Radiology and Oncology | Ljubljana | Slovenia | www.radioloncol.com Radiol Oncol 2025; 59(2): 257-266. doi: 10.2478/raon-2025-0015 257 research article Predictive value of pretreatment peripheral blood N/CD4 and N/CD8 ratios for the efficacy of radiotherapy for esophageal cancer Yu-Rong Jiang1, Yu-Ting Su2, Jing Hu1, Yan Ding3, Lu Wang2, Zi-Yu Wang1, Wan-Ying Sheng1, Yi-Xu Fan1, Liang-Mei Chu1, Yu-Fei Yang3, Yi Wen1, Miao Han3, Si-Yuan Zhou1, Chun-Hua Dai1, Xu Wang1 1 Department of Thoracic Oncology, Cancer Institute of Jiangsu University, Affiliated Hospital of Jiangsu University, Zhenjiang, P. R. China 2 Department of Abdominal Oncology, Cancer Institute of Jiangsu University, Affiliated Hospital of Jiangsu University, Zhenjiang, P. R. China 3 Department of Head and Neck and Comprehensive Oncology, Cancer Institute of Jiangsu University, Affiliated Hospital of Jiangsu University, Zhenjiang, P. R. China. Radiol Oncol 2025; 59(2): 257-266. Received 28 August 2024 Accepted 6 December 2024 Correspondence to: Chun-Hua Dai and Xu Wang, Department of Thoracic Oncology, Cancer Institute of Jiangsu University, Affiliated Hospital of Jiangsu University, Zhenjiang 212001, P. R. China. E-mail: Xu Wang at jsdxwx@126.com. Disclosure: No potential conflicts of interest were disclosed. This is an open access article distributed under the terms of the CC-BY license (https://creativecommons.org/licenses/by/4.0/). Background. This study aimed to explore the predictive value of pretreatment peripheral blood immune cell subsets in analyzing the outcomes of patients who underwent radiation therapy for esophageal cancer at their first visit. Patients and methods. This study included 72 patients with esophageal cancer (EC) treated at Jiangsu University Hospital from December 2021 to December 2023. Among them, 48 were males and 24 were females, with a median age of 64 years (range: 52–98 years). Comprehensive clinical data, laboratory results, and imaging findings were collected to analyze survival differences. The log-rank test was used for univariate analysis to assess the sensitivity of these patients to radiotherapy. The statistically significant and clinically relevant factors identified from the univariate analysis were subsequently incorporated into a Cox proportional hazards regression model for multivariate analysis to investigate the associations between pretreatment peripheral blood immune cell subsets and patient survival. Results. Univariate Cox regression analysis revealed that the Eastern Cooperative Oncology Group (ECOG) score, CD4+ T-cell ratio, neutrophil-to-CD4+ T-cell ratio (N/CD4), neutrophil-to-CD8+ T-cell ratio (N/CD8), and neutrophil-to-B-cell ratio (N/B) were significantly correlated with survival outcomes in patients receiving radiotherapy for tumors. Furthermore, multivariate Cox regression analysis identified N/CD4+ T cells and N/CD8+ T cells as critical prognostic indicators for these patients. Receiver operating characteristic curve analysis was employed to evaluate the work characteristics of the subjects, resulting in area under the curve values of 0.763 for both N/CD4 and N/CD8. The analysis also revealed that the optimal cutoff values for N/CD4+ T cells and N/CD8+ T cells were 0.01053329 and 0.01184294, respectively. Conclusions. N/CD4 and N/CD8 have emerged as viable prognostic predictors for patients undergoing radiother- apy for EC, offering valuable insights for clinicians to strategize further treatment options. However, the retrospective nature of this study introduces potential bias in assessment, underscoring the necessity for large-scale, prospective, randomized controlled trials to substantiate and validate these findings. Key words: peripheral blood N/CD4 and N/CD8; esophageal cancer; radiotherapy; efficacy prediction Introduction Esophageal cancer (EC) is a prevalent gastroin- testinal tumor. Global cancer statistics from 2020 revealed that there were 604,000 new cases of EC and 544,000 