Oncology Residents Research Articles

Radiation Oncology Residency Training in Saudi Arabia: Direction in Attaining Competencies

Radiation Oncology Residency Training in Saudi Arabia: Direction in Attaining Competencies

Problem-based learning on the WeChat public platform in radiation oncology residency training programs.

This study explored the effectiveness of a Problem-based Learning (PBL) teaching model on the WeChat public platform for radiation oncology residency training programs. The WeChat PBL program was initiated in 2019. The study recruited student participants, on a voluntary basis, who were in their first and second years of standardized training in radiation oncology. We selected classic and trending issues in radiation oncology as the two main teaching topics. Students in the PBL group searched for relevant literature, summarizing PowerPoint presentations or academic speeches on specific issues published on the professional WeChat public platform after an in-depth review by teachers. The final national standardized training examination scores for resident physicians were used to evaluate teaching effectiveness. The graduation scores of the PBL and non-PBL groups were compared, and a stratified analysis was conducted based on the year of participation to assess the teaching effectiveness of this model. Moreover, questionnaires were administered to evaluate students' experiences. Among the 36 students who joined the study in 2019, 16 (44.0%) voluntarily joined the PBL teaching group. Nine students started teaching PBL in their first year of residency, accounting for 47.4% of that year, and seven started in their second year, accounting for 41.2%. The average graduation scores of the PBL group were superior to those of the non-PBL-focused group for the same grade. The rate of high scores among students in the PBL group (56.3%) was higher than that of students in the non-PBL group (25%). Specifically, first-year residents who joined the PBL group had an average score of 92.3 ± 2.2, significantly higher than their non-PBL counterparts, who scored an average of 88.6 ± 4.6, showing a statistically significant advantage (p = 0.042). All students were satisfied with the PBL WeChat teaching and would recommend the PBL WeChat course to others. The PBL residency teaching model on the WeChat platform improved residency scores and garnered student satisfaction.

MSOR08 Presentation Time: 8:35 AM: Confidence in Brachytherapy Proficiency among Graduating Radiation Oncology Residents between 2020-2023

MSOR08 Presentation Time: 8:35 AM: Confidence in Brachytherapy Proficiency among Graduating Radiation Oncology Residents between 2020-2023

MSOR09 Presentation Time: 8:40 AM: Individuals Who Graduate from a US Radiation Oncology Residency Program and Subsequently Complete a Brachytherapy Fellowship: Who Are They?

MSOR09 Presentation Time: 8:40 AM: Individuals Who Graduate from a US Radiation Oncology Residency Program and Subsequently Complete a Brachytherapy Fellowship: Who Are They?

Second Look Opportunity for Radiation Oncology Medical Residency During Virtual Interview Season

PurposeDespite easing of COVID-19 travel restrictions and social distancing, medical radiation oncology (RO) residency interviews for the 2023 Match remained exclusively virtual. Virtual interviews can be limited in providing program atmosphere, resident camaraderie, and city culture. Our institution offered a voluntary in-person second look (SL) to address these concerns and supplement the virtual interview. Methods and MaterialA voluntary in-person SL across 3 dates was offered to all applicants who successfully interviewed with the RO department for the 2023 Match (n=54). Attendees of the SLs (n=38) were invited to complete a voluntary 10-question anonymous survey after Match Day regarding their perspectives on this opportunity including motivations for attending, financial burden, and perceived benefits of SLs. Results38 individuals (70%) attended one of the departmental SLs with 19 participants (50%) completing the survey. 16 out of 19 (84%) participants traveled >200 miles to attend. All surveyed applicants were grateful for the in-person SL opportunity and agreed such opportunities should continually be offered with exclusively virtual residency interviews. All participants reported that their decision to attend the SL was affected by departmental financial support. Two applicants felt pressured to attend the SL to remain competitive to the program. Majority of applicants agreed that they achieved a better “feel” for the program culture and the larger institution, resident camaraderie, and the surrounding city from this in-person SL encounter, compared to virtual interview alone (18, 94%). ConclusionThese in-person second look opportunities were well-attended, well-received, and offered insights and experiences to RO resident applicants in the setting of exclusively virtual interviews. The cost of attendance may be a limiting factor when applicants are deciding to attend in-person SLs. Caution is needed to ensure applicants do not feel obligated to attend and SLs are not used as a platform for inappropriate post interview communication.

