Abstract
Objectives: To evaluate the diagnostic and prognostic value of coagulation markers - including activated partial thromboplastin time (APTT), prothrombin time (PT), fibrinogen (FIB), platelet count (PLT), and D-dimer (DD) - and platelet-derived growth factor-BB (PDGF-BB) in patients with nasopharyngeal carcinoma (NPC) undergoing intensity-modulated radiotherapy (IMRT). Methods: A total of 210 NPC patients receiving IMRT and 160 healthy controls were enrolled. Baseline levels of PDGF-BB and coagulation markers were compared between groups. The association of PDGF-BB with clinical staging was analyzed, and receiver operating characteristic (ROC) curve analysis was used to assess its diagnostic performance. Cox regression analyses were performed to identify independent predictors of five-year survival. A dynamic nomogram was developed to provide individualized survival predictions. Results: NPC patients exhibited significantly higher levels of PDGF-BB, APTT, PT, FIB, PLT, and DD compared to healthy controls (all P < 0.001). PDGF-BB was positively correlated with TNM stage (stage III/IV vs. I/II, P < 0.001), T stage (P = 0.005), and N stage (P = 0.020). Multivariate Cox regression identified low PDGF-BB (< 628.18) (HR = 0.492, P = 0.009), low DD (< 746.1) (HR = 0.456, P = 0.002), age 51-64 years (HR = 2.057, P = 0.032) and ≥ 65 years (HR = 4.138, P < 0.001), EBV DNA negativity (HR = 0.273, P = 0.012), and TNM stage III/IV (HR = 3.042, P = 0.023) as independent prognostic factors. Conclusions: PDGF-BB and DD, alongside age, EBV DNA status, and TNM stage, are promising biomarkers for NPC prognosis. A dynamic nomogram integrating these factors offers accurate survival prediction and supports personalized treatment strategies in NPC management.
Keywords: Nasopharyngeal carcinoma, intensity-modulated radiotherapy, PDGF-BB, coagulation markers, prognosis
Introduction
Nasopharyngeal carcinoma (NPC), a malignancy arising in the nasopharyngeal epithelium, exhibits a distinct geographic distribution, with high prevalence in Southeast Asia-particularly in southern China, where incidence rates reach 20-50 per 100,000 in regions such as Guangdong, Hong Kong, and Macao [1,2]. Its pathogenesis is multifactorial, involving genetic predisposition, environmental exposure, Epstein-Barr virus (EBV) infection, and lifestyle factors including smoking and alcohol consumption [3]. Intensity-modulated radiotherapy (IMRT) remains the cornerstone of NPC treatment due to its ability to deliver precise radiation doses to the tumor while minimizing damage to adjacent healthy tissues [4,5]. However, the insidious onset and non-specific early symptoms often result in late-stage diagnoses, complicating treatment and worsening prognosis [6].
Despite advances in imaging and molecular diagnostics, early detection and accurate prognostic assessment of NPC remain challenging [7]. Current diagnostic modalities, such as computed tomography (CT), magnetic resonance imaging (MRI), and EBV DNA quantification, provide essential information but have limited utility for early-stage identification and real-time disease monitoring [8,9]. Traditional prognostic indicators-such as TNM staging and patient age-demonstrate variable predictive power across populations [10,11]. Recent studies have highlighted the potential involvement of coagulation markers and platelet-derived growth factor-BB (PDGF-BB) in tumor biology, implicating them in cancer progression, metastasis, and treatment responsiveness [12]. This study aims to evaluate the diagnostic and prognostic value of coagulation markers and PDGF-BB in NPC patients undergoing IMRT, with the goal of improving individualized treatment strategies.
The role of the coagulation system extends beyond hemostasis and into cancer biology. Emerging evidence indicates that it contributes to multiple stages of tumorigenesis, including initiation, progression, and metastasis [13]. PDGF-BB, a growth factor secreted by platelets and certain tumor cells, plays a crucial role in cell proliferation, migration, and angiogenesis [14]. In malignancies, PDGF-BB acts as a double-edged sword: it promotes tumor angiogenesis and sustains tumor growth by enhancing vascularization, while also remodeling the tumor microenvironment to facilitate metastasis and therapy resistance [15]. Previous research has suggested associations between PDGF-BB levels and tumor aggressiveness, metastatic potential, and treatment outcomes, positioning it as a promising biomarker for diagnosis and prognosis [16].
Although prior studies have explored the roles of coagulation indices and PDGF-BB in various malignancies, their specific functions in NPC remain unclear. This study investigates the relationships between these biomarkers and NPC clinical characteristics, treatment responses, and 5-year survival outcomes by comparing their levels in NPC patients and healthy controls. The findings are expected to provide new insights into the diagnostic and prognostic utility of coagulation markers and PDGF-BB in NPC, potentially informing more effective and personalized management strategies.
