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ORIGINAL RESEARCH article

Front. Mol. Biosci., 02 September 2025

Sec. Molecular Diagnostics and Therapeutics

Volume 12 - 2025 | https://doi.org/10.3389/fmolb.2025.1660379

This article is part of the Research TopicAdvancing Biomarker Discovery, Molecular Mechanisms, and Immunological Insights in Tumor Precision MedicineView all 4 articles

The association between composite inflammatory indicators and the clinicopathological characteristics of differentiated thyroid carcinoma

  • 1Department of Medical Oncology, Brunch of Minhang, Fudan University Shanghai Cancer Hospital Shanghai, The People’s Republic of China, Shanghai, China
  • 2Department of Pathology, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China

Purpose: This study examined the associations between composite inflammatory indicators—including the Monocyte-to-Lymphocyte Ratio (MLR), Systemic Inflammation Response Index (SIRI), and Systemic Immune-Inflammation Index (SII)—and the clinicopathological characteristics in patients with Differentiated Thyroid Carcinoma (DTC). To provide a novel insight into refining patient selection criteria for active surveillance (AS) strategies in DTC patients.

Methods: This retrospective study analyzed preoperative MLR, SIRI, and SII values in 231 DTC patients treated at Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine between January 2021 and February 2023. Comparisons of these inflammatory indicators were performed across subgroups stratified by clinicopathological characteristics. Subsequently, patients were categorized into low-expression and high-expression groups based on the median values of MLR, SIRI, and SII, followed by comparative analyses of clinicopathological features between the two groups.

Results: Comparative Analysis: SIRI levels were significantly elevated (P < 0.05) in patients with larger maximum tumor diameter, higher Ki-67 index, lymph node metastasis (LNM), capsular invasion and bilateral thyroid tumors. Similarly, SII levels were significantly elevated (P < 0.05) in patients with larger maximum tumor diameter, aggressive pathologic variants, LNM, and capsular invasion. In contrast, the MLR showed no significant associations with any of the clinicopathological subgroups analyzed (all P > 0.05). Subgroup Analysis: Compared to the high-MLR group, the low-MLR group showed a significantly lower prevalence of psammoma bodies, and lower incidence of multifocal tumors (all P < 0.05). SIRI Group Comparisons: The high-SIRI group exhibited significantly larger maximum tumor diameter, higher rates of lymphovascular invasion compared to those in the low-SIRI group (P < 0.05). SII Group Comparisons: The high-SII group demonstrated a significantly higher prevalence of aggressive pathologic variants compared to the low-SII group (P < 0.05).

Conclusion: Patients with DTC presenting elevated preoperative levels of MLR, SIRI, and SII demonstrated a significantly higher incidence of multiple adverse clinicopathological features postoperatively compared to those with lower baseline inflammatory indicators levels. These findings suggest that MLR, SIRI, and SII may serve as predictive biomarkers for adverse tumor clinicopathological characteristics in DTC.

1 Introduction

DTC encompassing papillary thyroid carcinoma (PTC), oncocytic follicular thyroid carcinoma (OFTC) and follicular thyroid carcinoma (FTC) as its subtypes, has demonstrated a progressively rising incidence in recent years, accompanied by a gradual trend toward younger age groups in disease onset (Li et al., 2020; Miranda-Filho et al., 2021). The clinicopathological characteristics of DTC have been shown to play a critical role in guiding therapeutic strategies and prognostic evaluation for patients. According to the American Thyroid Association (ATA) guidelines for thyroid cancer management, active surveillance (AS) is recommended as a viable alternative to immediate surgery for low-risk papillary thyroid carcinoma (PTC) with tumor diameters <1 cm. Furthermore, emerging studies from multiple research institutions have demonstrated promising outcomes in expanding the eligibility criteria for AS, with some prospective trials even extending the maximum tumor diameter threshold to ≤2 cm while maintaining oncologic safety (Ghai et al., 2024; Kim et al., 2024; Miyauchi et al., 2019; Miyauchi et al., 2023; Sawka et al., 2018).

