Remote Mentorship in Radiation Oncology: Lessons to Share.
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ABSTRACT:
SUBMITTER: Seldon C
PROVIDER: S-EPMC8188242 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:To analyze survey information regarding mentorship practices and cross-correlate the results with objective metrics of academic productivity among academic radiation oncologists at US Accreditation Council for Graduate Medical Education (ACGME)-accredited residency training programs.An institutional review board-approved survey for the Radiation Oncology Academic Development and Mentorship Assessment Project (ROADMAP) was sent to 1031 radiation oncologists employed at an ACGME-accredited residency training program and administered using an international secure web application designed exclusively to support data capture for research studies. Data collected included demographics, presence of mentorship, and the nature of specific mentoring activities. Productivity metrics, including number of publications, number of citations, h-index, and date of first publication, were collected for each survey respondent from a commercially available online database, and m-index was calculated.A total of 158 academic radiation oncologists completed the survey, 96 of whom reported having an academic/scientific mentor. Faculty with a mentor had higher numbers of publications, citations, and h- and m-indices. Differences in gender and race/ethnicity were not associated with significant differences in mentorship rates, but those with a mentor were more likely to have a PhD degree and were more likely to have more time protected for research. Bivariate fit regression modeling showed a positive correlation between a mentor's h-index and their mentee's h-index (R2=0.16; P<.001). Linear regression also showed significant correlates of higher h-index, in addition to having a mentor (P=.001), included a longer career duration (P<.001) and fewer patients in treatment (P=.02).Mentorship is widely believed to be important to career development and academic productivity. These results emphasize the importance of identifying and striving to overcome potential barriers to effective mentorship.
| S-EPMC4085773 | biostudies-literature
Project description:The coronavirus pandemic is more fully exposing ubiquitous economic and social inequities that pervade conservation science. In this time of prolonged stress on members of the research community, primary investigators or project leaders (PLs) have a unique opportunity to adapt their programs to jointly create more equitable and productive research environments for their teams. Institutional guidance for PLs pursuing field and laboratory work centers on the physical safety of individuals while in the lab or field, but largely ignores the vast differences in how team members may be experiencing the pandemic. Strains on mental, physical, and emotional health; racial trauma; familial responsibilities; and compulsory productivity resources, such as high-speed internet, quiet work spaces, and support are unequally distributed across team members. The goal of this paper is to summarize the shifting dynamics of leadership and mentorship during the coronavirus pandemic and highlight opportunities for increasing equity in conservation research at the scale of the project team. Here, we (1) describe how the pandemic differentially manifests inequity on project teams, particularly for groups that have been structurally excluded from conservation science, (2) consider equitable career advancement during the coronavirus pandemic, and (3) offer suggestions for PLs to provide mentorship that prioritizes equity and wellbeing during and beyond the pandemic. We aim to support PLs who have power and flexibility in how they manage research, teaching, mentoring, consulting, outreach, and extension activities so that individual team members' needs are met with compassion and attention to equity.
| S-EPMC8455165 | biostudies-literature
Project description:Radiomics leverages existing image datasets to provide non-visible data extraction via image post-processing, with the aim of identifying prognostic, and predictive imaging features at a sub-region of interest level. However, the application of radiomics is hampered by several challenges such as lack of image acquisition/analysis method standardization, impeding generalizability. As of yet, radiomics remains intriguing, but not clinically validated. We aimed to test the feasibility of a non-custom-constructed platform for disseminating existing large, standardized databases across institutions for promoting radiomics studies. Hence, University of Texas MD Anderson Cancer Center organized two public radiomics challenges in head and neck radiation oncology domain. This was done in conjunction with MICCAI 2016 satellite symposium using Kaggle-in-Class, a machine-learning and predictive analytics platform. We drew on clinical data matched to radiomics data derived from diagnostic contrast-enhanced computed tomography (CECT) images in a dataset of 315 patients with oropharyngeal cancer. Contestants were tasked to develop models for (i) classifying patients according to their human papillomavirus status, or (ii) predicting local tumor recurrence, following radiotherapy. Data were split into training, and test sets. Seventeen teams from various professional domains participated in one or both of the challenges. This review paper was based on the contestants' feedback; provided by 8 contestants only (47%). Six contestants (75%) incorporated extracted radiomics features into their predictive model building, either alone (n = 5; 62.5%), as was the case with the winner of the "HPV" challenge, or in conjunction with matched clinical attributes (n = 2; 25%). Only 23% of contestants, notably, including the winner of the "local recurrence" challenge, built their model relying solely on clinical data. In addition to the value of the integration of machine learning into clinical decision-making, our experience sheds light on challenges in sharing and directing existing datasets toward clinical applications of radiomics, including hyper-dimensionality of the clinical/imaging data attributes. Our experience may help guide researchers to create a framework for sharing and reuse of already published data that we believe will ultimately accelerate the pace of clinical applications of radiomics; both in challenge or clinical settings.