Methods and materials
Sample size calculation
Based on a previously reported 5-year mortality rate of approximately 30% for nasopharyngeal carcinoma (NPC) [17], the required sample size was calculated using the formula: N = Z2 [P (1-P)]/E2, where P = 0.30, E = 0.05, Z = 1.96. The calculated sample size was approximately 323. However, the actual number of participants was determined by the availability of eligible clinical samples.
General information
This study included 210 patients diagnosed with NPC and treated at Longyou County People’s Hospital between January 2017 and December 2019. Additionally, 160 healthy individuals undergoing routine physical examinations during the same period were enrolled as the control group. The study was approved by the Medical Ethics Committee of Longyou County People’s Hospital (Figure 1).
Figure 1.
Sample screening flow chart.
Inclusion and exclusion criteria
Inclusion criteria: (1) Histopathological confirmation of NPC [18]. (2) Age between 18 and 70 years. (3) Scheduled to receive IMRT. (4) Availability of complete clinical, imaging, and pathological data required for the study.
Exclusion Criteria: (1) Presence of severe cardiovascular or cerebrovascular disease, hepatic/renal dysfunction, diabetes, or other conditions affecting coagulation function. (2) History of primary or secondary coagulation disorders. (3) History of malignancies other than NPC. (4) Pregnancy or lactation. (5) Current use of anticoagulant or antiplatelet medications. (6) Stage IVB NPC.
Treatment regimens
Patients received IMRT via linear accelerators (e.g., Varian TrueBeam). Treatment protocols varied by clinical stage:
Stage I (T1N0M0): Radical radiotherapy alone; 66-70 Gy to the nasopharynx and 54-60 Gy to the cervical lymph nodes.
Stage II (T0-2N0-1M0): For T2N1 cases, concurrent chemoradiotherapy (typically cisplatin-based) is recommended; others may receive radiotherapy alone or in combination with chemotherapy. Radiation doses are the same as in Stage I.
Stages III-IVA (locally advanced): Induction chemotherapy (e.g., TP or GP regimen) followed by concurrent chemoradiotherapy, or concurrent chemoradiotherapy plus adjuvant chemotherapy. Radiation doses are 66-70 Gy for the nasopharynx and 54-60 Gy for the cervical lymph nodes, including bilateral retropharyngeal and level II-Vb lymph nodes.
Clinical data collection
Comprehensive baseline data were collected to compare clinical characteristics between NPC patients and healthy controls, providing a foundation for subsequent analysis.
Demographic and behavioral variables included age, sex, education level, smoking history, alcohol consumption history, TNM stage, tumor differentiation, and EBV DNA status.
All data were obtained from the hospital’s electronic medical records to ensure accuracy and completeness.
Laboratory indicator collection and testing
Laboratory indicators - including PDGF-BB, activated partial thromboplastin time (APTT), prothrombin time (PT), fibrinogen (FIB), platelet count (PLT), and D-dimer (DD), were measured using standardized protocols and equipment.
(1) PDGF-BB (pg/mL): Measured by ELISA (ELISA Bio, Shanghai; Batch No. ml105299). (2) PLT was determinedusing an automated hematology analyzer (Sysmex XN-9000, Japan). (3) APTT, PT, FIB, and DD were measured using a coagulation analyzer (Sysmex CS-5100, Japan).
All blood samples were collected upon patient admission, and processed and stored following standardized protocols to ensure reliability.
Clinical prognosis follow-up
Five-year survival outcomes were determined through structured follow-up. Patients were followed every 6 months for the first year, and annually thereafter, up to 5 years post-treatment. Survival status and clinical progress were recorded at each visit.
Outcome measurements
Primary outcome measures
Comparison of the baseline levels of coagulation markers (APTT, PT, FIB, PLT, DD) and PDGF-BB between healthy individuals and NPC patients.
Identification of independent prognostic factors influencing five-year survival in NPC patients using Cox regression analysis.
Secondary outcome measures
Comparison of coagulation markers and PDGF-BB levels among NPC patients with different clinical characteristics (e.g., age, gender, smoking history, etc.).
Comparison of expression levels of coagulation markers and PDGF-BB in patients with varying treatment responses (complete response [CR], partial response [PR], stable disease [SD], and progressive disease [PD]).
Evaluation of the expression and predictive value of coagulation markers and PDGF-BB in patients with improved treatment outcomes.
Statistical analysis
Statistical analyses were conducted using SPSS 26.0 and R 4.3.3. The Kolmogorov-Smirnov (K-S) test was first applied to assess data normality. For normally distributed continuous variables presented as (mean ± SD) deviation, independent samples t-tests were used to compare differences between groups. Continuous variables with non-normal distribution were expressed as median with interquartile range (IQR, 25th-75th percentile), and group comparisons were performed using the Mann-Whitney U test.
Categorical variables expressed as numbers (percentages) (e.g., sex, EBV DNA status) were analyzed using the chi-square test.
