FOSP 50 Anos

Este vídeo comemorativo destaca nossa história de excelência e conquistas. Uma homenagem inspiradora à nossa jornada de meio século de sucesso.

Developmental surveillance and screening practices in a pediatric oncology clinic: Initial progress of a quality improvement study.

BACKGROUND: Pediatric cancer patients' oncology teams regularly take on a primary care role, but due to the urgent nature of cancer treatment, developmental screenings may be deprioritized. This leaves patients at risk of developmental diagnoses and referrals being delayed. AIMS: Clarify the current developmental surveillance and screening practices of one pediatric oncology team. MATERIALS AND METHODS: Researchers reviewed charts for patients (n = 66) seen at a pediatric oncology clinic in a suburban academic medical center to determine engagement in developmental screening (including functioning around related areas such as speech, neurocognition, etc.) and referrals for care in these areas. RESULTS: Developmental histories were collected from all patients through admission history and physical examination (H&P), but there was no routinized follow-up. Physicians did not conduct regular developmental screening per American Academy of Pediatrics guidelines for any patients but identified n = 3 patients with needs while the psychology team routinely surveilled all patients seen during this time (n = 41) and identified n = 18 patients as having delays. DISCUSSION: Physicians did not routinely screen for development needs beyond H&P and were inconsistent in developmental follow-up/referrals. Integrated psychologists were key in generating referrals for developmental-based care. However, many oncology patients were not seen by psychologists quickly or at all, creating a significant gap in care during a crucial developmental period. CONCLUSION: The case is made for further routinization of ongoing developmental screening in pediatric oncology care.

Artificial intelligence- image learning and its applications in neurooncology: a review.

Image learning involves using artificial intelligence (AI) to analyse radiological images. Various machine and deeplearning- based techniques have been employed to process images and extract relevant features. These can later be used to detect tumours early and predict their survival based on their grading and classification. Radiomics is now also used to predict genetic mutations and differentiate between tumour progression and treatment-related side effects. These were once completely dependent on invasive procedures like biopsy and histopathology. The use and feasibility of these techniques are now widely being explored in neurooncology to devise more accurate management plans and limit morbidity and mortality. Hence, the future of oncology lies in the exploration of AI-based image learning techniques, which can be applied to formulate management plans based on less invasive diagnostic techniques, earlier detection of tumours, and prediction of prognosis based on radiomic features. In this review, we discuss some of these applications of image learning in current medical dynamics.

Effects of on-site Supportive Communication Training (On-site SCT) on doctor-patient communication in oncology: Study protocol of a randomized, controlled mixed-methods trial.

BACKGROUND: The quality of communication in oncology significantly impacts patients' health outcomes, as poor communication increases the risk of unnecessary treatment, inadequate pain relief, higher anxiety levels, and acute hospitalizations. Additionally, ineffective communication skills training (CST) is associated with stress, low job satisfaction, and burnout among doctors working in oncology. While acknowledging the importance of effective communication, the specific features of successful CST remain uncertain. Role-play and recorded consultations with direct feedback appear promising for CST but may be time-consuming and face challenges in transferring acquired skills to clinical contexts. Our aim is to bridge this gap by proposing a novel approach: On-site Supportive Communication Training (On-site SCT). The concept integrates knowledge from previous studies but represents the first randomized controlled trial employing actual doctor-patient interactions during CST. METHODS: This randomized multicenter trial is conducted at three departments of oncology in Denmark. Doctors are randomized 1:1 to the intervention and control groups. The intervention group involves participation in three full days of On-site SCT facilitated by a trained psychologist. On-site SCT focuses on imparting communication techniques, establishing a reflective learning environment, and offering emotional support with a compassionate mindset. The primary endpoint is the change in percentage of items rated "excellent" by the patients in the validated 15-item questionnaire Communication Assessment Tool. The secondary endpoints are changes in doctors' ratings of self-efficacy in health communication, burnout, and job satisfaction measured by validated questionnaires. Qualitative interviews will be conducted with the doctors after the intervention to evaluate its relevance, feasibility, and working mechanisms. Doctors have been actively recruited during summer/autumn 2023. Baseline questionnaires from patients have been collected. Recruitment of new patients for evaluation questionnaires is scheduled for Q1-Q2 2024. DISCUSSION: This trial aims to quantify On-site SCT efficacy. If it significantly impacts patients/doctors, it can be a scalable CST concept for clinical practice. Additionally, qualitative interviews will reveal doctors' insight into the most comprehensible curriculum parts. TRIAL REGISTRATION: April 2023 - ClinicalTrials.gov (NCT05842083). April 2023 - The Research Ethics Committee at the University of Southern Denmark (23/19397).

