Search

Fatigue after breast cancer treatment is a common burden that is challenging to treat. The aim of this study was to explore if such integrated rehabilitation program reduces the prevalence of chronic fatigue compared to simple, non-integrated rehabilitation.

The aim of the study was to report on the experience in a single tertiary cancer center about the treatment and outcome of patients with Graves’ disease (GD) and metastatic thyroid cancer as compared with patients without GD in our country.

Tramadol is an opioid analgesic often used for pain management after breast cancer surgery. Its analgesic activity is due to the activation of the μ-opioid receptor, encoded by the OPRM1 gene. This study investigated the association of genetic variability in OPRM1 and its regulatory miRNA genes with outcomes of tramadol/paracetamol treatment after breast cancer surgery with axillary lymphadenectomy.

The development of high-resolution mapping models for forest attributes based on remote sensing data combined with machine or deep learning techniques has become a prominent topic in the field of forest observation and monitoring. This has resulted in the availability of multiple, sometimes conflicting, sources of information, but, at face value, it also makes it possible to learn about forest attribute uncertainty through the joint interpretation of multiple models. This article seeks to endorse the latter by utilizing the Bayesian model averaging approach to diagnose and interpret the differences between predictions from different models. The predictions in our case are forest canopy height estimations for metropolitan France arising from five different models. An independent reference dataset, containing four different definitions of forest height (dominant, mean, maximum, and Lorey's) was established based on around 5500 plots of the French National Forest Inventory (NFI), distributed across the entire area of interest. In this study, we evaluate models with respect to their probabilities of correctly predicting measurements or estimations obtained from NFI plots, highlighting the spatial variability in respective model probabilities across the study area. We observed significant variability in these probabilities depending on the forest height definition used, implying that the different models inadvertently predict different types of canopy height. We also present the respective inter-model and intra-model variance estimations, enabling us to grasp where the employed models have comparable contributions but contrasting predictions. We show that topography has an important impact on the models spread. Moreover, we observed that the forest stand vertical structure, the dominant tree species, and the type of forest ownership systematically emerge as statistically significant factors influencing the model divergences. Finally, we observed that the fitted higher-order mixtures, which enabled the presented analyses, do not necessarily reduce bias or prevent the saturation of the predicted heights observed in the individual models. [ABSTRACT FROM AUTHOR]

Objectives: Vocational rehabilitation plays a vital role in helping breast cancer survivors overcome physical, psychological, and occupational challenges, enabling a smoother return to work and improving quality of life. The aim of this study was to evaluate the effect of vocational rehabilitation as part of early integrated rehabilitation compared to conventional rehabilitation on sick leave duration, work ability, and disability rates. Methods: The study was designed as a prospective, interventional study. We enrolled 435 breast cancer patients, 211 patients in the control group, and 224 in the intervention group. The control group received the conventional rehabilitation as offered to breast cancer patients before the pilot study on individualized, integrated rehabilitation, while patients in the intervention group were referred for additional treatments and vocational rehabilitation. Results: There were no differences between the control and the intervention group of patients in terms of patient demographics, tumor size, disease stage, or oncologic treatment. However, compared to the control group, the intervention group had 50 days shorter sick leave (p = 0.002), better work ability (p < 0.001), and a lower proportion of patients with disabilities (p < 0.001) and better work ability (p < 0.001) one year after the beginning of cancer treatment. Vocational rehabilitation was likely associated with shorter sick leave (p < 0.069). Conclusions: Integrated rehabilitation was associated with shorter sick leave, and vocational rehabilitation was likely associated with shorter sick leave. Integrated rehabilitation was associated with improved work ability and disability rate. [ABSTRACT FROM AUTHOR]

Ovarian cancer is the seventh most common cancer in women worldwide and the eighth most common cause of cancer death. Due to the lack of effective early detection strategies and the unspecific onset of symptoms, it is diagnosed at an advanced stage in 75% of cases. The cancer antigen (CA) 125 is used as a prognostic marker and its level is elevated in more than 85% of women with advanced stages of epithelial ovarian cancer (EOC). The standard treatment is primary debulking surgery (PDS) followed by adjuvant chemotherapy (ACT), but the later approach is neoadjuvant chemotherapy (NACT) followed by interval debulking surgery (IDS). Several studies have been conducted to find out whether preoperative CA-125 serum levels influence treatment choice, surgical resection and survival outcome. The aim of our study was to analyse experience of single institution as Cancer comprehensive center with preoperative usefulness of CA-125.