Emerging evidence has demonstrated strong associations between inflammatory indicators and the clinicopathological features as well as prognosis of various solid malignancies. In cancers including but not limited to gastric, colorectal, ovarian, non-small cell lung cancer (NSCLC), and renal cell carcinoma, inflammation-related indicators such as the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), C-reactive protein (CRP), and prognostic nutritional index (PNI) have demonstrated significant predictive value for tumor aggressiveness and prognosis (Bagley et al., 2017; Luo et al., 2019; Meng et al., 2021; Numakura et al., 2024; Winata et al., 2024). However, research on the clinical relevance of these inflammation-related indicators in DTC remains limited, with existing studies yielding inconsistent conclusions regarding their correlations with clinicopathological characteristics and prognosis (Boi et al., 2017; Cai et al., 2024; Denk and Greten, 2022; Ferrari et al., 2019; Li et al., 2024; Pasquali et al., 2023).

The inflammatory indicators evaluated in this study were calculated using the following formulas: MLR: = M/L where M and L represent the absolute counts of peripheral blood monocytes and lymphocytes, respectively (Napolitano et al., 2022). SIRI:= N × M/L where N, M, and L represent the absolute counts of peripheral blood neutrophils, monocytes, and lymphocytes, respectively (Zuo et al., 2023). SII:=P × N/L where P, N, and L represent the absolute counts of peripheral platelets, neutrophils, and lymphocytes, respectively (Kou et al., 2023).

Previous studies have demonstrated that the MLR, SIRI, and SII are negatively correlated with prognosis in various solid tumors (Bagley et al., 2017; Luo, et al., 2019; Meng et al., 2021; Numakura et al., 2024; Winata et al., 2024). However, their associations with the clinicopathological characteristics of DTC patients remain underexplored. This study aims to investigate the relationships between preoperative MLR, SIRI, and SII and the clinicopathological characteristics of DTC patients, providing a novel insight into the potential application of these inflammatory indicators in guiding AS strategies for DTC. The findings are reported as follows.

2 Methods

2.1 Data collection

This study was conducted in strict adherence to the principles of the Declaration of Helsinki. Ethical approval was granted by the Ethics Committee of the Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine (Approval No. 2021-KY-109(K)). Given the retrospective nature of this study and the utilization of fully anonymized patient data, the requirement for written informed consent was formally waived. The final cohort comprised 231 patients.

Medical records of DTC patients treated at Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine between January 2021 and February 2023 were reviewed. Inclusion criteria: ① confirmed postoperative pathological diagnosis of DTC; ② availability of fasting blood samples collected between 8:00–10:00 a.m. preoperatively for complete blood count analysis. Exclusion criteria: ① concurrent conditions affecting white blood cell counts; ② history of other malignancies; ③ preoperative use of medications affecting inflammatory cells. Based on the above criteria, 231 eligible patients were ultimately enrolled in this study.

Collection of Baseline Clinical Data: Clinical documentation must include baseline characteristics (age, gender, body mass index), hematologic indices such as complete blood count (CBC).

Collection of pathological data: The histopathological diagnostic report include assessment of maximum tumor diameter, histological subtype, lymphovascular invasion status, presence of psammoma bodies, tumor-infiltrating lymphocytes (TILs), concurrent Hashimoto’s thyroiditis (HT), thyroid capsular invasion, multifocality (defined as ≥2 tumor foci in the surgical specimen), bilateral thyroid tumors, LNM, genetic mutation profile, and Ki-67 index.

Evaluate the differences in MLR, SIRI, and SII values among patients with distinct clinicopathological characteristics, including maximum tumor diameter, LNM, and lymphovascular invasion, the patient cohort was stratified into the following groups based on the median values of these indicators: low-MLR group (MLR < median), high-MLR group (MLR ≥ median), low-SIRI group (SIRI < median), high-SIRI group (SIRI ≥ median), low-SII group (SII < median), and high-SII group (SII ≥ median). The differential distribution of clinicopathological characteristics (e.g., maximum tumor diameter, LNM, and lymphovascular invasion) across these groups was subsequently analyzed.

2.2 Statistical analysis

Data analysis was performed using R statistical software (version 4.4.1). Categorical variables were presented as frequencies and percentages (%), with intergroup comparisons conducted using the chi-square test. Continuous variables were expressed as mean ± standard deviation (SD) and analyzed with the Student’s t-test for group comparisons. Comparisons among multiple groups were assessed using analysis of variance (ANOVA). P-value<0.05 was considered statistically significant. Fisher’s exact test governed by sample size and expected frequency thresholds was supplemented by residual decomposition analysis to isolate significant contributors. Separate univariable and multivariable logistic regression models were performed treating aggressive pathological variants and lymph node metastasis as distinct dependent variables. ROC analysis was used to evaluate the predictive performance of inflammatory markers for lymph node metastasis and their ability to discriminate aggressive pathologic variants.

