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. 2025 Nov 7;138(23):3131–3138. doi: 10.1097/CM9.0000000000003553

Serum immune parameters as predictors for treatment outcomes in cervical cancer treated with concurrent chemo-radiotherapy

Lihua Chen 1,2,4, Weilin Chen 3, Yingying Lin 4, Xinran Li 1,2, Yu Gu 1,2, Chen Li 1,2, Yuncan Zhou 5, Ke Hu 5, Fuquan Zhang 5, Yang Xiang 1,2,✉
Editors: Sihan Zhou, Xiuyuan Hao
PMCID: PMC12700757  PMID: 41199468

Abstract

Background:

Concurrent chemo-radiotherapy (CCRT) is the standard treatment for locally advanced cervical cancer (LACC), but there are still many patients who suffer tumor recurrence. However, valuable predictors of treatment outcomes remain limited. This study aimed to assess the value of the serum immune biomarkers to predict the prognosis.

Methods:

We reviewed cervical cancer patients treated with CCRT between January 2014 and May 2018 at Peking Union Medical College Hospital. The systemic immune inflammation index (SII), systemic inflammation response index (SIRI), and lactate dehydrogenase (LDH) were calculated using blood samples. The relationship between immune markers and the treatment outcome was analyzed. The area under the receiver operating characteristic (ROC) curve was used to evaluate the predictive efficiency. The Cox proportional hazards model and log-rank were used to predict overall survival (OS) and disease-free survival (DFS).

Results:

This study included 667 patients. Among them, 195 (29.2%) patients were defined as treatment failure, including 127 (19.0%) patients with pelvic failure, 94 (14.1%) distant failure, and 25 (3.7%) concurrent pelvic and distant failure. It revealed that the tumor stage, size, metastatic lymph nodes (MLNs), and serum immune biomarkers, such as SII, SIRI, and LDH, were significantly related to treatment outcomes. We demonstrated that the optimal cut-off of the SII, SIRI, and LDH were 970.4 × 109/L, 1.3 × 109/L, and 207.52 U/L, respectively. Importantly, this study presented that LDH level had the highest OR (OR = 4.2; 95% CI [2.3–10.8]). Furthermore, the OS and DFS for patients with pre-SII ≥970.5 × 109/L were significantly worse than those with pre-SII <970.5 × 109/L. Similarly, pre-SIRI ≥1.25 × 109/L and pre-LDH ≥207.5 U/L were related to poor survival outcomes.

Conclusions:

This study demonstrated that the baseline SII, SIRI, and LDH levels can be used to accurately and effectively predict the treatment outcomes after CCRT and long-term prognosis. Our results may offer additional prognostic information in clinical, which helps to detect the potential recurrent metastasis in time.

Keywords: Serum parameters, Cervical cancer, Prognosis, Immune, Inflammatory, Concurrent chemo-radiotherapy

Introduction

Cervical cancer is one of the most common malignant tumors in women, especially in developing countries, which seriously endangers women’s life and health. In 2022, there were 661,021 new cases and 348,189 deaths globally, which has an increasing trend.[1,2] The prognosis of early cervical cancer is better. Due to the uneven development of medical levels in different regions, cervical cancer screening and vaccination in developing countries are not yet popularized. Thus, more than half of cervical cancer patients have advanced at diagnosis.[3] Several guidelines recommend platinum-based concurrent chemo-radiotherapy (CCRT) as the standard therapy for locally advanced cervical cancer (LACC).[4] However, 20–40% of patients still suffer tumor recurrence, and the 5-year survival rate is 60–70%.[5,6] Therefore, reducing the recurrence of cervical cancer after CCRT is still a challenging problem and a hot issue.

