Image-guided moderately hypofractionated radiotherapy for localized prostate cancer: a multicentric retrospective study (IPOPROMISE).

BACKGROUND: Moderate hypofractionated radiotherapy is a treatment option for the cure of localized prostate cancer (PCa) patients based on the results of randomized prospective trials, but there is a clinical concern about the relatively short length of follow-up, and real-world results on outcome and toxicity based on cutting-edge techniques are lacking. The objective of this study is to present the long-term results of a large multicentric series. MATERIALS AND METHODS: We retrospectively evaluated 1325 PCa patients treated with daily volumetric image-guided hypofractionated radiotherapy between 2007 and 2020 in 16 Centers. For survival endpoints, we used Kaplan-Meier survival curves and fitted univariate and multivariable Cox's proportional hazards regression models to study the association between the clinical variables and each survival type. RESULTS: At the end of the follow-up, 11 patients died from PCa. The 15-year values of cancer-specific survival (CSS) and biochemical relapse-free survival (b-RFS) were 98.5% (95%CI 97.3-99.6%) and 85.5% (95%CI 81.9-89.4%), respectively. The multivariate analysis showed that baseline PSA, Gleason score, and the use of androgen deprivation therapy were significant variables for all the outcomes. Acute gastrointestinal (GI) and genitourinary (GU) toxicities of grade ≥ 2 were 7.0% and 16.98%, respectively. The 15-year late grade ≥ 2 GI and GU toxicities were 5% (95%CI 4-6%) and 6% (95%CI 4-8%), respectively. CONCLUSION: Real-world long-term results of this multicentric study on cutting-edge techniques for the cure of localized PCa demonstrated an excellent biochemical-free survival rate of 85.5% at 15 years, and very low rates of ≥ G3 late GU and GI toxicity (1.6% and 0.9% respectively), strengthening the results of the available published trials.

The psychological impact of the covid-19 pandemic on radiotherapy cancer patients.

In March 2020, the World Health Organization (WHO) characterized the outbreak of the coronavirus disease 2019 (COVID-19) as a pandemic. The aim of this study was to evaluate the psychological impact of the COVID-19 pandemic on cancer patients undergoing radiotherapy. Were enrolled 210 patients in treatment and in follow-up who had access to the Radiation Oncology Department of the Campus Bio-Medico University Hospital Foundation between April and May 2020. The sample was subjected to structured interview and validated questionnaires. 37% of patients showed significant levels of distress; depressive symptoms were reported by 22.4% of patients and 99% of sample had clinically significant anxiety symptoms. All patients anxiety worsened during the COVID-19 pandemic (p=< 0.001). Patients on active treatment had higher levels of distress (3.5 vs 2.6; p = 0.04) and anxiety (3.5 vs 2.6; p = 0.04). Lung cancer patients appeared to be more afraid of COVID-19 than other patients (24.2 vs 22.2). This study highlights the presence of clinically significant anxiety in 99% of sample. This conclusion reflects the condition of emotional distress present during the pandemic which makes it necessary to treat patients in a multidisciplinary perspective that includes psychological support in the care plan.

Radiation-Induced Pneumonitis in the Era of the COVID-19 Pandemic: Artificial Intelligence for Differential Diagnosis.

(1) Aim: To test the performance of a deep learning algorithm in discriminating radiation therapy-related pneumonitis (RP) from COVID-19 pneumonia. (2) Methods: In this retrospective study, we enrolled three groups of subjects: pneumonia-free (control group), COVID-19 pneumonia and RP patients. CT images were analyzed by mean of an artificial intelligence (AI) algorithm based on a novel deep convolutional neural network structure. The cut-off value of risk probability of COVID-19 was 30%; values higher than 30% were classified as COVID-19 High Risk, and values below 30% as COVID-19 Low Risk. The statistical analysis included the Mann-Whitney U test (significance threshold at p < 0.05) and receiver operating characteristic (ROC) curve, with fitting performed using the maximum likelihood fit of a binormal model. (3) Results: Most patients presenting RP (66.7%) were classified by the algorithm as COVID-19 Low Risk. The algorithm showed high sensitivity but low specificity in the detection of RP against COVID-19 pneumonia (sensitivity = 97.0%, specificity = 2%, area under the curve (AUC = 0.72). The specificity increased when an estimated COVID-19 risk probability cut-off of 30% was applied (sensitivity 76%, specificity 63%, AUC = 0.84). (4) Conclusions: The deep learning algorithm was able to discriminate RP from COVID-19 pneumonia, classifying most RP cases as COVID-19 Low Risk.

Repeated courses of radiation treatment in an HER2-positive breast cancer patient with diffuse brain metastases: A case report.

In human epidermal growth factor receptor 2 (HER2+) expressing breast cancer subtype, the incidence of brain metastases is common and patients often die due to uncontrolled cranial disease. This is a case report of a HER2+ breast cancer woman with diffuse brain metastases that experienced long survival and clinical benefit from multiple radiotherapy treatments and combined systemic therapy, without increased toxicity.