Predictive model based on folate receptor-positive circulating tumor cells in neoadjuvant immunochemotherapy for esophageal cancer

Introduction

Esophageal cancer (EC) ranks seventh among global cancer-related deaths, with incident cases projected to surge by approximately 70% by 2050, according to 2022 global cancer statistics (1). Esophageal squamous cell carcinoma (ESCC) represents the predominant histological subtype of this malignancy. A major clinical challenge lies in the silent onset of early-stage tumors: many ESCC patients present at advanced stages beyond the curative surgical window (2), while those undergoing resection often exhibit suboptimal R0 resection rates (50%), both contributing to a high incidence of early postoperative recurrence (3,4). Retrospective data have demonstrated that preoperative neoadjuvant immunochemotherapy (nICT) can render locally advanced EC resectable, reduce postoperative recurrence, and achieve a ypT0N0 pathological response in 24.2% of patients. In addition, an objective response rate of 59.1% was observed (5). Additionally, nICT is associated with relatively low toxicity and does not generally delay surgical intervention (6). Despite these promising outcomes suggesting nICT’s potential to improve survival in resectable locally advanced ESCC, its clinical application remains largely investigational, highlighting an urgent need for robust real-world evidence to validate its efficacy and guide clinical practice.

The standard pathological metrics for assessing neoadjuvant therapy response include neoadjuvant pathologic tumor node metastasis classification (ypTNM) staging and tumor regression grade (TRG). According to the 8th edition of the American Joint Committee on Cancer (AJCC) staging system, ypTNM is used to stage ESCC following neoadjuvant treatment; given that neoadjuvant therapy frequently induces tumor downstaging, ypTNM has been shown to predict prognosis more accurately than pathological tumor node metastasis classification (pTNM) in this clinical setting (7). TRG is another pivotal prognostic indicator: patients achieving TRG0 (complete tumor regression) consistently exhibit longer disease-free survival (DFS) compared to those with incomplete regression (non-TRG0) (8,9). While these pathological markers provide valuable insights, they rely on invasive tissue sampling via puncture or surgery, limiting their utility for real-time monitoring and early prognostic stratification.In contrast, circulating tumor cells (CTCs)—tumor cells shed into the peripheral bloodstream—offer a minimally invasive alternative for tumor detection and monitoring. CTCs can disseminate to distant tissues or organs via the circulatory system, initiating metastatic lesions that drive tumor recurrence and increase patient mortality. Notably, CTCs possess inherent advantages including repeatable sample acquisition, broad detection scope, and rapid analysis, making them a promising non-invasive tumor biomarker. Folate receptor-positive CTCs (FR-CTCs) are obtained by adding specific recognition of folate receptors (FR) on the basis of conventional CTC detection, and this method can improve the detection rate of CTCs (10). Emerging evidence supports the clinical utility of FR-CTCs in ESCC management: for instance, preoperative detection of FR-CTCs or high FR-CTCs counts may identify patients who would benefit from neoadjuvant therapy (11), and recent studies have shown that combining CTCs with postoperative pathological staging enhances prognostic prediction in patients with esophageal adenocarcinoma receiving nICT (12).However, despite the growing recognition of FR-CTCs as prognostic biomarkers, there remains a paucity of studies focusing on their role in predicting nICT efficacy and prognosis specifically in ESCC. This critical research gap hinders the accurate stratification of ESCC patients likely to benefit from nICT and impedes the development of personalized treatment strategies. To address this unmet need, our research group conducted a retrospective study to analyze the utility of FR-CTCs in predicting nICT efficacy in ESCC patients. We further established and validated an FR-CTC-based prognostic model, with the aims of identifying patients who derive clinical benefit from nICT, predicting treatment outcomes, and providing a robust framework to guide individualized treatment decision-making for locally advanced ESCC. We present this article in accordance with the TRIPOD reporting checklist (available at https://jgo.amegroups.com/article/view/10.21037/jgo-2025-1-1088/rc).