The mechanisms of cervical cancer recurrence post-CCRT have not been determined yet. Therefore, it is valuable to find the risk factors of recurrence as early as possible to identify patients with a high risk of recurrence and to give them more active treatment. Improving the survival rate of cervical cancer patients in clinics is significant. Recent studies have shown that age, pathological types, the International Federation of Gynecology and Obstetrics (FIGO) stage, and lymph node metastasis influence tumor responsiveness to radiotherapy and patient survival.[7,8] However, the clinical value of those indicators remains limited due to the lack of quantitative predictive power.

The existence of tumor tissue heterogeneity can lead to differences in biological phenomena such as immunity, metabolism, proliferation, and metastasis. Inflammation and immune status play an important role in carcinogenesis and progression and can even be used to measure disease progression.[9] Lactate dehydrogenase (LDH), as a marker of systemic inflammation and tumor burden, can modulate the tumor microenvironment (TME) by increasing the production of lactate and promoting immunosuppression.[9,10] The level of serum LDH is associated with the prognosis of several cancers, including nasopharyngeal, colon, and lung cancers.[11,12] Systemic inflammatory markers are independent prognostic factors for the survival of multiple malignancies.[13,14] Blood neutrophil–lymphocyte ratio (NLR) is a commonly used inflammatory marker, and some studies indicate that increased NLR is a poor prognostic factor for cervical cancer.[15] Fortunately, the systemic immune inflammation index (SII) and systemic inflammation response index (SIRI) are novel and comprehensive inflammatory predictors that can affect systemic inflammation and local immune status.[16–18] In addition, studies have demonstrated that SII and SIRI can better reflect the chronic inflammatory state than NLR and other inflammatory indicators.[19,20] Therefore, they can serve as valuable predictors of immune status and systemic inflammation with more diagnostic effectiveness and stability. Furthermore, easy access to peripheral blood provides an accessible source for investigating the potential serum biomarkers in disease. Nevertheless, the relationships of serum biomarkers with the treatment outcome and long-term prognosis after CCRT remain unknown.

The objective of this study was to investigate the association between serum immune-related biomarkers (including SII, SIRI, and LDH) and both treatment outcomes and long-term prognosis.

Methods

Participants

This study was approved by the Institutional Ethic Review Board of Peking Union Medical College Hospital (No. K3824) and complied with the Declaration of Helsinki. All patients provided informed consent. We reviewed patients with cervical cancer and treated them with CCRT between January 2014 and May 2018 in Peking Union Medical College Hospital. All participants met the following criteria: (1) pathological diagnosis of squamous carcinoma of the cervix (SCC), adenocarcinoma of the cervix (AC), and adenosquamous carcinoma (ASC); (2) FIGO stage (2009) IB-IVA; (3) treated with standardized CCRT and achieved complete response (CR) after 3 months; (4) complete clinical and follow-up data; (5) without coexisting acute and chronic infectious diseases; (6) follow-up time at least 36 months; and (7) without other primary tumors. The flowchart of the study is presented in Figure 1.

Figure 1.

Figure 1

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The flowchart of cervical cancer patients treated with CCRT inclusion and group allocation of the study. CCRT: Concurrent chemo-radiotherapy; PUMCH: Peking Union Medical College Hospital.

Treatment

The detailed treatment was described in previous studies.[21,22] All patients carried out intensity-modulated radiation therapy (IMRT) and intracavitary brachytherapy (ICBT). IMRT was delivered with fix-field IMRT, volumetric-modulated arc therapy, or helical tomotherapy. All participants gained standardized CCRT, which included the chemotherapy and radiotherapy. A 45–50 Gy dose in 25–28 fractions was given to the pelvis, and 59–61 Gy was prescribed to the metastatic lymph nodes (MLNs). Weekly cone beam computed tomography (CBCT) was performed for image guidance. ICBT was delivered with an Ir192 source, with 30–36 Gy in 5–6 fractions to point A. Weekly cisplatin was the first-line regimen of concurrent chemotherapy. The preferred regimen is the weekly cisplatin (30–40 mg/m2) concurrent chemotherapy.