3 Results

3.1 Clinical Characteristics

This study included 231 patients [78 males (33.8%) and 153 females (66.2%) ]with an age range of 17–80 years (mean: 43.71 ± 12.9 years). Body mass index (BMI) ranged from 16.26 to 34.29 kg/m2 (mean: 24.04 ± 3.51 kg/m2), and maximum tumor diameter varied between 0.1 and 6.5 cm (mean: 1.16 ± 1.06 cm). The MLR ranged from 0.08 to 1.33 (mean: 0.28 ± 0.16; median: 0.24). The SIRI ranged from 0.25 to 13.2 (mean: 1.40 ± 1.70; median: 0.94), while the SII ranged from 148.89 to 6,509 (mean: 725.94 ± 724.69; median: 520.59). Patients were dichotomized into high and low groups for MLR, SIRI, and SII using the median value of each index within the study cohort.

3.2 Differences in preoperative MLR, SIRI, and SII values among DTC patients with different clinicopathological characteristics

3.2.1 SIRI and MLR

SIRI levels differed significantly across the following clinicopathological subgroups (all P < 0.05): tumors >1 cm vs. ≤ 1 cm in maximum tumor diameter, high KI67 index (≥3%) vs. low KI67 (<3%), LNM-positive vs. LNM-negative, capsular invasion vs. non-invasion, and bilateral vs. unilateral thyroid tumors. Specifically, patients with larger maximum tumor diameter (>1 cm) exhibited higher SIRI levels compared to those with smaller maximum tumor diameter (≤1 cm). Similarly, elevated SIRI levels were observed in subgroups with high KI67 index (≥3%), LNM-positive, capsular invasion, and bilateral thyroid tumors (Table 1). In contrast, no statistically significant differences in MLR levels were observed among the subgroups (Table 2).

Table 1
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Table 1. SIRI levels in DTC patients with different clinicopathological characteristics (n = 231).

Table 2
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Table 2. MLR levels in DTC patients stratified by clinicopathological characteristics (n = 231).

3.2.2 SII

SII levels showed statistically significant differences among the following groups (all P < 0.05): tumors >1 cm vs. ≤1 cm in maximum diameter, aggressive pathologic variants vs. non-aggressive pathologic variants, LNM-positive vs. LNM-negative, and capsular invasion vs. non-invasion. Patients with larger maximum tumor diameter (>1 cm), aggressive pathologic variants, LNM-positive, and capsular invasion demonstrated significantly higher SII levels compared to their respective counterparts (Table 3).

Table 3
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Table 3. SII levels in DTC patients with different clinicopathological characteristics (n = 231).

3.3 Comparative analysis of clinicopathological characteristics between low and high MLR, SIRI, and SII groups

3.3.1 Comparative analysis of clinicopathological characteristics between low and high MLR groups

Comparison between the low MLR group and the high MLR group revealed no statistically significant differences (p > 0.05) in gender, age, maximum tumor diameter, proportion of aggressive pathologic variants, presence of lymphovascular invasion, Ki67 index, gene mutation profile, presence of TILs, concurrent Hashimoto’s thyroiditis, LNM status, capsular invasion status, and presence of bilateral thyroid tumors. However, among patients younger than 55 years, those in the low MLR group were significantly younger than those in the high MLR group (P < 0.05). Additionally, the low MLR group exhibited significantly higher BMI (P < 0.05), a significantly lower proportion of psammoma bodies (P < 0.05), and a significantly lower proportion of multifocal tumors (P < 0.05) compared to the high MLR group (Table 4).

Table 4
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Table 4. Comparison of clinicopathological characteristics between low and high MLR groups (n = 231).

3.3.2 Comparative analysis of clinicopathological characteristics between low and high SIRI groups

No significant associations were observed between SIRI groups (low SIRI group vs. high SIRI group) and the following parameters: gender, age, BMI, proportion of aggressive pathologic variants, presence of psammoma bodies, Ki67 index, gene mutation status, TILs, prevalence of concurrent Hashimoto’s thyroiditis, LNM, capsular invasion, multifocal tumor, and bilateral thyroid tumor (all P > 0.05). However, patients in the high SIRI group exhibited significantly larger maximum tumor diameter and a significantly higher incidence of lymphovascular invasion (both P < 0.05) (Table 5).