Navigating the Complexities of Artificial Intelligence-Enabled Real-World Data Collection for Oncology Pharmacovigilance.

This new editorial discusses the promise and challenges of successful integration of natural language processing methods into electronic health records for timely, robust, and fair oncology pharmacovigilance.

[A look into the neighboring discipline: eHealth in oncology]. / Ein Blick in die Nachbardisziplin: eHealth in der Onkologie.

Digitalization is dramatically changing the entire healthcare system. Keywords such as artificial intelligence, electronic patient files (ePA), electronic prescriptions (eRp), telemedicine, wearables, augmented reality and digital health applications (DiGA) represent the digital transformation that is already taking place. Digital becomes real! This article outlines the state of research and development, current plans and ongoing uses of digital tools in oncology in the first half of 2024. The possibilities for using artificial intelligence and the use of DiGAs in oncology are presented in more detail in this overview according to their stage of development as they already show a noticeable benefit in oncology.

Geriatric Oncology: A 5-Year Strategic Plan.

The increasing rate of the older adult population across the world over the next 20 years along with significant developments in the treatment of oncology will require a more granular understanding of the older adult population with cancer. The ASCO Geriatric Oncology Community of Practice (COP) herein provides an outline for the field along three fundamental pillars: education, research, and implementation, inspired by ASCO's 5-Year Strategic Plan. Fundamental to improving the understanding of geriatric oncology is research that intentionally includes older adults with clinically meaningful data supported by grants across all career stages. The increased knowledge base that is developed should be conveyed among health care providers through core competencies for trainees and continuing education for practicing oncologists. ASCO's infrastructure can serve as a resource for fellowship programs interested in acquiring geriatric oncology content and provide recommendations on developing training pathways for fellows interested in pursuing formalized training in geriatrics. Incorporating geriatric oncology into everyday practice is challenging as each clinical setting has unique operational workflows with barriers that limit implementation of valuable geriatric tools such as Geriatric Assessment. Partnerships among experts in quality improvement from the ASCO Geriatric Oncology COP, the Cancer and Aging Research Group, and ASCO's Quality Training Program can provide one such venue for implementation of geriatric oncology through a structured support mechanism. The field of geriatric oncology must continue to find innovative strategies using existing resources and partnerships to address the pressing needs of the older adult population with cancer to improve patient outcomes.

Applications of artificial intelligence in urologic oncology.

PURPOSE: With the recent rising interest in artificial intelligence (AI) in medicine, many studies have explored the potential and usefulness of AI in urological diseases. This study aimed to comprehensively review recent applications of AI in urologic oncology. MATERIALS AND METHODS: We searched the PubMed-MEDLINE databases for articles in English on machine learning (ML) and deep learning (DL) models related to general surgery and prostate, bladder, and kidney cancer. The search terms were a combination of keywords, including both "urology" and "artificial intelligence" with one of the following: "machine learning," "deep learning," "neural network," "renal cell carcinoma," "kidney cancer," "urothelial carcinoma," "bladder cancer," "prostate cancer," and "robotic surgery." RESULTS: A total of 58 articles were included. The studies on prostate cancer were related to grade prediction, improved diagnosis, and predicting outcomes and recurrence. The studies on bladder cancer mainly used radiomics to identify aggressive tumors and predict treatment outcomes, recurrence, and survival rates. Most studies on the application of ML and DL in kidney cancer were focused on the differentiation of benign and malignant tumors as well as prediction of their grade and subtype. Most studies suggested that methods using AI may be better than or similar to existing traditional methods. CONCLUSIONS: AI technology is actively being investigated in the field of urological cancers as a tool for diagnosis, prediction of prognosis, and decision-making and is expected to be applied in additional clinical areas soon. Despite technological, legal, and ethical concerns, AI will change the landscape of urological cancer management.