Cox proportional hazards regression (using the survival package in R) was employed to identify independent prognostic factors for five-year survival. Hazard ratios (HRs) and corresponding P-values were reported. A dynamic nomogram was constructed using the DynNom package in R to integrate clinical and laboratory variables, enabling real-time, individualized survival prediction. All tests were two-sided, and P < 0.05 was considered statistically significant.
Results
Comparison of baseline characteristics
There were no significant differences in age (P = 0.849), gender (P = 0.541), education level (P = 0.653), smoking history (P = 0.234), or alcohol consumption (P = 0.270) between NPC patients and healthy controls. Tumor-related characteristics such as T stage, N stage, TNM stage, and differentiation degree also showed no significant differences. However, the EBV DNA positivity rate was significantly higher in the NPC group than in controls (all P < 0.001; Table 1).
Table 1.
Comparison and presentation of clinical characteristics
| Variable | Total | Control group (n = 160) | NPC group (n = 210) | χ2 | P |
|---|---|---|---|---|---|
| Age | |||||
| ≤ 50 | 135 | 61 | 74 | 0.327 | 0.849 |
| 51-64 | 152 | 64 | 88 | ||
| ≥ 65 | 83 | 35 | 48 | ||
| Gender | |||||
| Male | 234 | 104 | 130 | 0.374 | 0.541 |
| Female | 136 | 56 | 80 | ||
| Educational level | |||||
| ≤ Junior high school | 149 | 61 | 88 | 0.852 | 0.653 |
| Senior high school | 152 | 70 | 82 | ||
| ≥ University | 69 | 29 | 40 | ||
| Smoking history (cigarettes/day) | |||||
| < 10 | 202 | 93 | 109 | 1.417 | 0.234 |
| ≥ 10 | 168 | 67 | 101 | ||
| Alcohol consumption history (ml/d) | |||||
| < 1000 | 224 | 102 | 122 | 1.216 | 0.270 |
| ≥ 1000 | 146 | 58 | 88 | ||
| T staging | |||||
| T1 | 80 | ||||
| T2 | 66 | ||||
| T3 | 55 | ||||
| T4 | 9 | ||||
| N staging | |||||
| N0 | 46 | ||||
| N1 | 38 | ||||
| N2 | 80 | ||||
| N3 | 46 | ||||
| TNM staging | |||||
| I | 18 | ||||
| II | 32 | ||||
| III | 105 | ||||
| IV | 55 | ||||
| Differentiation degree | |||||
| Well differentiated | 40 | ||||
| Moderately differentiated | 47 | ||||
| Poorly differentiated | 123 | ||||
| EBV DNA positivity | |||||
| Yes | 184 | 16 | 168 | 177.994 | < 0.001 |
| No | 186 | 144 | 42 |
Notes: TNM, Tumor, Node, Metastasis; T, Tumor; N, Node; EBV, Epstein-Barr Virus.
Comparison of the baseline levels of coagulation markers and PDGF-BB
NPC patients showed significantly elevated levels of PDGF-BB compared to healthy controls (P < 0.001). Similarly, APTT, PT, FIB, PLT, and DD levels were all significantly higher in the NPC group (all P < 0.001), suggesting notable coagulation and platelet-related changes in NPC pathophysiology (Table 2).
Table 2.
Comparison of the distribution of baseline levels of coagulation markers and PDGF-BB
| Variable | Total | Control group (n = 160) | NPC group (n = 210) | Statistic | P |
|---|---|---|---|---|---|
| PDGF-BB (pg/mL) | 284.40 ± 251.34 | 30.08 ± 10.04 | 478.17 ± 155.61 | 36.354 | < 0.001 |
| APTT (s) | 37.56 ± 4.51 | 35.33 ± 2.94 | 39.26 ± 4.76 | 9.198 | < 0.001 |
| PT (s) | 12.50 [11.90, 13.10] | 12.10 [11.50, 12.50] | 12.90 [12.30, 13.50] | 9.886 | < 0.001 |
| FIB (g/L) | 3.57 ± 0.99 | 3.12 ± 0.53 | 3.91 ± 1.13 | 8.121 | < 0.001 |
| PLT (×109/L) | 230.82 ± 66.69 | 203.11 ± 42.51 | 251.93 ± 73.76 | 7.477 | < 0.001 |
| DD (ng/mL) | 342.75 [216.95, 626.59] | 226.10 [170.05, 285.28] | 593.92 [394.48, 827.78] | 12.991 | < 0.001 |
Notes: PDGF-BB, Platelet-Derived Growth Factor-BB; APTT, Activated Partial Thromboplastin Time; PT, Prothrombin Time; FIB, Fibrinogen; PLT, Platelet Count; DD, D-dimer.
