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The predictive value of serum inflammatory markers for the severity of cervical lesions

BMC Cancer volume 24, Article number: 780 (2024) Cite this article

Abstract

Objective

Exploring the predictive value of NLR, PLR, MLR, and SII for the severity of cervical cancer screening abnormalities in patients.

Methods

A retrospective analysis was conducted on the data of 324 patients suspected of cervical lesions due to abnormal TCT and/or HPV in our hospital from January 2023 to December 2023, who underwent colposcopy. The pathological results of colposcopic biopsy confirmed that there were 140 cases of chronic cervicitis, which classified as the group without cervical lesions. The cervical lesion group included 184 cases, including 91 cases of LSIL, 71 cases of HSIL, and 22 cases of cervical cancer. Compared the differences in preoperative peripheral blood NLR, PLR, MLR, and SII among different groups of patients, and evaluated their predictive value for the severity of cervical lesions using Receiver Operating Characteristic (ROC) curves.

Results

The levels of NLR, PLR, and SII in the group without cervical lesions were lower than those in the group with cervical lesions (p < 0.05), and there was no statistically significant difference in MLR (p > 0.05). The comparison of NLR among LSIL, HSIL, and cervical cancer groups showed statistically significant differences (p < 0.05), while PLR, MLR, and SII showed no statistically significant differences (p > 0.05). The AUC of peripheral blood NLR, PLR, and SII for predicting cervical lesions were 0.569, 0.582, and 0.572, respectively. The optimal cutoff values were 2.3,176.48, and 603.56. The sensitivity and specificity were 38.6% and 73.6%, 28.8% and 85.7%, 37.5% and 76.4%, respectively. At the same time, the joint testing of the three had the highest efficiency, with sensitivity of 69% and specificity of 45%.

Conclusion

Although the peripheral blood NLR, PLR, and SII of the cervical lesions patients were higher than those without cervical lesions in cervical cancer screening abnormal patients, the predictive ROC curve discrimination was low. Therefore, it is not recommended to use preoperative peripheral blood inflammatory markers as markers for cervical cancer screening abnormal patient diversion.

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Introduction

Cervical cancer is a malignant tumor of the female reproductive system, ranking fourth among all malignant tumors [1], which posing a threat to women’s health and life. The popularization of cervical cancer screening has improved the diagnostic rate of cervical intraepithelial neoplasia (CIN) and reduced the incidence of advanced cervical cancer. At the same time, the global goal is to eliminate cervical cancer through three-level prevention [2] measures [3,4,5]. Therefore, early diagnosis of CIN has become an important measure for the prevention and treatment of cervical cancer. In clinical practice, patients with abnormal for cervical cancer screening need to be referred for colposcopy and biopsy, which increases the detection rate of cervical precancerous lesions and cervical cancer. However, the false positive rate and colposcopy referral rate both increase, and excessive intervention leads to an increase in complications [6]. Previous studies had confirmed that the levels of neutrophils, platelets, and lymphocytes in peripheral blood could cause systemic immune inflammatory responses. Neutrophil/lymphocyte ratio (NLR), lymphocyte/monocyte ratio (LMR), and platelet/lymphocyte ratio (PLR) were three non-specific indicators of systemic inflammation [7, 8], which had been proven to predict the prognosis of multiple malignant tumors [9,10,11]. The Systemic Immune-inflammation Index (SII) was a new inflammatory marker, calculated using the formula Platelet count × Neutrophil count/Lymphocyte count was now also used as an important biomarker for prognostic evaluation of various cancer patients [12,13,14,15,16,17]. Neutrophils are a major subgroup of white blood cells that promote tumor cell proliferation, angiogenesis, and metastasis by producing pro angiogenic chemokines, cytokines, and growth factors such as vascular endothelial growth factor. Monocytes can release various chemokines and cytokines, promoting tumor progression and metastasis [18], while lymphocytes produce cytokines that inhibit tumor cell proliferation, metastasis, or promote cell death [19].Platelets can stimulate the proliferation and adhesion of tumor cells to other cells by secreting cytokines, chemokines, etc., and help tumor cells evade immune monitoring, promoting the growth and spread of tumor cells [20–21]. Research has shown that elevated levels of neutrophils, monocytes, and platelets in peripheral blood, as well as lower levels of lymphocytes, may correspond to higher invasiveness of tumors [22]. Some inflammatory factors in the blood were related to the occurrence and development of tumors, and had been reported in lung cancer [23], breast cancer [24], and bladder cancer [25]. Research showed that chronic inflammation may play an important role in the development of breast cancer, and had a certain impact on the occurrence, development, diagnosis and prognosis of breast cancer [26,27,28,29]. HU et al. [30] demonstrated that an increase in PLR values indicated a higher likelihood of inguinal lymph node metastasis in patients with penile cancer. ZHU et al. [31] found that there was a statistically significant difference in NLR between lung cancer patients and healthy individuals, with lung cancer patients having a higher NLR, the NLR cutoff value was 2.14. An increase in NLR was closely related to an increased risk of lung cancer, and this correlation was more pronounced within one year before the diagnosis of lung cancer [32, 33]. Research had found that the NLR of cervical cancer patients was significantly higher than that of the healthy population group. ROC curve analysis showed that NLR was a predictive factor for the diagnosis of cervical cancer, with an optimal critical value of 2.02 (AUC = 0.682, sensitivity of 71%, specificity of 60%) [34]. However, there was no clear conclusion on the use of preoperative serum inflammatory markers in the cervical cancer screening abnormal patients. In view of this, this study retrospectively analyzed 324 patients with cervical cancer screening abnormal who underwent colposcopy as the research subjects, with biopsy pathology results as the gold standard for diagnosis. Attempting to find more effective alternative biomarkers for predicting cervical lesions, providing more accurate indications for colposcopy, in order to achieve precise patient diversion, reduce unnecessary colposcopy referrals, allocate medical resources reasonably, improve screening efficiency, and reduce overtreatment.