Premarket Evidence and Postmarketing Requirements for Real-Time Oncology Review Indication Approvals.

This cross-sectional study evaluates the use of the US Food and Drug Administration's Real-Time Oncology Review (RTOR) program in confirming the effectiveness of cancer drugs.

Improving routine use of clinical pathway decision support through integration of an EHR with a clinical library resource designed to provide evidence-based guidance within oncology workflows.

BACKGROUND: The rapid evolution, complexity, and specialization of oncology treatment makes it challenging for physicians to provide care based on the latest and best evidence. We hypothesized that physicians would use evidence-based trusted care pathways if they were easy to use and integrated into clinical workflow at the point of care. METHODS: Within a large integrated care delivery system, we assembled clinical experts to define and update drug treatment pathways, encoded them as flowcharts in an online library integrated with the electronic medical record, communicated expectations that clinicians would use these pathways for every eligible patient, and combined data from multiple sources to understand usage over time. RESULTS: We were able to achieve > 75% utilization of eligible protocols ordered through these pathways within two years, with > 90% of individual oncologists having consulted the pathway at least once, despite no requirements or external incentives associated with pathway usage. Feedback from users contributed to improvements and updates to the guidance. CONCLUSIONS: By making our clinical decision support easily accessible and actionable, we find that we have made considerable progress toward our goal of having physicians consult the latest evidence in their treatment decisions.

Virtual consultations: the experience of oncology and palliative care healthcare professionals.

OBJECTIVES: To maintain continuity of care during the Covid-19 pandemic, virtual consultations (VC) became the mainstay of patient-healthcare practitioner interactions. The aim of this study was to explore the views of oncology and palliative care healthcare professionals (HCPs) regarding the medium of VC. METHOD: A cross sectional mixed methodology observational study of oncology and palliative care HCPs, analysed via an inductive thematic approach. This was undertaken in accordance with relevant guidelines and regulations. RESULTS: 87 surveys were completed. Three master themes were identified. Personal, professional, and familial factors including patient age, illness and VC skillset all influenced practitioner's experience of VC. Relationships and connection were highlighted by survey respondents as important influences, with a perception that VC could reduce usual relationships with patients, compared to previous face-to-face consults. There was a perceived loss in these domains with VC. Sharing bad news and having challenging conversations was seen as particularly difficult via VC. Many survey respondents emphasized that they preferred to have first time consultations face-to-face, and not virtually. Within the domain of logistical and practical implications reduced travel and increased accessibility were seen as a significant benefit of VC. The inability to examine patients and concerns regarding missing clinical signs was emphasised as a significant worry, alongside the challenges faced with occasionally failing technology. CONCLUSION: VC were felt to have a role for those patients who are already known to professionals, where there was an established relationship. VC for difficult discussions and for unstable patients were felt to be inadequate. Triaging patient suitability prior to offering VC, with emphasis on the importance of patient choice, was seen as a priority in this new era of VC.

Controversies in orthopaedic oncology.