Comparison of coagulation markers and PDGF-BB in NPC patients with different clinical characteristics
NPC patients were stratified into low and high PDGF-BB expression groups. No significant differences were found in age, sex, education level, smoking, alcohol consumption, EBV DNA status, or tumor differentiation (all P > 0.05). However, significant associations were observed with TNM stage (P < 0.001), T stage (P = 0.005), N stage (P = 0.020), and receipt of chemotherapy (P < 0.001), suggesting a potential link between PDGF-BB expression and disease severity or treatment need (Table 3). Comparisons for other coagulation markers are shown in Tables S1, S2, S3, S4, S5.
Table 3.
Analysis of differences in clinical characteristics stratified by PDGF-BB expression levels
| Variable | Total | PDGF-BB (pg/mL) | χ2 | P | |
|---|---|---|---|---|---|
|
| |||||
| Low expression (n = 105) | High expression (n = 105) | ||||
| Age | |||||
| ≤ 50 | 74 | 37 | 37 | 4.636 | 0.098 |
| 51-64 | 88 | 50 | 38 | ||
| ≥ 65 | 48 | 18 | 30 | ||
| Gender | |||||
| Male | 130 | 68 | 62 | 0.727 | 0.394 |
| Female | 80 | 37 | 43 | ||
| Educational level | |||||
| ≤ Junior high school | 88 | 45 | 43 | 0.884 | 0.643 |
| Senior high school | 82 | 38 | 44 | ||
| ≥ University | 40 | 22 | 18 | ||
| Smoking history (cigarettes/day) | |||||
| < 10 | 109 | 60 | 49 | 2.308 | 0.129 |
| ≥ 10 | 101 | 45 | 56 | ||
| Alcohol consumption history (ml/d) | |||||
| < 1000 | 122 | 66 | 56 | 1.956 | 0.162 |
| ≥ 1000 | 88 | 39 | 49 | ||
| EBV DNA positivity | |||||
| Yes | 168 | 81 | 87 | 1.071 | 0.301 |
| No | 42 | 24 | 18 | ||
| Differentiation degree | |||||
| Well differentiated | 40 | 17 | 23 | 1.320 | 0.517 |
| Moderately differentiated | 47 | 23 | 24 | ||
| Poorly differentiated | 123 | 65 | 58 | ||
| TNM staging | |||||
| I | 18 | 18 | 0 | 21.534 | < 0.001 |
| II | 32 | 18 | 14 | ||
| III | 105 | 45 | 60 | ||
| IV | 55 | 24 | 31 | ||
| T staging | |||||
| T1 | 80 | 47 | 33 | 12.955 | 0.005 |
| T2 | 66 | 37 | 29 | ||
| T3 | 55 | 20 | 35 | ||
| T4 | 9 | 1 | 8 | ||
| N staging | |||||
| N0 | 46 | 32 | 14 | 9.791 | 0.020 |
| N1 | 38 | 16 | 22 | ||
| N2 | 80 | 34 | 46 | ||
| N3 | 46 | 23 | 23 | ||
| Receive chemotherapy | |||||
| Yes | 165 | 64 | 85 | 10.189 | 0.001 |
| No | 45 | 41 | 20 | ||
Notes: PDGF-BB, Platelet-Derived Growth Factor-BB; EBV, Epstein-Barr Virus; TNM, Tumor, Node, Metastasis; T, Tumor; N, Node.
Comparison of coagulation markers and PDGF-BB expression across clinical stages
PDGF-BB levels differed significantly across TNM stages, with stage IV patients showing significantly higher levels than stage I patients (P < 0.001). In contrast, APTT, PT, FIB, PLT, and DD levels showed no significant differences among stages (all P > 0.05; Figure 2).
Figure 2.
Expression of coagulation markers and PDGF-BB across clinical stages. A: Distribution of PDGF-BB levels across different TNM stages. B: Distribution of APTT levels across different TNM stages. C: Distribution of PT levels across different TNM stages. D: Distribution of FIB levels across different TNM stages. E: Distribution of PLT levels across different TNM stages. F: Distribution of DD levels across different TNM stages. Notes: PDGF-BB, Platelet-Derived Growth Factor-BB; APTT, Activated Partial Thromboplastin Time; PT, Prothrombin Time; FIB, Fibrinogen; PLT, Platelet Count; DD, D-dimer. ****P < 0.0001.
Comparison of coagulation markers and PDGF-BB expression between early- and advanced-stage NPC patients
PDGF-BB levels were significantly higher in advanced-stage (III/IV) than in early-stage (I/II) patients (P < 0.001). PT and FIB also showed significant differences between these groups (both P < 0.05). However, no significant differences were observed in APTT, PLT, or DD (all P > 0.05; Figure 3).
Figure 3.
Expression differences of coagulation markers and PDGF-BB in early- and advanced-stage patients. A: Distribution of PDGF-BB in Stage I/II and Stage III/IV patients. B: Distribution of APTT in Stage I/II and Stage III/IV patients. C: Distribution of PT in Stage I/II and Stage III/IV patients. D: Distribution of FIB in Stage I/II and Stage III/IV patients. E: Distribution of PLT in Stage I/II and Stage III/IV patients. F: Distribution of DD in Stage I/II and Stage III/IV patients. Notes: PDGF-BB, Platelet-Derived Growth Factor-BB; APTT, Activated Partial Thromboplastin Time; PT, Prothrombin Time; FIB, Fibrinogen; PLT, Platelet Count; DD, D-dimer. *P < 0.05, ****P < 0.0001.