| S-EPMC6107800 | biostudies-literature
Project description:BACKGROUND AND PURPOSE:The COVID-19 pandemic warrants operational initiatives to minimize transmission, particularly among cancer patients who are thought to be at high-risk. Within our department, a multidisciplinary tracer team prospectively monitored all patients under investigation, tracking their test status, treatment delays, clinical outcomes, employee exposures, and quarantines. MATERIALS AND METHODS:Prospective cohort tested for SARS-COV-2 infection over 35 consecutive days of the early pandemic (03/19/2020-04/22/2020). RESULTS:A total of 121 Radiation Oncology patients underwent RT-PCR testing during this timeframe. Of the 7 (6%) confirmed-positive cases, 6 patients were admitted (4 warranting intensive care), and 2 died from acute respiratory distress syndrome. Radiotherapy was deferred or interrupted for 40 patients awaiting testing. As the median turnaround time for RT-PCR testing decreased from 1.5 (IQR: 1-4) to ?1-day (P < 0.001), the median treatment delay also decreased from 3.5 (IQR: 1.75-5) to 1 business day (IQR: 1-2) [P < 0.001]. Each patient was an exposure risk to a median of 5 employees (IQR: 3-6.5) through prolonged close contact. During this timeframe, 39 care-team members were quarantined for a median of 3 days (IQR: 2-11), with a peak of 17 employees simultaneously quarantined. Following implementation of a "dual PPE policy," newly quarantined employees decreased from 2.9 to 0.5 per day. CONCLUSION:The severe adverse events noted among these confirmed-positive cases support the notion that cancer patients are vulnerable to COVID-19. Active tracking, rapid diagnosis, and aggressive source control can mitigate the adverse effects on treatment delays, workforce incapacitation, and ideally outcomes.
| S-EPMC7256609 | biostudies-literature
Project description:PurposeTo investigate patterns of failure in institutional credentialing submissions to NRG/RTOG 1005 with the aim of improving the quality and consistency for future breast cancer protocols.Methods and materialsNRG/RTOG 1005 allowed the submission of 3-dimensional conformal radiation therapy (3DCRT), intensity-modulated radiation therapy (IMRT), and simultaneous integrated boost (SIB) breast plans. Credentialing required institutions to pass a 2-step quality assurance (QA) process: (1) benchmark, requiring institutions to create a plan with no unacceptable deviations and ≤1 acceptable variation among the dose volume (DV) criteria, and (2) rapid review, requiring each institution's first protocol submission to have no unacceptable deviations among the DV criteria or contours. Overall rates, number of resubmissions, and reasons for resubmission were analyzed for each QA step.ResultsIn total, 352 institutions participated in benchmark QA and 280 patients enrolled had rapid review QA. Benchmark initial failure rates were similar for 3DCRT (18%), IMRT (17%), and SIB (18%) plans. For 3DCRT and IMRT benchmark plans, ipsilateral lung most frequently failed the DV criteria, and SIB DV failures were seen most frequently for the heart. Rapid review contour initial failures (35%) were due to target rather than organs at risk. For 29% of the rapid review initial failures, the planning target volume boost eval volume was deemed an unacceptable deviation.ConclusionsThe review of the benchmark and rapid review QA submissions indicates that acceptable variations or unacceptable deviations for the ipsilateral lung and heart dose constraints were the most commonly observed cause of benchmark QA failure, and unacceptable deviations in target contouring, rather than normal structure contouring, were the most common cause of rapid review QA failure. These findings suggest that a rigorous QA process is necessary for high quality and homogeneity in radiation therapy in multi-institutional trials of breast cancer to ensure that the benefits of radiation therapy far outweigh the risks.
| S-EPMC7255922 | biostudies-literature
Project description:Radiation therapy is a critical component in the curative management of many solid tumor types, and advances in radiation delivery techniques during the past decade have led to improved disease control and quality of life for patients. During the same period, remarkable advances have also been made in understanding the genomic landscape of tumors; however, treatment decisions in radiation oncology continue to depend primarily on clinical and histopathologic characteristics rather than on the genetic features of the tumor or the patient. With the development of novel genomic techniques and their increasing use in clinical practice, radiation oncology is uniquely positioned to leverage these advances to identify novel biomarkers that could inform radiation dose, field, and the use of concurrent systemic agents. Here, we summarize efforts to use genomic techniques to guide radiation decisions, and we highlight some of the current opportunities and challenges that exist in attempting to apply precision oncology principles in radiation oncology.
