No abstract

Radiation oncology (RO) is a dynamic and rapidly changing field. Residents are uniquely positioned to identify issues relevant to graduate medical education and the future workforce. As the elected members of the Executive Committee for the Association of Residents in Radiation Oncology (ARRO), we communicate with the larger RO community about the issues that residents identify as being the most pressing. ARRO recently sent a brief survey to registered American Society for Radiation Oncology (ASTRO) members-in-training (N Z 710) asking them to rank in order any (or all) of 14 specified issues that "concern[ed them] as radiation oncologist[s]." Responses were received from 179 individuals from April 4th through May 10th (response rate Z 25.2%). The top 3 concerning issues (Fig. 1), by rank order, were the job market (91%), the American Board of Radiology (ABR) qualifying (written) examinations (85%), and residency expansion (84%). Other issues identified by trainees included oral boards, declining reimbursement, variability in training programs, and fellowship expansion. Additional free-text concerns were submitted by 90 trainees. The top 2 themes included clinical relevance of board certification examinations (n Z 17) and trust in leadership (n Z 11). Here, we will briefly discuss the top 3 issues. Job Market The principal concern identified by residents was the job market (Fig. 1). Not only did 91% of residents rank the job market as "a concerning issue," but 72% ranked it as 1 of the

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.

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This report summarizes the current multimodality treatment approaches for children with low‐ and high‐grade gliomas, germinoma, and nongerminomatous germ cell tumors, and craniopharyngiomas used in the Children's Oncology Group (COG) and the International Society of Pediatric Oncology (SIOP). Treatment recommendations are provided in the context of historical approaches regarding the roles of surgery, radiation, and chemotherapy. Future research strategies for these tumors in both COG and SIOP are also discussed.

these weeks, the prison-to-US incidence rate ratio was 5.0 (95% CI, 5.0-5.1), while the standardized mortality ratio was 2.7 (95% CI, 1.9-3.8).Discussion | COVID-19 incidence and standardized mortality rates remained consistently higher among the prison population than the overall US population in the first year of the pandemic. While COVID-19 incidence and mortality rates peaked in late 2020 and early 2021 and have since declined, the cumulative toll of COVID-19 has been several times greater among the prison population than the overall US population.A study limitation is reliance on publicly available data, which are subject to potential misreporting, delays, 4 and inconsistencies in population estimates. 3 In addition, differences in testing rates between the overall US population and the prison population may have biased incidence ratios. Also, the study period did not capture the more recent outbreak of COVID-19 cases due to the Delta variant. Nevertheless, this study underscores the importance of initiatives such as vaccination, decarceration, and continued disease surveillance in prison settings as long as the pandemic continues.

Background: Salvage radiotherapy (SRT) is an established treatment for men with biochemical recurrence following radical prostatectomy (RP). There are several risk factors associated with adverse outcomes; however, the value of postoperative prostate-specific antigen (PSA) kinetics is less clear in the ultrasensitive PSA era. Objective: To characterize the impact of PSA kinetics on outcomes following SRT and generate nomograms to aid in identifying patients with an increased risk of adverse clinical outcomes. Design, setting, and participants: A multi-institutional analysis was conducted of 1005 patients with prostate cancer treated with SRT after RP, with a median followup of 5 years. Outcome measurements and statistical analysis: Variables examined include immediate postoperative PSA, postoperative PSA doubling time (DT), and pre-SRT PSA, in addition to previously identified predictive factors. Multivariable survival analyses were completed using Fine-Gray competing risk regression. Rates of biochemical failure (BF), distant metastasis (DM), and prostate cancer-specific mortality (PCSM) were estimated by the cumulative incidence method. Nomograms were generated from multivariable competing risk regression with bootstrap cross-validation. Results and limitations: Factors associated with BF after SRT include PSA DT <6 mo, initial postoperative PSA 0.2 ng/ml, higher pre-SRT PSA, lack of androgen deprivation therapy, a higher Gleason score (GS), negative margins, seminal vesicle invasion, lack of pelvic nodal radiation, radiation total dose <66 Gy, a longer RP to SRT interval, and older age (p < 0.05 for each). Factors associated with DM include PSA DT <6 mo,

Objectives: Evaluate outcomes of patients with recurrent or metastatic (R/M) head and neck squamous cell carcinoma (HNSCC) treated with immunotherapy (IO). Methods: Among patients with R/M HNSCC treated with IO in this retrospective single-institution cohort, Cox regression was used to compare overall survival (OS) for those with platinum-refractory disease and those treated in the first-line setting with OS from KEYNOTE-040/048, respectively. Multivariable Cox regression was used to identify predictors of OS.Results: There was no significant OS difference for those treated in the platinum-refractory setting when compared to patients on KEYNOTE-040 (HR = 1.22, p = 0.27), nor for the first-line setting compared to KEYNOTE-048 (HR = 1.23, p = 0.19). ECOG-PS 1 (HR = 2.00, p = 0.02) and ECOG-PS 2 (HR = 3.13, p < 0.01) were associated with worse OS. Higher absolute lymphocyte count (ALC) was associated with improved OS (HR = 0.93 per 100 cells/μL, p = 0.03). Conclusions: Real-world outcomes of IO in R/M HNSCC are similar to outcomes in randomized control trials, with performance status and ALC correlating with OS.