Comparison of coagulation markers and PDGF-BB expression across different treatment responses
No significant differences were observed in the expression levels of PDGF-BB, APTT, PT, FIB, PLT, or DD among patients with different treatment responses (all P > 0.05; Figure 4).
Figure 4.
Expression of coagulation markers and PDGF-BB in patients with different treatment responses. A: Expression of PDGF-BB in patients with different treatment outcomes. B: Expression of APTT in patients with different treatment outcomes. C: Expression of PT in patients with different treatment outcomes. D: Expression of FIB in patients with different treatment outcomes. E: Expression of PLT in patients with different treatment outcomes. F: Expression of DD in patients with different treatment outcomes. Notes: PDGF-BB, Platelet-Derived Growth Factor-BB; APTT, Activated Partial Thromboplastin Time; PT, Prothrombin Time; FIB, Fibrinogen; PLT, Platelet Count; DD, D-dimer; CR, Complete Response; PR, Partial Response; SD, Stable Disease; PD, Progressive Disease.
Comparison of coagulation markers and PDGF-BB expression in patients with improved therapeutic outcomes
Similarly, no statistically significant differences were found in the levels of PDGF-BB, APTT, PT, FIB, PLT, or DD between patients who showed improved treatment outcomes and those who did not (all P > 0.05), as shown in Figure 5.
Figure 5.
Expression of coagulation markers and PDGF-BB in patients with different treatment responses. A: Expression of PDGF-BB in patients with improved outcomes versus disease progression. B: Expression of APTT in patients with improved outcomes versus disease progression. C: Expression of PT in patients with improved outcomes versus disease progression. D: Expression of FIB in patients with improved outcomes versus disease progression. E: Expression of PLT in patients with improved outcomes versus disease progression. F: Expression of DD in patients with improved outcomes versus disease progression. Notes: PDGF-BB, Platelet-Derived Growth Factor-BB; APTT, Activated Partial Thromboplastin Time; PT, Prothrombin Time; FIB, Fibrinogen; PLT, Platelet Count; DD, D-dimer; CR, Complete Response; PR, Partial Response; SD, Stable Disease; PD, Progressive Disease.
Prognostic value of coagulation markers and PDGF-BB for five-year survival
Overall survival outcomes
During the five-year follow-up period, 72 patients died, yielding a mortality rate of 34.29%. The average time to death was 19.83 months. These findings provided a foundation for assessing the prognostic significance of coagulation markers and PDGF-BB in NPC.
Univariate cox regression analysis
Univariate Cox regression revealed several significant predictors of five-year survival:
Each 1-unit increase of PDGF-BB levels was associated with a higher mortality risk (HR = 1.004, P < 0.001). DD also showed significant prognostic value (HR = 1.001, P < 0.001) Increased risk was observed in patients aged 51-64 years (HR = 1.998, P = 0.039) and ≥ 65 years (HR = 5.801, P < 0.001). EBV DNA positivity was associated with worse survival (HR = 0.201, P = 0.002). TNM stage III/IV: Significantly worse prognosis (HR = 5.486, P < 0.001). As for T stage T3/T4, increased mortality risk (HR = 1.855, P = 0.010).
Other variables - including sex, education level, smoking history, alcohol consumption, tumor differentiation, N stage, and chemotherapy-did not significantly impact survival (all P > 0.05; Table 4).
Table 4.