Follow-up

Follow-up was conducted by admission review and telephone call. All patients had follow-up examinations every 3 months in the first 2 years, every 6 months for 3–5 years, and once per year after 5 years. Follow-up examination items including gynecological examination, tumor markers, thoracic and abdominal CT, and pelvic magnetic resonance imaging (MRI) were performed. Some patients received positron emission tomography-computed tomography (PET/CT) when there is a high suspicion of tumor recurrence and metastasis. All patients were regularly followed up at least 3 years after treatment or until their death, and the final point time is July 1, 2023.

Definition

Treatment failure was defined as the disease progression with the standard CCRT after 3 months and the recurrence of the tumor during the follow-up period.

Cumulative incidence of recurrence (CIR) means the frequency of cervical cancer recurrence from the 3 months after CCRT to the follow-up endpoint. Local recurrence (LR) refers to the recurrence site being limited to the pelvic cavity. Those located in the vagina, cervical, and uterine intrauterine are called central pelvic recurrence (CPR); and those occurred in the pelvic lymph nodes, para-aortic lymph nodes, and inguinal lymph nodes are called lateral pelvic recurrence (LPR). Distant recurrence (DR) means the recurrent mass spread over the external pelvis beyond the radiation field, including distant organs and lymph node. Lymph node metastasis (LNM) needs to meet the following diagnostic criteria: (1) CT or MRI suggests lymph node short diameter ≥1 cm; (2) CT or MRI suggests lymph node with central low density or necrosis, rim ring enhancement; (3) CT or MRI suggests lymph node fusion in multiple clusters; and (4) PET-CT suggests lymph node short diameter ≥1 cm or standardized uptake value (SUV)max ≥2.5.[23] Overall survival (OS) was defined as the start of treatment until death due to any cause or more than 3 years of follow-up time. Disease-free survival (DFS) was defined as the time from the start of treatment until recurrence, metastasis, or death due to any cause or more than 3 years of follow-up time.

Serum biomarkers assay

The blood samples were collected during the face-to-face interviews before the CCRT procedure. LDH and blood cell count, including neutrophil, lymphocyte, monocyte, and platelet counts, were detected with a chemiluminescent microparticle using Architect i2000SR (IMX; Abbott Diagnostics, Chicago, IL, USA). The SII (platelet count × neutrophil count/lymphocyte count) was calculated with absolute platelet count (×109/L), neutrophil count (×109/L), and lymphocyte count (×109/L).[24,25] The SIRI (monocyte count × neutrophil count/lymphocyte count) was calculated with absolute monocyte count (×109/L), neutrophil count (×109/L), and lymphocyte count (×109/L).[24,25] The reference range of LDH in our study was 140–271 U/L.

Statistical analysis

For continuous variable, non-normally distributed data are indicated as median (Q1–Q3). Mann–Whitney U-test was conducted for comparison between groups; data conforming to a normal distribution were stated as mean ± standard deviation and compared between the two groups using the independent samples t-test.[26] The measurement data were calculated using chi-squared tests, and the counting data were calculated using t-tests. The area under the receiver operating characteristic (ROC) curve (AUC) was used to assess the predictive efficiency of serum immune markers (SII, SIRI, and LDH) with treatment outcomes after CCRT. The optimal cut-off values were determined by maximizing the sum of the sensitivity and specificity. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. Also, the Cox proportional hazards model was used to estimate the independent prognostic factors for predicting treatment failure. The results were presented as odds ratio (OR) and 95% confidence interval (CI). OS and DFS were plotted using Kaplan–Meier curves, and the comparison between subgroups was performed using log-rank test. The significance level was set at a P value <0.05. All statistical analyses were calculated using SPSS version 26.0 (IBM, Armonk, NY, USA).