associated deaths, with incidence and mortality rates varying significantly across different regions.1 China has been identified as a Radiol Oncol 2025; 59(2): 257-266. Jiang YR et al. / Predictive value of immune cell subsets for radiotherapy258 high-incidence area, with approximately 150000 deaths annually. EC typically affects more males than females, with onset commonly occurring af- ter the age of 40.2 The early stages of EC are often asymptomatic.3 However, as the esophageal lumen narrows to less than 14 mm, patients progressively experience dysphagia, initially with solid foods, then semisolids, and eventually liquids or saliva. In China, approximately 70% of patients with EC are diagnosed in the middle or late stages, missing the opportunity for radical surgical intervention.4 For inoperable patients, the treatment options include radiotherapy, chemotherapy, synchro- nous chemoradiotherapy, targeted therapy, and immunotherapy.5 Over 95% of ECs in China are squamous cell carcinomas, which are relatively sensitive to radiation4, thus underscoring the critical role of radiotherapy in comprehensive EC treatment.6 Advancements in technology, such as intensity-modulated radiotherapy (IMRT), image- guided radiation therapy (IGRT), volumetric arc therapy (VMAT), and proton therapy, have sig- nificantly improved the management of advanced EC.7 The search for molecular biomarkers to predict EC prognosis continues, with researchers facing challenges such as the high cost of testing rea- gents and the difficulty in obtaining specimens.8 Recently, routine blood tests, such as the neutro- - tion for their prognostic value in various solid tumors, including head and neck, nonsmall cell lung, and cervical cancers, and their association with poor EC outcomes.9,10 This study specifically examined peripheral blood immune cell subpopu- to assess their relationships with EC prognosis. The analysis of these immune cell ratios and ac- tivities could provide insights into the body’s im- mune function. We retrospectively analyzed data from 72 patients with EC treated at Jiangsu University Hospital to explore the correlation between pe- ripheral blood immune cell subsets and patient outcomes. The results of this study are detailed below. Patients and methods Patients of the study This study included 72 patients with esopha- geal cancer at the Affiliated Hospital of Jiangsu University from December 2021 to December 2023. The cohort comprised 48 males and 24 females, with a median age of 64 years (range: 52–98 years). The majority (68 patients) presented with squa- mous cell carcinoma of the esophagus, while 3 had small cell carcinoma, and 1 was diagnosed with adenocarcinoma. All individuals underwent a pathological examination at Jiangsu University Hospital, confirming advanced esophageal cancer and missing the optimal window for surgical in- tervention. Pathological diagnoses were conducted according to the 2019 World Health Organization (WHO) revised classification standards for diges- tive system tumors.11 The inclusion criteria were as follows: (1) patho- logically confirmed malignant tumors of the es- ophagus; (2) assessment of absolute lymphocyte subpopulation counts; (3) computed tomography (CT) scans conducted within one month prior to treatment and three months postradiotherapy; and (4) completion of the planned radiotherapy regimen. The exclusion criteria included the fol- lowing: (1) patients unsuitable for treatment ini- tiation; (2) patients with nonevaluable lesions; (3) patients with concomitant severe infections or autoimmune diseases; (4) patients with a history of other diagnosed tumors; (5) patients with poor- quality CT images with interfering artifacts; (6) pa- tients with concurrent severe medical conditions such as cardiac insufficiency or hepatic and renal dysfunction; (7) patients with cognitive or psy- chiatric disorders; and (8) patients with a history of drug abuse or alcoholism. This study adhered