IntroductionTo establish risk factors for onset and progression of endometrioid endometrial cancer still remains the aim of scientists. The aim of the study was to determine disease-free survival (DFS) and overall survival (OS) in women with endometrioid endometrial cancer.Material and methodsA retrospective review of 142 patients with endometrioid endometrial cancer after surgery treated with adjuvant radiotherapy and/or chemotherapy in the Regional Cancer Centre in Lodz between 2002 and 2004 was performed. Clinical and pathological data were correlated with clinical outcome and survival.ResultsIn 3 patients (2.1%) clinical progression was diagnosed during the treatment. In 23 patients (16.7%) after primary remission, relapse was diagnosed 2-56 months after treatment. DFS and OS were 81.7% and 83.1% respectively. Better DFS significantly correlated with larger number of pregnancies (> 1), stage I of the disease and optimal surgery. Lower stage of disease, pelvic lymph node dissection, optimal surgery and depth of myometrial infiltration ≤ 50% were independent prognostic factors for better OS.ConclusionsThe results of our study provided significant evidence that early detection of endometrioid endometrial cancer enables optimal surgery. It reduces the indications for adjuvant therapy in stage I of the disease, and makes the prognosis significantly better. Other clinical and pathological factors such as numerous pregnancies, pelvic lymphadenectomy, and depth of myometrial infiltration, although important, are of less significance. Further prospective, randomized studies are necessary to prove the role of these factors.

We aimed to externally validate five normal tissue complication probability (NTCP) models for radiation-induced hypothyroidism (RIHT) in a prospectively recruited cohort of 108 patients with oropharyngeal cancer (OPC). NTCP scores were calculated using original published formulas. Plasma thyrotropin (TSH) level was additionally assessed in the short-term after RT. After a median of 28 months of follow-up, thirty one (28.7%) patients developed RIHT. Thyroid mean dose and thyroid volume were significant predictors of RIHT: odds ratio equal to 1.11 (95% CI 1.03–1.19) for mean thyroid dose and 0.87 (95%CI 0.81–0.93) for thyroid volume in univariate analyses. Two of the evaluated NTCP models, published by Rønjom et al. and by Boomsma et al., had satisfactory performance with accuracies of 0.87 (95%CI 0.79–0.93) and 0.84 (95%CI: 0.76–0.91), respectively. Three remaining models, by Cella et al., Bakhshandeh et al. and Vogelius et al., performed significantly worse, overestimating the risk of RIHT in this patient cohort. A short-term TSH level change relative to baseline was not indicative of RIHT development in the follow-up (OR 0.96, 95%CI: 0.65–1.42, p = 0.825). In conclusion, the models by Rønjom et al. and by Boomsma et al. demonstrated external validity and feasibility for long-term prediction of RIHT in survivors of OPC treated with Intensity-Modulated Radiation Therapy (IMRT).

IntroductionThe aim was to evaluate the risk of acute side effects in the lung after 3-dimensional conformal radiotherapy (3D-CRT) in patients treated for non-small cell lung cancer (NSCLC). An attempt was made to single out clinical factors and factors related to treatment technique which may induce acute post-radiation pneumonitis.Material and methodsThe analysis concerned 34 consecutive patients who underwent radical radiation therapy for NSCLC. Intensity of early toxicity was evaluated using modified RTOG/EORTC toxicity score. The endpoint for this analysis was the occurrence of radiation pneumonitis of grade 2 or higher. Factors related to treatment techniques were included in the statistical analysis.ResultsFifty-three percent of patients included in the study suffered from acute post-radiation pneumonitis. The results of the study revealed the existence of lung tissue sensitivity to low doses of ionizing radiation. The multivariate analysis showed that total lung volume receiving a low dose of 10 Gy increased the risk of post-radiation pneumonitis (p = 0.01).ConclusionsAcute post-radiation pneumonitis was a relevant clinical problem in patients who underwent radical radiotherapy for non-small cell lung cancer. The lung volume receiving a dose of 10 Gy was the most important dosimetric factor which influenced the post-radiation acute pneumonitis.

Severe xerostomia is noted in the majority of patients irradiated for oropharyngeal cancer. Extracellular microRNAs (miRNAs) may serve as effective tools allowing prediction of radiation-related toxicity. The aim of this study was to create an efficient prognostic miRNA-based test for severe, patient-rated xerostomia 3 months after primary treatment. Methods and Materials: This prospective study enrolled patients with oropharyngeal cancer treated between 2016 and 2018 in 3 centers in Poland. The primary endpoint was severe (grade ≥3) xerostomia as assessed by the European Organisation for

State-of-art normal tissue complication probability (NTCP) models do not take into account more complex individual anatomical variations, which can be objectively quantitated and compared in radiomic analysis. The goal of this project was development of radiomic NTCP model for radiation-induced hypothyroidism (RIHT) using imaging biomarkers (radiomics). We gathered CT images and clinical data from 98 patients, who underwent intensity-modulated radiation therapy (IMRT) for head and neck cancers with a planned total dose of 70.0 Gy (33–35 fractions). During the 28-month (median) follow-up 27 patients (28%) developed RIHT. For each patient, we extracted 1316 radiomic features from original and transformed images using manually contoured thyroid masks. Creating models based on clinical, radiomic features or a combination thereof, we considered 3 variants of data preprocessing. Based on their performance metrics (sensitivity, specificity), we picked best models for each variant ((0.8, 0.96), (0.9, 0.93), (0.9, 0.89) variant-wise) and compared them with external NTCP models ((0.82, 0.88), (0.82, 0.88), (0.76, 0.91)). We showed that radiomic-based models did not outperform state-of-art NTCP models (p > 0.05). The potential benefit of radiomic-based approach is that it is dose-independent, and models can be used prior to treatment planning allowing faster selection of susceptible population.