Factors Associated With and Characteristics of Patients Receiving Proton Therapy at the End of Life.

Purpose: To identify the characteristics, indications, and toxicities among patients receiving proton beam therapy (PBT) in the final year of life at an academic medical center. Materials and Methods: A retrospective review of patients who received PBT within the final 12 months of life was performed. Electronic medical records were reviewed for patient and treatment details from 2010 to 2019. Patients were followed from the start of PBT until death or last follow-up. Acute (3 months) toxicities were graded using the Common Terminology Criteria for Adverse Events v5.0. Imaging response was assessed using the Response Evaluation Criteria in Solid Tumors v1.1. The χ2 test was used to evaluate factors associated with palliative treatment. Simple logistic regression was used to evaluate factors associated with toxicity. Results: Bet299 patients were treated at the end of life (EOL) out of 5802 total patients treated with PBT (5.2%). Median age was 68 years (19-94 years), 58% male. The most common cancer was nonsmall cell lung cancer (27%). Patients were treated for symptom palliation alone (11%), durable control (57%), curative intent (16%), local recurrence (14%), or oligometastatic disease (2%). Forty-five percent received reirradiation. Median treatment time was 32 days (1-189 days). Acute toxicity was noted in 85% of the patients (31% G1, 53% G2, 15% G3). Thirteen patients (4%) experienced chronic toxicity. Breast and hematologic malignancy were associated with palliative intent χ2 (1, N = 14) = 17, P = .013; (χ2 (1, N = 14) = 18, P = .009). Conclusion: The number of patients treated with PBT at the EOL was low compared to all comers. Many of these patients received treatment with definitive doses and concurrent systemic therapy. Some patients spent a large portion of their remaining days on treatment. A prognostic indicator may better optimize patient selection for PBT at the EOL.

NCCN Guidelines® Insights: Merkel Cell Carcinoma, Version 1.2024.

The NCCN Guidelines for Merkel Cell Carcinoma (MCC) provide recommendations for diagnostic workup, clinical stage, and treatment options for patients. The panel meets annually to discuss updates to the guidelines based on comments from expert review from panel members, institutional review, as well as submissions from within NCCN and external organizations. These NCCN Guidelines Insights focus on the introduction of a new page for locally advanced disease in the setting of clinical node negative status, entitled "Clinical N0 Disease, Locally Advanced MCC." This new algorithm page addresses locally advanced disease, and the panel clarifies the meaning behind the term "nonsurgical" by further defining locally advanced disease. In addition, the guideline includes the management of in-transit disease and updates to the systemic therapy options.

Basal Cell Skin Cancer, Version 2.2024, NCCN Clinical Practice Guidelines in Oncology.

Basal cell carcinoma (BCC) is the most common form of skin cancer in the United States. Due to the high frequency, BCC occurrences are not typically recorded, and annual rates of incidence can only be estimated. Current estimated rates are 2 million Americans affected annually, and this continues to rise. Exposure to radiation, from either sunlight or previous medical therapy, is a key player in BCC development. BCC is not as aggressive as other skin cancers because it is less likely to metastasize. However, surgery and radiation are prevalent treatment options, therefore disfigurement and limitation of function are significant considerations. The NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines) outline an updated risk stratification and treatment options available for BCC.

Combining natural and artificial intelligence for robust automatic anatomy segmentation: Application in neck and thorax auto-contouring.

BACKGROUND: Automatic segmentation of 3D objects in computed tomography (CT) is challenging. Current methods, based mainly on artificial intelligence (AI) and end-to-end deep learning (DL) networks, are weak in garnering high-level anatomic information, which leads to compromised efficiency and robustness. This can be overcome by incorporating natural intelligence (NI) into AI methods via computational models of human anatomic knowledge. PURPOSE: We formulate a hybrid intelligence (HI) approach that integrates the complementary strengths of NI and AI for organ segmentation in CT images and illustrate performance in the application of radiation therapy (RT) planning via multisite clinical evaluation. METHODS: The system employs five modules: (i) body region recognition, which automatically trims a given image to a precisely defined target body region; (ii) NI-based automatic anatomy recognition object recognition (AAR-R), which performs object recognition in the trimmed image without DL and outputs a localized fuzzy model for each object; (iii) DL-based recognition (DL-R), which refines the coarse recognition results of AAR-R and outputs a stack of 2D bounding boxes (BBs) for each object; (iv) model morphing (MM), which deforms the AAR-R fuzzy model of each object guided by the BBs output by DL-R; and (v) DL-based delineation (DL-D), which employs the object containment information provided by MM to delineate each object. NI from (ii), AI from (i), (iii), and (v), and their combination from (iv) facilitate the HI system. RESULTS: The HI system was tested on 26 organs in neck and thorax body regions on CT images obtained prospectively from 464 patients in a study involving four RT centers. Data sets from one separate independent institution involving 125 patients were employed in training/model building for each of the two body regions, whereas 104 and 110 data sets from the 4 RT centers were utilized for testing on neck and thorax, respectively. In the testing data sets, 83% of the images had limitations such as streak artifacts, poor contrast, shape distortion, pathology, or implants. The contours output by the HI system were compared to contours drawn in clinical practice at the four RT centers by utilizing an independently established ground-truth set of contours as reference. Three sets of measures were employed: accuracy via Dice coefficient (DC) and Hausdorff boundary distance (HD), subjective clinical acceptability via a blinded reader study, and efficiency by measuring human time saved in contouring by the HI system. Overall, the HI system achieved a mean DC of 0.78 and 0.87 and a mean HD of 2.22 and 4.53 mm for neck and thorax, respectively. It significantly outperformed clinical contouring in accuracy and saved overall 70% of human time over clinical contouring time, whereas acceptability scores varied significantly from site to site for both auto-contours and clinically drawn contours. CONCLUSIONS: The HI system is observed to behave like an expert human in robustness in the contouring task but vastly more efficiently. It seems to use NI help where image information alone will not suffice to decide, first for the correct localization of the object and then for the precise delineation of the boundary.