Results

Clinical characteristics

In all, 667 patients were included in the study. The detailed clinical characteristics are presented in Supplementary Table 1, http://links.lww.com/CM9/C378. The median age was 51 years (range, 25–76 years). The median pre-treatment SCC-Ag, SII, SIRI, and LDH levels were 3.5 (1.4–10.8) ng/mL, 670.4 (450.7–1089.2) × 109/L, 0.9 (0.5–1.5) × 109/L, and 174.0 (154.0–208.4) U/L, respectively. The median follow-up period was 71.5 months (2.0–102.0 months). In addition, 206 patients (30.8%), 196 patients (29.4%), and 26 patients (3.9%) suffered regional MLNs, pelvic MLNs, and para-aortic MLNs, respectively.

Association between the serum immune biomarkers and treatment outcomes

Out of 667 patients, a total of 195 (29.2%) patients were defined as treatment failure, including 126 (18.9%) patients with pelvic failure, 94 (14.1%) patients with distant failure, and 25 (3.7%) patients with concurrent pelvic and distant failure [Figure 2A–C]. As shown in Figure 2D, we found that the rates of death, recurrence, and treatment success in 1-year were 0.6% (5/667), 11.8% (79/667), and 87.4% (583/667), respectively; the rates of death, recurrence, and treatment success in 2-year were 5.1% (34/667), 13.8% (92/667), and 81.1% (541/667), respectively; and the rates of death, recurrence, and treatment success in 3-year were 10.8% (72/667), 13.2% (88/667), and 76.1% (507/667), respectively. The CIR increased rapidly with survival time. In particular, the fastest increase occurred before 18 months. Similarly, the CIR of LRR and DR presents the same pattern. The 3-year OS, DFS, CIR, CIR of LRR, and CIR of DR were 89.2%, 76.5%, 23.5%, 15.7%, and 11.4%, respectively [Figure 2E–G].

Figure 2.

Figure 2

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The characteristics of tumor recurrence in cervical cancer patients after CCRT. (A) Schematic illustration of tumor recurrence sites. (B) Venn diagram describing the number of sites-specific patients. (C) Overall and local distribution of cervical cancer recurrence site. R-class means the number of recurrence sites: R1 indicates recurrence in a single location; R2 indicates recurrence in two sites; R3 represents recurrence at multiple sites. P-class means the recurrence site: P1 indicates local regional recurrence; P2 indicates DR; P3 indicates constant local regional recurrence with DR; D-class means the detailed recurrence site. (D) the recurrence and death rates in 1-year, 2-year, and 3-year. (E–G) the CIR, CIR of local regional recurrence and CIR of DR. CCRT: Concurrent chemo-radiotherapy; CIR: Cumulative recurrence rate; DR: Distant recurrence.

Table 1 demonstrates that several factors—including later FIGO stage (2009), larger tumor size, increased number of positive regional MLNs, positive pelvic/para-aortic lymph nodes, and elevated pre-treatment SCC-Ag level—significantly augment the risk of treatment failure. In addition, the baseline serum immune biomarkers, such as SII, SIRI, and LDH, were related considerably to treatment outcomes.

Table 1.

The association between clinical factors and treatment outcomes with cervical cancer patients treated with CCRT.