Chondrosarcoma is the second most common surgically treated primary bone sarcoma. Despite a large number of scientific papers in the literature, there is still significant controversy about diagnostics, treatment of the primary tumour, subtypes, and complications. Therefore, consensus on its day-to-day treatment decisions is needed. In January 2024, the Birmingham Orthopaedic Oncology Meeting (BOOM) attempted to gain global consensus from 300 delegates from over 50 countries. The meeting focused on these critical areas and aimed to generate consensus statements based on evidence amalgamation and expert opinion from diverse geographical regions. In parallel, periprosthetic joint infection (PJI) in oncological reconstructions poses unique challenges due to factors such as adjuvant treatments, large exposures, and the complexity of surgery. The meeting debated two-stage revisions, antibiotic prophylaxis, managing acute PJI in patients undergoing chemotherapy, and defining the best strategies for wound management and allograft reconstruction. The objectives of the meeting extended beyond resolving immediate controversies. It sought to foster global collaboration among specialists attending the meeting, and to encourage future research projects to address unsolved dilemmas. By highlighting areas of disagreement and promoting collaborative research endeavours, this initiative aims to enhance treatment standards and potentially improve outcomes for patients globally. This paper sets out some of the controversies and questions that were debated in the meeting.

Managing Undernutrition in Pediatric Oncology: A Consensus Statement Developed Using the Delphi Method by the Polish Society for Clinical Nutrition of Children and the Polish Society of Pediatric Oncology and Hematology.

"Managing Undernutrition in Pediatric Oncology" is a collaborative consensus statement of the Polish Society for Clinical Nutrition of Children and the Polish Society of Pediatric Oncology and Hematology. The early identification and accurate management of malnutrition in children receiving anticancer treatment are crucial components to integrate into comprehensive medical care. Given the scarcity of high-quality literature on this topic, a consensus statement process was chosen over other approaches, such as guidelines, to provide comprehensive recommendations. Nevertheless, an extensive literature review using the PubMed database was conducted. The following terms, namely pediatric, childhood, cancer, pediatric oncology, malnutrition, undernutrition, refeeding syndrome, nutritional support, and nutrition, were used. The consensus was reached through the Delphi method. Comprehensive recommendations aim to identify malnutrition early in children with cancer and optimize nutritional interventions in this group. The statement underscores the importance of baseline and ongoing assessments of nutritional status and the identification of the risk factors for malnutrition development, and it presents tools that can be used to achieve these goals. This consensus statement establishes a standardized approach to nutritional support, aiming to optimize outcomes in pediatric cancer patients.

Epidemiology and Management Trends of Neuro-Oncology in Nigeria: A Systematic Review and Pooled Analysis.

OBJECTIVE: Access to neuro-oncologic care in Nigeria has grown exponentially since the first reported cases in the mid-1960s. In this systematic review and pooled analysis, we characterize the growth of neurosurgical oncology in Nigeria and build a reference paper to direct efforts to expand this field. METHODS: We performed an initial literature search of several article databases and gray literature sources. We included and subsequently screened articles published between 1962 and 2021. Several variables were extracted from each study, including the affiliated hospital, the number of patients treated, patient sex, tumor pathology, the types of imaging modalities used for diagnosis, and the interventions used for each individual. Change in these variables was assessed using Chi-squared independence tests and univariate linear regression when appropriate. RESULTS: A total of 147 studies were identified, corresponding to 5,760 patients. Over 4000 cases were reported in the past 2 decades from 21 different Nigerian institutions. The types of tumors reported have increased over time, with increasingly more patients being evaluated via computed tomography (CT) and magnetic resonance imaging (MRI). There is also a prevalent use of radiotherapy, though chemotherapy remains an underreported treatment modality. CONCLUSIONS: This study highlights key trends regarding the prevalence and management of neuro-oncologic pathologies within Nigeria. Further studies are needed to continue to learn and guide the future growth of this field in Nigeria.

High-throughput molecular assays for inclusion in personalised oncology trials - State-of-the-art and beyond.