Table 5
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Table 5. Comparative analysis of clinicopathological characteristics between low/high SIRI groups (n = 231).

3.3.3 Comparative analysis of clinicopathological characteristics between low and high SII groups

No significant associations were observed between SII groups (low SII group vs. high SII group) and the following parameters: gender, BMI, maximum tumor diameter, lymphovascular invasion, presence of psammoma bodies, Ki67 index, gene mutation status TILs, prevalence of concurrent Hashimoto’s thyroiditis, LNM, capsular invasion, multifocal tumor, and bilateral thyroid tumor (all P > 0.05). Notably, among patients aged <55 years, those in the high SII group were significantly older than those in the low SII group (P < 0.05). Additionally, the high SII group had a significantly higher proportion of aggressive pathologic variants compared to the low SII group (P < 0.05). Fisher’s exact test revealed no statistically significant difference in the distribution of pathologic variants between the low and high systemic immune-inflammation index groups (P = 0.215). However, standardized residual analysis identified clinically meaningful patterns: The classic variant was significantly more frequent than expected in the low-SII group (residual +1.90, P = 0.057) while substantially less frequent in the high-SII group (residual −1.90). The hobnail variant demonstrated a non-significant enrichment trend in the high-SII group (residual +1.24, P = 0.215) (Table 6).

Table 6
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Table 6. Comparative analysis of clinicopathological characteristics between low- and high-SII groups (n = 231).

3.3.4 Univariate and multivariate analyses with aggressive pathological variants and lymph node metastasis as dependent variables

Univariate and multivariate analyses with aggressive pathological variants as the dependent variable revealed that Lymphovascular Invasion (B=1.176,P=0.010), Age (B=-0.038,P=0.011), Ki-67 (B=0.342,P=0.003), and SII (B=0.434,P=0.030) remained significantly associated with aggressive variants after adjustment (p < 0.05 for all). This identifies Lymphovascular Invasion, Age, Ki-67, and SII as independent predictors of aggressive pathological variants (Table 7; Table 8).

Table 7
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Table 7. Univariate analyses with aggressive pathological variants as the dependent variable.

Table 8
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Table 8. Multivariate analyses with aggressive pathological variants as the dependent variable.

Univariate and multivariate analyses with lymph node metastasis as the dependent variable demonstrated that Gender (B=0.840,P=0.011), Psammoma Bodies (B=1.144,P=0.040), Non-BRAF mutation (B=-1.544,P=0.021), Tumor Size (B=0.456,P=0.047), and SIRI (B=0.380,P=0.011) were significantly associated with lymph node metastasis (p < 0.05 for all). This identifies Gender, Psammoma Bodies, Non-BRAF mutation, Tumor Size, and SIRI as independent predictors of lymph node metastasis (Table 9; Table 10).

Table 9
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Table 9. Univariate analyses with Lymph node metastasis as the dependent variable.

Table 10
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Table 10. Multivariate analyses with Lymph node metastasis as the dependent variable.

3.3.5 ROC analysis: SIRI predicts lymph node metastasis and SII identifies aggressive pathologic variants

ROC analysis demonstrated that the SIRI exhibited moderate discriminative ability in predicting lymph node metastasis, with an AUC of 0.744 (95% CI: 0.685–0.804). The optimal cutoff value for SIRI was identified as 2.555 through maximization of the Youden index. At this threshold, sensitivity reached 51.8%, while specificity was notably higher at 92.0%, yielding a Youden index of 0.438 (Figure 1).

Figure 1
ROC curve analysis graph for the predictor SIRI, displaying a blue line and a red diagonal line. The area under the curve (AUC) is 0.744 with a 95% confidence interval of 0.685 to 0.804. The cutoff is 2.555, sensitivity is 51.8%, and specificity is 92%. The x-axis shows 1-specificity (false positive rate), and the y-axis shows sensitivity (true positive rate).

Figure 1. ROC curve analysis of the SIRI for detecting lymph node metastasis in DTC. The AUC was 0.744 (95% CI: 0.685–0.804), indicating moderate accuracy. Using a cutoff of 2.555, SIRI identified metastatic patients with 92.0% specificity and 51.8% sensitivity.