Artificial intelligence-assisted delineation for postoperative radiotherapy in patients with lung cancer: a prospective, multi-center, cohort study

BackgroundPostoperative radiotherapy (PORT) is an important treatment for lung cancer patients with poor prognostic features, but accurate delineation of the clinical target volume (CTV) and organs at risk (OARs) is challenging and time-consuming. Recently, deep learning-based artificial intelligent (AI) algorithms have shown promise in automating this process.ObjectiveTo evaluate the clinical utility of a deep learning-based auto-segmentation model for AI-assisted delineating CTV and OARs in patients undergoing PORT, and to compare its accuracy and efficiency with manual delineation by radiation oncology residents from different levels of medical institutions.MethodsWe previously developed an AI auto-segmentation model in 664 patients and validated its contouring performance in 149 patients. In this multi-center, validation trial, we prospectively involved 55 patients and compared the accuracy and efficiency of 3 contouring methods: (i) unmodified AI auto-segmentation, (ii) fully manual delineation by junior radiation oncology residents from different medical centers, and (iii) manual modifications based on AI segmentation model (AI-assisted delineation). The ground truth of CTV and OARs was delineated by 3 senior radiation oncologists. Contouring accuracy was evaluated by Dice similarity coefficient (DSC), Hausdorff distance (HD), and mean distance of agreement (MDA). Inter-observer consistency was assessed by volume and coefficient of variation (CV).ResultsAI-assisted delineation achieved significantly higher accuracy compared to unmodified AI auto-contouring and fully manual delineation by radiation oncologists, with median HD, MDA, and DCS values of 20.03 vs. 21.55 mm, 2.57 vs. 3.06 mm, 0.745 vs. 0.703 (all P<0.05) for CTV, respectively. The results of OARs contours were similar. CV for OARs was reduced by approximately 50%. In addition to better contouring accuracy, the AI-assisted delineation significantly decreased the consuming time and improved the efficiency.ConclusionAI-assisted CTV and OARs delineation for PORT significantly improves the accuracy and efficiency in the real-world setting, compared with pure AI auto-segmentation or fully manual delineation by junior oncologists. AI-assisted approach has promising clinical potential to enhance the quality of radiotherapy planning and further improve treatment outcomes of patients with lung cancer.

Research on doctor-patient communication teaching for oncology residents: a new teaching model.

At present, there is no specific teaching method for doctor-patient communication for oncology residents. This study combined BOPPPS (bridge-in, learning objective, pretest, participatory learning, posttest, and summary) teaching model and SBAR (situation-background-assessment-recommendation) communication model to try a new teaching and assessment model of doctor-patient communication, aiming to explore and improve the teaching method of doctor-patient communication for oncology residents. Ninety residents were randomly divided into two groups: the experimental group (n = 45) was trained with the BOPPPS teaching model combined with the SBAR communication model, the routine teaching method was adopted in the control group (n = 45). Indicators of assessment included doctor-patient communication skills, satisfaction with teaching, and patient satisfaction. The scores for doctor-patient communication ability were significantly better in experimental group than control group (p < 0.05). The degree of satisfaction degree (very satisfied + satisfied) of the experimental group were higher than control group (p < 0.05). The overall teaching satisfaction of the experimental group was 100.00%, the control group was 77.78%, p < 0.001. Patients' satisfaction with the residents in the experimental group (93.3%) was significantly higher than control group (80.0%), p = 0.043. The application of the BOPPPS combined with the SBAR can effectively enhance residents' doctor-patient communication ability and improve teaching satisfaction and patient satisfaction. This new model can effectively improve resident physician‒patient communication ability, which is worth actively promoting in clinical teaching work.

Improving dihydropyrimidine dehydrogenase genotyping (DPYD) prior to initiation of fluoropyrimidine-based chemotherapy at a community-based hospital: A quality improvement initiative.

347 Background: Dihydropyrimidine dehydrogenase gene (DPYD) testing is crucial in preventing toxicities from fluoropyrimidine chemotherapy. Despite benefits and established guidelines, its adoption within healthcare organizations remains inconsistent and suboptimal. We implemented a quality improvement project to improve DPYD testing prior to fluoropyrimidine chemotherapy at a community-based hospital. We aimed to increase DPYD testing for patients receiving fluoropyrimidine-based chemotherapy from 65% to 95% between July 2023 to July 2024. Balancing measures included DPYD testing turnaround time. Methods: For baseline diagnostics, manual chart review was performed on 126 patients to identify frequency of DPYD testing, and turnaround time (TAT) between May 1, 2023 to August 4, 2023. Patients were excluded if they received fluoropyrimidine-based chemotherapy prior to May 1, 2023. A multidisciplinary team including medical oncology residents and staff, pharmacists, nurses, and clinical informatics specialists worked jointly to identify and address barriers to implementation. Barriers identified included lack of established workflows and awareness of the importance of testing. Diagnostic tools utilized included Ishikawa diagrams and process mapping. The team used Plan-Do-Study-Act (PDSA) cycles to address barriers. A p-chart was used to analyze the results. Results: The baseline DPYD testing rate was 65%. Barriers identified via multidisciplinary sessions included lack of established workflow, awareness and importance of testing. PDSA cycles included education sessions to breast medical oncologists and medical oncology nurses, and development of a best-practice advisory in the electronic medical record. The percentage of eligible patients receiving DPYD testing increased from 65% to 95.8% in the total population. For breast cancer patients, the rate increased from 16.7% to 100%. For gastrointestinal cancer patients, the rate increased from 56.1% to 94.2%. Sustainability was demonstrated two months post-intervention with TAT stable between 7-8 days. Conclusions: Through PDSA cycles, we improved the frequency of DPYD testing for patients receiving fluoropyrimidine chemotherapy from 65% to 95.8%. Future work will assess changes in chemotherapy prescribing behavior in the setting of variant DPYD results, and outcomes of patients with variant DPYD testing.

