R-CSS: A clinically applicable score to classify cachexia stages in patients with cancer undergoing intensity-modulated radiation therapy

Does Adjuvant Radiotherapy Enhance Survival in Intracranial Solitary Fibrous Tumor Patients?

OBJECTIVE

Intracranial solitary fibrous tumor is a rare central nervous system tumor that lacks a reliable prognostic clinical model. Uncertainty persists regarding the treatment outcomes of surgery and adjuvant radiotherapy (ART). To address this, we investigated the efficacy of ART and applied machine learning (ML) to develop accurate prognostic models.

METHODS

The Surveillance, Epidemiology, and End Results database was used for this study's analysis. To identify the prognostic variables, we conducted Cox regression analysis and constructed prognostic models using 5 ML algorithms to predict 5-year survival. A validation method incorporating the area under the curve of the receiver operating characteristic curve was used to validate the accuracy and reliability of the models. We investigated the role of ART and surgery using Kaplan-Meier survival analysis, competing risk analysis, and Bias Reduction through Analysis of Competing Events method.

RESULTS

The study population comprised 747 patients. Among them are 316 patients with "surgery" and 431 patients with "surgery + ART." The therapeutic groups showed significant differences in overall survival. Multivariate Cox regression analysis revealed that older age and surgery alone were poor prognostic factors. The most significant prognostic factors were the local tumor excision, followed by lobectomy and age.

CONCLUSIONS

Although ART did not lead to a substantial decrease in cancer-specific deaths, it did improve overall survival. This underscores the broader health benefits of ART, including effective management of comorbid conditions. Caution is advised when interpreting these survival benefits because of potential confounding factors in patient health and treatment management. Our web tool and ML models aid in clinical decision-making.

Toward a holistic understanding of cancer cachexia: Application of the human response to illness model

Cachexia is a commonly presenting multidimensional syndrome in individuals living with advanced cancer. Given its prevalence of between 50% and 80%, nurses are going to encounter individuals manifesting ongoing loss of skeletal muscle mass (with or without loss of fat mass) that can be partially but not entirely reversed by conventional nutritional support. Thus nurses require a comprehensive understanding of this complex clinical problem. Research suggests, however, that nurses receive minimal education about cachexia or its management. Limited understanding undermines the ability to confidently care for patients with cachexia and their families, thereby hampering effective practice. The human response to illness model provides nurses with an organizing framework to guide and make sense of their assessments in clinical practice when caring for patients with cancer cachexia and provides direction for appropriate intervention. This article illustrates the integration of the human response to illness model to clinical practice, thereby assisting nurses to develop a comprehensive understanding of the physiological, pathophysiological, behavioral, and experiential facets of cachexia in advanced cancer patients. Contemporary areas of further interest and research will be presented.