Methods

Patient selection

This cohort study retrospectively analyzed ESCC patients treated with nICT at The First Affiliated Hospital of Zhengzhou University and The Fifth Clinical Medical College of Henan University of Chinese Medicine (Zhengzhou People’s Hospital) between August 2020 and August 2023. Inclusion criteria were as follows: (I) clinical diagnosis of operable locally advanced ESCC by contrast-enhanced computed tomography (CT), endoscopic ultrasound, or positron emission tomography-CT (PET-CT) according to the 8th edition of the clinical staging guidelines for EC; (II) preoperative nICT; (III) laparotomy or thoracoscopic tumor resection at least 3 weeks after completion of nICT; (IV) postoperative pathological confirmation of ESCC; and (V) availability of complete clinicopathological data. Exclusion criteria included: (I) unresectable locally advanced EC or EC with distant metastases; (II) no preoperative nICT; (III) patients with other primary malignancies; (IV) patients with severe heart, lung, or kidney disease; and (V) patients in poor general condition and unable to tolerate surgery. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Ethics Committee of The Fifth Clinical Medical College of Henan University of Chinese Medicine (Zhengzhou People’s Hospital) (No. 2025-KY-0119) and The First Affiliated Hospital of Zhengzhou University (No. 2024-KY-2243). Written informed consent was waived because the study involved secondary analysis of existing anonymized data and posed minimal risk to participants. Patient data were anonymized before analysis to protect privacy.

Data collection

We collected the following patient data based on research needs: (I) gender, age, smoking status (nonsmokers defined as never smoking or having smoked fewer than 100 cigarettes in one’s lifetime), drinking status (14 g of pure ethanol was defined as one standard drink; nondrinkers defined as never drinking or drinking only on holidays, with less than one standard drink per drink), Body mass index (BMI) calculated as [weight (kg)/height² (m²)], serum albumin level, presence of comorbidities (e.g., hypertension, cardiovascular disease, diabetes), maximum tumor length, and presence of lymphovascular invasion (LVI); (II) nICT regimen and treatment duration; (III) FR-CTCs examination results before and after neoadjuvant therapy; and (IV) imaging examinations performed at each hospitalization or outpatient follow-up to assess efficacy. These include routine CT scans of the neck, chest, and abdomen, brain CT scans or magnetic resonance imaging (MRI), and PET-CT scans; (V) ypTNM stage (T: primary tumor status, N: lymph node clearance, and M: presence of distant metastasis) and TRG stage.

Treatment

All patients in this study received nICT between August 2020 and August 2023, a period when neoadjuvant immunotherapy for EC had not yet been incorporated into clinical guidelines. Treatment decisions were based on the superior efficacy of nICT over chemotherapy alone in the first-line treatment of advanced EC at that time, coupled with the initiation of relevant clinical studies on nICT (Keystone-001) in May 2020. The immunotherapy regimen consisted of programmed death-1 (PD-1) monoclonal antibody administered once every three weeks, while the neoadjuvant chemotherapy regimen adopted a 3-week cycle of platinum combined with nab-paclitaxel or docetaxel. All patients underwent esophagectomy at least 3 weeks after completing neoadjuvant therapy, and informed consent for treatment was obtained from each patient prior to initiation.

Follow-up and outcome measures

Follow-up

Patients were followed up every three months during the first two years post-surgery, and thereafter every six months. Follow-up data is mainly obtained from outpatient or inpatient electronic medical record systems, including laboratory test results, examination results, electronic medical records, and medical orders. Follow-up was censored on November 15, 2024. Follow-up time was defined as the interval from the date of initial nICT to the follow-up cutoff date. For patients who experienced recurrence, metastasis, or death before the cutoff, follow-up ended on the date of the event; for those lost to follow-up, the last valid follow-up date was used.

Primary outcome measures

DFS: DFS is defined as the time from the start of nICT treatment to the first confirmation of disease recurrence or cancer-related death. Recurrence is defined as the appearance of one or more new lesions, which can be local, regional, or distant in location from the primary resected site (assessed by imaging or pathology). All deaths without prior recurrence are considered as DFS events. For participants who remained alive and without recurrence, the follow-up cutoff date was used as the endpoint time for DFS. DFS rate: DFS rate is defined as the percentage of participants who remain disease-free (neither relapsed nor died) at a specific time point (such as 1-, 2-, or 3-year).