Univariate Cox regression analysis: prognostic value of coagulation markers and PDGF-BB for five-year survival
| Variable | Beta | Std Err | P | HR | Lower | Upper |
|---|---|---|---|---|---|---|
| PDGF-BB | 0.004 | 0.001 | < 0.001 | 1.004 | 1.003 | 1.006 |
| APTT | 0.001 | 0.024 | 0.981 | 1.001 | 0.954 | 1.049 |
| PT | 0.069 | 0.150 | 0.647 | 1.071 | 0.799 | 1.436 |
| FIB | -0.093 | 0.104 | 0.369 | 0.911 | 0.744 | 1.116 |
| PLT | -0.001 | 0.002 | 0.683 | 0.999 | 0.996 | 1.002 |
| DD | 0.001 | < 0.001 | < 0.001 | 1.001 | 1.001 | 1.002 |
| Age | ||||||
| ≤ 50 | ||||||
| 51-64 | 0.692 | 0.336 | 0.039 | 1.998 | 1.035 | 3.858 |
| ≥ 65 | 1.758 | 0.332 | < 0.001 | 5.801 | 3.024 | 11.127 |
| Gender | ||||||
| Male | ||||||
| Female | -0.202 | 0.248 | 0.414 | 0.817 | 0.503 | 1.327 |
| Educational level | ||||||
| ≤ Junior high school | ||||||
| Senior high school | 0.026 | 0.265 | 0.921 | 1.027 | 0.611 | 1.726 |
| ≥ University | 0.109 | 0.318 | 0.731 | 1.116 | 0.598 | 2.081 |
| Smoking history (cigarettes/day) | ||||||
| < 10 | ||||||
| ≥ 10 | 0.317 | 0.237 | 0.181 | 1.373 | 0.863 | 2.182 |
| Alcohol consumption history (ml/d) | ||||||
| < 1000 | ||||||
| ≥ 1000 | 0.228 | 0.237 | 0.336 | 1.256 | 0.790 | 1.996 |
| EBV DNA positivity | ||||||
| Yes | ||||||
| No | -1.603 | 0.515 | 0.002 | 0.201 | 0.073 | 0.552 |
| Differentiation degree | ||||||
| Well differentiated | ||||||
| Moderately differentiated | -0.202 | 0.392 | 0.607 | 0.817 | 0.379 | 1.763 |
| Poorly differentiated | 0.210 | 0.314 | 0.504 | 1.234 | 0.667 | 2.284 |
| TNM staging | ||||||
| I + II | ||||||
| III + IV | 1.702 | 0.464 | < 0.001 | 5.486 | 2.210 | 13.622 |
| T staging | ||||||
| T1 + T2 | ||||||
| T3 + T4 | 0.618 | 0.239 | 0.010 | 1.855 | 1.160 | 2.965 |
| N staging | ||||||
| N0 | ||||||
| N1-3 | 0.598 | 0.328 | 0.068 | 1.819 | 0.957 | 3.457 |
| Receive chemotherapy | ||||||
| Yes | ||||||
| No | -0.357 | 0.287 | 0.213 | 0.700 | 0.399 | 1.227 |
Notes: PDGF-BB, Platelet-Derived Growth Factor-BB; APTT, Activated Partial Thromboplastin Time; PT, Prothrombin Time; FIB, Fibrinogen; PLT, Platelet Count; DD, D-dimer; EBV, Epstein-Barr Virus; TNM, Tumor, Node, Metastasis; T, Tumor; N, Node; HR Hazard Ratio.
Kaplan-Meier survival curve analysis
Kaplan-Meier survival curves confirmed the prognostic significance of several factors. Significant survival differences (all P < 0.001) were observed based on the following items. Patients ≥ 65 years had notably lower survival than younger groups.
Positive EBV DNA status was associated with poorer survival outcomes. Patients with advanced TNM and T stages exhibited worse prognoses. High expression levels of PDGF-BB and DD were significantly associated with reduced survival. Detailed curves are presented in Figure 6.
Figure 6.
KM survival curves: influence of different clinical characteristics on five-year survival. A: Survival curves grouped by age. B: Survival curves grouped by EBV-DNA. C: Survival curves of patients with different TNM stages. D: Survival curves of patients with different T stages. E: Survival curves of patients with high vs. low PDGF-BB expression. F: Survival curves of patients with high vs. low DD expression. Notes: K-M, Kaplan-Meier; EBV, Epstein-Barr Virus; PDGF-BB, Platelet-Derived Growth Factor-BB; DD, D-dimer.
Multivariate cox regression analysis
Multivariate analysis identified the following independent predictors of five-year survival:
PDGF-BB levels < 628.18 were associated with better survival compared to ≥ 628.18 (HR = 0.492, P = 0.009). DD levels < 746.1 showed significant protective effect compared to ≥ 746.1 (HR = 0.456, P = 0.002). Strong independent effect for age 51-64 years (HR = 2.057, P = 0.032) and ≥ 65 years (HR = 4.138, P < 0.001). EBV DNA negativity was associated with better survival compared to positivity (HR = 0.273, P = 0.012). TNM stage III/IV was associated with increased mortality risk (HR = 3.042, P = 0.023). No sig- nificant effect was found in T stage (P = 0.624; Table 5).
Table 5.
Multivariate Cox regression analysis: prognostic value of coagulation markers and clinical characteristics for five-year survival
| Variable | Beta | Std Err | P | HR | Lower | Upper |
|---|---|---|---|---|---|---|
| PDGF-BB | ||||||
| ≥ 628.18 | ||||||
| < 628.18 | -0.710 | 0.273 | 0.009 | 0.492 | 0.288 | 0.840 |
| DD | ||||||
| ≥ 746.1 | ||||||
| < 746.1 | -0.785 | 0.249 | 0.002 | 0.456 | 0.280 | 0.743 |
| Age | ||||||
| ≤ 50 | ||||||
| 51-64 | 0.721 | 0.337 | 0.032 | 2.057 | 1.064 | 3.979 |
| ≥ 65 | 1.420 | 0.350 | < 0.001 | 4.138 | 2.084 | 8.215 |
| EBV DNA | ||||||
| Positive | ||||||
| Negative | -1.300 | 0.519 | 0.012 | 0.273 | 0.098 | 0.754 |
| TNM staging | ||||||
| I + II | ||||||
| III + IV | 1.113 | 0.491 | 0.023 | 3.042 | 1.163 | 7.958 |
| T staging | ||||||
| T1 + T2 | ||||||
| T3 + T4 | 0.122 | 0.250 | 0.624 | 1.130 | 0.692 | 1.845 |
Notes: PDGF-BB, Platelet-Derived Growth Factor-BB; DD, D-dimer; EBV, Epstein-Barr Virus; TNM, Tumor, Node, Metastasis; T, Tumor; HR, Hazard Ratio.
