26 research outputs found
Effects of chemotherapy-induced ovarian failure on bone and lipid metabolism in premenopausal breast cancer patients : Impact of adjuvant clodronate and tamoxifen
Luustolääkkeet estävät varhaisvaiheen rintasyöpää sairastavien murtumia ja parantavat taudin ennustetta
English summaryPeer reviewe
Nivolumab-associated pemphigoid-like blistering dermatosis after sun exposure
Non peer reviewe
Celiac disease in patients with severe liver disease: gluten-free diet may reverse hepatic failure
Peer reviewe
Eturauhassyöpää sairastavan potilaan luusto
Vertaisarvioitu.Eturauhassyöpä ja sen androgeenideprivaatiohoito (ADT) altistavat potilaan osteoporoosille ja luunmurtumille. Eturauhassyövän toteamisvaiheessa tulisi arvioida murtumariski ja aloittaa ainakin elintapahoitoon perustuva murtumien ehkäisy. Luustolääkkeiden käyttö ADT:hen liittyvän osteoporoosin hoidossa ei ole riittävästi vakiintunut. Luuhun levinnyt eturauhassyöpä voi aiheuttaa kipua, palliatiivisen sädehoidon tarvetta, murtumia tai selkäydinkompressiota. Näiden luustokomplikaatioiden estossa ja hoidossa käytetään bisfosfonaatteja ja denosumabia, mutta niiden hyöty on osoitettu vasta eturauhassyövän edettyä kastraatioresistenttiin vaiheeseen. Eturauhassyövän systeemihoitokin voi vähentää luuston haittatapahtumia. Luustoetäpesäkkeiden aiheuttamaa kipua lievitetään kipulääkkeiden lisäksi ulkoisella sädehoidolla.Peer reviewe
A graphical LASSO analysis of global quality of life, sub scales of the EORTC QLQ-C30 instrument and depression in early breast cancer
We aimed to (a) investigate the interplay between depression, symptoms and level of functioning, and (b) understand the paths through which they influence health related quality of life (QOL) during the first year of rehabilitation period of early breast cancer. A network analysis method was used. The population consisted of 487 women aged 35-68 years, who had recently completed adjuvant chemotherapy or started endocrine therapy for early breast cancer. At baseline and at the first year from randomization QOL, symptomatology and functioning by the EORTC QLQ-C30 and BR-23 questionnaires, and depression by the Finnish version of Beck's 13-item depression scale, were collected. The multivariate interplay between the related scales was analysed via regularized partial correlation networks (graphical LASSO). The median global quality of life (gQoL) at baseline was 69.9 +/- 19.0 (16.7-100) and improved to 74.9 +/- 19.0 (0-100) after 1 year. Scales related to mental health (emotional functioning, cognitive functioning, depression, insomnia, body image, future perspective) were clustered together at both time points. Fatigue was mediated through a different route, having the strongest connection with physical functioning and no direct connection with depression. Multiple paths existed connecting symptoms and functioning types with gQoL. Factors with the strongest connections to gQoL included: social functioning, depression and fatigue at baseline; emotional functioning and fatigue at month 12. Overall, the most important nodes were depression, gQoL and fatigue. The graphical LASSO network analysis revealed that scales related to fatigue and emotional health had the strongest associations to the EORTC QLQ-C30 gQoL score. When we plan interventions for patients with impaired QOL it is important to consider both psychological support and interventions that improve fatigue and physical function like exercise.Peer reviewe
Associations between Physical Exercise, Quality of Life, Psychological Symptoms and Treatment Side Effects in Early Breast Cancer
Peer reviewe
A graphical LASSO analysis of global quality of life, sub scales of the EORTC QLQ-C30 instrument and depression in early breast cancer
We aimed to (a) investigate the interplay between depression, symptoms and level of functioning, and (b) understand the paths through which they influence health related quality of life (QOL) during the first year of rehabilitation period of early breast cancer. A network analysis method was used. The population consisted of 487 women aged 35-68 years, who had recently completed adjuvant chemotherapy or started endocrine therapy for early breast cancer. At baseline and at the first year from randomization QOL, symptomatology and functioning by the EORTC QLQ-C30 and BR-23 questionnaires, and depression by the Finnish version of Beck's 13-item depression scale, were collected. The multivariate interplay between the related scales was analysed via regularized partial correlation networks (graphical LASSO). The median global quality of life (gQoL) at baseline was 69.9 +/- 19.0 (16.7-100) and improved to 74.9 +/- 19.0 (0-100) after 1 year. Scales related to mental health (emotional functioning, cognitive functioning, depression, insomnia, body image, future perspective) were clustered together at both time points. Fatigue was mediated through a different route, having the strongest connection with physical functioning and no direct connection with depression. Multiple paths existed connecting symptoms and functioning types with gQoL. Factors with the strongest connections to gQoL included: social functioning, depression and fatigue at baseline; emotional functioning and fatigue at month 12. Overall, the most important nodes were depression, gQoL and fatigue. The graphical LASSO network analysis revealed that scales related to fatigue and emotional health had the strongest associations to the EORTC QLQ-C30 gQoL score. When we plan interventions for patients with impaired QOL it is important to consider both psychological support and interventions that improve fatigue and physical function like exercise
Predicting Effective Adaptation to Breast Cancer to Help Women BOUNCE Back : Protocol for a Multicenter Clinical Pilot Study
Publisher Copyright: © 2022 Greta Pettini.Background: Despite the continued progress of medicine, dealing with breast cancer is becoming a major socioeconomic challenge, particularly due to its increasing incidence. The ability to better manage and adapt to the entire care process depends not only on the type of cancer but also on the patient's sociodemographic and psychological characteristics as well as on the social environment in which a person lives and interacts. Therefore, it is important to understand which factors may contribute to successful adaptation to breast cancer. To our knowledge, no studies have been performed on the combination effect of multiple psychological, biological, and functional variables in predicting the patient's ability to bounce back from a stressful life event,such as a breast cancer diagnosis. Here we describe the study protocol of a multicenter clinical study entitled "Predicting Effective Adaptation to Breast Cancer to Help Women to BOUNCE Back"or, in short, BOUNCE. Objective: The aim of the study is to build a quantitative mathematical model of factors associated with the capacity for optimal adjustment to cancer and to study resilience through the cancer continuum in a population of patients with breast cancer. Methods: A total of 660 women with breast cancer will be recruited from five European cancer centers in Italy, Finland, Israel, and Portugal. Biomedical and psychosocial variables will be collected using the Noona Healthcare platform. Psychosocial, sociodemographic, lifestyle, and clinical variables will be measured every 3 months, starting from presurgery assessment (ie, baseline) to 18 months after surgery. Temporal data mining, time-series prediction, sequence classification methods, clustering time-series data, and temporal association rules will be used to develop the predictive model. Results: The recruitment process stared in January 2019 and ended in November 2021. Preliminary results have been published in a scientific journal and are available for consultation on the BOUNCE project website. Data analysis and dissemination of the study results will be performed in 2022. Conclusions: This study will develop a predictive model that is able to describe individual resilience and identify different resilience trajectories along the care process. The results will allow the implementation of tailored interventions according to patients' needs, supported by eHealth technologies.Peer reviewe