In the last decades, the development of high-throughput molecular assays has revolutionised cancer diagnostics, paving the way for the concept of personalised cancer medicine. This progress has been driven by the introduction of such technologies through biomarker-driven oncology trials. In this review, strengths and limitations of various state-of-the-art sequencing technologies, including gene panel sequencing (DNA and RNA), whole-exome/whole-genome sequencing and whole-transcriptome sequencing, are explored, focusing on their ability to identify clinically relevant biomarkers with diagnostic, prognostic and/or predictive impact. This includes the need to assess complex biomarkers, for example microsatellite instability, tumour mutation burden and homologous recombination deficiency, to identify patients suitable for specific therapies, including immunotherapy. Furthermore, the crucial role of biomarker analysis and multidisciplinary molecular tumour boards in selecting patients for trial inclusion is discussed in relation to various trial concepts, including drug repurposing. Recognising that today's exploratory techniques will evolve into tomorrow's routine diagnostics and clinical study inclusion assays, the importance of emerging technologies for multimodal diagnostics, such as proteomics and in vivo drug sensitivity testing, is also discussed. In addition, key regulatory aspects and the importance of patient engagement in all phases of a clinical trial are described. Finally, we propose a set of recommendations for consideration when planning a new precision cancer medicine trial.

Agent-based approaches for biological modeling in oncology: A literature review.

CONTEXT: Computational modeling involves the use of computer simulations and models to study and understand real-world phenomena. Its application is particularly relevant in the study of potential interactions between biological elements. It is a promising approach to understand complex biological processes and predict their behavior under various conditions. METHODOLOGY: This paper is a review of the recent literature on computational modeling of biological systems. Our study focuses on the field of oncology and the use of artificial intelligence (AI) and, in particular, agent-based modeling (ABM), between 2010 and May 2023. RESULTS: Most of the articles studied focus on improving the diagnosis and understanding the behaviors of biological entities, with metaheuristic algorithms being the models most used. Several challenges are highlighted regarding increasing and structuring knowledge about biological systems, developing holistic models that capture multiple scales and levels of organization, reproducing emergent behaviors of biological systems, validating models with experimental data, improving computational performance of models and algorithms, and ensuring privacy and personal data protection are discussed.

In Silico Transcriptomic Expression of MSR1 in Solid Tumors Is Associated with Responses to Anti-PD1 and Anti-CTLA4 Therapies.

Immuno-oncology has gained momentum with the approval of antibodies with clinical activities in different indications. Unfortunately, for anti-PD (L)1 agents in monotherapy, only half of the treated population achieves a clinical response. For other agents, such as anti-CTLA4 antibodies, no biomarkers exist, and tolerability can limit administration. In this study, using publicly available genomic datasets, we evaluated the expression of the macrophage scavenger receptor-A (SR-A) (MSR1) and its association with a response to check-point inhibitors (CPI). MSR1 was associated with the presence of macrophages, dendritic cells (DCs) and neutrophils in most of the studied indications. The presence of MSR1 was associated with macrophages with a pro-tumoral phenotype and correlated with TIM3 expression. MSR1 predicted favorable overall survival in patients treated with anti-PD1 (HR: 0.56, FDR: 1%, p = 2.6 × 10-5), anti PD-L1 (HR: 0.66, FDR: 20%, p = 0.00098) and anti-CTLA4 (HR: 0.37, FDR: 1%, p = 4.8 × 10-5). When specifically studying skin cutaneous melanoma (SKCM), we observed similar effects for anti-PD1 (HR: 0.65, FDR: 50%, p = 0.0072) and anti-CTLA4 (HR: 0.35, FDR: 1%, p = 4.1 × 10-5). In a different dataset of SKCM patients, the expression of MSR1 predicted a clinical response to anti-CTLA4 (AUC: 0.61, p = 2.9 × 10-2). Here, we describe the expression of MSR1 in some solid tumors and its association with innate cells and M2 phenotype macrophages. Of note, the presence of MSR1 predicted a response to CPI and, particularly, anti-CTLA4 therapies in different cohorts of patients. Future studies should prospectively explore the association of MSR1 expression and the response to anti-CTLA4 strategies in solid tumors.