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Background: Medical students need to be prepared for various situations in clinical decision-making that cannot be systematically trained with real patients without risking their health or integrity. To target system-related limitations of actor-based training, digital learning methods are increasingly used in medical education, with virtual reality (VR)- training seeming to have high potential. Virtually generated training scenarios allow repetitive training of highly relevant clinical skills within a protected, realistic learning environment. Thanks to Artificial Intelligence (AI), face-to-face interaction with virtual agents is feasible. Combining this technology with VR-simulations offers a new way of situated context-based, first-person training for medical students.Project goal and method: The authors’ aim is to develop a modular digital training platform for medical education with virtual, interactable agents and to integrate this platform into the medical curriculum. The medical tr.AI.ning platform will provide veridical simulation of clinical scenarios with virtual patients, augmented with highly realistic medical pathologies within a customizable, realistic situational context. Medical tr.AI.ning is scaled to four complementary developmental steps with different scenarios that can be used separately and so each outcome can successively be integrated early within the project. Every step has its own focus (visual, movement, communication, combination) and extends an author toolbox through its modularity. The modules of each step will be specified and designed together with medical didactics experts. Perspective: To ensure constant improvement of user experience, realism, and medical validity, the authors will perform regular iterative evaluation rounds.Furthermore, integration of medical tr.AI.ning into the medical curriculum will enable long-term and large-scale detection of benefits and limitations of this approach, providing enhanced alternative teaching paradigms for VR technology.

In this multicenter survey (July 07 to August 08, 2020) in pediatric oncology centers (POCs) belonging to the German Society for Pediatric Oncology and Hematology (GPOH), 36 POCs participated (response rate 70.6%). Home schooling practice was judged as satisfying by 79% prior to and by 38% during the pandemic (=0.0007). The individual risk of a SARS-CoV-2 infection and the risk of transmission to other patients/caregivers were arguments against attendance. Most POCs recommended regular social participation/school attendance after the end of intensive therapy. 81% stated that persisting restrictions result in serious negative psychosocial consequences for the patients and their families. In-hospital school education, home schooling and re-attendance of school and kindergarten among pediatric cancer patients have suffered a severe setback during the SARS-CoV-2 pandemic. Continuous communication and education concerning protective measures as well as an individual risk assessment are required to avoid the detrimental exclusion of pediatric oncology patients from kindergarten and school.

Pediatric patients receiving conventional chemotherapy for malignant disease face an increased risk of bloodstream infection (BSI). Since BSI may represent an acute life-threatening event in patients with profound immunosuppression, and show further negative impact on quality of life and anticancer treatment, the prevention of BSI is of paramount importance to improve and guarantee patients’ safety during intensive treatment. The great majority of all pediatric cancer patients (about 85%) have a long-term central venous access catheter in use (type Broviac or Port; CVAD). Referring to the current surveillance definitions a significant proportion of all BSI in pediatric patients with febrile neutropenia is categorized as CVAD- BSI. This state of the art review summarizes the epidemiology and the distinct pathogen profile of BSI in pediatric cancer patients from the perspective of infection surveillance. Problems in executing the current surveillance definition in this patient population are discussed and a new concept for the surveillance of BSI in pediatric cancer patients is outlined.

Background: During intensive chemotherapy, bloodstream infection (BSI) represents an important complication in paediatric cancer patients. Most patients carry a long-term central venous access device (CVAD). Improved maintenance care of these vascular catheters may decrease the risk of BSI.Methods: Intervention study (adapted CVAD prevention protocol) with two observation periods (P1: 09-2009 until 05-2011; P2: 09-2011 until 05-2013); prospective surveillance of all laboratory confirmed BSIs. In P2, ready to use sterile NaCl 0.9% syringes were used for CVAD flushing and octenidine/isopropanol for the disinfection of catheter hubs and 3-way stopcocks. Results: During P1, 84 patients were included versus 81 patients during P2. There were no significant differences between the two patient populations in terms of median age, gender, underlying malignancy or disease status (first illness or relapse). Nearly all CVADs were Broviac catheters. The median duration from implantation to removal of the CVAD was 192 days (Inter-quartile-range (IQR); 110–288 days) in P1 and 191 days (IQR; 103–270 days) in P2. 28 BSI were diagnosed in 22 patients in P1 (26% of all patients experienced at least one BSI) and 15 BSI in 12 patients in P2 (15% of all patients). The corresponding results for incidence density (ID) were 0.44 (CI95 0.29–0.62) for P1 vs. 0.34 (0.19–0.53) BSI per 100 inpatient days for P2 and for incidence rate (IR) 7.76 (5.16–10.86) in P1 vs. 4.75 (2.66–7.43) BSI per 1,000 inpatient CVAD utilization days. In P1, 9 BSI were caused by CoNS vs. only 2 in P2 (IR 2.49; CI95 0.17–4.17 vs. 0.63; CI95 0.08–1.72). In P1 two BSI (7%) lead to early removal of the device. During P2 one CVAD was prematurely removed due to a Broviac-related BSI (6.7%).Conclusion: The preventive protocol investigated in this study led to a reduction of BSI in paediatric cancer patients. This result was clinically relevant but – due to insufficient power in a single centre observation – the difference did not reach statistical significance. The most pronounced trend in BSI reduction was observed for CoNS infections. Thus, improving maintenance care of the CVAD may result in lower CVAD-linked infection rates. The higher acquisition cost of the ready to use NaCl 0.9% flushing syringes and octenidine/propanol hub disinfection were probably balanced by cost savings in the intervention period.

