Novel Diagnostic and Prognostic Tools for Lung Cancer Cachexia: Based on Nutritional and Inflammatory Status

Chen-An Liu; Qi Zhang; Guo-Tian Ruan; Liu-Yi Shen; Hai-Lun Xie; Tong Liu; Meng Tang; Xi Zhang; Ming Yang; Chun-Lei Hu; Kang-Ping Zhang; Xiao-Yue Liu; Han-Ping Shi

doi:10.3389/fonc.2022.890745

Novel Diagnostic and Prognostic Tools for Lung Cancer Cachexia: Based on Nutritional and Inflammatory Status

Front Oncol. 2022 Jul 11:12:890745. doi: 10.3389/fonc.2022.890745. eCollection 2022.

Authors

Chen-An Liu^{1

2

3}, Qi Zhang^{1

2

3}, Guo-Tian Ruan^{1

2

3}, Liu-Yi Shen⁴, Hai-Lun Xie^{1

2

3}, Tong Liu^{1

2

3}, Meng Tang^{1

2

3}, Xi Zhang^{1

2

3}, Ming Yang^{1

2

3}, Chun-Lei Hu^{1

2

3}, Kang-Ping Zhang^{1

2

3}, Xiao-Yue Liu^{1

2

3}, Han-Ping Shi^{1

2

3}

Affiliations

¹ Department of Gastrointestinal Surgery, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
² Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
³ Key Laboratory of Cancer Food for Special Medical Purposes (FSMP) for State Market Regulation, Beijing, China.
⁴ Department of Pathology and Shanxi Key Laboratory of Carcinogenesis and Translational Research of Esophageal Cancer, Shanxi Medical University, Taiyuan, China.

Abstract

Background: Cachexia is one of the most common complications affecting lung cancer patients that seriously affects their quality-of-life and survival time. This study aimed to analyze the predictors and prognostic factors of lung cancer cachexia as well as to develop a convenient and accurate clinical prediction tool for oncologists.

Methods: In this multicenter cohort study, 4022 patients with lung cancer were retrospectively analyzed. The patients were randomly categorized into training and verification sets (7:3 ratio). Univariate and multivariate logistic regression analyses were performed to determine the risk factors of cachexia in patients with lung cancer. Cox regression analysis was applied to determine independent prognostic factors in the patients with lung cancer cachexia. Meanwhile, two nomograms were established and evaluated by time-dependent receiver operating characteristic curve, calibration curve, and decision curve analysis (DCA).

Results: Stage, serum albumin, ALI, anemia, and surgery were independent risk factors for cachexia in patients with lung cancer. Patients with lung cancer cachexia have a shorter survival time. Sex, stage, serum albumin, ALI, KPS score, and surgery served as independent prognostic factors for patients with lung cancer cachexia. The area under the curves (AUCs) of diagnostic nomogram in the training and validation sets were 0.702 and 0.688, respectively, the AUCs of prognostic nomogram in the training set for 1-, 3-, and 5-year were 0.70, 0.72, and 0.75, respectively, while in the validation set the AUCs were 0.71, 0.75, and 0.79, respectively. The calibration curves and DCA of the two nomograms were consistent and the clinical benefit rate was high.

Conclusion: Cachexia brings an additional economic burden and worsens the prognosis of lung cancer patients. The two nomograms can accurately screen and predict the probability of occurrence of cachexia in lung cancer and the prognosis of patients with lung cancer cachexia, and guide clinical work.

Keywords: Inflammation; cachexia; lung cancer; nomogram; nutrition; prognosis.