumab has cemented its role as a cornerstone of therapy for patients with clear-cell renal-cell carcinoma after surgery. While the increased risk of adverse events cannot be overlooked, the substantial survival benefit underscores the importance of this therapeutic breakthrough. As we advance, continuous research and patient monitoring will be paramount in optimizing the use of pembrolizumab, aiming for maximal benefit while mitigating risks. In the grand scheme of cancer treatment, pembrolizumab stands out as a beacon of hope, guiding us toward a future where cancer can be confronted more effectively and with renewed vigor. Ethical approval Not applicable. Consent Not applicable. Source of funding Not applicable. Author contribution A.A.: conceptualization, project administration, supervision, validation, writing—original draft and writing—review and editing. G.T.B.: validation, writing—original draft and writing—review and editing. P.S.: supervision, validation, writing—review and editing. R.K.S.: supervision, validation, writing—review and editing. D.S.: supervision, validation, writing—review and editing. M.A.: supervision, validation, writing—review and editing. M.N.K.: supervision, validation, writing—review and editing. S.G.: supervision, validation, writing—review and editing. Q.S.Z.: supervision, validation, writing—review and editing. S.R.: supervision, validation, writing—review and editing. Conflicts of interest disclosure The authors declare no conflicts of interests. Research registration unique identifying number (UIN) Not applicable. Guarantor Ayush Anand. Data availability statement Not applicable. Provenance and peer review Not commissioned, externally peer-reviewed.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,321
Score d'incertitude au seuil0,675

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,037
Tête enseignante GPT0,304
Écart entre enseignants0,267 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2024
Routes d'admission1
Résumé présentoui

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