Application of the dynamic nomogram in predicting five-year survival
Figures 7 and 8 illustrate the dynamic nomogram developed using the DynNom package in R. This tool enables real-time prediction of five-year survival probabilities based on individual patient characteristics, including age, EBV DNA status, TNM stage, T stage, and PDGF-BB level.
Figure 7.
Patient 5-year prognosis nomogram. Notes: DynNom, Dynamic Nomogram; PDGF-BB, Platelet-Derived Growth Factor-BB; EBV, Epstein-Barr Virus; TNM, Tumor, Node, Metastasis; T, Tumor.
Figure 8.
Five-year survival rate prediction based on the dynamic nomogram. Notes: DynNom, Dynamic Nomogram; PDGF-BB, Platelet-Derived Growth Factor-BB; EBV, Epstein-Barr Virus; TNM, Tumor, Node, Metastasis; T, Tumor.
By inputting specific values for these variables, clinicians can dynamically calculate and visualize personalized survival probabilities. For example, a patient aged ≥ 65 years with EBV DNA negativity, TNM stage III/IV, T3/T4 staging, and high PDGF-BB levels would generate a survival curve reflecting a lower five-year survival probability.
This dynamic nomogram provides an intuitive, interactive platform for individualized survival prediction, enhancing clinical decision-making in the management of NPC.
Discussion
NPC is highly prevalent in Southeast Asia, particularly in Guangdong, Hong Kong, and Macao [19]. Coagulation abnormalities within the tumor microenvironment are closely associated with cancer progression [20]. PDGF-BB, a key regulator of cell proliferation, migration, and angiogenesis, has been strongly implicated in the development of various solid tumors [21]. This study compared PDGF-BB levels and coagulation parameters between NPC patients and healthy controls, aiming to investigate their roles in diagnosis, disease staging, treatment efficacy, and prognosis, thereby providing a foundation for precision diagnosis and individualized treatment strategies in NPC.
Our findings revealed significantly elevated PDGF-BB levels in NPC patients compared to healthy individuals, highlighting its important role in tumor initiation and progression [22]. PDGF-BB secreted by tumor cells promotes proliferation and migration, while its interaction with PDGF receptors on vascular endothelial cells activates the MAPK and PI3K/Akt pathways, facilitating neovascularization. This vascular remodeling supplies oxygen and nutrients to the tumor, enhancing its growth [22]. Additionally, NPC patients exhibited significantly higher levels of coagulation markers-APTT, PT, FIB, PLT, and DD, reflecting a dysregulated coagulation system within the tumor microenvironment [23]. These abnormalities may result from tumor-derived procoagulant factors, local inflammatory responses, and extracellular matrix remodeling, all of which promote microthrombus formation and help tumor cells evade immune surveillance [23].
Previous studies have shown that coagulation markers, with the exception of thrombin time, are associated with NPC stage and metastatic risk [24]. Elevated PDGF-BB levels derived from platelets have also been observed in breast cancer, underscoring its role in tumor angiogenesis and metastasis across multiple solid tumors [25,26]. With the development of advanced detection technologies such as surface-enhanced Raman scattering-lateral flow assay biosensors, PDGF-BB can now be detected in prostate cancer plasma at picogram-per-milliliter levels, supporting its potential as an early diagnostic biomarker for NPC [27].
Further analysis revealed a strong positive correlation between PDGF-BB levels and TNM, T, and N stages, with higher expression observed in patients with advanced-stage NPC. Tumor-derived PDGF-BB facilitates angiogenesis and extracellular matrix remodeling by activating downstream signaling in endothelial and stromal cells, thereby promoting tumor invasiveness and metastatic potential [28,29]. Although APTT, PT, FIB, PLT, and DD showed stage-dependent variation trends, their collective alterations reflect underlying coagulation dysfunction and inflammation during tumor progression. Notably, He et al. [30] reported that elevated preoperative plasma FIB levels were positively associated with TNM stage and metastatic risk, highlighting the utility of multi-marker panels for tumor staging and prognostic evaluation.
