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Introduction: Biliary tract cancers (BTC) are rare and aggressive neoplasms. The current management of locally advanced or unresectable BTC is primarily based on chemotherapy (CHT) alone, linked to a median overall survival (OS) of approximately 12 months. However, international guidelines still consider concurrent chemoradiation (CRT) as an alternative treatment option. This study aims to review the current evidence on "modern" CRT for primary or recurrent unresectable BTC. Materials and Methods: A comprehensive search was conducted on PubMed, Scopus, and Cochrane Library to identify relevant papers. Prospective or retrospective trials reporting outcomes after concurrent CRT of unresectable non‐metastatic, primary, or recurrent BTC were included. Only English‐written papers published between January 2010 and June 2022 were considered. Results: Seventeen papers, comprising a total of 1961 patients, were included in the analysis. Among them, 11 papers focused solely on patients with primary unresectable BTC, while two papers included patients with isolated local recurrences and four papers encompassed both settings. In terms of tumor location, 12 papers included patients with intrahepatic, extrahepatic, and hilar BTC, as well as gallbladder cancer. The median CRT dose delivered was 50.4 Gy (range: 45.0–72.6 Gy) using conventional fractionation. Concurrent CHT primarily consisted of 5‐Fluorouracil or Gemcitabine. The pooled rates of 1‐year progression‐free survival (PFS) and OS were 40.9% and 56.2%, respectively. The median 1‐ and 2‐year OS rates were 63.1% and 29.4%, respectively. Grade ≥3 acute gastrointestinal toxicity ranged from 5.6% to 22.2% (median: 10.9%), while grade ≥3 hematological toxicity ranged from 1.6% to 50.0% (median: 21.7%). Conclusion: Concurrent CRT is a viable alternative to standard CHT in patients with locally advanced BTC, offering comparable OS and PFS rates, along with an acceptable toxicity profile. However, prospective trials are needed to validate and further explore these findings. [ABSTRACT FROM AUTHOR]

Background: The decision to administer palliative radiotherapy (RT) to patients with bone metastases (BMs), as well as the selection of treatment protocols (dose, fractionation), requires an accurate assessment of survival expectancy. In this study, we aimed to develop three predictive models (PMs) to estimate short‐, intermediate‐, and long‐term overall survival (OS) for patients in this clinical setting. Materials and Methods: This study constitutes a sub‐analysis of the PRAIS trial, a longitudinal observational study collecting data from patients referred to participating centers to receive palliative RT for cancer‐induced bone pain. Our analysis encompassed 567 patients from the PRAIS trial database. The primary objectives were to ascertain the correlation between clinical and laboratory parameters with the OS rates at three distinct time points (short: 3 weeks; intermediate: 24 weeks; prolonged: 52 weeks) and to construct PMs for prognosis. We employed machine learning techniques, comprising the following steps: (i) identification of reliable prognostic variables and training; (ii) validation and testing of the model using the selected variables. The selection of variables was accomplished using the LASSO method (Least Absolute Shrinkage and Selection Operator). The model performance was assessed using receiver operator characteristic curves (ROC) and the area under the curve (AUC). Results: Our analysis demonstrated a significant impact of clinical parameters (primary tumor site, presence of non‐bone metastases, steroids and opioid intake, food intake, and body mass index) and laboratory parameters (interleukin 8 [IL‐8], chloride levels, C‐reactive protein, white blood cell count, and lymphocyte count) on OS. Notably, different factors were associated with the different times for OS with only IL‐8 included both in the PMs for short‐ and long‐term OS. The AUC values for ROC curves for 3‐week, 24‐week, and 52‐week OS were 0.901, 0.767, and 0.806, respectively. Conclusions: We successfully developed three PMs for OS based on easily accessible clinical and laboratory parameters for patients referred to palliative RT for painful BMs. While our findings are promising, it is important to recognize that this was an exploratory trial. The implementation of these tools into clinical practice warrants further investigation and confirmation through subsequent studies with separate databases. [ABSTRACT FROM AUTHOR]

Simple Summary: This study investigates how the assessment of body mass index (BMI), together with body fat and muscle mass, might influence the success of treatments for advanced cervical cancer. Unlike most research which focuses on general health and cancer stages, this research pays particular attention to the patient's weight-to-height ratio, muscle mass, and especially the condition known as sarcopenic obesity—a combination of high body fat and low muscle mass. The findings reveal that sarcopenic obesity significantly affects patient outcomes, suggesting that it could be a key factor in deciding the best course of treatment. Recognizing these body composition indicators could lead to more personalized and effective treatment plans, marking a step forward in the way we approach care for cervical cancer patients. Locally advanced cervical cancer represents a significant treatment challenge. Body composition parameters such as body mass index, sarcopenia, and sarcopenic obesity, defined by sarcopenia and BMI ≥ 30 kg/m2, have been identified as potential prognostic factors, yet their overall impact remains underexplored. This study assessed the relationship between these anthropometric parameters alongside clinical prognostic factors on the prognosis of 173 cervical cancer patients. Survival outcomes in terms of local control (LC), distant metastasis-free survival (DMFS), disease-free survival (DFS), and overall survival (OS) were analyzed using Kaplan regression methods—Meier and Cox. Older age, lower hemoglobin levels, higher FIGO (International Federation of Gynecology and Obstetrics) stages, and lower total radiation doses were significantly associated with worse outcomes. Univariate analysis showed a significant correlation between BMI and the outcomes examined, revealing that normal-weight patients show higher survival rates, which was not confirmed by the multivariate analysis. Sarcopenia was not correlated with any of the outcomes considered, while sarcopenic obesity was identified as an independent negative predictor of DFS (HR: 5.289, 95% CI: 1.298–21.546, p = 0.020) and OS (HR: 2.645, 95% CI: 1.275–5.488, p = 0.009). This study highlights the potential of sarcopenic obesity as an independent predictor of clinical outcomes. These results support their inclusion in prognostic assessments and treatment planning for patients with advanced cervical cancer. [ABSTRACT FROM AUTHOR]

Simulators have revolutionized medical education and training across various disciplines, offering unique advantages in skill acquisition and performance improvement. In the context of interventional radiation therapy (IRT), simulators have emerged as valuable tools for training healthcare professionals in these complex procedures. This narrative review summarized the available evidence on the use of simulators in IRT training, highlighting their impact on proficiency, engagement, and self-confidence as well as their benefits for medical physicists and radiation therapists. A systematic search was conducted in PubMed, resulting in inclusion of 10 papers published since 2009, with 5 of them published since 2020. Publications originated from centers in USA, Ireland, Switzerland, Canada, and Japan, covering a range of IRT settings, including general, prostate, and cervical IRT. The review demonstrated that simulators provide a controlled and realistic environment for skill acquisition, allowing healthcare professionals to practice procedures, optimize image quality, and enhance technical proficiency. The use of simulators addressed the barriers associated with limited caseload and procedural complexity, ultimately contributing to improved education and IRT training. While cost considerations may exist, simulators offer long-term costeffective solutions, balancing the potential benefits in improving educational outcomes and patient care. Overall, simulators play a crucial role in IRT training, enhancing the skills and competence of healthcare providers and improving access to quality IRT care worldwide. Future research should focus on evaluating the long-term impact of simulation-based training on clinical outcomes and patient satisfaction, exploring different simulation models and training approaches, and addressing region-specific barriers to optimize the utilization of IRT. [ABSTRACT FROM AUTHOR]