to the ethical guidelines of the World Medical Association’s Declaration of Helsinki, which was revised in 2013.12 The study was approved by the Ethics Committee of the Affiliated Hospital of Jiangsu University. Samples were taken from pa- tients after providing informed consent and with the approval of the Affiliated Hospital of Jiangsu University Ethics Committee (Ethical approval Radiotherapy methods A thermoplastic body membrane was used to im- mobilize the patients during treatment. Positioning was further refined via CT-enhanced scans. All the patients underwent IMRT, IGRT, or VMAT. Enhanced CT localization scans with a slice thick- ness of 5 mm were performed in the supine posi- tion, and the resulting imaging data were integrat- ed into the radiation treatment planning system. At least two clinicians delineated the gross target volume (GTV), nodal GTV (GTVnd), and Radiol Oncol 2025; 59(2): 257-266. Jiang YR et al. / Predictive value of immune cell subsets for radiotherapy 259 critical organs at risk, such as the spinal cord and lungs, via upper gastrointestinal imaging and en- hanced CT scans. The clinical target volume (CTV) was defined by expanding the GTV laterally by 0.5 cm and vertically by 2.5 cm. Similarly, the GTVnd expanded laterally by 0.5 cm and vertically by 0.5 cm. The planning target volume (PTV) was es- tablished by extending the CTV by 0.5 cm in all directions. The prescribed radiation dose for the PTV was set at 60-70 Gy, delivered in 30 fractions over 6–7 weeks, with a frequency of 5 sessions per week, ensuring that 95% of the PTV received the prescribed dose. Diagnostic and staging methods Upon admission, each patient underwent a series of diagnostic procedures to determine the extent and location of disease invasion. These included endoscopy with biopsy, CT, gastrointestinal imag- ing, or positron emission tomography-computed tomography. The diagnosis of EC was established on the basis of the WHO histological classification, referencing the 2019 edition of the WHO classifica- tion of tumors of the gastrointestinal system, and staging system for EC (8th edition, American Joint Committee on Cancer (AJCC); 2017). The Response Evaluation Criteria in Solid Tumors were applied for staging and ongoing evaluation. These criteria classify the responses of patients with EC into four categories: complete response (CR), partial response (PR), stable disease (SD), and progressive disease (PD).13 The key end- points of the study included overall survival (OS) and progression-free survival (PFS). Clinical data collection This study employed a retrospective design to gather comprehensive data from patients treated for EC. The collected data included general clini- cal information, laboratory test results, and im- aging outcomes. The specific parameters docu- count, absolute lymphocyte subpopulation count, Eastern Cooperative Oncology Group (ECOG) per- formance status, and other relevant clinical char- acteristics. The primary endpoint was the OS of patients who underwent radiotherapy for EC. The protection measures of clinical data in this study mainly include data encryption, data anonymisa- tion and access control. These measures ensure the security of data during transmission and storage while protecting individual privacy. Researchers, healthcare providers and data managers can ac- cess the corresponding data, but all are subject to strict privilege management and ethical review. With these combined measures, the security and privacy of clinical data can be effectively pro- tected. All procedures conducted in this study ad- hered to the ethical standards of the 2013 revised World Medical Association (WMA) Declaration of Helsinki. Calculation of the neutrophil-to-CD4+ T-cell ratio (N/CD4) and the neutrophil- to-CD8+ T-cell ratio (N/CD8) After EDTA-blood samples from patients were for flow cytometry analysis. In brief, red blood cells were lysed with 2 ml lysing solution for 10 min. The remaining