Objectives: The increasing survival of cancer patients is the result of early detection, improved treatment, and demographic change. This poses urgent questions regarding the stresses and needs for care long-term survivors face.
Methods: A literature survey (PubMed, Scopus) was conducted based on all publications with a psychooncological background from 2004 to 2008 concerning long-term survivors.
Results: Of the 164 publications found, 74 referred to breast cancer; 62 % came from the United States and only 4 % from Germany. Although overall quality of life among long-term survivors appears to be good, considerable adverse somatic effects (long-term effects, late consequences, recidivism, second tumors) and mental effects (e.g., fear of recurrence) persist. Somatic and psychosocial determinants of long-term adjustment, health behaviour, health care needs and utilization, and the quality of life of next-to-kin have hardly been studied. The effects of psychotherapy on survival remain controversial.
Conclusions: In light of the growing number of long-term surviving cancer patients, it is necessary to study their strains and needs for care under a lifespan perspective.
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http://dx.doi.org/10.13109/zptm.2009.55.4.365 | DOI Listing |
BMC Res Notes
January 2025
Department of Computer Engineering, Chungbuk National University, Chungdae-ro 1, Cheongju, 28644, Republic of Korea.
Background: Drug response prediction can infer the relationship between an individual's genetic profile and a drug, which can be used to determine the choice of treatment for an individual patient. Prediction of drug response is recently being performed using machine learning technology. However, high-throughput sequencing data produces thousands of features per patient.
View Article and Find Full Text PDFBiomark Res
January 2025
Department of Liver Surgery and Transplantation, Liver Cancer Institute and Zhongshan Hospital, Fudan University180 Fenglin Road, Shanghai, 200032, China.
Background: Predicting the efficacy of immune-based therapy in patients with unresectable hepatocellular carcinoma (HCC) remains a clinical challenge. This study aims to evaluate the prognostic value of the systemic immune-inflammation index (SII) in forecasting treatment response and survival outcomes for HCC patients undergoing immune-based therapy.
Methods: We analyzed a cohort of 268 HCC patients treated with immune-based therapy from January 2019 to March 2023.
J Transl Med
January 2025
Department of Stem Cell and Regenerative Medicine, Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, 400038, China.
Background: It is worthwhile to establish a prognostic prediction model based on microenvironment cells (MCs) infiltration and explore new treatment strategies for triple-negative breast cancer (TNBC).
Methods: The xCell algorithm was used to quantify the cellular components of the TNBC microenvironment based on bulk RNA sequencing (bulk RNA-seq) data. The MCs index (MCI) was constructed using the least absolute shrinkage and selection operator Cox (LASSO-Cox) regression analysis.
Chin Med
January 2025
Department of Neurobiology and Acupuncture Research, The Third Clinical Medical College, Key Laboratory of Acupuncture and Neurology of Zhejiang Province, Zhejiang Chinese Medical University, Hangzhou, China.
Background: Paclitaxel-induced peripheral neuropathy (PIPN) is prevalent among patients receiving paclitaxel chemotherapy, which results in sensory abnormality as well as neuropathic pain. Conventional medications lack effectiveness on PIPN. Clinical trials identified beneficial effects of acupuncture on PIPN among patients receiving chemotherapy.
View Article and Find Full Text PDFCancer Metab
January 2025
Department of Neurosurgery, Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, 250021, China.
Invasiveness of pituitary adenoma is the main cause of its poor prognosis, mechanism of which remains largely unknown. In this study, the differential proteins between invasive and non-invasive pituitary tumors (IPA and NIPA) were identified by TMT labeled quantitative proteomics. The differential metabolites in venous bloods from patients with IPA and NIPA were analyzed by untargeted metabolomics.
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