Plan quality assessment in clinical practice: Results of the 2020 ESTRO survey on plan complexity and robustness.

PURPOSE: Plan complexity and robustness are two essential aspects of treatment plan quality but there is a great variability in their management in clinical practice. This study reports the results of the 2020 ESTRO survey on plan complexity and robustness to identify needs and guide future discussions and consensus. METHODS: A survey was distributed online to ESTRO members. Plan complexity was defined as the modulation of machine parameters and increased uncertainty in dose calculation and delivery. Robustness was defined as a dose distribution's sensitivity towards errors stemming from treatment uncertainties, patient setup, or anatomical changes. RESULTS: A total of 126 radiotherapy centres from 33 countries participated, 95 of them (75%) from Europe and Central Asia. The majority controlled and evaluated plan complexity using monitor units (56 centres) and aperture shapes (38 centres). To control robustness, 98 (97% of question responses) photon and 5 (50%) proton centres used PTV margins for plan optimization while 75 (94%) and 5 (50%), respectively, used margins for plan evaluation. Seventeen (21%) photon and 8 (80%) proton centres used robust optimisation, while 10 (13%) and 8 (80%), respectively, used robust evaluation. Primary uncertainties considered were patient setup (photons and protons) and range calculation uncertainties (protons). Participants expressed the need for improved commercial tools to control and evaluate plan complexity and robustness. CONCLUSION: Clinical implementation of methods to control and evaluate plan complexity and robustness is very heterogeneous. Better tools are needed to manage complexity and robustness in treatment planning systems. International guidelines may promote harmonization.

The burden of readmission after discharge from necrotizing soft tissue infection.

BACKGROUND: The need for extensive surgical debridement with necrotizing soft tissue infections (NSTIs) may put patients at high risk for unplanned readmission. However, there is a paucity of data on the burden of readmission in patients afflicted with NSTI. We hypothesized that unplanned readmission would significantly contribute to the burden of disease after discharge from initial hospitalization. METHODS: The Nationwide Readmission Database was used to identify adults undergoing debridement for NSTI hospitalizations from 2010 to 2017. Risk factors for 90-day readmission were assessed by Cox proportional hazards regression. RESULTS: There were a total of 82,738 NSTI admissions during the study period, of which 25,076 (30.3%) underwent 90-day readmissions. Median time to readmission was 25 days (interquartile range, 9-49 days). Fragmentation of care, longer length of index stay (>2 weeks), and Medicaid status were independent risk factors for readmission. Median cost of a readmission was US $10,543. Readmission added 174,640 hospital days to episodes of care over the study period, resulting in an estimated financial burden of US $1.4 billion. CONCLUSION: Unplanned readmission caused by NSTIs is common and costly. Interventions that target patients at risk for readmission may help decrease the burden of disease. LEVEL OF EVIDENCE: Economic/Epidemiological, level IV.

Report dose-to-medium in clinical trials where available; a consensus from the Global Harmonisation Group to maximize consistency.

PURPOSE: To promote consistency in clinical trials by recommending a uniform framework as it relates to radiation transport and dose calculation in water versus in medium. METHODS: The Global Quality Assurance of Radiation Therapy Clinical Trials Harmonisation Group (GHG; www.rtqaharmonization.org) compared the differences between dose to water in water (Dw,w), dose to water in medium (Dw,m), and dose to medium in medium (Dm,m). This was done based on a review of historical frameworks, existing literature and standards, clinical issues in the context of clinical trials, and the trajectory of radiation dose calculations. Based on these factors, recommendations were developed. RESULTS: No framework was found to be ideal or perfect given the history, complexity, and current status of radiation therapy. Nevertheless, based on the evidence available, the GHG established a recommendation preferring dose to medium in medium (Dm,m). CONCLUSIONS: Dose to medium in medium (Dm,m) is the preferred dose calculation and reporting framework. If an institution's planning system can only calculate dose to water in water (Dw,w), this is acceptable.

Association of cardiac biomarkers and comorbidities with increased mortality, severity, and cardiac injury in COVID-19 patients: A meta-regression and decision tree analysis.

BACKGROUND: Coronavirus disease-2019 (COVID-19) has a deleterious effect on several systems, including the cardiovascular system. We aim to systematically explore the association of COVID-19 severity and mortality rate with the history of cardiovascular diseases and/or other comorbidities and cardiac injury laboratory markers. METHODS: The standardized mean difference (SMD) or odds ratio (OR) and 95% confidence intervals (CIs) were applied to estimate pooled results from the 56 studies. The prognostic performance of cardiac markers for predicting adverse outcomes and to select the best cutoff threshold was estimated by receiver operating characteristic curve analysis. Decision tree analysis by combining cardiac markers with demographic and clinical features was applied to predict mortality and severity in patients with COVID-19. RESULTS: A meta-analysis of 17 794 patients showed patients with high cardiac troponin I (OR = 5.22, 95% CI = 3.73-7.31, P < .001) and aspartate aminotransferase (AST) levels (OR = 3.64, 95% CI = 2.84-4.66, P < .001) were more likely to develop adverse outcomes. High troponin I more than 13.75 ng/L combined with either advanced age more than 60 years or elevated AST level more than 27.72 U/L was the best model to predict poor outcomes. CONCLUSIONS: COVID-19 severity and mortality are complicated by myocardial injury. Assessment of cardiac injury biomarkers may improve the identification of those patients at the highest risk and potentially lead to improved therapeutic approaches.