cells were washed twice in wash buffer and then stained with a cell viability dye in PBS for 15 min at room temperature. Cell surface staining was performed with in a cocktail of antibodies, including anti-human CD3, CD4, CD8, CD45RO, and CCR7, in instructed dilutions for 25 min at 4°C. The cells were then fixed and permeabilized with a kit and intracellular stain- ing of FOXP3 was performed. After staining, the whole single-cell suspension of each sample was aspired and analyzed flow cytometry (BD FACS Canto II) till the FACS tubes were empty.14 blood test results at the time of initial diagno- neutrophil count (× 109 + absolute T-lymphocyte count (× 109 neutrophil count (× 109 + absolute T-lymphocyte count (× 109 Follow-up and prognostic analysis In this study, patient follow-up was conducted primarily through reviews of hospitalization re- cords and outpatient visits. Telephone follow-up was conducted for unresolved or overlooked is- sues. These follow-ups were scheduled quarterly, with a final cutoff date of December 31, 2023. PFS was measured from the time of disease diagnosis until disease progression or last follow-up contact, whether by phone or outpatient visit. OS was de- fined as the time from diagnosis to death from any cause or until final follow-up. Radiol Oncol 2025; 59(2): 257-266. Jiang YR et al. / Predictive value of immune cell subsets for radiotherapy260 Methods of statistical analysis Statistical analysis of the data was performed via Statistical Product and Service Solutions (SPSS) (version 26.0) software. Receiver operating char- acteristic (ROC) curves were generated to evalu- CD8, with OS status serving as the state variable. The area under the curve (AUC) was calculated for each sample, with values greater than 0.5 indicat- ing significant discriminative ability. The optimal + + T cells were determined on the basis of the maximal Demographic and clinical characteristics, in- and ECOG score, were categorized and analyzed. Categorical data are expressed as percentages 2 test for intergroup utilized to construct survival curves for patients categorized into low and high groups on the basis of test variables, and differences in survival were assessed via the log-rank test. Influential factors, + T lymphocytes, CD8+ included in the univariate analyses. Factors that reached statistical significance in these analyses were further evaluated via a multivariate Cox pro- portional hazard regression model to assess their impact on survival outcomes. All the statistical tests were two-sided, with p < 0.05 considered sta- tistically significant. Results General clinical information Among the 72 patients in this study, 48 were male and 24 were female, with a median age of 64 years (52–98 years). Sixty-one patients (84.7%) were aged > 64 years. Sixteen (22.2%) patients had a history of smoking. Seventeen (23.6%) patients had a history of alcohol consumption. The pathological types were as follows: 68 cases (94.4%) of squamous car- cinoma, 1 case (1.4%) of adenocarcinoma, and 3 cas- es (4.2%) of small-cell carcinoma; 10 cases (13.9%) were poorly differentiated, 51 cases (70.8%) were moderately differentiated, and 11 cases (15.3%) were highly differentiated. The lesions were lo- cated in the upper segment in 15 patients (20.8%), the middle segment in 36 patients (50.0%), and the lower segment in 21 patients (29.2%). The T stage TABLE 1. Basic physiological and physiological characteristics of 72 patients Characteristic No of patents (%) All patients (%) 72 (100%) Sex Female 24 (33.3%) Male 48 (66.7%) Age Mean-SD 64 years Range 52-98 64-year old or older 61 (84.7%) Under 64-year old 11 (15.3%) History of smoking Yes 16 (22.2%) No 56 (77.8%) Drinking history Yes 17 (23.6%) No 55 (76.4%) Differentiation Highly differentiation 11 (15.3%) Medium differentiation 51 (70.8%) Low differentiation 10 (13.9%) Tumor site Upper thoracic portion 15 (20.8%) Middle thoracic portion 36 (50.0%) Low thoracic portion 21 (29.2%) Histology Squamous 68 (94.4%) Non-squamous 1 (1.4%) Small cell 3 (4.2%) T-staging T1 + T2 30 (41.7%) T3 + T4 42 (58.3%) N-staging N0 29 (40.3%) N1 + N2 43 (59,7%) Nutriture Benign 32 (44.4%) Unbenign 40 (55.6%) Anemic state Not anemic 51 (70.8%) Anemia 21 (29.2%) Coagulation state Normal 63 (87.5%) Abnormal 9 (12.5%) ECOG score 0 point 44 (61.1%) 1 point 22 (30.6%) 2 point 6 (8.3%) ECOG = Eastern Cooperative Oncology Group; SD = standard deviation Radiol Oncol 2025; 59(2): 257-266. Jiang YR et al. / Predictive value of immune cell subsets for radiotherapy 261 for 29 patients (40.3%). An ECOG score of 0 was ob- served in 44 patients (61.1%), 1 in 22 (30.6%), and 2 in 6 (8.3%). There were 40 patients (55.6%) with malnutrition, 21 patients (29.2%) with anemia, and 9 patients (12.5%) with coagulation abnormalities (Table 1). Univariate Cox regression analysis of prognosis in patients with EC To explore the relationship between patients’ gen- eral clinical information and peripheral blood lymphocyte subpopulations and the prognosis of patients with EC undergoing radiotherapy and to remove some irrelevant predictor variables, we performed a one-way analysis of the collated data via SPSS. The results of the prognostic univari- ate analysis of patients with EC revealed that the ECOG score, CD4+ + T lym- + T lymphocytes, and neutrophil- - vival of patients who were treated with definitive radiotherapy for EC (p < 0.05). The results of the prognostic univariate analysis of patients with EC are as follows (Table 2). Multivariate Cox regression analysis of the prognosis of patients with EC On the basis of the results of univariate analyses of prognosis in patients with EC, we performed multivariate analyses to disentangle the effects of other confounders further to determine the correlation between predictor variables and the prognosis of patients with EC. The results of the multifactorial analysis of the prognosis of patients 4.14474183122331E+73, p 4.26629029136702E-41, p risk factors affecting the prognosis of patients with EC (Table 3). ROC curves In the dataset, we find class imbalances when there are many more negative samples than posi- tive samples (or vice versa), and the distribution of positive and negative samples in the data may also change over time. When the distribution of posi- tive and negative samples in the data changed, the ROC curve remained unchanged. However, the ROC curve does not clearly indicate which vari- able is more effective. The AUC is defined as the TABLE 2. Univariate Cox regression analysis of the relationship between pathophysiological parameters and survival time of patients Parameter 95% CI P-value Sex 0.5551–0.7782 0.863 Age 0.7621–0.9324 0.424 Smoking history 0.1238–0.3206 0.150 Drinking history 0.1356–0.3366 0.073 Differentiation 1.8861–2.1416 0.876 Tumor site 1.9172–2.2495 0.977 Histology 0.9993–1.1951 0.150 T-staging 1.4667–1.7000 0.484 N-staging 0.4812–0.7133 0.644 ECOG score 0.3196–0.6248 0.000 Lymphocytes 1.1019–1.3953 0.690 Neutrophils 4.5463–6.0399 0.101 CD4 494.9039–630.8183 0.003 CD8 318.8047–410.5008 0.099 B 127.2621–174.9045 0.441 NK 311.61–429.0567 0.345 CD4/CD8 1.5587–1.9595 0.380 NLR 4.11727–5.9177 0.219 N/CD4 0.00989131–0.01451622 0.000 N/CD8 0.01492113–0.02114241 0.000 N/B 0.04171439–0.07256377 0.020 N/NK 0.01579055–0.02567177 0.141 B = B cell; CD4 = CD4+ T-cell; CD8 = CD8+ T-cell; CI = confidence interval; ECOG = Eastern Cooperative Oncology Group; NK = natural killer cells; N = neutrophil cells; N/CD4 = neutrophil-to-CD4+ T-cell ratio; N/NCD8 = neutrophil-to-CD8+ T-cell ratio; NLR = neutrophil-lymphocyte ratio TABLE 3. Multivariate Cox regression analysis of the relationship between clinical variables and patient survival Parameter HR 95% CI Lower 95% CI Upper P-value N/CD4 4.14E+73 3.39128E+18 5.07E+128 0.009 ECOG 2.151826047 1.202835884 3.849532092 0.010 N/CD8 4.27E-41 2.01E-75 9.04E-07 0.021 N/B 0.00138624 6.32E-12 303904.1296 0.502 CD4 0.999658052 