Materials and methods

The general materials

Retrospective analysis of data from patients with suspected cervical lesions due to Thin Cytology Test (TCT) and/or Human Papilloma Virus (HPV) abnormal who underwent colposcopy and biopsy in our hospital from January 2023 to December 2023. Inclusion criteria: Patients with cervical cancer screening abnormal who underwent colposcopy in our hospital, and tissue biopsy would be performed simultaneously during procedure; The clinical and pathological data were all based on the results of our hospital; Non pregnant women; No history of treatment for cervical lesions. Exclusion criteria: Patients with major organ failure such as heart, liver, and kidneys; Patients who received antibiotic treatment before enrollment; Patients with obvious infections; Combination of malignant tumor, blood system or other infectious diseases; Those who were dissatisfied with colposcopy and affect the diagnostic results; oral medication that affected inflammatory markers(e.g., steroid); Incomplete clinical data. A total of 324 patients were enrolled, aged 18–77 years, with a median age of 47 (36,55) years. BMI fluctuates between 16.2 and 35.34, with a median BMI of 24 (22.5,25.78). This study was approved by ethics committees of Senior Department of Obstetrics & Gynecology of PLA General Hospital having approval no. 2024KY007-KS001 on January 19, 2024.

Methods

Extract general information such as age of enrolled patients and routine blood test within one week before colposcopy from electronic medical records, and calculate NLR, PLR, MLR, and SII.

Statistical analysis

SPSS 23.0 software was used for statistical analysis. The measurement data that do not conform to the normal distribution, the median and quartile were used, and the Mann-Whitney U test was used for inter-group comparison. Compare three groups and applied Kruskal-Wallis test. The predictive value was evaluated using the ROC curve analysis. The difference was statistically significant (p < 0.05).

Results

A retrospective analysis was conducted on the clinical and pathological data of 324 patients enrolled, and the pathological results of colposcopic biopsy confirmed that there were 140 cases (43.2%, 140/324) of chronic cervicitis in the group without cervical lesions. And the cervical lesion group consisted of 184 cases (56.8%, 184/324), including 91 cases of low-grade squamous intraepithelial lesion(LSIL) (28%, 91/324), 71 cases of high-grade squamous intraepithelial lesion (HSIL) (21.9%, 71/324), and 22 cases of cervical cancer (6.7%, 22/324).

Comparison of onset age, NLR, PLR, MLR, and SII between the group without cervical lesions and the group with cervical lesions

The onset age, NLR, PLR, and SII levels of the group without cervical lesions were significantly different from those of the group with cervical lesions (p < 0.05), indicating that the onset age of the group without cervical lesions was higher than that of the group with cervical lesions, while the levels of NLR, PLR, and SII were lower than those of the latter. However, there was no statistically significant difference in BMI, MLR between the two groups (p > 0.05), as shown in Table 1.

