Scientific communication in oncology supports clinical and policy screening decisions by providing access to published, assessable, and verifiable evidence. In this context, scientific integrity is not only an ethical imperative but the foundation of evidence-based oncology practice. Recent data indicate an increase in retractions, associated with the expansion of paper mills, image manipulation, and methodological transparency limitations, a scenario that is aggravated by digital technologies and generative artificial intelligence (AI), which can both aid in scientific wording as well as facilitate the production of non-verifiable content. As a response, international editorial guidelines and Brazilian institutional initiatives have reinforced principles of transparency, accountability, and AI-usage disclaimers. The conclusion is that preventing misconduct requires a multifaceted approach, involving education in integrity, fraud detection, consistent investigation, and sanction policies, in addition to rigor in the use of references as a scientific literature tracking and auto-correction mechanism.
Erratas - “Manejo Anestésico y Control del Dolor Posoperatorio en un Paciente Pediátrico Sometido a Nefrectomía Radical Unilateral Asociada a Cavectomía: Informe de Caso”, https://doi.org/10.32635/2176-9745.RBC.2025v71n4.5151, publicado en el periódico Rev. Bras. Cancerol. 2025; 71(4): e-015151, página 2: el número de parecer 8082699 (CAAE: 94734725.4.0000.5274).
Endoscopic Sleeve Gastroplasty (ESG) is an established minimally invasive bariatric intervention, while artificial intelligence (AI) has been increasingly explored across clinical and procedural domains. However, evidence integrating AI into ESG remains limited and fragmented. To systematically identify and critically interpret the clinical, technical, and educational applications of AI in ESG. This systematic review followed PRISMA guidelines and was prospectively registered in PROSPERO. Searches were conducted in PubMed, Embase, Scopus, Web of Science, and the Cochrane Library. Original studies applying AI to ESG in clinical practice, simulation, or education were included. Given marked heterogeneity, results were synthesized qualitatively with emphasis on clinical interpretability. Five studies met inclusion criteria. A preoperative model predicting 30-day reintervention, 3.3
Erratum - “Anesthetic Management and Postoperative Pain Control in a Pediatric Patient Undergoing Unilateral Radical Nephrectomy Associated with Cavectomy: Case Report”, https://doi.org/10.32635/2176-9745. RBC.2025v71n4.5151, published on the Rev. Bras. Cancerol. 2025; 71(4): e-015151, page 2: report number 8082699 (CAAE (submission for ethical review): 94734725.4.0000.5274)
RESUMEN Objetivo: Analizar la correlación entre la intensidad de los síntomas físicos y el nivel general de bienestar en pacientes oncológicos hospitalizados que reciben cuidados paliativos. Método: Este estudio cuantitativo, descriptivo y analítico se realizó con 155 pacientes ingresados en unidades de cuidados paliativos de un hospital universitario. Se utilizaron el Cuestionario de Confort General (CCG) y la Escala de Evaluación de Síntomas de Edmonton (ESAS). Los datos se analizaron utilizando estadística descriptiva e inferencial, empleando la correlación de Pearson (p ≤ 0,05). Resultados: La evaluación de síntomas de la escala ESAS reveló una elevada carga sintomática, destacando la ansiedad, la pérdida de apetito y la depresión como los síntomas con la mayor intensidad media. Se encontró una correlación negativa estadísticamente significativa entre la intensidad de la mayoría de los síntomas y el bienestar general, lo que indica que una mayor carga de síntomas se asoció con una menor comodidad. Conclusión: El aumento de la intensidad de los síntomas físicos se asocia con una reducción significativa del bienestar general, lo que refuerza la importancia de contar con estrategias eficaces para el manejo de estos síntomas en la práctica de enfermería paliativa.