Variables Treatment failure Treatment success χ2 P values
Age
<65 years 178 (91.3) 443 (93.9) 1.424 0.233
≥65 years 17 (8.7) 29 (6.1)
FIGO stage (2009)
IB-IIA 25 (12.8) 110 (23.3) 9.396 0.002
IIB-IVA 170 (87.2) 362 (76.7)
Primary tumor size
<4 cm 82 (42.1) 252 (53.4) 7.096 0.008
≥4 cm 113 (57.9) 220 (46.6)
No 94 (48.2) 367 (77.8)
Para-aortic MLNs
Yes 19 (9.7) 7 (1.5) 25.136 <0.001
No 176 (90.3) 465 (98.5)
Pelvic MLNs
Yes 94 (48.2) 102 (78.4) 47.035 <0.001
No 101 (51.8) 370 (21.6)
Histology
SCC 175 (89.7) 459 (97.2) 16.515 <0.001
ASCC/AC 20 (10.3) 13 (2.8)
Pre-SCC-Ag (ng/mL) 6.1 (1.4–19.3) 2.9 (1.4–8.2) – <0.001
Pre-SII (×109/L) 1222.3 (764.1–1752.8) 577.7 (418.9–998.5) – <0.001
Pre-SIRI (×109/L) 1.6 (1.1–2.4) 0.7 (0.2–1.2) – <0.001
Pre-LDH (U/L) 235.0 (180.5–266.5) 164.0 (147.0–184.0) – <0.001
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Categorical data were analyzed using chi-squared tests, and continuous data were analyzed with t-tests. Data were presented as n (%) or median (Q1–Q3). AC: Adenocarcinoma of the cervix; ASCC: Adenosquamous carcinoma of the cervix; FIGO: International Federation of Gynecology and Obstetrics; LDH: Lactate dehydrogenase; MLNs: Metastatic lymph nodes; SCC: Squamous carcinoma of the cervix; SCC-Ag: Squamous cell carcinoma antigen; SII: Systemic immune inflammation index; SIRI: Systemic inflammation response index; –: Not applicable.

Predictive value of serum immune biomarkers for treatment outcomes after CCRT

As presented in Figure 3, ROC curve analysis of serum immune biomarkers was performed to obtain the optimal cut-off points to predict treatment failure after CCRT. The baseline SII, SIRI, and LDH levels were analyzed. We demonstrated that AUC for the SII, SIRI, and LDH levels were 0.797, 0.781, and 0.825, respectively. In addition, the combination of SII, SIRI, and LDH had the highest AUC (0.849). Furthermore, the optimal cut-off values of the SII, SIRI, and LDH were 970.4 × 109/L (sensitivity 66.67%, specificity 85.81%, PPV 65.99%, and NPV 86.17%), 1.3 × 109/L (sensitivity 68.72%, specificity 80.30%, PPV 59.03%, and NPV 86.14%), and 207.5 U/L (sensitivity 61.54%, specificity 90.04%, PPV 71.86%, and NPV 85.00%), respectively. The combined SII, SIRI, and LDH levels had the highest predicted efficacy with sensitivity 66.67%, specificity 91.74%, PPV 76.92%, and NPV 86.95%.

Figure 3.

Figure 3

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The optimal cut-off values of serum immune markers were used to predict the treatment outcomes of locally advanced cervical cancer patients treated with concurrent chemo-radiotherapy. (A) Pre-SII level; (B) pre-SIRI level; (C) pre-LDH level; and (D) the combined three parameters. CI: Confidence interval; FPR: False positive rate; LDH: Lactate dehydrogenase; SII: Systemic immune inflammation index; SIRI: Systemic inflammation response index; TPR: True positive rate.

After the multivariable analysis, this study revealed that the baseline LDH level had the highest OR (OR = 4.151; 95% CI [2.314–10.7890]), followed by the SII level (OR = 3.104; 95% CI [1.231–5.654]), the SIRI level (OR = 2.987; 95% CI [1.361–4.987]), the histology (OR = 2.946; 95% CI [1.326–6.236]), FIGO stage (OR = 2.421; 95% CI [1.123–4.345]), pre-SCC-Ag level (OR = 2.136; 95% CI [1.023–4.093]), the para-aortic MLNs (OR = 2.102; 95% CI [1.456–4.012]), and the primary tumor size (OR = 1.842; 95% CI [1.326–3.231]) [Figure 4].

Figure 4.

Figure 4

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Independent risk factors for predicting the treatment failure. FIGO: International Federation of Gynecology and Obstetrics; LDH: Lactate dehydrogenase MLNs: Metastatic lymph nodes; OR: Odds ratio; SCC-Ag: Squamous cell carcinoma antigen; SII: Systemic immune inflammation index; SIRI: Systemic inflammation response index.