0.997587163 1.00173324 0.747 B = B cells; CD4 = CD4+ T-cell; CI = confidence interval; HR = hazard ratio; N = neutrophil cells; N/CD4 = neutrophil-to-CD4+ T-cell ratio; N/NCD8 = neutrophil-to-CD8+ T-cell ratio Radiol Oncol 2025; 59(2): 257-266. Jiang YR et al. / Predictive value of immune cell subsets for radiotherapy262 area under the ROC curve as a numerical value; its value range is generally between 0.5 and 1, which clearly and intuitively indicates that the indicator is better. Therefore, we used the AUC as an evalua- + T cells and was 0.01053329, with a sensitivity of 0.72, speci- ficity of 0.702, and AUC of 0.763 (95% confidence Figure 1A). The best 0.88, specificity of 0.553, and AUC of 0.763 (95% CI: 0.640–0.886) (Figure 1B). Survival analysis of patients with EC stratified by N/CD4+ T lymphocytes and N/CD8+ T lymphocytes The median follow-up time of the 72 patients with EC in this study was 12 months (0–25 months). The median OS time for patients in the low- and high- group was also significantly greater than that of CI: 2.44–134.90, p < 0.05) (Figure 2A). The median + T-cell groups were 751 and 310 days, respectively. Moreover, the 1-year OS rate of patients in the low- CI: 1.43–8.00, p < 0.05) (Figure 2B). Relationships between patients’ clinical characteristics and N/CD4+ T cells or N/ CD8+ T cells - The differences in tumor location and anemia status between the two groups were statistically significant (p < 0.05). However, the differences in the other clinical characteristics were not statis- tically significant (p > 0.05) (Table 4). According 0.01184294), and 43 patients were included in the - mor location, tumor differentiation, ECOG score, and RT efficacy of the patients in the two groups were compared. Furthermore, the differences were statistically significant (p < 0.05), and no statistical- FIGURE 1. Receiver operating characteristics (ROC) curve plotted to determine the value of a statistically significant variable in the Cox regression model for neutrophil-to-CD4+ T-cell ratio (N/CD4) (A) and neutrophil-to-CD8+ T-cell ratio (N/CD8) (B) according to ROC analysis, the area under the curve of N/CD4 and N/CD8 was 0.763 and 0.763, respectively, and the optimal cutoff point was 0.01053329 and 0.01184294, respectively. A B FIGURE 2A. Kaplan-Meier survival curves for patients with advanced oesophageal cancer in different neutrophil-to-CD4+ T-cell ratio (N/CD4) groups. The red curve represents the overall survival of patients with an N/CD4 less than 0.01053329, while the blue curve represents the overall survival of patients with an N/CD4 greater than or equal to 0.01053329. The mean survival time of patients in the low- and hight-N/CD4 group were 372 and 750 days, respectively, with a p < 0.05, indicating a significant difference between the two groups. FIGURE 2B. Kaplan-Meier survival curves for patients with advanced cancer in different neutrophil-to-CD4+ T-cell ratio (N/CD4) groups. The red curve represents the overall survival of patients with an N/CD4 less than 0.01184294, while the blue curve represents the overall survival of patients with an N/CD4 greater than or equal to 0.01184294. The mean survival time of patients in the low- and high-N/ CD4 group were 751 and 310 days, respectively, with a p < 0.05, indicating a significant difference between the two groups. Radiol Oncol 2025; 59(2): 257-266. Jiang YR et al. / Predictive value of immune cell subsets for radiotherapy 263 ly significant differences were found when other clinical characteristics were compared (p > 0.05) (Table 5). Discussion EC is a malignant tumor originating from the epi- thelial cells of the esophagus. The primary clini- cal manifestations of EC include choking while swallowing food, the sensation of a foreign body in the throat, retrosternal pain, and significant dysphagia. Complications can escalate when the tumor metastasizes to or invades nearby organs, leading to pain and discomfort in the affected ar- eas. Statistically, 