Discriminatory performance of SII ROC analysis revealed that the SII demonstrated moderate discriminatory ability in identifying invasive pathological subtypes, with an AUC of 0.647 (95% CI: 0.581–0.713). The optimal cutoff value was determined as 1,015.98 by maximizing the Youden index. At this threshold, SII achieved exceptionally high specificity of 96.0% (95% CI: 92.4%–98.1%), but low sensitivity of 32.8% (95% CI: 25.3%–41.2%). The resultant Youden index was 0.288, indicating suboptimal overall diagnostic efficacy (Figure 2).

Figure 2
ROC curve analysis for predictor SII shows sensitivity against 1-specificity. The curve has an AUC of 0.647 with a 95% confidence interval of 0.581 to 0.713. A cutoff point at 1015.98 has sensitivity of 32.8% and specificity of 98%.

Figure 2. The SII as a specific biomarker for aggressive pathologic variants in DTC. ROC analysis showed an AUC of 0.647 (95% CI: 0.581–0.713). At a cutoff of 1015.98, the SII ruled in aggressive pathologic variants with 96.0% specificity, while sensitivity was 32.8%.

4 Discussion

Over the past decade, AS has been established as a novel clinical management strategy for low-risk thyroid cancer. Multiple prospective studies have progressively expanded its applicability and demonstrated favorable outcomes (Ito et al., 2023; Kim et al., 2024; Miyauchi et al., 2023; Miyauchi et al., 2018; Miyauchi and Ito, 2019; Oda et al., 2017; Sasaki et al., 2023). Currently, the clinical significance of various inflammatory indicators, such as the NLR, PLR, and MLR, in the pathogenesis, treatment response, and prognostic evaluation of solid tumors has been extensively investigated (Gao et al., 2024; Hu et al., 2014; Lu et al., 2024; Zhou et al., 2023; Zuo et al., 2023). This study aims to provide a novel perspective on the utility of inflammatory indicators for risk stratification and dynamic monitoring of patients undergoing AS for differentiated thyroid cancer.

The MLR, calculated from absolute peripheral blood monocyte and lymphocyte counts, serves as a hematological biomarker. Peripheral blood monocytes take participate in paracrine signaling to secrete abundant inflammatory cytokines (e.g., TNF-α, IL-1, IL-6) and chemokines. They can be recruited into the tumor tissue thus leading to a decrease in cytotoxic CD8+ T cell infiltration. Studies demonstrate that targeted inhibition of monocyte-derived populations within tumors elevates CD8+ T-cell density, thereby suppressing growth across multiple solid malignancies (Li et al., 2017; Mitchem et al., 2013). Notably, non-classical monocytes facilitate NK cell recruitment to metastatic sites through secretion of chemokine ligands (CCL3, CCL4, CCL5). The close relationship between monocytes and lymphocytes has led us to increase our focus on MLR. Substantial evidence establishes MLR as an independent prognostic factor across multiple solid malignancies, including lung cancer, urothelial carcinoma, ovarian cancer, and gastrointestinal stromal tumors (GISTs) (Cananzi et al., 2019; Huai et al., 2023; Kovacs et al., 2023; Shao et al., 2020). Our study demonstrates that elevated MLR levels significantly correlate with adverse clinicopathological features in DTC patients. Specifically, patients with high MLR exhibit increased likelihood of psammoma bodies—a histopathological marker strongly associated with LNM and distant spread (Cai et al., 2015; O'Connor et al., 2022). Furthermore, high MLR independently predicts multifocal tumor occurrence (P < 0.05).