NCCN Guidelines® Insights: Squamous Cell Skin Cancer, Version 1.2022.

The NCCN Guidelines for Squamous Cell Skin Cancer provide recommendations for diagnostic workup, clinical stage, and treatment options for patients with cutaneous squamous cell carcinoma. The NCCN panel meets annually to discuss updates to the guidelines based on comments from panel members and the Institutional Review, as well as submissions from within NCCN and external organizations. These NCCN Guidelines Insights focus on the introduction of a new surgical recommendation terminology (peripheral and deep en face margin assessment), as well as recent updates on topical prophylaxis, immunotherapy for regional and metastatic disease, and radiation therapy.

Introducing Multidisciplinary Oncology Management to the Medical Student.

Despite the fact that a large portion of medical students pursue training in a cancer-related discipline, oncology is emphasized to a disproportionately lesser extent than are other disciplines in medical school. Medical students have wide gaps in their oncology-specific knowledge, and undergraduate medical education fails to address the multidisciplinary nature of oncology. To address these shortcomings and improve medical students' understanding of the multidisciplinary nature of oncology, we have instituted a clinical oncology elective for medical students: an optional, 2-day session held after classes and promoted by student interest groups. Day 1 comprised a series of short faculty lectures beginning with the concepts of and rationale for staging, an approach to breaking bad news, guideline-based management, and multidisciplinary tumor board discussion. Three multidisciplinary tumor boards were simulated on the second day, run by attending surgeons, medical oncologists, and radiation oncologists with expertise in the cancer of interest, using real patient examples. Ultimately, the clinical oncology elective shows medical students how the oncology care team works together to care for cancer patients.

Comparative Effectiveness of Neoadjuvant Chemoradiation Versus Upfront Surgery in the Management of Recto-Sigmoid Junction Cancer.

INTRODUCTION: The optimal management of locally advanced recto-sigmoid cancer is unclear. Although some experts advocate for upfront surgery, others recommend neoadjuvant chemoradiation followed by surgery. We used the National Cancer Database to characterize patterns-of-care and overall survival (OS) associated with these treatment strategies. PATIENTS AND METHODS: Patients with clinical stage II or III recto-sigmoid cancer who underwent surgery with or without adjunctive chemotherapy and/or radiotherapy from 2006 to 2014 were identified, and dichotomized into: (1) upfront surgery, and (2) neoadjuvant chemoradiation cohorts. Patterns-of-care were assessed using multivariable logistic regression. The association between neoadjuvant chemoradiation use and OS was assessed using Cox proportional hazards analysis with propensity score-matching. RESULTS: Of 9313 identified patients, 6756 (73%) underwent upfront surgery and 2557 (27%) received neoadjuvant chemoradiation. Treatment at academic facilities and higher clinical T stage were predictors of neoadjuvant chemoradiation use. Compared with upfront surgery, neoadjuvant chemoradiation resulted in fewer positive circumferential resection margins (384 [11%] patients vs. 108 [8%] patients; P = .001), and 478 [18.7%] patients achieved a pathologic complete response at surgery. In propensity score-matched analysis, neoadjuvant chemoradiation use was associated with improved OS (hazard ratio, 0.79; 95% confidence interval, 0.69-0.90) compared with upfront surgery; 5-year estimated OS was 77.0% versus 72.0%, respectively. The improvement in OS persisted in landmark analysis of patients who survived at least 12 months. CONCLUSION: Only a small percentage of patients with locally advanced recto-sigmoid cancer receive neoadjuvant chemoradiation even though its use might result in improved OS relative to upfront surgery. Prospective research is warranted to validate and standardize therapeutic strategies in patients with recto-sigmoid cancer.