To assess treatment response, this study systematically compared biomarker profiles across patient groups stratified by clinical efficacy. Despite thorough statistical analysis, no significant differences were found in PDGF-BB or coagulation marker levels (APTT, PT, FIB, PLT, DD) between patients with treatment response and those with disease progression. Nevertheless, ROC analysis indicated that PDGF-BB retained predictive value in identifying treatment-related improvement. The complexity of clinical efficacy assessment may limit the ability of individual coagulation markers to reflect therapeutic outcomes, which are often influenced by diverse treatment protocols, tumor heterogeneity, and patient-specific factors such as therapy tolerance.
Supporting this view, Yang et al. [31] reported that reductions in PDGF-BB levels after treatment were associated with better clinical outcomes, reinforcing its potential as a response biomarker. Therefore, while no significant group differences were observed in this cohort, PDGF-BB may still play a critical role in monitoring therapeutic efficacy. Future studies incorporating broader clinical variables, diverse treatment regimens, and extended follow-up are warranted to further clarify its role in efficacy evaluation.
Using multivariate Cox regression analysis, this study identified PDGF-BB as an independent risk factor for five-year survival in NPC patients, with each unit increase in PDGF-BB levels associated with a proportional rise in mortality risk. In univariate analysis, DD also demonstrated significant prognostic value. Additionally, age, EBV DNA status, and TNM stage were found to significantly influence survival outcomes, with elderly patients, EBV DNA-positive individuals, and those with advanced-stage disease exhibiting poorer prognoses [32].
Among coagulation markers, DD was notably elevated in NPC patients and has been widely validated as a prognostic biomarker. Chen et al. [33] reported that elevated DD reflects a hypercoagulable state and is significantly associated with worse disease-free survival, distant metastasis-free survival, and overall survival, findings that align with our results. He et al. [34] further demonstrated that combined detection of DD and albumin enhances prognostic accuracy in NPC. DD levels are closely related to tumor invasiveness and metastatic potential, reinforcing their utility as a prognostic marker. Moreover, when integrated with traditional clinical factors such as TNM stage and age, survival prediction accuracy is further improved.
PDGF-BB also plays a central role in both coagulation and tumor biology. As highlighted by Liang et al. [35], PDGF-BB facilitates tumor proliferation, migration, and angiogenesis, and is strongly associated with aggressive behavior and metastatic capacity. Our study further supports this role in the NPC microenvironment.
In our analysis, age, EBV DNA status, and TNM stage emerged as strong independent prognostic indicators. Specifically, older patients, EBV DNA-positive cases, and advanced-stage tumors were consistently linked to reduced survival. EBV DNA is an established biomarker in NPC, and the study by Mazurek et al. [36] emphasized its dual value in diagnosis and prognosis. Elevated EBV DNA levels are linked to poor local control and a markedly increased risk of distant metastasis.
TNM staging remains the cornerstone of prognostic evaluation in clinical practice. However, integrating TNM stage with emerging biomarkers such as PDGF-BB and DD can significantly enhance survival prediction accuracy. Kaplan-Meier survival curves in our study demonstrated that high PDGF-BB and DD levels were strongly correlated with poorer five-year survival, validating their prognostic utility.
Interestingly, studies in other cancers also support PDGF-BB’s prognostic value. For example, in esophageal cancer, post-radiotherapy reductions in PDGF-BB levels were significantly associated with longer survival durations [37]. This finding supports the potential application of PDGF-BB in monitoring treatment efficacy and survival outcomes in NPC as well.
Based on multivariate Cox regression results, we developed a dynamic nomogram incorporating PDGF-BB, age, EBV DNA status, TNM stage, and T stage to predict individualized five-year survival. This model offers a user-friendly, interactive platform for real-time survival prediction and risk assessment, enabling clinicians to tailor treatment strategies according to patient-specific clinical profiles. With further validation in multi-center cohorts, this model holds promise for broader application in NPC and other malignancies, contributing to the advancement of precision oncology.
This study has several limitations. First, its single-center, retrospective design and limited sample size may restrict the generalizability of findings. Second, variability in detection technologies and sample processing may have reduced the sensitivity of certain coagulation parameters in predicting treatment response, limiting the utility of single-marker analysis.
Future studies should aim to conduct multi-center, prospective trials with larger cohorts to validate the diagnostic and prognostic value of PDGF-BB and coagulation biomarkers in NPC. Investigating combined biomarker panels, dynamic changes during treatment, and the molecular mechanisms underlying PDGF-BB and coagulation dysregulation will improve predictive models and guide therapeutic interventions. Integration of clinical, molecular, and imaging data will be essential for enhancing early detection, personalized treatment, and overall clinical outcomes in NPC patients.
In conclusion, PDGF-BB and key coagulation markers, particularly DD, represent promising biomarkers for prognostic assessment in nasopharyngeal carcinoma. When combined with clinical factors such as age, EBV DNA status, and TNM staging, these biomarkers can significantly enhance the accuracy of personalized survival predictions, offering valuable guidance for clinical decision-making in NPC patients receiving IMRT.
Disclosure of conflict of interest
None.
Supporting Information
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