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Introduction: In the spring of 2020, coronavirus disease 2019 posed a substantial challenge for countries and their healthcare systems. In Germany, over 70% of all cancer patients are treated in an outpatient setting, so gynecologic oncology practices are the guarantors of optimal patient care. We developed a survey to evaluate the management of gynecologic oncology patients. Methods: The survey consisted of 38 questions and was sent to the members of the Berufsverband Niedergelassener Gynäkologischer Onkologen in Deutschland e.V. (BNGO), a professional association of gynecologic oncologists in the outpatient sector in Germany. Results: The survey was completed by 54 out of 133 (41%) gynecologic oncologists from 14 out of 15 (93%) federal states where the BNGO is represented. Facing the pandemic, popular measures were mask requirements (100%), restriction of access to practices (94%), increased number of disinfectant dispensers (85%), installment of panes of acrylic glass (76%), or spatial alterations (67%). For most patients the pandemic had no influence on prioritization of therapies (82%) or prescribed systemic treatments (87%). Despite an increase in perceived psychological burden among the staff (72%), 85% (45/54) of the practices were not offered any additional psychological support. Discussion and Conclusion: As most cancer patients in Germany are treated in an outpatient setting, a suitable reaction of oncology centers to the new circumstances was crucial to secure optimal treatment and patient care. Nevertheless, the low prioritization of mental health or distress of healthcare workers poses a serious threat to the maintenance of optimal medical care in further waves of the pandemic. [ABSTRACT FROM AUTHOR]

Simple Summary: To assess the impact of thoracic (low) dose irradiation on pulmonary function changes after thoracic radiotherapy (RT) data of 62 patients were analyzed. There were several significant correlations between pulmonary function and dose parameters of the lung and heart, most of which remained significant in the multivariate analysis. Objective: To assess the impact of (low) dose irradiation to the lungs and heart on the incidence of pneumonitis and pulmonary function changes after thoracic radiotherapy (RT). Methods/Material: Data of 62 patients treated with curative thoracic radiotherapy were analyzed. Toxicity data and pulmonary function tests (PFTs) were obtained before RT and at 6 weeks, at 12 weeks, and at 6 months after RT. PFTs included ventilation (e.g., vital capacity) and diffusion parameters (e.g., diffusion capacity for carbon monoxide (DLCO)). Dosimetric data of the lung and heart were extracted to assess the impact of dose on PFT changes and radiation pneumonitis (RP). Results: No statistically significant correlations between dose parameters and changes in ventilation parameters were found. There were statistically significant correlations between DLCO and low-dose parameters of the lungs (V5Gy–V30Gy (%)) and irradiation of the heart during the follow-up up to 6 months after RT, as well as a temporary correlation of the V60Gy (%) on the blood gas parameters at 12 weeks after RT. On multivariate analysis, both heart and lung parameters had a significant impact on DLCO. There was no statistically significant influence of any patient or treatment-related (including dose parameters) factors on the incidence of ≥G2 pneumonitis. Conclusion: There seems to be a lasting impact of low dose irradiation to the lung as well as irradiation to the heart on the DLCO after thoracic radiotherapy. No influence on RP was found in this analysis. [ABSTRACT FROM AUTHOR]

Purpose: Technological progress of machine learning and natural language processing has led to the development of large language models (LLMs), capable of producing well-formed text responses and providing natural language access to knowledge. Modern conversational LLMs such as ChatGPT have shown remarkable capabilities across a variety of fields, including medicine. These models may assess even highly specialized medical knowledge within specific disciplines, such as radiation therapy. We conducted an exploratory study to examine the capabilities of ChatGPT to answer questions in radiation therapy., Methods and Materials: A set of multiple-choice questions about clinical, physics, and biology general knowledge in radiation oncology as well as a set of open-ended questions were created. These were given as prompts to the LLM ChatGPT, and the answers were collected and analyzed. For the multiple-choice questions, it was checked how many of the answers of the model could be clearly assigned to one of the allowed multiple-choice-answers, and the proportion of correct answers was determined. For the open-ended questions, independent blinded radiation oncologists evaluated the quality of the answers regarding correctness and usefulness on a 5-point Likert scale. Furthermore, the evaluators were asked to provide suggestions for improving the quality of the answers., Results: For 70 multiple-choice questions, ChatGPT gave valid answers in 66 cases (94.3%). In 60.61% of the valid answers, the selected answer was correct (50.0% of clinical questions, 78.6% of physics questions, and 58.3% of biology questions). For 25 open-ended questions, 12 answers of ChatGPT were considered as "acceptable," "good," or "very good" regarding both correctness and helpfulness by all 6 participating radiation oncologists. Overall, the answers were considered "very good" in 29.3% and 28%, "good" in 28% and 29.3%, "acceptable" in 19.3% and 19.3%, "bad" in 9.3% and 9.3%, and "very bad" in 14% and 14% regarding correctness/helpfulness., Conclusions: Modern conversational LLMs such as ChatGPT can provide satisfying answers to many relevant questions in radiation therapy. As they still fall short of consistently providing correct information, it is problematic to use them for obtaining medical information. As LLMs will further improve in the future, they are expected to have an increasing impact not only on general society, but also on clinical practice, including radiation oncology., Competing Interests: Nikola Cihoric is a technical lead for the SmartOncology project and medical advisor for Wemedoo AG, Steinhausen AG, Switzerland., (© 2023 The Author(s).)

Introduction: In the spring of 2020, coronavirus disease 2019 posed a substantial challenge for countries and their healthcare systems. In Germany, over 70% of all cancer patients are treated in an outpatient setting, so gynecologic oncology practices are the guarantors of optimal patient care. We developed a survey to evaluate the management of gynecologic oncology patients., Methods: The survey consisted of 38 questions and was sent to the members of the Berufsverband Niedergelassener Gynäkologischer Onkologen in Deutschland e.V. (BNGO), a professional association of gynecologic oncologists in the outpatient sector in Germany., Results: The survey was completed by 54 out of 133 (41%) gynecologic oncologists from 14 out of 15 (93%) federal states where the BNGO is represented. Facing the pandemic, popular measures were mask requirements (100%), restriction of access to practices (94%), increased number of disinfectant dispensers (85%), installment of panes of acrylic glass (76%), or spatial alterations (67%). For most patients the pandemic had no influence on prioritization of therapies (82%) or prescribed systemic treatments (87%). Despite an increase in perceived psychological burden among the staff (72%), 85% (45/54) of the practices were not offered any additional psychological support., Discussion and Conclusion: As most cancer patients in Germany are treated in an outpatient setting, a suitable reaction of oncology centers to the new circumstances was crucial to secure optimal treatment and patient care. Nevertheless, the low prioritization of mental health or distress of healthcare workers poses a serious threat to the maintenance of optimal medical care in further waves of the pandemic., Competing Interests: The authors have no conflicts of interest to declare., (Copyright © 2021 by S. Karger AG, Basel.)