Table 1 Comparison of clinical data and inflammatory indicators between two groups
Full size table

Comparison of onset age, NLR, PLR, MLR, and SII among LSIL, HSIL, and cervical cancer groups in the cervical lesion group

The onset age and NLR of LSIL, HSIL, and cervical cancer groups showed statistically significant differences (p < 0.05), while PLR, MLR, and SII showed no statistically significant differences (p > 0.05) among the three groups, as shown in Table 2.

Table 2 Comparison of clinical data and inflammatory indicators among three groups
Full size table

The pairwise comparison of onset age in LSIL, HSIL, and cervical cancer groups

The results showed that there was a statistically significant difference in LSIL-CA groups (p = 0.038) and HSIL-CA groups (p = 0.16), while there was no statistically significant difference in LSIL-HSIL groups (p > 0.05), as shown in Fig. 1.

Fig. 1
figure 1

Comparison of onset age groups for LSIL, HSIL, and cervical cancer

Full size image

The pairwise comparison of NLR in LSIL, HSIL, and cervical cancer groups

The results showed a statistically significant difference between HSIL-CA (p = 0.034), while there was no statistically significant difference in LSIL-HSIL groups (p = 0.454) and LSIL-CA groups (p = 0.3) (p > 0.05), as shown in Fig. 2.

Fig. 2
figure 2

Comparison of NLR among LSIL, HSIL, and cervical cancer groups

Full size image

The predictive value of serum inflammatory markers for cervical lesions

Using cervical lesions (LSIL, HSIL, and cervical cancer) as state variables and NLR, PLR, and SII as test variables, ROC curves were plotted. The results showed that NLR, PLR, and SII predicted AUC of cervical lesions at 0.569, 0.582, and 0.572, respectively, with the best cutoff values of 2.3,176.48,603.56. At the same time, the joint testing of the three had the highest efficiency, with a sensitivity of 69% and a specificity of 45%. Shown as Fig. 3; Table 3.

Fig. 3
figure 3

ROC curve for predicting cervical lesions using NLR, PLR, SII, and their combined detection

Full size image
Table 3 Predictive value of NLR, PLR, SII, and their combined detection in predicting cervical lesions
Full size table

Discussion

Cervical cancer is a common gynecological tumor in women [20, 21], and is also the main cause of cancer-related deaths for women in developing countries [35]. Human papilloma virus (HPV) is the primary cause of cervical dysplasia and cervical cancer [36]. Cervical cancer is a complex process from precancerous lesions to cancer, and CIN reflects the continuous process of cervical cancer occurrence and development. Screening to detect CIN and timely treatment of HSIL is an effective measure to prevent cervical cancer. With the popularization of cervical cancer screening, the early diagnosis rate of cervical cancer has significantly improved, and the survival rate of patients has been greatly improved [37]. The purpose of cervical cancer screening is to identify patients with precancerous lesions of the cervix. Those with abnormal screening results should undergo colposcopy or cervical biopsy. If diagnosed with HSIL, the cervical lesion tissue should be removed to prevent progression to cervical cancer. In this study, patients with abnormal for cervical cancer screening who underwent colposcopy were ultimately confirmed by pathology to have HSIL accounting for 21.9% and cervical cancer accounting for 6.7%. The sensitivity of colposcopy in diagnosing HSIL and above was relatively low. Therefore, this study aimed to search for suitable serum inflammatory markers to improve the efficacy of colposcopy in patients with cervical cancer screening abnormal.

The results of this study showed that in patients with cervical cancer screening abnormal, the levels of NLR, PLR, and SII in the group without cervical lesions were lower than those in the group with cervical lesions. However, if peripheral blood inflammatory markers were used as biomarkers for cervical cancer screening abnormal patients, their area under the ROC curve for predicting cervical lesions also needed to be considered. The AUC of peripheral blood NLR, PLR, SII, and their combined prediction for cervical lesions were 0.569, 0.582, 0.572, and 0.584, respectively, all < 0.6, indicating that the predictive value of serum inflammatory markers for cervical lesions was not reliable, and the conclusion was difficult to extrapolate. According to the above analysis, NLR, PLR, and SII had low predictive discrimination for patients with cervical cancer screening abnormal, and were influenced by various factors such as systemic inflammatory response, making them unstable. Therefore, in the absence of clear mechanisms related to tumor immunity, the author did not recommend using NLR, PLR, and SII as diversion markers for the patients with cervical cancer screening abnormal.

