A [18F]FDG PET based nomogram to predict cancer-associated cachexia and survival outcome: A multi-center study
- Yang Jiang 1, Mouqing Huang 2, Yufei Zhao 1, Jingyue Dai 1, Qingwen Yang 3, Xingzhe Tang 1, Xinxiang Li 1, Ying Cui 1, Jingqi Zhang 1, Jialu Sun 1, Lin Fu 1, Hui Mao 4, Xin-Gui Peng 5
- Yang Jiang 1, Mouqing Huang 2, Yufei Zhao 1
- 1Nurturing Center of Jiangsu Province for State Laboratory of AI Imaging & Interventional Radiology, Department of Radiology, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China.
- 2Department of Nuclear Medicine, Ganzhou People's Hospital, Ganzhou, China.
- 3Department of Internal Medicine, Ulm University & Ulm University Hospital, Ulm, Germany.
- 4Department of Radiology and Imaging Sciences, Emory University, Atlanta, Georgia, USA.
- 5Nurturing Center of Jiangsu Province for State Laboratory of AI Imaging & Interventional Radiology, Department of Radiology, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China; Department of Radiology, Nanjing Lishui People's Hospital, Zhongda Hospital Lishui Branch, Southeast University, Nanjing, China.
- 0Nurturing Center of Jiangsu Province for State Laboratory of AI Imaging & Interventional Radiology, Department of Radiology, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China.
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View abstract on PubMed
Summary
This summary is machine-generated.This study developed a nomogram using [<sup>18</sup>F]FDG PET scans and blood tests to predict cancer-associated cachexia. The tool also helps assess prognosis, offering valuable insights for patient care.
Area Of Science
- Oncology
- Nuclear Medicine
- Biochemistry
Background
- Cancer cachexia significantly worsens prognosis and survival in cancer patients.
- Early detection and accurate prognosis prediction for cachexia are critical clinical challenges.
Purpose Of The Study
- To develop and validate a nomogram integrating [<sup>18</sup>F]fluoro-2-deoxy-D-glucose ([<sup>18</sup>F]FDG) PET findings and clinical biochemistry for predicting cancer-associated cachexia.
- To assess the nomogram's prognostic value for overall survival in cancer patients.
Main Methods
- Retrospective analysis of 658 cancer patients from two centers.
- Logistic regression to identify predictors (age, hemoglobin, liver SUVmax, subcutaneous fat SUVmin).
- External validation of the nomogram using AUC, calibration, and decision curve analyses; Cox regression and Kaplan-Meier for survival analysis.
Main Results
- The combined nomogram demonstrated good predictive performance for cachexia (AUC=0.807 in development, 0.726 in validation).
- Key predictors included age, hemoglobin, maximum standardized uptake value (SUV) of the liver, and minimum SUV of subcutaneous fat.
- The nomogram effectively categorized overall survival, indicating prognostic value.
Conclusions
- A nomogram integrating [<sup>18</sup>F]FDG PET data and routine blood tests can effectively predict cancer-associated cachexia.
- This tool aids in assessing cachexia and its impact on cancer patient prognosis.
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