70% of EC cases in China are di- agnosed at a middle or late stage, which often pre- cludes curative surgical resection.4 Predominantly, these cancers are diagnosed as squamous cell car- cinomas, accounting for more than 95% of EC cas- es in the region.4 This subtype is notably sensitive to radiation, underscoring the need for a compre- hensive treatment strategy that typically combines preoperative radiotherapy with surgical interven- tion or intensive radiochemotherapy to increase patient survival.5 The ongoing research and development of mo- lecular biomarkers have become crucial in predict- ing the prognosis of patients with EC.8 However, the use of these biomarkers in clinical practice is challenging because of the high costs and logisti- cal difficulties associated with obtaining and pro- cessing the necessary test samples. Despite these hurdles, the identification of more effective and accessible biomarkers is critical. These biomarkers could significantly improve prognostic accuracy and help tailor individualized treatment plans for patients, thereby potentially improving the over- all outcomes of EC management. As challenges in the discovery of reliable and accurate biomarkers, we consider the following points in our future re- search: 1. Standardised methods: inter- and intra- vari- ability can be significantly reduced by stand- ardised experimental and analytical methods, improving the reliability and reproducibility of biomarkers.15 2. Multi-centre studies: multi-centre studies can better assess the performance of biomarkers in different populations and reduce the variability caused by individual differences, thus increas- ing the value of their clinical application.16 3. Repeated measurements: repeating measure- ments several times and using statistical meth- TABLE 4. Association of pathological features and neutrophil-to-CD4+ T-cell ratio (N/CD4) in patients Characteristic, n = 72 N/CD4 N/CD4 P-value Sex Female 12 12 Male 28 20 0.502 Age 33 28 < 64 years old 7 4 0.558 History of smoking Yes 8 8 No 24 32 0.612 Drinking history Yes 10 7 No 30 25 0.756 Differentiation Highly differentiation 6 5 Medium differentiation 29 22 Low differentiation 5 5 0.228 Tumor site Upper thoracic portion 9 6 Middle thoracic portion 23 13 Low thoracic portion 8 13 0.032 Histology Squamous 36 32 Nonsquamous 1 0 Small cell 3 0 0.368 T-staging T1 + T2 15 15 T3 + T4 25 17 0.423 N-staging N0 19 10 N1 + N2 21 22 0.162 Nutriture Benign 19 13 Unbenign 21 19 0.56 Anemic state Not anemic 7 15 Anemia 33 17 0.007 Coagulation state Normal 30 23 Abnormal 10 9 0.765 ECOG score 0 point 24 20 1 point 11 11 2 point 5 1 0.366 Treatment efficacy CR + PR 26 21 SD + PD 14 11 0.956 CR = complete response; ECOG = Eastern Cooperative Oncology Group; PR = partial response; SD = stable disease; PD = progressive disease Radiol Oncol 2025; 59(2): 257-266. Jiang YR et al. / Predictive value of immune cell subsets for radiotherapy264 ods to assess consistency can more accurately assess the performance of biomarkers.17 4. Quality control: strict quality control measures can reduce technical variability, including the use of internal standards and regular calibra- tion of instruments, thus improving the reliabil- ity of results.18 In recent years, routine blood tests have become the cornerstone of clinical protocols for diagnosing and managing malignant tumors, playing a crucial role in treatment guidance and patient outcome as- sessment. Among the metrics derived from these predictor of prognosis across various solid tumors, including head and neck cancer, non-small cell lung cancer, and breast cancer.9,10 Studies such as those conducted by Shao et al.19 and Shao et al.20 A risk factor in patients with lung cancer (OS: 22.0 months vs. p 11.1 vs. 6.0 months, p < 0.001)19 an independent protective factor in patients with breast cancer (PFS: 14.8 vs. p vs. 56.0 months, p 20 is strongly associated with adverse outcomes. However, the specific