The SIRI, calculated from peripheral neutrophil, monocyte, and lymphocyte counts, serves as an indicator of systemic inflammatory status. Elevated SIRI values correlate not only with heightened inflammatory activity but also carry significant biological implications within the tumor microenvironment. Existing research on SIRI has primarily focused on gastric, colorectal, breast and lung cancers, consistently demonstrating a significant association between high SIRI and poorer prognosis in these malignancies (Cao et al., 2023; Ren et al., 2024; Wu and Zhao, 2024; Ye et al., 2024; Zhang and Cheng, 2024). However, investigations into the correlation between SIRI and clinicopathological characteristics specifically in patients with DTC remain limited. Our findings indicate that DTC patients within the high-SIRI group exhibit significantly more adverse clinicopathological characteristics than those in the low-SIRI group. Specifically, patients with high SIRI had larger maximum tumor diameter and a higher prevalence of lymphovascular invasion. The biological underpinning for these associations may involve the roles of inflammatory cells within the tumor microenvironment. Neutrophils and monocytes can secrete various cytokines and enzymes that promote tumor cell proliferation and survival. For instance, inflammatory cytokines like IL-6 can activate the STAT3 signaling pathway, thereby upregulating the expression of anti-apoptotic and proliferative proteins (El-Tanani et al., 2022). Monocytes recruited into tumor tissue differentiate into tumor-associated macrophages (TAMs). TAMs secrete numerous cytokines and matrix metalloproteinases (MMPs), which degrade the extracellular matrix and reduce tumor cell adhesion, thereby facilitating tumor cell invasion and metastasis (Liu et al., 2019). Conversely, lymphocytes, particularly cytotoxic CD8+ T cells, are integral to anti-tumor immune responses. A reduction in lymphocyte count impairs immune surveillance, thereby promoting tumor immune evasion and progression (Christo et al., 2024; Galassi et al., 2024; Lawson et al., 2020; Ribot et al., 2021). The ROC analysis reveals that the SIRI exhibits a moderately strong discriminatory capacity (AUC = 0.744; 95% CI: 0.685–0.804) in predicting lymph node metastasis of DTC. Its high specificity (0.92) underscores SIRI’s utility as a reliable tool to rule out non-metastatic patients, which is critical for selecting candidates suitable for active surveillance. However, the suboptimal sensitivity (0.518) implies a substantial risk of false negatives, necessitating caution when using SIRI alone for positive identification. The optimal cutoff value (2.555) derived from the Youden index provides a clinically actionable threshold.

The SII, derived from the combined counts of neutrophils, lymphocytes, and platelets, serves as a metric to assess systemic inflammatory status in patients. Current clinical evidence indicates that elevated circulating neutrophil levels correlate with poor prognosis in cancer patients (Shaul and Fridlender, 2019). There are multiple complex interactions between platelets and tumors, and these interactions play important roles in tumor growth, metastasis, immune escape, and chemotherapy resistance. Platelet-derived TGF-β can induce Epithelial-Mesenchymal Transition (EMT) in tumor cells, thereby enhancing their migratory and invasive potential. Furthermore, platelets promote tumor angiogenesis by releasing pro-angiogenic factors such as VEGF and Angiopoietins (Ang1-2), establishing a microenvironment conducive to tumor growth and dissemination (Filippelli et al., 2022; Gao et al., 2024; Lu et al., 2024; Zhou et al., 2023). Conversely, lymphocytes, particularly CD8+ T cells, are pivotal in anti-tumor immunity. They induce tumor cell apoptosis via the Fas/FasL pathway and inhibit metastatic niche formation through the secretion of Granzyme B (Martinez-Lostao et al., 2015). By mediating cytotoxic cell death and suppressing tumor cell proliferation and migration, lymphocytes play a critical role in cancer immunosurveillance and defense (Galassi et al., 2024; Lawson et al., 2020; Ribot et al., 2021). Consequently, the concurrent manifestation of elevated neutrophil counts, increased platelet levels, and reduced lymphocyte counts–indicative of a high SII value–typically signifies a pronounced inflammatory response coupled with a weakened immune response. This pathological interplay facilitates enhanced tumor cell invasion and metastasis, ultimately resulted in poor prognosis for the patient. Our study revealed that among patients younger than 55 years, those in the high-SII group were significantly older than those in the low-SII group. Additionally, the proportion of patients exhibiting aggressive pathologic variants was significantly greater in the high-SII group compared to the low-SII group. The ROC analysis demonstrated that the systemic immune-inflammation index (SII) exhibits a modest discriminatory capacity (AUC = 0.647; 95%CI:0.581–0.713) in distinguishing aggressive pathologic variants of DTC. While the high specificity (0.96) suggests SII effectively excludes non-aggressive cases, its suboptimal sensitivity (0.328) indicates substantial limitations in identifying true aggressive pathologic variants. The Youden index-derived optimal cutoff (1,015.98) yielded a balanced performance metric of 0.288, positioning SII as a potential adjunctive screening tool. However, the considerable false-negative rate implied by low sensitivity warrants caution in standalone application. These findings underscore the need for multimarker validation studies to enhance diagnostic precision for aggressive DTC subtyping.