| S-EPMC7446508 | biostudies-literature
Project description:Leveraging Electronic Health Records (EHR) and Oncology Information Systems (OIS) has great potential to generate hypotheses for cancer treatment, since they directly provide medical data on a large scale. In order to gather a significant amount of patients with a high level of clinical details, multicenter studies are necessary. A challenge in creating high quality Big Data studies involving several treatment centers is the lack of semantic interoperability between data sources. We present the ontology we developed to address this issue.Radiation Oncology anatomical and target volumes were categorized in anatomical and treatment planning classes. International delineation guidelines specific to radiation oncology were used for lymph nodes areas and target volumes. Hierarchical classes were created to generate The Radiation Oncology Structures (ROS) Ontology. The ROS was then applied to the data from our institution.Four hundred and seventeen classes were created with a maximum of 14 children classes (average = 5). The ontology was then converted into a Web Ontology Language (.owl) format and made available online on Bioportal and GitHub under an Apache 2.0 License. We extracted all structures delineated in our department since the opening in 2001. 20,758 structures were exported from our "record-and-verify" system, demonstrating a significant heterogeneity within a single center. All structures were matched to the ROS ontology before integration into our clinical data warehouse (CDW).In this study we describe a new ontology, specific to radiation oncology, that reports all anatomical and treatment planning structures that can be delineated. This ontology will be used to integrate dosimetric data in the Assistance Publique-Hôpitaux de Paris CDW that stores data from 6.5 million patients (as of February 2017).
| S-EPMC5774757 | biostudies-literature
Project description:The mounting global cancer burden has generated an increasing demand for oncologists to join the workforce. Yet, students report limited oncology exposure in undergraduate medical curricula, while undergraduate oncology mentorships remain underutilised. We established an undergraduate oncology society-led mentorship programme aimed at medical students across several UK universities to increase medical student oncology exposure. We electronically recruited and paired oncologist mentors and medical student mentees and distributed a dedicated questionnaire (pre- and post-mentorship) to compare mentees' self-reported cancer specialty knowledge and oncology career motivation after undertaking a 6-week mentorship. We also determined students' interest across specialties and subspecialties and measured mentor availability via percentage programme uptake. Statistical analysis included univariate inferential tests on SPSS software. Twentynine (23.4%) of 124 oncology specialists agreed to become mentors. The mentorship was completed by 30 students across three medical schools: 16 (53.3%) Barts, 10 (33.3%) Birmingham, and 4 (13.3%) King's; 11 (36.7%) mentored by medical oncologists, 10 (33.3%) by clinical/radiation oncologists, and 9 (30%) by surgical oncologists. The mentorship generated a statically significant increase in students' knowledge of the multidisciplinary team and all oncology-related specialties including academia/research but not interest towards a career in oncology. Undergraduate oncology mentoring is an effective educational, networking and motivational tool for medical students. Student societies are a valuable asset in cultivating medical student oncology interest by connecting students to faculty and increasing mentor accessibility. Further research should focus on developing an optimal mentorship structure and evaluating long-term outcomes of such educational initiatives.
| S-EPMC7688447 | biostudies-literature
Project description:Nanotechnology, the manipulation of matter on atomic and molecular scales, is a relatively new branch of science. It has already made a significant impact on clinical medicine, especially in oncology. Nanomaterial has several characteristics that are ideal for oncology applications, including preferential accumulation in tumors, low distribution in normal tissues, biodistribution, pharmacokinetics, and clearance, that differ from those of small molecules. Because these properties are also well suited for applications in radiation oncology, nanomaterials have been used in many different areas of radiation oncology for imaging and treatment planning, as well as for radiosensitization to improve the therapeutic ratio. In this article, we review the unique properties of nanomaterials that are favorable for oncology applications and examine the various applications of nanotechnology in radiation oncology. We also discuss the future directions of nanotechnology within the context of radiation oncology.
| S-EPMC4152716 | biostudies-literature
Project description:Despite the promising efficacy of immunotherapy in some patients, many other patients are resistant. The synergistic effect of radiotherapy (RT) in combination with immunotherapy reported in case reports and clinical trials has piqued the interest of radiologists in investigating the underlying mechanisms and efficacy of the combination in preclinical and clinical trials. To date, the reported data are limited to small-sized samples, trials lacking a comparison arm, and trials using diverse immunotherapies, various radiation doses, and fractionations. There are just a few studies comparing the efficacy of immunotherapy and radiotherapy to that of conventional therapies or different combinations. Radiologists should design and conduct clinical trials wisely to confirm the efficacy of the combination, particularly the abscopal effect, identify the best combination of various immunotherapeutic drugs and different radiation models for patients, identify the best sequence of the combination, determine the optimal timing of the combination, select the target site and volume, lower adverse effects, and explore predictive models to identify patients who may benefit from the combination therapy. We expect that these clinical trials performed by radiologists will offer definitive evidence for the wide use of the combination of RT and immunotherapy in clinical practice. IMPLICATIONS FOR PRACTICE: This review will provide an update on the use of a combination of radiotherapy and immunotherapy, a cautious interpretation of preliminary results, and future directions for radiologists to perform well-designed clinical trials.
| S-EPMC6394774 | biostudies-literature