Research had confirmed that chronic inflammation plays an important role in the occurrence and development of cervical cancer [38, 39], and terminal malignant tumors were accompanied by neutropenia and lymphocyte depletion, and thrombocytosis [40]. Taguchi et al. [41] showed that high levels of NLR were effective predictors of recurrence and metastasis in cervical cancer patients after treatment. Trinh et al. [42] showed that an increased in NLR and PLR before treatment resulted in a lower PFS and OS for cervical cancer after radiotherapy; and LMR increased before treatment had a good prognosis. SII was a new inflammatory biomarker that includes three types of peripheral blood inflammation biomarkers and was considered superior to other inflammatory indicators [43]. The prognostic value of SII in patients with stage I-II esophageal squamous cell carcinoma was superior to NLR, PLR, and MLR [44]. Meanwhile, studies had shown that high pre-treatment SII in cervical cancer patients indicated low OS and PFS [45]. Tas et al. [34] showed that peripheral blood NLR and PLR could distinguish cervical cancer from precancerous lesions, and the NLR and PLR of cervical cancer patients were higher than CIN. Another study also confirmed that the PLR of the cervical cancer group was significantly increased compared to the low-grade squamous intraepithelial lesions of the cervix, the highly squamous intraepithelial lesions of the cervix, and the healthy control group [46]. Preoperative NLR categorization was a strong independent prognostic factor for recurrences after surgical excision of CIN2, CIN3, and carcinoma in situ, the odd ratio for recurrence significantly higher in patients with NLR ≥ 2 (5.2% and 27.3%) [47]. When NLR >1.9, the patient with cervical intraepithelial neoplasia has a high recurrence rate, and they need excision more tissues during excisional surgery [48]. Xu et al. [49] showed that a high NLR value independently predicted CIN and the stage of CIN. At present, there were many reports on the use of inflammatory markers in peripheral blood for the diagnosis and prognosis of cervical cancer [41, 50, 51], but no relevant literature reports on the diversion of patients with cervical cancer screening abnormal have been found yet.

In addition, this study had the following limitations: firstly, as a single center retrospective study, there were differences in onset age, BMI, and parity among the patients in different groups, which may caused some confounding bias, and preoperative single routine blood test may produced random errors. Secondly, cervical lesions are associated with HPV infection [21], but the HPV infection status, types, and duration among different groups of patients were not included in the research, which may caused some bias in the results. Finally, this study did not follow up the object of study, which had certain limitations on the research results. In the future studies, further follow-up is needed to determine the changes in subsequent detection indicators to confirm the clinical application value of each detection scheme.

Conclusion

In summary, although the peripheral blood NLR, PLR, and SII of cervical lesions patients are higher than those without cervical lesions in cervical cancer screening abnormal patients. Based on current data analysis, the significance of preoperative peripheral blood inflammatory markers in predicting cervical lesions is not clear. Therefore, it is not recommended to use preoperative peripheral blood inflammatory markers as markers for the diversion of cervical cancer screening abnormal patients.

Data availability

The datasets used and/or analysed during the current study available from the corresponding author on reasonable request.

References

  1. Yang Q, Zhou Q, He X, et al. Retrospective analysis of the incidence and predictive factors of parametrial involvement in FIGO IB1 cervical cancer[J]. J Gynecol Obstet Hum Reprod. 2021;50(8):102145.

    Article  PubMed  Google Scholar 

  2. Hall MT, Smith MA, Simms KT, et al. Elimination of cervical cancer in Tanzania: Modelled analysis of elimination in the context of endemic HIV infection and active HIV control[J]. Int J Cancer. 2021;149(2):297–306.

    Article  CAS  PubMed  Google Scholar 

  3. Arbyn M, Weiderpass E, Bruni L, et al. Estimates of incidence and mortality of cervical cancer in 2018: a worldwide analysis[J]. Lancet Glob Health. 2020;8(2):e191–203.

    Article  PubMed  Google Scholar 

  4. Blake J. The elimination of Cervical Cancer in our Lifetime[J]. J Obstet Gynaecol Can. 2018;40(12):1555–7.

    Article  PubMed  Google Scholar 

  5. Taghavi K, Moono M, Asangbeh S, et al. Strengthening global commitment to eliminating cervical cancer: what lessons from the past can we apply to the future?[J]. J Glob Health. 2020;10(2):20385.

    Article  Google Scholar 

  6. Perkins RB, Guido RS, Castle PE, et al. 2019 ASCCP Risk-Based Management Consensus guidelines for abnormal cervical Cancer screening tests and Cancer Precursors[J]. J Low Genit Tract Dis. 2020;24(2):102–31.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Kang Y, Zhu X, Lin Z et al. Compare the Diagnostic and Prognostic Value of MLR, NLR and PLR in CRC Patients[J]. Clin Lab, 2021,67(9).

