Quality of life and decision regret in patients with late-hypothyroidism after radioiodine treatment for Graves' disease.

OBJECTIVE: Patients with Graves' disease often engage in shared decision-making to select an individualised treatment regimen from multiple options. Radioactive iodine (RAI) is one of the treatment choices for their condition, aims to improve quality of life and well-being. Likewise, dissatisfaction with treatment outcomes can result in decision regret. We employed validated questionnaires to assess the prospective quality of life, decision regret and relative factors involved in decision-making of patients with late hypothyroidism after RAI therapy. METHODS: A questionnaire survey was conducted among patients in hypothyroidism status for more than 1 year after RAI therapy. Disease-specific and generic QoL were assessed using the short form of thyroid-related patient-reported outcome (ThyPRO-39) questionnaire. Patient satisfaction regarding their decision to undergo RAI was assessed using the Decision Regret Scale (DRS) and patients were asked about the importance of relative factors in decision-making. RESULTS: Of 254 patients who responded to the survey, the mean age of patients was 45.3 years (range: 18-78 years) and the median time from RAI therapy to survey was 4 years (range: 1-30 years). Patients' median and mean DRS score were 34.4 and 38.8 (range: 0-100), respectively. A total of 100 (39.4%) patients express absent-to-mild regret (score: 0-25), 154 (60.6%) patients express moderate-to-severe regret (score: >25). The mean score of the absent-to-mild regret group were significantly higher than those of the moderate-to-severe regret group on most ThyPRO-39 scales. A statistically significant positive correlation was observed between DRS score and most ThyPRO-39 scale score. There was a significant positive association between higher DRS score and longer time intervals after RAI treatment, a brief duration of hyperthyroidism, and the significance of long-time outpatient follow-up. More decision regret was negatively associated Iodine-free diet, ineffectiveness of ATD, fear of surgery. CONCLUSION: Impairment of quality of life was positively correlated with decision regret in patients with late-hypothyroidism after radioiodine therapy. Patients with insufficient information support before decision-making are more likely to have higher decision regret after treatment. Our findings suggest that health providers should fully communicate with patients and provide information support in multiple dimensions during the shared-decision-making process.

Deep Learning Features and Metabolic Tumor Volume Based on PET/CT to Construct Risk Stratification in Non-small Cell Lung Cancer.

RATIONALE AND OBJECTIVES: To build a risk stratification by incorporating PET/CT-based deep learning features and whole-body metabolic tumor volume (MTVwb), which was to make predictions about overall survival (OS) and progression-free survival (PFS) for those with non-small cell lung cancer (NSCLC) as a complement to the TNM staging. MATERIALS AND METHODS: The study enrolled 590 patients with NSCLC (413 for training and 177 for testing). Features were extracted by employing a convolutional neural network. The combined risk stratification (CRS) was constructed by the selected features and MTVwb, which were contrasted and integrated with TNM staging. In the testing set, those were verified. RESULTS: Multivariate analysis revealed that CRS was an independent predictor of OS and PFS. C-indexes of the CRS demonstrated statistically significant increases in comparison to TNM staging, excepting predicting OS in the testing set (for OS, C-index=0.71 vs. 0.691 in the training set and 0.73 vs. 0.736 in the testing set; for PFS, C-index=0.702 vs. 0.686 in the training set and 0.732 vs. 0.71 in the testing set). The nomogram that combined CRS with TNM staging demonstrated the most superior model performance in the training and testing sets (C-index=0.741 and 0.771). CONCLUSION: The addition of CRS improves TNM staging's predictive power and shows potential as a useful tool to support physicians in making treatment decisions.