A Survey of Perspectives and Educational Needs of Canadian Oncology Residents on Artificial Intelligence.

This study evaluated the perspectives and educational needs of Canadian oncology residents with regard to artificial intelligence (AI) in medicine, exploring the influence of factors such as program of choice, gender, and tech literacy on their attitudes towards AI. An ethics-approved survey collected anonymous responses from Canadian oncology residents from December 2022 to July 2023. Comparisons by demographics were made using Chi-square and Mann-Whitney U tests. A total of 57 residents and fellows responded out of an expected 182, with representation from each oncology training program in Canada. Over half of the participants were male (63.2%), with radiation oncology programs being better represented than medical oncology programs (68.4% vs. 31.6%). There was balanced representation across all years of training. Most trainees (73%) were interested in learning more about AI, and many believed the topic should be formally taught during residency (63%), preferably through workshops (79%). Among evaluated factors, tech literacy showed the most impact over AI perspectives, driving a perception shift towards viewing AI as an improvement tool, rather than as a threat to professionals. In conclusion, Canadian oncology residents anticipate AI's growing influence in medicine but face educational deficiencies. Gender, oncology discipline, and self-reported tech literacy impact attitudes toward AI, highlighting the need for inclusive education.

1571P The reasons that motivate a change of specialties among oncology residents

1571P The reasons that motivate a change of specialties among oncology residents

180 Implementation of a PGY-1 Multidisciplinary Surgical Block in Radiation Oncology Residency Training

180 Implementation of a PGY-1 Multidisciplinary Surgical Block in Radiation Oncology Residency Training

1574P Medical oncology residents mentors (MORM): A target for resiliency interventions

1574P Medical oncology residents mentors (MORM): A target for resiliency interventions

Psychiatric assessment for patients who decline cancer treatment: perspectives from medical residents.

Among patients with cancer, a comorbid mental disorder is associated with higher mortality. This could be partially attributed to reduced access to oncological care, sometimes due to treatment refusal. Recommendations were issued in 2018 by the French and Francophone Society of Psycho-Oncology concerning the management of oncological treatment refusal. This study aimed to examine oncology residents' view on psychiatric assessment in this context. In February 2021, we conducted a descriptive, observational, cross-sectional pilot study among French residents involved in oncology regarding their management of cancer treatment refusal and the importance they assign to psychiatric assessment, using an online questionnaire with 12 multiple-choice questions. Among 87 respondents, only 35.6% systematically explore the history of mental disorders when facing cancer treatment refusal. Even in cases with a known history of mental disorders, only 42.5% systematically refer the patient to a psychiatrist. 96.5% of them were unaware of the 2018 recommendations. The importance given to psychiatric assessment in cases of oncological treatment refusal remains insufficient. Qualitative studies are needed to understand the underlying reasons for this refusal. The development of psychiatric consultation-liaison interventions in oncology centers is necessary to improve the management of these cases and provide appropriate training.

Impact of Small Group Session on Medical Student Interest in Applying for Residency in Radiation Oncology

Impact of Small Group Session on Medical Student Interest in Applying for Residency in Radiation Oncology

Coaching for Radiation Oncology Residents and Faculty- A Pilot Program

Coaching for Radiation Oncology Residents and Faculty- A Pilot Program

Analysis of Radiation Oncology Residency Program Websites: A Call For Further Improvements

Analysis of Radiation Oncology Residency Program Websites: A Call For Further Improvements

Assessment of an Onco-Radiology Course for Radiation Oncology Residents

Assessment of an Onco-Radiology Course for Radiation Oncology Residents

Radiation Oncology Education Collaborative Study Group Physics Curriculum Needs Assessment for Radiation Oncology Residents

Radiation Oncology Education Collaborative Study Group Physics Curriculum Needs Assessment for Radiation Oncology Residents

Utility of Virtual Sessions to Inform Medical Students about Radiation Oncology Residency Programs

Utility of Virtual Sessions to Inform Medical Students about Radiation Oncology Residency Programs

Cloud-based Self-directed Contouring Modules in Radiation Oncology Residency: Interim Results

Cloud-based Self-directed Contouring Modules in Radiation Oncology Residency: Interim Results