This study elucidates the pivotal role of SII and SIRI in stratifying DTC patients for active surveillance. The consistently high specificity (SII: 0.96; SIRI: 0.92) of both indices demonstrates robust capability to rule out high-risk phenotypes—a critical prerequisite for identifying candidates suitable for non-operative management. Although suboptimal sensitivity (SII: 0.328; SIRI: 0.518) limits their power to detect all low-risk cases, this characteristic is clinically acceptable in active surveillance paradigms where minimizing false-positive inclusions outweighs the need for exhaustive case identification. The derived optimal cutoffs (SII: 1,015.98; SIRI: 2.55) provide actionable thresholds for implementing these biomarkers in clinical workflows. When integrated with established tools like ultrasonography and molecular testing, SII/SIRI enhance precision in selecting patients with indolent disease biology. Future validation studies should prospectively assess these indices in risk-adapted management protocols, particularly focusing on long-term outcomes of surveillance cohorts stratified by inflammatory profiling.

Limitations of this study include the following: First, the current sample size requires expansion, as the single-center recruitment may introduce selection bias; thus, future multi-center large-sample prospective studies are warranted to validate our findings. Second, the retrospective design entailed subject selection based on pre-existing data rather than random sampling. Third, the favorable prognosis of differentiated thyroid carcinoma (DTC), characterized by rare postoperative recurrence, metastasis, and disease-specific mortality, undermines prediction model reliability—manifested as inflated AUC with wide confidence intervals in ROC analysis and overfitting risks in Cox regression. External validation through multicenter cohorts is imperative.

5 Conclusion

In summary, DTC patients with different preoperative MLR levels demonstrated significant differences in the presence of psammoma bodies and multifocal tumors. Patients with different preoperative SIRI levels exhibited significant differences in maximum tumor diameter and the rate of lymphovascular invasion. Furthermore, significant differences in the proportion of aggressive pathologic variants were observed among patients with different preoperative SII levels. These findings suggest that the MLR, SIRI, and SII levels can serve as predictive indicators for clinical-pathological features of DTC. Multivariable analyses confirmed SIRI as an independent predictor of lymph node metastasis and SII as an independent predictor of aggressive pathological variants. Monitoring SIRI and SII may offer new perspectives for optimizing patient selection in thyroid cancer active surveillance.

SII and SIRI demonstrate significant rule-out utility for high-risk DTC phenotypes, establishing their value as triaging tools in active surveillance programs. Despite suboptimal sensitivity, their high negative predictive power supports clinical deployment at derived cutoffs to identify candidates for non-operative management. Integration with imaging and molecular biomarkers is recommended to mitigate false-negative risks. Prospective validation of these indices in risk-stratified surveillance cohorts is warranted.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics statement

The studies involving humans were approved by Ethics Committee of the Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine (Approval No. 2021-KY-109(K)). The studies were conducted in accordance with the local legislation and institutional requirements. The ethics committee/institutional review board waived the requirement of written informed consent for participation from the participants or the participants’ legal guardians/next of kin because Given the retrospective nature of this study and the utilization of fully anonymized patient data, the requirement for written informed consent was formally waived.

Author contributions

L-YY: Writing – review and editing, Formal Analysis, Data curation, Conceptualization, Writing – original draft. L-PY: Writing – review and editing, Writing – original draft.

Funding

The author(s) declare that financial support was received for the research and/or publication of this article. Clinical research funds from Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine (Grant No. ynhg202114).

Acknowledgments

We gratefully acknowledge the participation of all patients in this study.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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The author(s) declare that no Generative AI was used in the creation of this manuscript.

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Keywords: differentiated thyroid carcinoma, clinicopathological characteristics, monocyte-to-lymphocyte ratio, systemic inflammation response index, systemic immune-inflammation index

Citation: Yang L-Y and Yang L-P (2025) The association between composite inflammatory indicators and the clinicopathological characteristics of differentiated thyroid carcinoma. Front. Mol. Biosci. 12:1660379. doi: 10.3389/fmolb.2025.1660379

Received: 05 July 2025; Accepted: 12 August 2025;
Published: 02 September 2025.

Edited by:

Chao Liu, Harvard Medical School, United States

Reviewed by:

Deniz Gezer, Mersin City Hospital, Türkiye
Eren Ozan Yildiz, Akdeniz University Faculty of Tourism, Türkiye

Copyright © 2025 Yang and Yang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Li-Peng Yang, eWFuZ2xpcGVuZ2Z1ZGFuQG91dGxvb2suY29t

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