Secondary outcome measures

Overall survival (OS): OS is defined as the time from the beginning of treatment until the death of the patient. For subjects that are alive, the follow-up cutoff date was used as the OS endpoint. OS rate: OS rate is defined as the percentage of participants who are still alive 1-, 2-, and 3-year after starting treatment. Outcomes were determined by two independent clinicians who were unaware of all predictor values and the patient’s baseline characteristics. Any disagreement regarding outcome determination was resolved by a third senior clinician in a blinded manner.

FR-CTCs detection

The FR-CTCs detection method used in this study is based on the CytoploRare kit to enrich and quantify FR-CTCs. To ensure the reliability of the results, 10% of the samples were randomly sampled for repeated testing. The coefficient of variation for repeated testing ranged from 0 to 1.68%, all remaining below 5%, indicating that the test results are stable and reliable (Table S1). Although this kit is currently primarily used for clinical testing of lung cancer, studies have shown that it also has good detection results and clinical relevance in EC (11). All study participants were required to provide 3 mL of fasting venous blood samples in the early morning at two specific time points: 1 week before neoadjuvant therapy (defined as baseline CTCs, FR-CTCs) and 1 week after surgery. The blood samples were immediately placed in ethylenediaminetetraacetic acid anticoagulant tubes. The detection method for FR-CTCs involves two main steps: first, immune magnetic beads are used to remove white blood cells, enriching the FR-CTCs from 3 mL of whole blood. Then, tumor-specific ligands (folate and synthetic oligonucleotide conjugates) are used for labeling. After washing away free conjugates, ligand-targeted polymerase chain reaction (LT-PCR) is used to quantitatively detect the FR-CTCs levels. In this study, the unit of FR-CTCs was defined as the number of FR-CTCs detected in 3 mL of blood (Fu/3 mL). The described detection method is the standard protocol used in the hospital’s testing process.Histological evaluation All pathological specimens were fixed in formalin, then processed according to standard pathological section preparation protocols and stained with hematoxylin-eosin. Two experienced pathologists independently evaluated each tissue section under a light microscope for histopathological assessment. ypTNM and TRG were used to evaluate the outcomes of patients after nICT. ypTNM stage was based on the 8th edition of the AJCC and the International Union Against Cancer (UICC) EC tumor node metastasis classification (TNM) stage system, and TRG was assessed according to the American Society for Clinical Pathology National Comprehensive Cancer Network (NCCN) standards: TRG0 (pathological complete response, no residual cancer cells), TRG1 (major pathological response, 10% or single cancer cell or cell clusters residual), TRG2 (fibrotic reaction exceeding residual cancer cells), and TRG3 (minimal fibrosis, large cancer cell clusters remaining). TRG0 and TRG1 were defined as the postoperative pathological response group (pPR), while TRG2 and TRG3 were considered the non-pathological response group (nPR).

This study was a retrospective cohort study. Missing values are handled using a complete-case analysis (delete directly). All predictors included in the model were objective laboratory test indicators and examination reports (specific indicator names can be supplemented as appropriate, e.g., FR-CTCs, albumin, pathological results), and the tests were performed in accordance with standardized protocols. To ensure data objectivity and reduce bias, strict blind management was implemented during the data extraction phase: two well-trained researchers independently extracted predictors, demographic data, and clinical baseline information from the electronic medical record system, without being informed of the patients’ recurrence or death status during the extraction process. After extraction, cross-verification was conducted by the two researchers, and discrepancies were verified and corrected by reviewing the original data to ensure data accuracy and completeness. Since the predictors were objective indicators, no additional blind interpretation was required, and the aforementioned blind management measures during data extraction have guaranteed the objectivity of predictor assessment.

