Construction of a nomogram for preoperative prediction of occult peritoneal metastasis in advanced gastric cancer based on circulating tumor cells and fibrinogen to albumin ratio

Discover Oncology https://doi.org/10.1007/s12672-026-05371-9 Article in Press Construction of a nomogram for preoperative prediction of occult peritoneal metastasis in advanced gastric cancer based on circulating tumor cells and fibrinogen to albumin ratio Zhipeng Wu, Cheng Zuo, Changlei Wu, Huakai Tian, Zhengming Zhu, Wenjie Zhu, Liang Sun & Zitao Liu Received: 9 January 2026 Accepted: 1 June 2026 Cite this article as: Wu Z., Zuo C., Wu C. et al. Construction of a nomogram for preoperative prediction of occult peritoneal metastasis in advanced gastric cancer based on circulating tumor cells and fibrinogen to albumin ratio. Discov Onc (2026). https://doi. org/10.1007/s12672-026-05371-9 A E R P S S We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply. 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To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/. ACCEPTED ARTICLEMANUSCRIPT IN PRESS Construction of a nomogram for preoperative prediction of occult peritoneal metastasis in advanced gastric cancer based on circulating tumor cells and fibrinogen to albumin ratio Zhipeng Wu1#, Cheng Zuo2#, Changlei Wu2#, Huakai Tian3, Zhengming Zhu2, Wenjie Zhu2*, Liang Sun2*, Zitao Liu2* 1 Department of Hepatobiliary Surgery, Jiangxi Province Hospital of Integrated Chinese & Western Medicine, Nanchang, Jiangxi Province, China. 2 Department of General Surgery, The Second Afffliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi Province, China. 3 Department of General Surgery, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi Province, China. # Zhipeng Wu, Cheng Zuo and Changlei Wu have contributed equally to this work. * Correspondence to: Zitao Liu, 1 MinDe Road, Nanchang 330006, China, . Abstract Background ： Occult peritoneal metastasis (OPM) represents a type of distant metastasis that is often overlooked during the preoperative diagnosis of advanced gastric cancer (AGC). Methods: We employed the negative enrichment combined with immunofluorescence in situ hybridization (imFISH) technique to detect the number of circulating tumor cells (CTC) in the peripheral blood of patients with AGC. 523 AGC patients were randomly divided into a training set (N=367) and a validation set (N=156) in a 7:3 ratio. We constructed a nomogram for predicting OPM risk through multivariate logistic regression. Finally, we evaluated the performance of the nomogram using multi-index cross-validation and clinical decision curve analysis (DCA). Results: The number of CTC and the level of the fibrinogen-to-albumin ratio (FAR) in patients with OPM positivity were significantly higher than those in OPM-negative patients. Multivariate logistic regression analysis revealed that CTC> 4/5 mL, FAR > 0.094, CA125> 35.000 U/mL, and tumor invasion of the serosal layer were identified as independent risk factors for OPM in AGC. The areas under the ROC curve of the nomogram in the training and validation sets were 0.898 and 0.823, respectively. After performing 100 iterations of 10-fold cross-validation, the goodness of fit (R²), area under the curve (AUC), Brier score, and maximum and minimum deviations from the ideal model (Emax and Eavg) all indicated that the nomogram exhibited good performance. Conclusions: The nomogram developed using CTCs and FAR enhances the early diagnosis of OPM and supports the formulation of personalized treatment plans for patients. Keywords: circulating tumor cells counts, FAR, occult peritoneal metastasis, advanced gastric cancer E L C I T R A IN S S E R P ACCEPTED ARTICLEMANUSCRIPT IN PRESS Introduction Peritoneal metastasis (PM) is the most common form of distant metastasis in advanced gastric cancer (AGC) and represents a significant factor contributing to poor patient prognosis(1). Currently, the clinical diagnosis of PM primarily relies on imaging methods such as CT and MRI. However, 10-30% of patients with AGC do not exhibit the typical imaging characteristics of PM preoperatively and are diagnosed with PM during surgery, a condition clinically referred to as occult peritoneal metastasis (OPM)(2). The prognosis for OPM patients is better than that for patients with imaging characteristics of PM, but worse than that for patients without PM(3). In recent years, with the continuous improvement of treatment regimens, including chemotherapy, targeted therapy, and immunotherapy, the prognosis for OPM patients has significantly improved(4-6). Some early-stage OPM patients even have the opportunity to achieve surgical cure following conversion therapy(7). Therefore, the early identification and diagnosis of OPM are crucial for improving patients' prognosis and quality of life. Recent studies have also developed several predictive models. However, most are based on radiomic results to evaluate the possibility of OPM through machine learning (8, 9). Due to the complexity of the radiomics analysis process, which includes image segmentation, feature extraction, and model establishment, there is a lack of unified standards across these stages, thereby limiting the clinical applicability of these models. Therefore, there is an urgent need to develop a non-invasive predictive model that is convenient for clinical use. Circulating tumor cells (CTC) are a primary method of liquid biopsy and can accurately reflect tumor burden(10). CTC refer to tumor cells that detach from the primary tumor site or metastatic lesions and enter the bloodstream(11). Previous studies have confirmed that CTC detection aids in the early diagnosis, prognosis, and evaluation of clinical treatment efficacy in cancer patients(11-14). For instance, Xie et al’s stud (...truncated)