Anaplastic thyroid cancer (ATC) is one of the most aggressive tumors. The aim of the study was to determine the correlation between a higher dietary intake of iodine, frequency of ATC and the characteristics of ATC, and to find out how often patients with ATC had a history of radioiodine (RAI) therapy.

The development of high-resolution mapping models for forest attributes based on remote sensing data combined with machine or deep learning techniques, has become a prominent topic in the field of forest observation and monitoring. This has resulted in an extensive availability of multiple sources of information, which can either lead to a potential confusion, or to the possibility to learn both about models and about forest attributes through the joint interpretation of multiple models. This article seeks to endorse the latter, by relying on the Bayesian model averaging (BMA) approach, which can be used to diagnose and interpret differences among predictions of different models. The predictions in our case are the forest canopy height estimations for the metropolitan France coming from five different models (Lang et al., 2023; Liu et al., 2023; Morin et al., 2022; Potapov et al., 2021; Schwartz et al., 2024). An independent reference dataset, containing four different definitions of the forest height (dominant, mean, maximum and Lorey's), comes from the French National Forest Inventory (NFI) providing some 5 500 plots used in the study, distributed across the entire area of interest. In this contribution, we line up the evoked models with respect to their probabilities to be the ones generating measurements/estimations at the NFI plots. Stratifying the probabilities based on French sylvo-ecological regions reveals spatial variation in the respective model probabilities across the area of interest. Furthermore, we observe significant variability in these probabilities depending on the forest height definition used. This leads us to infer that the different models inadvertently exhibit dominant predictions for different types of canopy height. We also present the respective inter-model and intra-model variance estimations, allowing us to come to understand where the employed models have comparable weights but contrasted predictions. We show that the mountainous terrain has an important impact on the models spread. Moreover, we observe that the forest stand vertical structure, the dominant tree species and the type of forest ownership systematically appear to be statistically significant factors influencing the models divergence. Finally, we demonstrate that the derived mixture models exhibit higher R 2 scores and lower RMSE values compared to individual models, although they may not necessarily exhibit lower biases. [ABSTRACT FROM AUTHOR]

Diabetes mellitus (DM) and DM related comorbidities may initiate difficulties during cancer specific treatment and may have an impact on cancer management and outcome. The aim of our study was to find out if DM in patients with advanced colorectal carcinoma (CRC) is associated with cancer-specific or overall survival.

Locoregional recurrence is common in patients with locally advanced differentiated thyroid carcinoma (DTC). Our aim was to find out the rate of locoregional control of the disease after external beam radiotherapy (EBRT) of the neck and mediastinum in patients with DTC and pT4 tumor.

Hurthle cells of the thyroid gland are very rich in mitochondria and oxidative enzymes. As a high level oxidative metabolism may lead to higher level of oxidative stress and can be associated with an increased risk for cancer, we investigated whether common functional polymorphisms in antioxidant genes (SOD2, CAT, GPX, GSTP1, GSTM1 and GSTT1) are associated with the development or clinical course of Hurthle cell thyroid carcinoma (HCTC).

Preoperative ultrasound (US) evaluation of central and lateral neck compartments is recommended for all patients undergoing a thyroidectomy for malignant or suspicious for malignancy cytologic or molecular findings. Our aim was to find out how frequent was recurrence in regional lymph nodes in patients with follicular or Hürthle cell neoplasm and usefulness of preoperative neck US investigation in patients with neoplasm.

Background. There is a paradigm that chemotherapy is ineffective in thyroid carcinoma. The aim of our study was to find out whether neoadjuvant chemotherapy before thyroid surgery had an effect on the size of primary tumour in patients with poorly differentiated thyroid carcinoma (PDTC) based on Turin proposal.