Statistical analysis

Normality of continuous variables was preliminarily assessed with relevant statistical tests (Shapiro-Wilk test for small sample sizes). Normally distributed variables were expressed as mean ± standard deviation (SD) and compared between groups via the independent samples t-test. Non-normally distributed continuous variables were summarized as median [interquartile range (IQR), 25th–75th percentiles], with intergroup comparisons performed using the Mann-Whitney U test. Categorical variables were summarized as counts (percentages); the chi-square test was applied for intergroup comparisons, and Fisher’s exact test was substituted when Chi-squared assumptions were violated (i.e., expected cell frequency <5). Kaplan-Meier survival analysis was used to generate survival curves, and the log-rank test was employed to compare survival rates between groups. Univariable and multivariable Cox proportional hazards models were used to estimate the hazard ratios (HRs) and 95% confidence intervals (95% CIs) for postoperative recurrence in patients. Multivariable Cox proportional hazards regression analysis analyzed FR-CTC as both a continuous and categorical variable. For the categorical variable, the median of FR-CTCs was used as the cutoff value to divide it into low level (Q1) and high level (Q2). Covariates were adjusted based on clinical relevance and univariate analysis results as follows: Model 1 was adjusted for age and gender; Model 2 was further adjusted for smoking, drinking, albumin level, hypertension, diabetes mellitus, and cardiovascular disease on the basis of Model 1; Model 3 was additionally adjusted for TRG, tumor stage (T stage), node stage (N stage) and ypTNM stage on the basis of Model 2. The overall goodness of fit of the Cox proportional hazards model was assessed using Cox-Snell residuals. The cumulative hazard of the Cox-Snell residuals was estimated and compared with the reference line, with adequate model fit indicated by close agreement with the 45-degree line. All statistical analyses and graphing were conducted using Free Statistics Software Version 2.3 and R software (Version 4.2.1; http://www.R-project.org). All tests were two-tailed, and a P value <0.05 was considered statistically significant.

Development and validation of the nomogram

To develop a nomogram predicting the prognosis of EC patients receiving nICT, the least absolute contraction and selection operator (LASSO) regression method was first used to reduce the dimensionality of candidate variables and decrease the risk of model overfitting. Subsequently, the selected variables were comprehensively evaluated based on univariate Cox regression analysis results and clinical relevance. After collinearity testing, variables with a variance inflation factor (VIF) >5 were excluded. Finally, the eligible variables were included in a multivariate Cox regression model to construct the nomogram. The performance of the nomogram was comprehensively evaluated in accordance with established guidelines for prognostic model assessment, focusing on discrimination, calibration, and clinical utility. Discrimination was evaluated using the concordance index (C-index) and time-dependent receiver operating characteristic (ROC) curves, with the corresponding areas under the curves (AUCs) calculated at predefined time point. Based on the optimal cut-off value of the total nomogram score determined by the Youden index, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated to quantify the model’s ability to distinguish between high- and low-risk patients. In addition, overall predictive accuracy was evaluated using the time-dependent Brier score, with lower values indicating better performance.

Model calibration, reflecting the agreement between predicted probabilities and observed outcomes, was evaluated using calibration curves. Internal validation was performed using bootstrap resampling with 1,000 repetitions to minimize overfitting and enhance the robustness of the estimates. For each bootstrap sample, predicted risks were compared with actual outcomes. The 45-degree diagonal line represented perfect calibration, indicating exact concordance between predicted and observed event probabilities across the full range of risk estimates. Decision curve analysis (DCA) was conducted to assess the clinical utility of the nomogram by quantifying the net benefit across a range of threshold probabilities while accounting for the relative consequences of true-positive and false-positive classifications. The nomogram was considered clinically useful if it yielded a greater net benefit than both the treat-all and treat-none strategies within a clinically relevant range of threshold probabilities.

A flowchart detailing the study methodology is presented in Figure S1.

Results

Baseline FR-CTCs and patient characteristics

Sixty-four patients with ESCC met the inclusion criteria. Clinical and pathological characteristics are summarized in Table 1. Forty-six patients (71.9%) received PD-1 inhibitor combined with albumin-bound paclitaxel and platinum. Postoperatively, 24 patients (37.5%) achieved pPR. At last follow-up, 24 patients (37.5%) had experienced recurrence and 16 (25.0%) had died. This study defined high or low FR-CTCs levels as the median baseline FR-CTCs (11 Fu/3 mL). T stage (P=0.047) and LVI status (P=0.03) were significantly different between the two groups.

Survival outcomes following nICT

The median follow-up time in this study was 25.2 months. At the end of follow-up, the median DFS was 34.8 months and the median OS was 43.9 months. The overall 1-, 2- and 3-year DFS rates were 93.7% (95% CI: 88–99.9%), 68.3% (95% CI: 56.9–81.9%) and 45.4% (95% CI: 28.5–72.4%), respectively (Figure 1A). Corresponding OS rates at 1-, 2- and 3-year were 96.8% (95% CI: 92.6–100%), 82.9% (95% CI: 73.7–93.3%) and 74.8% (95% CI: 63.4–88.3%) (Figure 1B). Patients achieving pPR had significantly longer DFS and OS than those with nPR (DFS: not reached vs. 26.9 months, P=0.002; OS: 43.9 vs. 40.7 months, P=0.02) (Figure 1C,1D).

