Impact of Severe Winter Weather on Operations of a Radiation Oncology Department.

Purpose: During winter 2022, western New York faced 2 major storms with blizzard conditions and record-breaking snowfall. The severe weather resulted in power outages and travel bans. This study investigates the impact of these conditions on patient adherence to radiation therapy. Combining data from a large academic center and its satellite clinic, this single-center study sheds light on the challenges faced by cancer care facilities during severe weather and proposes suggestions to prevent and mitigate harm done by severe weather. Methods and Materials: In this study, data were collected using the MOSAIQ Record and Verify system (v. 2.81) to generate deidentified reports of scheduled and treated patients. The treatment adherence rate was calculated by dividing the number of patients treated by the total number of patients scheduled. Data were specifically collected for patients undergoing treatment on linear accelerators at a primary academic center and a satellite facility. The study focused on working days from November 1, 2022, to March 31, 2023, excluding weekends and holidays (as treatments are not routinely scheduled). Severe weather days were identified using advisories from the National Weather Service and the local institution, including specific periods in November, December, and January. Results: In the study, 15,010 scheduled treatment visits were recorded across the academic center and the satellite clinic. The mean daily treatment adherence rate was 91.7%. Severe weather conditions led to a significant reduction in adherence, with rates dropping to 77.8%. Adherence rates during nonsevere weather days were notably higher at 93.9%. Statistical analysis confirmed the substantial influence of severe weather on adherence (P < .001). Severe weather had a more pronounced impact on the satellite clinic during periods of severe weather, with absolute reduction in adherence rates of 21.9% versus 15% in the primary hospital. Moreover, adherence at the satellite clinic was lower than at the primary hospital site even under standard operating conditions (92.2% vs 94.0%, P < .001). Conclusion: As a part of operational planning, it is important to be aware how severe weather can impact treatment adherence. Study findings underscore the importance of proactive measures to ensure patient access to health care services during adverse weather events and highlight the broader significance of incorporating consideration of social determinants of health into contingency planning for maintaining treatment continuity.

Navigating the global IV contrast shortage: The experience of a comprehensive cancer center.

PURPOSE/OBJECTIVE(S): In March 2022, a COVID-19 associated lockdown at an intravenous (IV) contrast production facility resulted in global shortages. We report our experience as a comprehensive cancer center navigating the IV contrast shortage. METHODS: A triage prioritization system was developed to serve as a guideline for ordering clinicians to reduce contrast use. The triage team reviewed all requests and made final determination based on patient history, treatment plan, prior imaging, possible alternative modalities, and competing requests. RESULTS: Our institution performed a median of 194 CT studies per day. Contrast utilization as a percentage of all CTs ordered was approximately 80% prior to the shortage, nadired at 9% during peak shortage, and has since returned to pre-shortage levels. Over the study period, 132 requests were reviewed. Fifty studies (38%) were approved by the team for contrast administration, 56 (42%) were recommended to be performed without contrast, 15 (11%) for a change in modality, and 11 (8%) were felt suitable for delay. There was overall general concordance between the recommendations of the triage team and studies conducted without significant distributional differences (χ2 = 4.004, two-tailed p = 0.2610). CONCLUSION: The concept of resilience involves the development of system-based practices that allow for sustained operations during periods of sudden change, or loss of critical supplies. The effort to optimally allocate limited supply of contrast was an extensive effort across the organization including from senior leadership, IT, radiology, nursing, physicians, and APPs. Concepts from heuristics and behavioral science can aid the conservation of a scarce resource. Decisions made by the team appeared to be sound without any known patient harm associated with a lack of contrast.

Process Modeling a Radiation Oncology Clinic Workflow From Therapeutic Simulation to Treatment: Identifying Impending Strain and Possible Treatment Delays.

Purpose: The administration of safe, high-quality radiation therapy requires the systematic completion of a series of steps from computed tomography simulation, physician contouring, dosimetric treatment planning, pretreatment quality assurance, plan verification, and, ultimately, treatment delivery. Nevertheless, due consideration to the cumulative time required to complete each of these steps is often not given sufficient attention when determining patient start date. We set out to understand the systemic dynamics as to how varying patient arrival rate can affect treatment turnaround times using Monte Carlo simulations. Methods and Materials: We developed a process model workflow for a single physician, single linear accelerator clinic that simulated arrival rates and processing times for patients undergoing radiation treatment using the AnyLogic Simulation Modeling software (AnyLogic 8 University edition, v8.7.9). We varied the new patient arrival rate from 1 to 10 patients per week to understand the effect of treatment turnaround times from simulation to treatment. We used processing-time estimates determined in prior focus studies for each of the required steps. Results: Altering the number of patients simulated from 1 per week to 10 per week resulted in a corresponding increase in average processing time from simulation to treatment from 4 to 7 days. The maximum processing time for patients from simulation to treatment ranged from 6 to 12 days. To compare individual distributions, we used the Kolmogorov-Smirnov statistical test. We found that altering the arrival rate from 4 patients per week to 5 patients per week resulted in a statistically significant change in the distributions of processing times (P = .03). Conclusions: The results of this simulation-based modeling study confirm the appropriateness of current staffing levels to ensure timely patient delivery while minimizing staff burnout. Simulation modeling can help guide staffing and workflow models to ensure timely treatment delivery while ensuring quality and safety.