Serum immune biomarkers can be valuable prognostics for recurrence after CCRT

In analyzing the predictive value of the baseline SII, SIRI, and LDH levels with OS and DFS, those serum immune biomarkers were significantly associated with survival outcomes. As shown in Figure 5, the OS and PFS for patients with pre-SII ≥970.5 × 109/L were significantly worse than pre-SII <970.5 × 109/L (P <0.001). Similarly, pre-SIRI ≥1.3 × 109/L and pre-LDH ≥207.5 U/L were related with poor survival outcomes.

Figure 5.

Figure 5

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OS and DFS in patients after CCRT with prognostic factor analysis. (A) OS of the patients after CCRT; (B) DFS of the patients after CCRT; (C, D) OS and DFS of the different pre-SII groups; (E, F) OS and DFS of the different pre-SIRI groups; and (G, H) OS and DFS of the different pre-LDH groups. CCRT: Concurrent chemo-radiotherapy; DFS: Disease-free survival; LDH: Lactate dehydrogenase; OS: Overall survival; SII: Systemic immune inflammation index; SIRI: Systemic inflammation response index.

Discussion

Several guidelines recommend CCRT as the standard treatment for LACC.[4] Unfortunately, 20–40% of patients still suffer from tumor recurrence, currently having limited treatment options and poor prognoses. However, if we can accurately identify them clinically and provide more aggressive treatment, we may significantly reduce recurrence rates and improve the long-term survival. However, how to predict recurrence early is still a challenging problem and a hot issue. There need to be more quantitative and effective indicators.

In this study, the 3-year OS, DFS, CIR, CIR of LRR, and CIR of DR were 89.2%, 76.5%, 23.5%, 15.7%, and 11.4%, respectively. Similarly, Wang et al[22] reported that the 3-year OS and DFS were 87.2% and 80.3%. Also, it is reported that CCRT is the first-line treatment for LACC, which has more than 60% of the 5-year survival rate.[27] Kato et al[28] conducted a multicenter study in eight countries, which showed that the two-year local control rate and OS rate after CCRT were 87.1% and 79.6%, respectively. However, some studies have analyzed the long-term effect of CCRT in LACC patients, and the results suggest that the 3-year OS and 5-year OS are 73.0% and 69.5%.[29] This study significantly improved OS, probably due to upgrading radiotherapy instruments in recent years and improving treatment regimens.

This study revealed that the FIGO stage, histology, tumor size, the regional MLNs, the pelvic MLNs, the para-aortic MLNs, and pre-SCC-Ag level significantly increased the treatment failure. This conclusion is similar to the previous studies. Some studies reported that the 5-year OS of patients with tumor size <4 cm and tumor size ≥4 cm was 89.6% and 61.7%.[30] In addition, pathological types of cervical cancer include SCC, AC, and ASC. SCC was the most common among them, accounting for 75% of cases, followed by AC, accounting for 20–24% of cases. Recently, the incidence of SCC has gradually decreased, and cervical AC/ASC has increased.[31] Jonska-Gmyrek et al[32] showed higher mortality and recurrence rates in AC patients with the same FIGO stage. The 5-year OS of AC and SCC patients in stage FIGO II were 63% and 82%. MLNs is currently recognized as an important prognostic factor for survival. Ryu et al[33] reported that the 5-year OS in the LN-negative and LN-positive groups was 73.5% and 41.7%, respectively.