Figure 1 K-M survival curves. (A) DFS of all patients. (B) OS of all patients. (C) DFS of patients in the pPR and nPR groups. (D) OS of patients in the pPR and nPR groups. CI, confidence interval; DFS, disease-free survival; K-M, Kaplan-Meier; nPR, non-pathological response; OS, overall survival; pPR, postoperative pathological response.

Association between baseline FR-CTCs and postoperative recurrence

Univariable Cox proportional hazards analysis identified baseline FR-CTCs level (P<0.001), serum albumin (P=0.03), T stage (P=0.002), N stage (P=0.02), ypTNM stage (P=0.001), and TRG (P=0.002) as factors significantly associated with postoperative recurrence (Table 2).

To avoid collinearity, baseline FR-CTCs were entered into the multivariable Cox models either as a continuous or as a categorical variable in separate models. After adjustment for age, sex, smoking status, alcohol consumption, serum albumin, hypertension, diabetes mellitus, coronary heart disease, T stage, N stage, ypTNM stage, and TRG, baseline FR-CTCs level remained independently associated with recurrence risk (Table 3). For every unit increase in FR-CTCs, the risk of EC recurrence after surgery increases by 81% (HR =1.81; 95% CI, 1.34–2.45; P<0.001). When analyzed as a categorical variable, patients with high baseline FR-CTCs levels exhibited a markedly higher risk of postoperative recurrence compared with those with low FR-CTCs levels (HR =14.35; 95% CI, 2.28–90.17; P=0.005). The wide CI likely reflects the limited number of recurrence events in the high FR-CTCs group and should therefore be interpreted with caution. Notably, the association remained consistent when FR-CTC was modeled as a continuous variable. The Cox-Snell residual plot shows that the Cox proportional hazards model has a good overall fit, with slight deviations from the reference line at higher residual values (Figure S2).

Nomogram construction

Based on the results of univariable Cox regression and LASSO regression (Figure 2), the following variables were ultimately selected to construct the prognostic nomogram (Figure 3): serum albumin, T stage, ypTNM stage, TRG, and baseline FR-CTCs level. Each variable was assigned a weighted point value, and the total score derived from the sum of these points corresponded to the estimated probability of DFS at the specified time points. Collinearity diagnostics indicated no significant multicollinearity among the selected variables (Table S2).

Figure 2 Least absolute shrinkage and selection operator regression.

Figure 3 Nomogram for predicting postoperative DFS in esophageal cancer patients treated with nICT. DFS, disease-free survival; FR-CTC, folate receptor-positive circulating tumor cell; nICT, neoadjuvant immunochemotherapy; T, tumor; TRG, tumor regression grade; ypTNM, neoadjuvant pathologic tumor node metastasis classification.

Predictive performance and validation of the nomogram

The nomogram showed good discriminative ability, with a C-index of 0.821. Time-dependent ROC curves were used to evaluate the discriminative capacity of the model for predicting postoperative recurrence at 1-, 2-, and 3-year following nICT (Figure 4). The AUCs for 1- and 2-year recurrence prediction were 0.933 and 0.904, respectively, with corresponding diagnostic efficacy metrics at the Youden index-derived optimal cut-off value showing excellent performance: 1-year recurrence prediction yielded a sensitivity of 1.0, specificity of 0.85, PPV of 0.31 and NPV of 1.0; 2-year recurrence prediction had a sensitivity of 0.89, specificity of 0.76, PPV of 0.70 and NPV of 0.92 (Table S3). Consistently, the nomogram yielded low Brier scores at 1-, 2-, and 3-year (0.05, 0.14 and 0.17, respectively), indicating satisfactory overall predictive accuracy (Table S3). Owing to the limited sample size and extended follow-up duration, the predictive performance for 3-year recurrence was comparatively modest.

Figure 4 The time-dependent ROC curves 1-, 2- and 3-year for nomogram. AUC, area under the curve; ROC, receiver operating characteristic.