Departmental quality initiative to establish turnaround times from simulation to treatment.

INTRODUCTION: The process of treatment delivery involves a series of steps from patient evaluation, therapeutic simulation (simulation), followed by dosimetric treatment planning, pre-treatment quality assurance and plan verification, and ultimately treatment delivery. Each step has a strict precedence relationship, requiring the preceding task to be completed prior to the initiation of the next task. The minimum time for a patient to undergo treatment is based on the summation of times of the individual tasks. Nevertheless, patients are often scheduled based on factors that do not directly consider the overall time required to complete these steps. MATERIALS AND METHODS: To better help in scheduling patients and to ensure quality and safety of treatment planning and delivery, we undertook a quality initiative based on team members tabulating time required to complete tasks required for treatment delivery. We established "fastest possible" turnaround times based how quickly a task could be accomplished if there were minimal or no competing obligations, as well as processing times under routine operating conditions. RESULTS: For urgent situations, we found that our center can accommodate treatment within 24 h. For routine plans using 3D conformal radiation, an approximately 1-week turnaround time is needed. For patients being treated with IMRT/VMAT an approximately 2-week turnaround time is needed. CONCLUSIONS: The growing complexity of radiotherapy delivery also requires additional steps which has increased turnaround times from simulation to treatment compared to historical standards. We report our estimates for turnaround time based on plan type and acuity level. While our turnaround times may not be applicable to all centers, we believe that this exercise was helpful to facilitate inter- and intra- departmental communication regarding reasonable start times for patients.

Testicular, Spermatic Cord, and Scrotal Soft Tissue Sarcomas: Treatment Outcomes and Patterns of Failure.

INTRODUCTION: Paratesticular sarcomas are defined as tumors that arise within the scrotum and include the subsites of epididymis, spermatic cord, and tunica vaginalis and represent the most common type of GU sarcoma. The mainstay of treatment is often surgical resection, combined with histology specific chemotherapy and radiotherapy. Due to the rare nature of the disease, there are limited data to guide management. We present our single-institution retrospective experience regarding the management and treatment of paratesticular sarcomas. MATERIALS AND METHODS: We queried our oncology registry database for patients treated for testicular, spermatic cord, and scrotal soft tissue sarcomas between 1971 and 2017. Patients in this series had pathological confirmation of a sarcoma diagnosis by a sarcoma-specialized pathologist. Only patients with localized disease were included in this analysis with the exception of patients with a diagnosis of rhabdomyosarcoma where patients with both localized and metastatic disease were included on this study. RESULTS: A total of 34 patients were included in this retrospective analysis. The median was 24 (range, 5-78), and the median tumor size was 6.25 cm. Twenty-six patients had localized disease (76.6%) at the time of diagnosis. A predominance of patients had tumors involving the spermatic cord (45.5%), and the most common histology was rhabdomyosarcoma (35.3%), leiomyosarcoma (26.5%), and well-differentiated liposarcoma (23.5%). The median follow-up was 71.0 months (range, 2.5-534.4 months). A total of 7 patients experienced an isolated local failure (20.6%), four patients developed distant metastatic disease (11.8%), and one patient (2.9%) with synovial sarcoma of the spermatic cord experienced a regional recurrence. The median progression-free survival (PFS) was 99.6 months, 95% CI (45.8-534.3 months), with a three-year PFS rate of 71%, 95% CI (53%-83%), and a 5-year PFS rate of 64% (range, 46%-78%). We did not find any statistically significant associations based on surgery type (p=0.15), the use of chemotherapy, (p=0.36), or final margin status (p=0.21). Two patients who were treated with preoperative radiotherapy had significant wound healing complication with chronic sinus tracts, though these patients did not experience a local recurrence. CONCLUSIONS: We provide a characterization of the natural history and treatment patterns of paratesticular sarcomas. While effective at reducing a local recurrence, preoperative radiotherapy was associated with significant toxicity. As a result, we prefer the use of postoperative radiotherapy in patients as clinically indicated. We did not find any specific treatment patterns associated with an improvement in clinical outcomes.

