Development and validation of serological dynamic risk score to predict outcome in gastric cancer with adjuvant chemotherapy: a multicentre, longitudinal, cohort study

Linbin Lu; Wenzheng Fang; Jun Yu; Xianchun Gao; Xinlin Wang; Yan Pan; Weili Han; Junya Yan; Huahong Xie; Liping Yao; Jianjun Yang; Jianyong Zheng; Liu Hong; Jipeng Li; Mengbin Li; Lei Shang; Kaichun Wu; Gang Ji; Yongzhan Nie

doi:10.3389/fonc.2024.1327691

Development and validation of serological dynamic risk score to predict outcome in gastric cancer with adjuvant chemotherapy: a multicentre, longitudinal, cohort study

Front Oncol. 2024 Feb 20:14:1327691. doi: 10.3389/fonc.2024.1327691. eCollection 2024.

Authors

Linbin Lu^#¹, Wenzheng Fang^#^{2

3}, Jun Yu^#¹, Xianchun Gao¹, Xinlin Wang¹, Yan Pan¹, Weili Han¹, Junya Yan¹, Huahong Xie¹, Liping Yao¹, Jianjun Yang¹, Jianyong Zheng¹, Liu Hong¹, Jipeng Li¹, Mengbin Li¹, Lei Shang⁴, Kaichun Wu¹, Gang Ji¹, Yongzhan Nie¹

Affiliations

¹ State Key Laboratory of Holistic Integrative Management of Gastrointestinal Cancers and National Clinical Research Center for Digestive Diseases, Xijing Hospital of Digestive Diseases, Fourth Military Medical University, Xi'an, China.
² Department of Oncology, People's Hospital Affiliated to Fujian University of Traditional Chinese Medicine, Fuzhou, China.
³ Department of Oncology, the 900th Hospital of Joint Logistic Support Force, Chinese People's Liberation Army (PLA), Fuzong Clinical College of Fujian Medical University, Fuzhou, Fujian, China.
⁴ Department of Medical Statistics, School of Preventive Medicine, Fourth Military Medical University, Xi'an, China.

^# Contributed equally.

Abstract

Background: Baseline serological biomarkers have the potential to predict the benefits of adjuvant chemotherapy in patients with gastric cancer. However, the fluctuating nature of postoperative recurrence risk makes precise treatment challenging. We aimed to develop a risk score in real-time predicting outcomes for postoperative GC patients using blood chemistry tests.

Materials and methods: This was a retrospective, multicentre, longitudinal cohort study from three cancer centres in China, with a total of 2737 GC patients in the pTNM stage Ib to III. Among them, 1651 patients with at least two serological records were assigned to the training cohort. Model validation was carried out using separate testing data with area under curve (AUC). The least absolute shrinkage and selection operator (LASSO) and random forest-recursive feature elimination (RF-RFE) algorithm were used to select the parameters.

Results: The Cox regression model derived six risk factors to construct a composite score (low-risk: 0-2 score; high risk: 3-6 score), including CEA, CA125, CA199, haemoglobin, albumin, and neutrophil to lymphocyte ratio. The risk score accurately predicted mortality in 1000-time bootstrap (AUROCs:0.658; 95% CI: 0.645, 0.670), with the highest AUROC (0.767; 95% CI: 0.743, 0.791) after 1 year since the gastrectomy. In validation dataset, the risk score had an AUROC of 0.586 (95% CI 0.544, 0.628). Furthermore, patients with high risk at 1 month derived significant clinical benefits from adjuvant chemotherapy (P for interaction <0.0001). Compared with the low-low-low risk group, the low-low-high risk group of the long-term state chain (risk state at baseline, 6 months, 1 year) had the worse OS (HR, 6.91; 95%CI: 4.27, 11.19) and DFS (HR, 7.27; 95%CI: 4.55, 11.63).

Conclusion: The dynamic risk score is an accurate and user-friendly serological risk assessment tool for predicting outcomes and assisting clinical decisions after gastrectomy.

Keywords: adjuvant chemotherapy; gastrectomy; gastric cancer; predictive model; risk score; risk state chains.

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work was supported by the National Natural Science Foundation of China (82202837, 81730016, and 81972761), and the National Key R&D Program of China (Grant Nos. 2016YFC1303200, 2022YFC2505100, and 2017YFC0908300).