Calibration curves for 1- and 2-year DFS are shown in Figure S3. The nomogram demonstrated good calibration at both time points, with a high degree of agreement between predicted probabilities and observed outcomes. DCA results are presented in Figure 5. Across a wide range of threshold probabilities (0–1.0), the standardized net benefit of the Cox-based prediction model consistently exceeded that of both the treat-all and treat-none strategies. These findings indicate that, across most clinically relevant decision thresholds, use of the nomogram for postoperative risk stratification in ESCC may yield superior net clinical benefit, supporting its potential clinical applicability.

Figure 5 Decision curve of the model.

Discussion

The effects of nICT on tumor downstaging and survival outcomes in patients with locally advanced ESCC remain incompletely defined. In the present study, survival analyses demonstrated a high R0 resection rate (100%) following nICT, with a postoperative pPR rate of 37.5% and an nPR rate of 62.5%. The median DFS and OS were 34.83 months and 43.93 months, respectively. In addition, we developed a predictive model to estimate the risk of postoperative recurrence after nICT in ESCC patients, which showed good discrimination, calibration, and clinical utility. Although substantial real-world evidence is still required to confirm the efficacy of nICT in EC, our findings provide supportive data and a preliminary evidence base for its clinical application.

In recent years, immunotherapy combined with chemotherapy or other treatment has demonstrated synergistic antitumor effects in ESCC, highlighting the promising potential of combination strategies in this setting (13). Several studies have shown that nICT improves pPR compared with neoadjuvant chemotherapy alone (14-16). In a study by Song et al. (17), patients with locally advanced ESCC treated with nICT achieved a pPR rate of 38% and a median DFS of 34 months, which is consistent with our findings. Nevertheless, the postoperative recurrence rate in our cohort remained 35.9%, suggesting the presence of residual lesions or minimal residual disease (MRD) that may lead to recurrence or metastasis.

FR-CTCs may serve as a biologically meaningful surrogate marker for MRD. Although some patients achieve radiological or pathological remission, occult tumor cells may still persist in the circulation and retain metastatic potential. Owing to its high sensitivity, FR-CTCs detection enables the identification of these residual CTCs, thereby providing molecular-level evidence of MRD earlier than conventional imaging or pathological assessment. In addition to FR-CTCs, other circulating biomarkers have been investigated for MRD detection in ESCC, including circulating tumor DNA (ctDNA), cell-free DNA, and microRNAs (18). Compared with other circulating biomarkers, FR-CTCs detection offers several advantages for MRD evaluation, including simpler operation, higher sensitivity, lower cost, and greater patient acceptance. FR-CTCs have been widely applied in the diagnosis of early-stage breast cancer, lung cancer, prostate cancer, and other malignancies (19). In this study, FR-CTCs detection was performed using the CytoploRare kit, which enriches and quantifies FR-CTCs. Although this kit is currently approved by the China Food and Drug Administration only for clinical use in lung cancer detection, multiple studies have demonstrated that the FR, a cell surface glycoprotein, is highly expressed in various tumor types, including ESCC (20,21). For example, in ESCC, preoperative FR-CTCs levels have been identified as an independent prognostic factor for DFS (11). In addition, FR-CTCs have shown high sensitivity in diagnosing both early- and late-stage head and neck squamous cell carcinoma (22). Collectively, these findings provide a theoretical basis for exploring the association between FR-CTCs and nICT in EC. In the present study, FR-CTCs levels were found to be associated with different T stages and LVI, indicating that FR-CTCs counts reflect tumor burden. Furthermore, multivariable Cox regression analysis showed that, after adjustment for confounding factors, high FR-CTCs levels were consistently associated with an increased risk of postoperative recurrence, regardless of whether FR-CTCs were analyzed as continuous or categorical variables. These results suggest that FR-CTC may serve as a predictive biomarker for postoperative recurrence in ESCC patients.

