Introduction
In the United States, neoadjuvant chemoradiotherapy (NCRT) combined with total mesorectal excision (TME) remains the standard of care for patients with resectable stage II/III rectal cancer (1,2). Although NCRT is able to effectively reduce local recurrence rates, its impact on overall survival (OS) remains uncertain (3,4). Total neoadjuvant therapy (TNT), a novel approach that combines chemotherapy and chemoradiotherapy prior to TME, has demonstrated improved survival outcomes in patients with locally advanced rectal cancer. Additionally, TNT can increase the number of patients eligible for organ-sparing therapies without increasing treatment toxicity or negatively impacting patient compliance (5–9). Although the benefits of TNT in improving OS remain limited, there is a need for more targeted and personalized treatment strategies. Identifying prognostic factors in clinical stage II/III rectal cancer is crucial, as this would enable clinicians to make informed decisions about whether to initiate intensified chemotherapy regimens. Such an approach would facilitate the development of personalized treatment plans tailored to individual risk profiles and thereby improve survival outcomes while minimizing treatment-related toxicities.
For predicting the prognosis of rectal cancer, clinical factors, tumor staging and histopathological features are crucial; however, their utility is often limited by the reliance on surgical procedures (10,11). As a result, research has increasingly focused on identifying reliable biomarkers that can effectively predict the prognosis of rectal cancer. Among these, blood cell-related biomarkers, such as carcinoembryonic antigen (CEA), neutrophil-to-lymphocyte ratio (NLR), as well as white blood cells, lymphocytes, neutrophils and eosinophils, have garnered notable attention from clinicians due to their ease of measurement and proven ability to predict disease progression and prognosis (12–15).
The objectives of the present study were to develop a prognostic model using readily available clinical biomarkers, such as CEA, CA19-9, post-NCRT NLR, neutrophils, lymphocytes and eosinophils, to predict OS and disease-free survival (DFS) in patients undergoing NCRT. The rationale for this approach is that combining clinical biomarkers with clinical and pathological characteristics will produce a robust model capable of accurately forecasting OS and DFS while providing valuable insights into clinical treatment strategies. To achieve this aim, clinical biomarkers associated with OS and DFS were first identified, which were then integrated with clinical characteristics. The predictive performance of the model was assessed using calibration and discrimination metrics. Based on readily accessible and non-invasive biomarkers, this model serves as a practical tool for risk stratification and outcome prediction in patients treated with NCRT, facilitating personalized treatment and optimizing clinical management.
Discussion
In the present retrospective cohort study of patients with rectal cancer who underwent NCRT and surgical resection, prognostic nomograms to predict 3-year OS and DFS were developed and internally validated using readily available clinical biomarkers. The principal findings were as follows: i) Pre-treatment CEA was consistently associated with both OS and DFS, confirming its established role as a surrogate marker of tumor burden and aggressive biological behavior (13,17); ii) peripheral immune-inflammatory indicators, particularly neutrophil and lymphocyte counts, independently predicted survival outcomes; iii) post-NCRT NLR stratification demonstrated a notable prognostic effect, with a high-NLR associating with significantly higher risks of mortality and disease recurrence; and iv) calibration curves showed notable agreement between predicted and observed 3-year outcomes, indicating that the proposed models provide clinically meaningful, individualized survival estimates.
CEA is an oncofetal glycoprotein, and in patients with cancer, including rectal malignancies, elevated CEA levels are typically associated with tumor burden and biological aggressiveness. Numerous studies have established CEA as a notable prognostic marker for predicting OS and DFS in rectal, gastric and periampullary cancers (17–19). Specifically, elevated pre-treatment CEA levels in rectal cancer are associated with poor prognosis, higher recurrence rates and reduced survival (20–22). Mechanistically, this effect may be attributed to the role of CEA in mediating tumor cell adhesion, migration and metastasis, thereby facilitating disease progression (23,24). Consistent findings across multiple cohorts highlight CEA as a reliable biomarker for assessing baseline tumor burden and treatment efficacy (25–27). Furthermore, postoperative CEA elevation serves as an early indicator of disease recurrence, enabling timely clinical intervention (4,28,29). Therefore, CEA remains invaluable not only for cancer diagnosis but also for prognostication, facilitating risk stratification and guiding tailored therapeutic strategies. Integrating CEA with other parameters, such as immune-inflammatory biomarkers, can further enhance its prognostic accuracy.
CA 19-9 is a well-established tumor marker for gastrointestinal malignancies, particularly pancreatic and biliary cancers, and has been explored in colorectal cancer, although its prognostic value in rectal cancer remains less well established (19,30). However, it did not demonstrate a statistically significant association with survival outcomes in the univariable Cox regression analysis performed in the present study and was therefore not retained in the multivariable model. This aligns with previous studies highlighting that CEA offers superior sensitivity and specificity over CA 19-9 to predict recurrence and survival in rectal cancer (30,31). The lack of prognostic significance of CA 19-9 in the present study may be due to its elevation being more frequently associated with advanced disease stages or specific biological subtypes (30). Conversely, CEA serves as a more robust and universal indicator of tumor burden and therapeutic response in stage II/III rectal cancer (30,31).
Immune-inflammatory markers, particularly neutrophil and lymphocyte counts, exhibit notable independent associations with OS and DFS in various malignancies, such as lung, breast and cervical cancers (32–35). Systemic inflammation typically elevates circulating peripheral neutrophils, which promote tumor progression by secreting pro-inflammatory cytokines, proteases and other pro-tumorigenic factors that facilitate angiogenesis, immunosuppression and metastasis (36–38). By contrast, lymphocytes, such as cytotoxic T lymphocytes, are the primary effectors of antitumor immunity (39). Consequently, peripheral lymphopenia is consistently associated with a poorer prognosis and reduced survival in multiple types of cancer, including breast cancer and cervical cancer (34,35).
