Porciello Giuseppe, Di Lauro Teresa, Luongo Assunta, Coluccia Sergio, Prete Melania, Abbadessa Ludovica, Coppola Elisabetta, Di Martino Annabella, Mozzillo Anna Licia, Racca Emanuela, Piccirillo Arianna, Di Giacomo Vittoria, Fontana Martina, D'Amico Maria, Palumbo Elvira, Vitale Sara, D'Errico Davide, Turrà Valeria, Parascandolo Ileana, Stallone Tiziana, Augustin Livia S A, Crispo Anna, Celentano Egidio, Pignata Sandro
Epidemiology and Biostatistics Unit, Istituto Nazionale Tumori IRCCS "Fondazione G. Pascale", 80131 Naples, Italy.
Department of Urology and Gynecology, Istituto Nazionale Tumori IRCCS "Fondazione G. Pascale", 80131 Naples, Italy.
Nutrients. 2025 Apr 18;17(8):1376. doi: 10.3390/nu17081376.
: Cancer and related treatments can impair body composition (BC), increasing the risk of malnutrition and sarcopenia, poor prognosis, and Health-Related Quality of Life (HRQoL). To enhance BC parameter interpretation through Bioelectrical Impedance Analysis (BIA), we developed a predictive model based on unsupervised approaches including Principal Component Analysis (PCA) and k-means clustering for sarcopenia risk in cancer patients at the Istituto Nazionale Tumori IRCCS "Fondazione G. Pascale" (Naples). : Sarcopenia and malnutrition risks were assessed using the NRS-2002 and SARC-F questionnaires, anthropometric measurements, and BIA. HRQoL was evaluated with the EORTC QLQ-C30 questionnaire. PCA and clustering analysis were performed to identify different BC profiles. Data from 879 cancer patients (mean age: 63 ± 12.5 years) were collected: 117 patients (13%) and 128 (15%) were at risk of malnutrition and sarcopenia, respectively. PCA analysis identified three main components, and k-means determined three clusters, namely HMP (High Muscle Profile), MMP (Moderate Muscle Profile), and LMP (Low Muscle Profile). Patients in LMP were older, with a higher prevalence of comorbidities, malnutrition, and sarcopenia. In the multivariable analysis, age, lung cancer site, diabetes, and malnutrition risk were significantly associated with an increased risk of sarcopenia; among the clusters, patients in LMP had an increased risk of sarcopenia (+62%, = 0.006). : The NUTRISCREEN project, part of the ONCOCAMP study (ClinicalTrials.gov ID: NCT06270602), provides a personalized nutritional pathway for early screening of malnutrition and sarcopenia. Using an unsupervised approach, we provide distinct BC profiles and valuable insights into the factors associated with sarcopenia risk. This approach in clinical practice could help define risk categories, ensure the most appropriate nutritional strategies, and improve patient outcomes by providing data-driven care.
癌症及相关治疗会损害身体成分（BC），增加营养不良、肌肉减少症、预后不良以及健康相关生活质量（HRQoL）下降的风险。为了通过生物电阻抗分析（BIA）增强对BC参数的解读，我们在那不勒斯的国家肿瘤研究所IRCCS“G. Pascale基金会”，基于包括主成分分析（PCA）和k均值聚类在内的无监督方法，开发了一种预测癌症患者肌肉减少症风险的模型。使用NRS - 2002和SARC - F问卷、人体测量以及BIA评估肌肉减少症和营养不良风险。使用欧洲癌症研究与治疗组织QLQ - C30问卷评估HRQoL。进行PCA和聚类分析以识别不同的BC特征。收集了879例癌症患者的数据（平均年龄：63±12.5岁）：分别有117例患者（13%）和128例患者（15%）存在营养不良和肌肉减少症风险。PCA分析确定了三个主要成分，k均值聚类确定了三个类别，即高肌肉特征（HMP）、中等肌肉特征（MMP）和低肌肉特征（LMP）。LMP类别的患者年龄更大，合并症、营养不良和肌肉减少症的患病率更高。在多变量分析中，年龄、肺癌部位、糖尿病和营养不良风险与肌肉减少症风险增加显著相关；在各个类别中，LMP类别的患者肌肉减少症风险增加（+62%，P = 0.006）。NUTRISCREEN项目是ONCOCAMP研究的一部分（ClinicalTrials.gov标识符：NCT06270602），为营养不良和肌肉减少症的早期筛查提供个性化营养途径。通过无监督方法，我们提供了不同的BC特征以及与肌肉减少症风险相关因素的有价值见解。这种方法在临床实践中有助于定义风险类别，确保采取最合适的营养策略，并通过提供数据驱动的护理改善患者预后。