FR expression may represent more than a detection marker, instead defining a tumor cell subpopulation with enhanced survival and metastatic potential. In epithelial malignancies including ESCC, FR overexpression has been linked to increased proliferation, epithelial-mesenchymal transition, and stemness-related features, collectively promoting tumor dissemination and resistance to systemic therapy (23). Moreover, CTCs exhibit intrinsic immune-evasive properties (24), such as the expression of immune checkpoint-related regulators, enabling escape from immune surveillance and facilitating metastatic spread (25,26). In this context, FR-CTCs detected during or after nICT may reflect residual tumor cells capable of evading antitumor immunity, thereby serving as an indirect indicator of suboptimal immune response. This biological framework may partly explain the strong association between elevated FR-CTCs levels and increased post-treatment recurrence risk, supporting the incorporation of FR-CTCs into prognostic models not only for risk stratification but also for capturing key mechanisms of immune escape, MRD, and treatment resistance in ESCC.

At present, no standardized protocol exists for nICT including the choice between monotherapy and combination therapy or the optimal number of treatment cycles. In this study, all patients received nICT, which is commonly used in clinical practice. The number of treatment cycles ranged from one to four, with most patients (57.8%) receiving two cycles. Previous studies have similarly reported no statistically significant association between the number of treatment cycles and therapeutic efficacy (27,28), which is consistent with our findings. Consequently, the optimal number of nICT cycles remains controversial and warrants further investigation. Currently, clinical decisions regarding additional treatment cycles are often guided by the extent of tumor downstaging after initial therapy.

Postoperative recurrence remains a major challenge in patients with ESCC treated with nICT followed by curative resection. However, prognostic tools specifically designed for recurrence risk assessment in this clinical context remain limited. In the present study, we developed a prognostic nomogram that integrates readily available clinicopathological variables with baseline FR-CTCs levels, with the aim of providing an exploratory framework for DFS risk stratification in patients with resectable locally advanced ESCC. This distinction is particularly relevant for patients who achieve favorable pathological responses yet still experience early recurrence, underscoring the potential limitations of relying on pathological assessment alone. Although external validation is warranted, the proposed model highlights the potential value of combining liquid biopsy-based biomarkers with conventional pathological factors to refine postoperative risk assessment. These findings may help inform future prospective investigations and support the development of risk-adapted surveillance strategies in this evolving treatment landscape.

Several limitations of this study should be acknowledged. First, the retrospective design and missing data resulted in a relatively small cohort, with a limited number of events among patients with poor survival, which may have affected model stability. In addition, validation was restricted to internal assessment, thereby limiting the generalisability of the model. Second, the conclusion that FR-CTCs can predict ESCC prognosis was primarily based on published literature rather than experimental validation. We did not evaluate the specificity or sensitivity of the CytoploRare reagent for FR-CTCs detection in ESCC using cell lines or immunofluorescence assays. Future research will combine cell experiments and immunofluorescence assays for multicenter external validation to confirm the universality of the nomogram. The nomogram will also be combined with ctDNA or other liquid biopsy biomarkers to further improve postoperative risk stratification, early detection, and dynamic monitoring of disease progression in EC.

Conclusions

This study found that baseline FR-CTCs may serve as a predictive factor for DFS. This study also constructed and validated a nomogram to predict DFS in patients undergoing nICT. This nomogram demonstrated excellent predictive performance and clinical utility, providing new clinical insights for the use of nICT in EC patients.

Acknowledgments

We would like to thank all patients involved in the study and their family members.

Footnote

Reporting Checklist: The authors have completed the TRIPOD reporting checklist. Available at https://jgo.amegroups.com/article/view/10.21037/jgo-2025-1-1088/rc

Data Sharing Statement: Available at https://jgo.amegroups.com/article/view/10.21037/jgo-2025-1-1088/dss

Peer Review File: Available at https://jgo.amegroups.com/article/view/10.21037/jgo-2025-1-1088/prf

Funding: This study was supported by the Henan Provincial Medical Science and Technology Innovation Program-Joint Construction Project (No. LHGJ20250696).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jgo.amegroups.com/article/view/10.21037/jgo-2025-1-1088/coif). All authors report that this study was supported by the Henan Provincial Medical Science and Technology Innovation Program-Joint Construction Project (No. LHGJ20250696). The authors have no other conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Ethics Committee of The Fifth Clinical Medical College of Henan University of Chinese Medicine (Zhengzhou People’s Hospital) (No. 2025-KY-0119) and The First Affiliated Hospital of Zhengzhou University (No. 2024-KY-2243). Written informed consent was waived because the study involved secondary analysis of existing anonymized data and posed minimal risk to participants.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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