Evaluation of radiation treatment volumes for unknown primaries of the head and neck in the era of FDG PET.

OBJECTIVES: Positron-emission tomography (PET) has improved identification of the primary tumor as well as occult nodal burden in cancer of the head and neck. Nevertheless, there are still patients where the primary tumor cannot be located. In these situations, the standard of care is comprehensive head and neck radiation therapy however it is unclear whether this is necessary. This study examines the effects of radiation treatment volume on outcomes among using data from two cancer centers in unknown primary carcinoma of the head and neck. METHODS: Patients received unilateral (n = 34), or bilateral radiation (n = 28). Patient factors such as age, gender, smoking history, and patterns of failure were compared using Mann Whitney U and Chi Square. Overall survival (OS) and disease free survival (DFS) trends were estimated using Kaplan-Meier survival curves. Effect of treatment volume on survival was examined using multivariate cox proportional hazard regression model. RESULTS: No significant differences were observed in the frequency of local (p = 0.32), regional (p = 0.50), or distant (p = 0.76) failures between unilateral and bilateral radiation therapy. By Kaplan-Meier estimates, OS (3-year OS bilateral = 71.67%, unilateral = 77.90%, p = 0.50) and DFS (3-year DFS bilateral = 77.92%, unilateral = 69.43%, p = 0.63) were similar between the two treatment approaches. Lastly, multivariate analysis did not demonstrate any significant differences in outcome by treatment volumes (OS: HR = 0.74, 95% CI: 0.31, 1.81, p = 0.51; DFS: HR: 0.68, 95% CI: 0.24, 1.93, p = 0.47). CONCLUSIONS: Unilateral radiation therapy compared with bilateral produced similar survival.

Cancer cachexia and treatment toxicity.

PURPOSE OF REVIEW: Cancer cachexia is a metabolic disturbance resulting in a loss of skeletal muscle mass that is generally not reversed through traditional nutritional interventions. We review on both the impact of nutritional status on cancer treatment side effects, as well as cancer- specific outcomes. RECENT FINDINGS: Cancer-specific cachexia and sarcopenia are associated with increased treatment-associated toxicity, and overall worse cancer-specific outcomes across all cancer types in surgical, chemotherapeutic, and radiotherapeutic populations. Despite the fact that cancer cachexia is generally thought to be irreversible, there is some evidence that nutritional intervention can be helpful. SUMMARY: Nutritional status is an important factor to consider in determining cancer therapy. Patients with poor nutritional status should be identified prior to the initiation of therapy and be monitored judiciously.

The Lessons Learned from Patients We Didn't Help.

This short narrative is a reflection of an unintended, adverse outcome, and the lessons to be learned.

Myxoid Liposarcoma: Treatment Outcomes from Chemotherapy and Radiation Therapy.

INTRODUCTION: Myxoid liposarcoma (MLS) is a subtype of liposarcoma characterized morphologically by lipomatous differentiation with a myxoid stroma. The purpose of this study was to review clinical and pathological information for patients treated for MLS at our institution to better understand neoadjuvant and adjuvant therapy. MATERIALS AND METHODS: An institutional database of sarcomas was queried for patients who were treated for MLS at our institution between 1992 and 2013. Survival curves were constructed using Kaplan-Meier analysis, and univariate and multivariate statistics were performed using the Cox-proportional hazards model and using linear regression. RESULTS: A total of 85 patients with myxoid liposarcoma were identified. The mean and median histologic response rate to treatment for patients who received preoperative radiation therapy was 77.6%. Five-year disease-free survival, distant metastasis-free survival, local recurrence-free survival, and overall survival were 78.6% (95% CI: 67.8-86.1), 84.7% (95% CI: 74.5-91.0), 95.6% (95% CI: 86.9-98.6), and 87.5% (95% CI: 77.2-93.3) respectively. On univariate analysis, there was a trend towards higher necrosis or treatment response rates in patients who received concurrent chemotherapy, 84.7% (95% CI: 75.9-93.4) and 69.5% (95% CI: 55.1-83.8), p=0.061. Tumor size was associated with inferior disease-free and overall survival. Hazard ratio for disease-free survival is 1.08 (per cm) (95% CI: 1.01-1.16), p=0.019. CONCLUSIONS: Myxoid liposarcoma exhibits histological response to chemotherapy and radiation therapy. Tumor size appears to be greatest predictor of long-term disease control and overall survival. We were not able to show that chemotherapy provides a clinical benefit with regard to local control, disease-free survival, or overall survival. However, it is important to note that the selected usage of chemotherapy in the highest risk patients confounds this analysis. Further investigation is needed to help better determine the optimal use of chemotherapy in this group of patients.