First-line cadonilimab plus chemotherapy in HER2-negative advanced gastric or gastroesophageal junction adenocarcinoma: a randomized, double-blind, phase 3 trial
A Novel Definition and Grading Diagnostic Criteria for Tumour‐Type‐Specific Comprehensive Cachexia Risk
Author Correction: First-line cadonilimab plus chemotherapy in HER2-negative advanced gastric or gastroesophageal junction adenocarcinoma: a randomized, double-blind, phase 3 trial
Corrigendum to “Identifying cancer cachexia in patients without weight loss information: machine learning approaches to address a real-world challenge” Am J Clin Nutr 116 (2022) 1229–1239
Hepatocellular carcinoma escapes immune surveillance through deceiving thymus into recalling peripheral activated CD8+ T cells
Explainable deep learning model WAL-net for individualised assessment of potentially reversible malnutrition in patients with cancer: a multicentre cohort study
WITHDRAWN: 2116P FS-1502 combined with serplulimab in patients with HER2 expression, locally advanced or metastatic gastric or gastroesophageal junction adenocarcinoma (GC/GEJ): An open-label, multicenter, phase II study
The potential of machine learning models to identify malnutrition diagnosed by GLIM combined with NRS-2002 in colorectal cancer patients without weight loss information
Association of possible sarcopenia with all-cause mortality in patients with solid cancer: A nationwide multicenter cohort study
Efficacy, Safety, and Population Pharmacokinetics of MW032 Compared With Denosumab for Solid Tumor–Related Bone Metastases
Value of the modified Patient‐Generated Subjective Global Assessment in indicating the need for nutrition intervention and predicting overall survival in patients with malignant tumors in at least two organs
Development and validation of an inflammatory biomarkers model to predict gastric cancer prognosis: a multi-center cohort study in China
Exploring the optimal indicator of short‐term peridiagnosis weight dynamics to predict cancer survival: A multicentre cohort study
Investigation on quality of life of hospitalized patients in China with digestive system malignancy
Safety and antitumour activity of cadonilimab, an anti-PD-1/CTLA-4 bispecific antibody, for patients with advanced solid tumours (COMPASSION-03): a multicentre, open-label, phase 1b/2 trial
Comparison of the performance of the GLIM criteria, PG-SGA and mPG-SGA in diagnosing malnutrition and predicting survival among lung cancer patients: A multicenter study
Sarcopenia prevalence in patients with cancer and association with adverse prognosis: A nationwide survey on common cancers
Ensemble learning system to identify nutritional risk and malnutrition in cancer patients without weight loss information
Comment on: “Triceps skinfold‐albumin index significantly predicts the prognosis of cancer cachexia: A multicentre cohort study” by Yin et al. ‐ the authors reply
Sex differences in the scored Patient-Generated Subjective Global Assessment in 19,528 cancer patients
Toripalimab plus chemotherapy in treatment-naïve, advanced esophageal squamous cell carcinoma (JUPITER-06): A multi-center phase 3 trial
A Randomized, Open-Label, Multicenter, Phase 3 Study of High-Dose Vitamin C Plus FOLFOX ± Bevacizumab versus FOLFOX ± Bevacizumab in Unresectable Untreated Metastatic Colorectal Cancer (VITALITY Study)
Identifying cancer cachexia in patients without weight loss information: machine learning approaches to address a real-world challenge
Reference values of low body mass index, mid-upper arm circumference, and calf circumference in cancer patients: A nationwide multicenter observational study
Triceps skinfold–albumin index significantly predicts the prognosis of cancer cachexia: A multicentre cohort study
SO-17 A randomized, open-label, multicenter, phase III study of high-dose vitamin C plus FOLFOX +/- bevacizumab versus FOLFOX +/- bevacizumab as first-line treatment in patients with unresectable metastatic colorectal cancer
De novo Creation and Assessment of a Prognostic Fat-Age-Inflammation Index “FAIN” in Patients With Cancer: A Multicenter Cohort Study
Scored-GLIM as an effective tool to assess nutrition status and predict survival in patients with cancer
A fusion decision system to identify and grade malnutrition in cancer patients: Machine learning reveals feasible workflow from representative real-world data
Development and validation of a Modified Patient‐Generated Subjective Global Assessment as a nutritional assessment tool in cancer patients