Rectal cancer (RC) is among the most common malignancies of the digestive system, and its incidence and mortality rate are increasing worldwide (1). Surgical resection remains the primary treatment modality, and inadequate resection margins may contribute to disease recurrence (2). Pathological examination is still considered the gold standard for evaluating RC staging, and insufficient lymph node (LN) retrieval may compromise the accuracy of tumor staging (3). Multiple clinical guidelines recommend the retrieval of at least 12 LNs following surgery to ensure accurate staging and guide subsequent treatment decisions (4, 5).

Despite the widespread acceptance of this “12 LNs” standard, a considerable proportion of RC patients fail to meet this threshold in clinical practice (6). The number of LNs retrieved is influenced by a variety of factors including the surgical technique, pathological process, and patient-specific clinical characteristics (7–10). Although previous studies have explored the relationship between clinical variables and LN yield, comprehensive investigations specifically targeting RC patients remain limited.

The accurate identification of clinical factors affecting LN retrieval is crucial for both preoperative assessment and postoperative management (11–13). This information can assist surgeons in formulating more precise intraoperative strategies to maximize LN harvest; it may also help identify high-risk patients postoperatively and provide a basis for further therapeutic interventions. In this study, based on a through retrospective analysis of multiple clinical variables, we developed a simple and effective predictive tool to estimate the probability of retrieving 12 LNs in RC patients after surgery. This predictive model offers valuable insights for clinical evaluation and individualized treatment planning.

This retrospective study identified several key factors potentially influencing the likelihood of retrieving 12 LNs after RC surgery. These factors include age, T stage, N stage, CEA, CA19-9, tumor size, Hb level, and PLT. Based on these variables, we developed a predictive model and visualized it as a nomogram. The ROC curve, calibration curve, and DCA indicated that the model demonstrated good accuracy and strong clinical utility.

Previous studies on the prediction of LN yield are limited. Through a retrospective analysis of 1,375 RC patients, Zhang et al. found that age, tumor size, and CEA level were associated with the number of LNs retrieved (14), in alignment with our results. Similarly, Emile et al. conducted a retrospective analysis of 67,529 CRC patients and concluded that higher age and neoadjuvant chemoradiotherapy (nCRT) were major contributors to inadequate LN retrieval; in contrast, higher TNM stage, higher tumor grade, and minimally invasive surgery were associated with the successful retrieval of 12 LNs (15). In the current study, we also found that higher T and N stages were significant predictors of adequate LN yield. Retrieving at least 12 LNs has become a standard criterion for assessing postoperative treatment plans in CRC. However, patients who undergo nCRT may experience a reduced number of detectable LNs. Yang et al. retrospectively analyzed 257 RC patients who underwent laparoscopic radical resection after nCRT and found that retrieving fewer than 12 LNs did not negatively impact long-term survival (16). A similar conclusion was reached by Ryu and colleagues (17). Our current study lacks detailed preoperative treatment information, limiting the applicability of our model in patients who received nCRT. We recommend that clinicians individualize treatment strategies for these patients.

In the nomogram results, patients with elevated CA19–9 levels and low Hb levels scored higher in nomogram, suggesting these factors significantly influence LN yield. Patients with elevated CA19–9 levels were more likely to have ≥ 12 LNs retrieved than patients with normal or low CA19–9 levels. This implies that CA19–9 may not only reflect tumor biology, it may also be associated with lymphatic changes within the tumor microenvironment. Previous studies have linked elevated CA19–9 levels with tumor progression, local invasion, and distant metastasis (18–20). LNs are also critically involved in immune and anti-tumor responses (21, 22). For example, in a retrospective analysis of 2,244 stage III colon cancer patients, Kuo et al. found that a higher number of negative LNs correlated with better prognosis (23). Similarly, Quan et al.’s study on pN1 right-sided colon cancer showed improved DFS and OS in patients with more than nine negative LNs (24), emphasizing the importance of LNs. Tumor cells can interact with surrounding stromal and inflammatory cells to form an inflammatory tumor microenvironment (25). Engle et al. showed that overexpression of CA19–9 in mice accelerated pancreatitis, and this inflammatory response was reversed by anti-CA19–9 antibodies, indicating a close relationship between CA19–9 and inflammation (26). Zhang et al. performed single-cell sequencing on three CA19-9-positive and three CA19-9-negative patients and found that cancer-associated fibroblasts produced CA19–9 to promote the M2 polarization of macrophages in the pancreatic tumor microenvironment, thereby accelerating tumor progression (27). These pro-inflammatory effects and microenvironmental changes induced by CA19–9 may attract more immune cell infiltration and LN response, resulting in an increased number of retrievable LNs postoperatively.

In the present study, we found that patients with below-normal Hb levels had significantly higher rates of retrieving ≥ 12 LNs, suggesting that anemia may affect LN detection. In a case-control study involving 5,075 early-onset CRC patients, Fritz et al. found that anemia was associated with increased CRC risk (28). One potential cause of anemia is iron deficiency, which has been shown to impair cancer immune surveillance and alter the tumor immune microenvironment, facilitating tumor progression (29). These anemia-induced changes may lead to reactive hyperplasia of mesenteric LNs, increasing their size and making them more identifiable in surgical specimens. Additionally, anemia is closely linked with hypoxia. Guo et al. found that genetic variants in hypoxia-related genes were associated with increased CRC risk and enhanced immune infiltration (30), possibly leading to the promotion of LN immune response and indirectly increasing the number of detectable LNs. However, current research on the relationship between anemia and LN yield remains limited, and the underlying mechanisms are not fully understood. Further basic and clinical studies are needed to validate these findings.

This was a single-center retrospective study based on clinical data from RC patients. We developed a nomogram with good predictive performance and practical value, providing a useful tool for assessing the likelihood of retrieving 12 LNs postoperatively. Using this model, patients with fewer than 12 LNs detected postoperatively may not necessarily be classified as high-risk candidates requiring adjuvant chemotherapy. Pathologists can preliminarily estimate whether the number of retrieved LNs meets the threshold of 12 using this model. When the model predicts fewer than 12 LNs, it can also help reduce the tissue sampling time and facilitate more efficient staging assessment in the pathology department. However, this study has several limitations, including a relatively small sample size and potential selection bias. AUC values suggest moderate discriminatory power, factors such as surgeon experience, pathologist proficiency, and neoadjuvant chemoradiotherapy, which were not included in the analysis, may have influence outcomes. Moreover, the model has not been externally validated. Future studies involving larger, multi-center, or prospective cohorts are warranted to externally validate and optimize the model, thereby improving its robustness and clinical applicability.

In conclusion, we developed an effective model for predicting the likelihood of retrieving 12 LNs after RC surgery, providing valuable guidance for clinicians in staging and treatment planning. This model not only facilitates more accurate prognostic assessment, it also contributes to improving the quality of surgical and pathological evaluation, ultimately aiding in the optimization of individualized patient management. In the future, an online calculator or application based on the nomogram may be developed to facilitate easy and accessible use in real-world clinical settings.