Objective: Prognostic awareness is essential for making treatment decisions in malignant diseases. Being confronted with a poor prognosis, however, can affect patients' mental health. Therefore, it is important to study coping in the context of malignant diseases. Acceptance is an adaptive coping strategy associated with less psychological distress. This study sought to explore the facilitators and barriers for prognostic acceptance in a sample in which both hope and uncertainty regarding prognosis are pronounced: multiple myeloma patients.
Methods: In a German university hospital, 20 multiple myeloma patients participated in semistructured interviews. Following thematic content analysis by Kuckartz, the interview transcripts were coded for facilitators and barriers for prognostic acceptance. Additionally, patients completed questionnaires on prognostic awareness and sociodemographic characteristics.
Results: Patients described the following facilitators for prognostic acceptance: social support, positive thinking, focusing on the Here and Now, proactive confrontation, having little to no symptoms, and being there for others. The indicated barriers were distressing physical symptoms and restricted functioning, social distress, and additional distress from other areas of life.
Conclusions: Patients reported a variety of factors-related to the social realm, symptom burden, and specific attitudes-that help or hinder them in accepting their prognosis. Oncologists and psycho-oncologists may support prognostic acceptance by encouraging patients to both actively deal with realistic information as well as enjoy pleasant and meaningful moments in the present during which the disease and its prognosis recedes into the background.
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http://dx.doi.org/10.1002/pon.5535 | DOI Listing |
J Inflamm Res
January 2025
Department of Clinical Laboratory, National Center for Respiratory Medicine, National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, 510140, People's Republic of China.
Background: Rejection hinders long-term survival in lung transplantation, and no widely accepted biomarkers exist to predict rejection risk. This study aimed to develop and validate a prognostic model using laboratory data to predict the time to first rejection episode in lung transplant recipients.
Methods: Data from 160 lung transplant recipients were retrospectively collected.
Sisli Etfal Hastan Tip Bul
December 2024
Department of Radiation Oncology, University of Health Sciences Türkiye, Sisli Hamidiye Etfal Training and Research Hospital, Istanbul, Türkiye.
Objectives: Nonsmall cell lung cancer (NSCLC) accounts for about 85% of all lung cancers. Asymmetric dimethylarginine (ADMA) is an emerging molecule that is highlighted in carcinogenesis and tumor progression in lung cancer. Since elevated concentrations of ADMA are observed in lung cancer patients, we aimed to explore its associations with inflammation markers and established prognostic indices.
View Article and Find Full Text PDFRadiol Artif Intell
January 2025
From the Department of Radiation Oncology, State Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, 651 Dongfeng Road East, Guangzhou 510060, P. R. China (J.K., C.F.W., Z.H.C., G.Q.Z., Y.Q.W., L.L., Y.S.); Department of Radiation Therapy, Nanhai People's Hospital, The Sixth Affiliated Hospital, South China University of Technology, Foshan, China (J.Y.P., L.J.L.); and Department of Electronic Engineering, Information School, Yunnan University, Kunming, China (W.B.L.).
Purpose To develop and evaluate a deep learning-based prognostic model for predicting survival in locoregionally- advanced nasopharyngeal carcinoma (LA-NPC) using serial MRI before and after induction chemotherapy (IC). Materials and Methods This multicenter retrospective study included 1039 LA-NPC patients (779 male, 260 female, mean age 44 [standard deviation: 11]) diagnosed between April 2009 and December 2015. A radiomics- clinical prognostic model (Model RC) was developed using pre-and post-IC MRI and other clinical factors using graph convolutional neural networks (GCN).
View Article and Find Full Text PDFEur J Med Res
January 2025
Division of Radiology, Saraburi Hospital, Saraburi, Thailand.
Introduction: Stroke-associated pneumonia (SAP) is a major cause of mortality during the acute phase of stroke. The ADS score is widely used to predict SAP risk but does not include 24-h non-contrast computed tomography-Alberta Stroke Program Early CT Score (NCCT-ASPECTS) or red cell distribution width (RDW). We aim to evaluate the added prognostic value of incorporating 24-h NCCT-ASPECTS and RDW into the ADS score and to develop a novel prediction model for SAP following thrombolysis.
View Article and Find Full Text PDFPLoS One
January 2025
Regional Health System Office, National University Health System, Singapore, Singapore.
Introduction: The population is heterogeneous with varying levels of healthcare needs. Clustering individuals into health segments with more homogeneous healthcare needs allows for better understanding and monitoring of health profiles in the population, which can support data-driven resource allocation.
Methods: Using the developed criteria, data from several of Singapore's national administrative datasets were used to classify individuals into the various health segments.
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