A notable finding of the present study is the independent association between elevated eosinophil counts and worse DFS. Although traditionally linked to allergic reactions and parasitic infections, research has revealed a complex role for eosinophils in cancer biology (40). Eosinophils can secrete epidermal growth factor and transforming growth factor-β1, which promote tumor proliferation and epithelial-mesenchymal transition (40). By contrast, eosinophil-derived cationic proteins, neurotoxins and granzymes can induce tumor apoptosis, whereas their production of interferon-γ, CXCL9 and CXCL10 enhances CD8+ T cell-mediated cytotoxicity (40). Despite these antitumor mechanisms, the present study observed that peripheral eosinophilia was associated with inferior DFS, which suggests that eosinophil-driven inflammation may represent an adverse immune signature within the tumor microenvironment. However, the precise underlying pathways remain to be fully elucidated; thus, this preliminary finding warrants cautious interpretation.
The NLR integrates two interconnected biological processes: Systemic inflammatory activation and the suppression of anti-tumor immune surveillance, thereby reflecting the balance between pro-tumorigenic inflammation and host immunity (32). As a composite metric, the NLR is less vulnerable to physiological fluctuations in individual leukocyte counts, offering a stable representation of the systemic immune-inflammatory state. The post-NCRT NLR likely captures both baseline host immunity and dynamic biological responses to neoadjuvant therapy, which may explain its robust prognostic value relative to single-cell markers. Mechanistically, systemic inflammation is increasingly recognized as a key driver of colorectal cancer progression. Neutrophils facilitate this through multiple pathways, including the secretion of pro-tumorigenic cytokines, stimulation of angiogenesis and promotion of metastasis (36–38). Conversely, circulating lymphocytes serve as a primary index of host cytotoxic capacity, with lymphopenia denoting compromised immune surveillance and diminished anti-tumor efficacy.
In the present study, elevated neutrophil and reduced lymphocyte counts were significantly associated with inferior OS and DFS, reflecting the delicate balance between pro-tumorigenic inflammation and anti-tumor immunity. Notably, the post-NCRT NLR demonstrated a marked prognostic impact on both survival metrics. By integrating markers of systemic inflammation and immune capacity, the NLR provides an intuitive and clinically applicable surrogate for host immune status. This concurrent reflection of different biological phenomena produces a comprehensive immune-inflammatory profile, likely explaining the superior predictive value of NLR compared with individual cell counts (41). Although baseline leukocyte counts indicate pre-treatment status, the post-NCRT NLR captures treatment-induced inflammatory remodeling and dynamic biological shifts following neoadjuvant therapy (28). Consequently, the association between a high post-NCRT NLR and poor outcomes may indicate persistent inflammatory activation or incomplete immune restoration, reflecting more aggressive tumor biology and an inadequate immune response.
Due to the routine accessibility of these laboratory markers, the nomograms developed in the present study offer a practical tool for individualized risk estimation. By incorporating an established tumor marker (CEA) alongside dynamic immune parameters (neutrophil, lymphocyte and eosinophil counts, as well as post-NCRT NLR), these models facilitate the identification of high-risk patients who may benefit from intensified adjuvant therapy or closer long-term surveillance. Ultimately, this approach enhances clinical risk stratification, addressing the prognostic heterogeneity often observed among patients with identical conventional tumor characteristics. Future studies should explore alternative modeling strategies, such as evaluating the NLR as a continuous variable or employing spline-based techniques, to better elucidate potential non-linear associations.
Further research is required to rigorously validate the proposed prognostic model. External validation in diverse clinical settings and large patient cohorts is essential to confirm its robustness. Additionally, integrating novel biomarkers will be crucial for refining the predictive accuracy of the model. Ultimately, the application of advanced analytical technologies can further improve early risk stratification and personalized prognostication for patients with rectal cancer.
Several limitations of the present study should be acknowledged. First, due to the retrospective single-center study design, the present study was inherently susceptible to selection and information bias. Second, the models underwent only internal bootstrap validation; therefore, external validation in prospective, multicenter cohorts is required to confirm their generalizability. At present, we are unable to perform external validation using publicly available independent cohorts, as existing datasets lack the specific post-NCRT immune-inflammatory biomarkers required by the present model. Third, the proposed nomograms were not directly compared with established prognostic frameworks, such as TNM staging or microsatellite instability (MSI) status. TNM staging remains the cornerstone of prognostic stratification in colorectal cancer, and MSI status has emerged as a notable biomarker predicting treatment response and survival (42,43). Future studies should evaluate the incremental prognostic value of these biomarker-based models relative to standard clinical tools. Finally, relying primarily on univariable significance for multivariable candidate selection may introduce bias and model instability. Subsequent studies should employ more robust variable selection methods, such as penalized regression (such as LASSO), to mitigate these risks.
In conclusion, the present study developed prognostic nomograms to predict OS and DFS in patients with stage II/III rectal cancer undergoing NCRT and surgical resection. The post-NCRT NLR emerged as a notable prognostic determinant, underscoring the role of host immune-inflammatory responses in shaping long-term clinical outcomes. Although the proposed models demonstrated robust predictive accuracy and were successfully internally validated, external multicenter prospective validation are warranted to confirm their generalizability and clinical utility.