Importantly, we demonstrated that the baseline serum immune biomarkers, such as SII, SIRI, and LDH, were significantly related to treatment outcomes. Also, the AUC for the SII, SIRI, and LDH levels were 0.797, 0.781, and 0.825, respectively. Furthermore, this study revealed that the LDH level had the highest OR (OR = 4.151; 95% CI [2.314–10.789]), followed by the SII, histology, and SIRI levels. The level of serum LDH is associated with the prognosis of several cancers, including nasopharyngeal, colon, and lung cancers.[11,12] Serum inflammatory markers are independent prognostic factors for the survival of multiple malignancies.[13,14] Studies have demonstrated that neutrophils can secrete IL-18, vascular endothelial growth factor, and matrix metalloproteinase, which can directly participate in tumor-related angiogenesis, growth, and metastasis.[14] NLR is a commonly used inflammatory marker. Some studies indicate that increased NLR is a poor prognostic factor for cervical cancer.[14] Platelets and lymphocytes, are closely associated with local inflammation and the immune system responses related to tumor progression.[34] Some studies have reported that platelet lymphocyte ratio (PLR) is an independent risk factor for the prognosis of cervical cancer patients.[35] Chen et al[36] suggested that elevated pre-treatment NLR and PLR are poor prognostic factors for OS and RFS in LACC patients. Many studies have shown that relevant indicators in hematology are closely related to the occurrence, development, and prognosis of tumors. Still, these indicators are relatively single and cannot comprehensively and stably reflect the overall inflammatory state of the body and the level of the immune system. SII and SIRI are novel and comprehensive inflammatory predictors that can affect systemic inflammation and local immune status.[16–18] In addition, studies have demonstrated that SII and SIRI can better reflect the chronic inflammatory state than NLR and other inflammatory indicators.[19,20] Jin et al[37] showed that high SII level was associated with poorer OS in patients with renal cell carcinoma. A meta-analysis revealed that pre-SII could be used as a valid predictor to assess the prognosis and progression of patients with urological cancer.[38] Wang et al[39] found that pre-SIRI levels were closely associated with the prognosis of breast cancer patients. There is a retrospective study, which demonstrated that elevated SIRI was an independent prognostic factor in patients with metastatic pancreatic cancer.[40]

It is no doubt that this study had some limitations. First, the present study is retrospective, which may cause selection bias. Therefore, a prospective study and a randomized controlled trial are necessary. Second, this study was a single-center study with all Peking Union Medical College Hospital cases. Therefore, it may not be representative of the overall treatment level. Third, there are limitations in using serum immune parameters as predictors of treatment outcomes, such as the potential for false positives and false negatives.

In conclusion, this study demonstrated that the FIGO stage, tumor size, MLNs, and serum immune biomarkers, such as SII, SIRI, and LDH, were significantly related to treatment outcomes after CCRT. Moreover, the baseline SII, SIRI, and LDH levels can be used as quantitative indicators to accurately and effectively predict the long-term prognosis. We advocate combined measurement of baseline SII, SIRI, and LDH levels as a suitable and practical method to predict the treatment outcome with peripheral blood from non-invasive procedures. Our results may offer additional prognostic information in clinical and guide the clinical follow-up strategy of patients with high-risk recurrence and metastasis, which helps to detect the potential recurrent metastasis in time. It is of great value for improving the patient treatment outcome and survival.

Funding

This work was funded by grants from the National Natural Science Foundation of China (No. 82371757), National High-Level Hospital Clinical Research Funding (No. 2022-PUMCH-B-083), and Joint Funds for the Innovation of Science and Technology, Fujian province (No. 2020Y9147).

Conflicts of interest

None.

Supplementary Material

cm9-138-3131-s001.doc (43.5KB, doc)
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Footnotes

Lihua Chen, Weilin Chen, and Yingying Lin contributed equally to this work.

How to cite this article: Chen LH, Chen WL, Lin YY, Li XR, Gu Y, Li C, Zhou YC, Ke H, Zhang FQ, Xiang Y. Serum immune parameters as predictors for treatment outcomes in cervical cancer treated with concurrent chemo-radiotherapy. Chin Med J 2025;138:3131–3138. doi: 10.1097/CM9.0000000000003553

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