Reliable tools for prognosis prediction are crucially needed by oncologists so they can tailor individual treatments. However, the wide spectrum of histologies and prognostic behaviors of sarcomas challenges their development. In this field, nomograms could definitely better account for their granularity compared to the more widely used AJCC/UICC TNM staging system. Nomograms are predictive tools that incorporate multiple risk factors and return a numerical probability of a clinical event. Since the development of the first nomogram in 2002, several other nomograms have been built, either general, site-specific, histology-specific, or both. Recently, some new "dynamic" nomograms and prognostic tools have been developed, allowing doctors to "recalculate" a patient's prognosis by taking into account the time since primary surgery, the event history, and the potential time-dependent effect of covariates. Due to these new tools, prognosis prediction is no longer limited to the time of the first computation but can be adapted and recalculated based on the occurrence (or not) of any event as time passes from the first computation. In this review, we aimed to give an overview of the available nomograms for STS and to help clinicians in the process of selecting the best tool for each patient.
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http://dx.doi.org/10.3390/curroncol30040278 | DOI Listing |
Clin Nutr ESPEN
January 2025
Department of Clinical Nutrition, Daping Hospital, Army Medical University (Third Military Medical University), Chongqing, 400042, China; Chongqing Municipal Health Commission Key Laboratory of Intelligent Clinical Nutrition and Transformation, Chongqing, 400042, China. Electronic address:
Background: Acute pancreatitis (AP) is a common acute abdominal condition that can lead to severe complications. Malnutrition significantly impacts the prognosis of patients with AP, so effective tools are needed to identify those at high nutritional risk. This study validated the ability of the modified NUTRIC score to predict all-cause mortality and identify nutritional risk in patients with acute pancreatitis in the ICU.
View Article and Find Full Text PDFPLoS One
January 2025
College of Medicine, King Faisal University, Alahsa, Saudi Arabia.
Acute kidney injury (AKI) is a frequent clinical complication lacking early diagnostic tests and effective treatments. Novel biomarkers have shown promise for enabling earlier detection, risk stratification, and guiding management of AKI. We conducted a systematic review to synthesize evidence on the efficacy of novel biomarkers for AKI detection and management.
View Article and Find Full Text PDFJ Cardiovasc Surg (Torino)
February 2025
Department of Vascular Surgery, ASST Settelaghi Universitary Teaching Hospital, University of Insubria, Varese, Italy.
Optimizing the longevity of vascular access in hemodialysis patients remains a critical aspect of patient care, given the significant role of arteriovenous fistulas (AVFs) and arteriovenous grafts (AVGs) in enabling effective dialysis. Vascular access complications, such as stenosis, thrombosis, and cannulation-related damage, continue to challenge both the functionality and the sustainability of these access points. Recent advancements underscore the importance of a robust follow-up strategy, integrating clinical evaluations with diagnostic tools like color Doppler ultrasound (CDU) and emerging interventional approaches such as drug-coated balloon (DCB) angioplasty.
View Article and Find Full Text PDFNeurooncol Adv
January 2025
Department of Neurological Surgery, Weill Cornell Medicine, New York Presbyterian Hospital, New York, NY 10065, USA.
The blood-brain barrier (BBB) remains an obstacle for delivery of chemotherapeutic agents to gliomas. High grade and recurrent gliomas continue to portend a poor prognosis. Multiple methods of bypassing or manipulating the BBB have been explored, including hyperosmolar therapy, convection-enhanced delivery (CED), laser-guided interstitial thermal therapy (LITT), and Magnetic Resonance Guided Focused Ultrasound (MRgFUS) to enhance delivery of chemotherapeutic agents to glial neoplasms.
View Article and Find Full Text PDFFront Immunol
January 2025
Research Laboratory Center, Guizhou Provincial People's Hospital, Guiyang, Guizhou, China.
Background: The rising incidence of breast cancer and its heterogeneity necessitate precise tools for predicting patient prognosis and tailoring personalized treatments. Epigenetic changes play a critical role in breast cancer progression and therapy responses, providing a foundation for prognostic model development.
Methods: We developed the Machine Learning-derived Epigenetic Model (MLEM) to identify prognostic epigenetic gene patterns in breast cancer.
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