immune cells contributing to these effects remain underexplored, partly be- numerous subgroups, and few studies have ap- plied these subgroups to the prognosis of patients with EC. Typically, the balance between various lymphocyte subpopulations, including T cells, and regulating the immune functions of the body. Accordingly, analyzing the ratios and activities of these cells is essential for evaluating their immune competence. This study retrospectively analyzed the data of 72 patients with EC from Jiangsu University Hospital to explore the relationships between pe- ripheral blood immune cell subsets and EC prog- nosis. Our findings suggest that the relationship with EC might vary, possibly because different cutoff values are applied across diverse patient groups and geographical regions. Univariate anal- ysis revealed that factors, including the ECOG per- formance score and the ratios of CD4+ T lympho- + + T lympho- with the survival outcomes of patients who under- went definitive radiotherapy for EC (p < 0.05). TABLE 5. Association of pathological features and neutrophil-to-CD8+ T-cell ratio (N/CD8) in patients Characteristic, n = 72 N/CD8 N/CD8 P-value Sex Female 9 15 Male 20 28 0.734 Age 26 35 < 64 years old 3 8 0.339 History of smoking Yes 6 10 No 23 33 0.797 Drinking history Yes 6 11 No 23 32 0.632 Differentiation Highly differentiation 5 6 Medium differentiation 19 32 Low differentiation 5 5 0.040 Tumor site Upper thoracic portion 4 11 Middle thoracic portion 15 21 Low thoracic portion 10 11 0.047 Histology Squamous 27 41 Nonsquamous 1 0 Small cell 1 2 0.802 T-staging T1 + T2 12 18 T3 + T4 17 25 0.968 N-staging N0 13 16 N1 + N2 16 27 0.518 Nutriture Benign 15 17 Unbenign 14 26 0.307 Anemic state Not anemic 7 15 Anemia 22 28 0.332 Coagulation state Normal 20 33 Abnormal 9 10 0.463 ECOG score 0 point 22 22 1 point 7 15 2 point 0 6 0.035 Treatment efficacy CR + PR 26 21 SD + PD 3 22 0.000 CR = complete response; ECOG = Eastern Cooperative Oncology Group; PR = partial response; SD = stable disease; PD = progressive disease Radiol Oncol 2025; 59(2): 257-266. Jiang YR et al. / Predictive value of immune cell subsets for radiotherapy 265 Furthermore, the multifactorial analy- 4.14474183122331E+73, p 4.26629029136702E-41, p factors that adversely affect EC prognosis. This CD8 ratios to refine prognostic evaluations and optimize treatment plans for patients with EC un- dergoing radiation therapy. ROC curve analysis re- 0.01053329 (with a sensitivity of 0.72, specificity of 0.702, and AUC of 0.763, 95% CI: 0.649–0.876) and of 0.88, specificity of 0.553, and AUC of 0.763, 95% CI: 0.640–0.886). Subgroup analysis on the basis of these cutoff values revealed statistically signifi- cant differences in tumor location, anemia status, degree of tumor differentiation, ECOG score, and efficacy of radiation therapy between the groups - firming the practical value of these biomarkers in clinical settings. In conclusion, the results of this study suggest risk factors affecting the prognosis of patients with inexpensive and easily accessible clinical indica- tors, may have predictive value for the prognosis of patients with EC. However, this study is a small- sample, single-center, retrospective observational study, which still needs to be validated by further large-sample prospective studies. Acknowledgement The clinical data collected for this study are con- fidential and subject to patient privacy protection regulations. Access to the raw data is restricted to protect patient confidentiality. However, summary data and aggregated results can be made available upon request. Researchers interested in accessing the data for collaboration or further analysis may contact the corresponding author for data shar- ing agreements and permissions. The requests for data should be directed to corresponding author Xu Wang. References 1. He J, Chen WQ, Li ZS, Li N, Ren JS, Tian JH, et al. 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