Cancer exhibits substantial heterogeneity, manifesting as distinct morphological and molecular variations across tumors, which frequently undermines the efficacy of conventional oncological treatments. Developments in multiomics and sequencing technologies have paved the way for unraveling this heterogeneity. Nevertheless, the complexity of the data gathered from these methods cannot be fully interpreted through multimodal data analysis alone. Mathematical modeling plays a crucial role in delineating the underlying mechanisms to explain sources of heterogeneity using patient-specific data. Intra-tumoral diversity necessitates the development of precision oncology therapies utilizing multiphysics, multiscale mathematical models for cancer. This review discusses recent advancements in computational methodologies for precision oncology, highlighting the potential of cancer digital twins to enhance patient-specific decision-making in clinical settings. We review computational efforts in building patient-informed cellular and tissue-level models for cancer and propose a computational framework that utilizes agent-based modeling as an effective conduit to integrate cancer systems models that encode signaling at the cellular scale with digital twin models that predict tissue-level response in a tumor microenvironment customized to patient information. Furthermore, we discuss machine learning approaches to building surrogates for these complex mathematical models. These surrogates can potentially be used to conduct sensitivity analysis, verification, validation, and uncertainty quantification, which is especially important for tumor studies due to their dynamic nature. [ABSTRACT FROM AUTHOR]

The massive amount of human biological, imaging, and clinical data produced by multiple and diverse sources necessitates integrative modeling approaches able to summarize all this information into answers to specific clinical questions. In this paper, we present a hypermodeling scheme able to combine models of diverse cancer aspects regardless of their underlying method or scale. Describing tissue-scale cancer cell proliferation, biomechanical tumor growth, nutrient transport, genomic-scale aberrant cancer cell metabolism, and cell-signaling pathways that regulate the cellular response to therapy, the hypermodel integrates mutation, miRNA expression, imaging, and clinical data. The constituting hypomodels, as well as their orchestration and links, are described. Two specific cancer types, Wilms tumor (nephroblastoma) and non-small cell lung cancer, are addressed as proof-of-concept study cases. Personalized simulations of the actual anatomy of a patient have been conducted. The hypermodel has also been applied to predict tumor control after radiotherapy and the relationship between tumor proliferative activity and response to neoadjuvant chemotherapy. Our innovative hypermodel holds promise as a digital twin-based clinical decision support system and as the core of future in silico trial platforms, although additional retrospective adaptation and validation are necessary. [ABSTRACT FROM AUTHOR]

Introduction: Introduction: Renal cell carcinoma (RCC) is a very rare pediatric renal tumor. Robust evidence to guide treatment is lacking and knowledge on targeted therapies and immunotherapy is mainly based on adult studies. Currently, the International Society of Pediatric Oncology–Renal Tumor Study Group (SIOP-RTSG) 2016 UMBRELLA protocol recommends sunitinib for metastatic or unresectable RCC. Methods: This retrospective study describes the effects of tyrosine kinase inhibitors (TKI), anti-programmed cell death 1 (PD-(L)1) monoclonal antibodies, and immunotherapeutic regimens in advanced-stage and relapsed pediatric RCC. Results: Of the 31 identified patients (0–18 years) with histologically proven RCC, 3/31 presented with TNM stage I/II, 8/31 with TNM stage III, and 20/31 with TNM stage IV at diagnosis. The majority were diagnosed with translocation type RCC (MiT-RCC) (21/31) and the remaining patients mainly presented with papillary or clear-cell RCC. Treatment in a neoadjuvant or adjuvant setting, or upon relapse or progression, included mono- or combination therapy with a large variety of drugs, illustrating center specific choices in most patients. Sunitinib was often administered as first choice and predominantly resulted in stable disease (53%). Other frequently used drugs included axitinib, cabozantinib, sorafenib, and nivolumab; however, no treatment seemed more promising than sunitinib. Overall, 15/31 patients died of disease, 12/31 are alive with active disease, and only four patients had a complete response. The sample size and heterogeneity of this cohort only allowed descriptive statistical analysis. Conclusion: This study provides an overview of a unique series of clinical and treatment characteristics of pediatric patients with RCC treated with targeted therapies. [ABSTRACT FROM AUTHOR]

Background: Acute graft-versus-host disease (aGvHD) is a major cause of death for patientsfollowing allogeneic hematopoietic stem cell transplantation (HSCT). Effective management of moderate to severe aGvHD remains challenging despite recent advances in HSCT, emphasizing the importance of prophylaxis and risk factor identification. Methods: In this study, we analyzed data from 1479 adults who underwent HSCT between 2005 and 2017 to investigate the effects of aGvHD prophylaxis and time-dependent risk factors on the development of grades II–IV aGvHD within 100days post-HSCT. Results: Using a dynamic longitudinal time-to-event model, we observed a nonmonotonic baseline hazard overtime with a low hazard during the first few days and a maximum hazard at day 17, described by Bateman function with a mean transit time of approximately 11days. Multivariable analysis revealed significant time-dependent effects of white blood cell counts and cyclosporine A exposure as well as static effects of female donors for male recipients, patients with matched related donors, conditioning regimen consisting of fludarabine plus total body irradiation, and patient age in recipients of grafts from related donors on the risk to develop grades II–IV aGvHD. Additionally, we found that higher cumulative hazard on day 7 after allo-HSCT are associated with an increased incidence of grades II–IV aGvHD within 100days indicating that an individual assessment of the cumulative hazard on day 7 could potentially serve as valuable predictor for ater grades II–IV aGvHD development. Using the final model, stochastic simulations were performed to explore covariate effects on the cumulative incidence over time and to estimate risk ratios. Conclusion: Overall, the presented model showed good descriptive and predictive performance and provides valuable insights into the interplay of multiple static and time-dependent risk factors for the prediction of aGvHD. [ABSTRACT FROM AUTHOR]