  8. Huang Z, Fu Z, Huang W, et al. Prognostic value of neutrophil-to-lymphocyte ratio in sepsis: a meta-analysis[J]. Am J Emerg Med. 2020;38(3):641–7.

    Article  PubMed  Google Scholar 

  9. Huang H, Liu Q, Zhu L, et al. Prognostic value of preoperative systemic Immune-inflammation index in patients with cervical Cancer[J]. Sci Rep. 2019;9(1):3284.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Zhang K, Hua YQ, Wang D, et al. Systemic immune-inflammation index predicts prognosis of patients with advanced pancreatic cancer[J]. J Transl Med. 2019;17(1):30.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Cupp MA, Cariolou M, Tzoulaki I, et al. Neutrophil to lymphocyte ratio and cancer prognosis: an umbrella review of systematic reviews and meta-analyses of observational studies[J]. BMC Med. 2020;18(1):360.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Inoue H, Kosuga T, Kubota T, et al. Significance of a preoperative systemic immune-inflammation index as a predictor of postoperative survival outcomes in gastric cancer[J]. World J Surg Oncol. 2021;19(1):173.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Zhao M, Duan X, Mi L, et al. Prognosis of hepatocellular carcinoma and its association with immune cells using systemic inflammatory response index[J]. Future Oncol. 2022;18(18):2269–88.

    Article  CAS  PubMed  Google Scholar 

  14. Toyoda J, Sahara K, Maithel SK, et al. Prognostic utility of systemic Immune-inflammation index after resection of Extrahepatic Cholangiocarcinoma: results from the U.S. Extrahepatic biliary malignancy Consortium[J]. Ann Surg Oncol. 2022;29(12):7605–14.

    Article  PubMed  Google Scholar 

  15. Ji Y, Wang H. Prognostic prediction of systemic immune-inflammation index for patients with gynecological and breast cancers: a meta-analysis[J]. World J Surg Oncol. 2020;18(1):197.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Wu Y, Tu C, Shao C. Inflammatory indexes in preoperative blood routine to predict early recurrence of hepatocellular carcinoma after curative hepatectomy[J]. BMC Surg. 2021;21(1):178.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Huang Y, Gao Y, Wu Y, et al. Prognostic value of systemic immune-inflammation index in patients with urologic cancers: a meta-analysis[J]. Cancer Cell Int. 2020;20:499.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Olingy CE, Dinh HQ, Hedrick CC. Monocyte heterogeneity and functions in cancer[J]. J Leukoc Biol. 2019;106(2):309–22.

    Article  CAS  PubMed  Google Scholar 

  19. Gao J, Ren Y, Guo H, et al. A new method for predicting survival in stage I non-small cell lung cancer patients: nomogram based on macrophage immunoscore, TNM stage and lymphocyte-to-monocyte ratio[J]. Ann Transl Med. 2020;8(7):470.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Bray F, Ferlay J, Soerjomataram I, et al. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries[J]. CA Cancer J Clin. 2018;68(6):394–424.

    Article  PubMed  Google Scholar 

  21. Xu M, Wu Q, Cai L, et al. Systemic inflammatory score predicts overall survival in patients with cervical Cancer[J]. J Cancer. 2021;12(12):3671–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Franco AT, Corken A, Ware J. Platelets at the interface of thrombosis, inflammation, and cancer[J]. Blood. 2015;126(5):582–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Şahin F, Aslan AF. Relationship between inflammatory and biological markers and Lung Cancer[J]. J Clin Med, 2018,7(7).

  24. Yin Y, Zhang Y, Li L, et al. Prognostic value of pretreatment lymphocyte-to-monocyte ratio and development of a nomogram in breast Cancer Patients[J]. Front Oncol. 2021;11:650980.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Yıldız HA, Değer MD, Aslan G. Prognostic value of preoperative inflammation markers in non-muscle invasive bladder cancer[J]. Int J Clin Pract. 2021;75(6):e14118.

    Article  PubMed  Google Scholar 

  26. Danforth DN. The role of chronic inflammation in the development of breast Cancer[J]. Cancers (Basel), 2021,13(15).

  27. Chen L, Kong X, Yan C, et al. The Research Progress on the Prognostic Value of the common hematological parameters in peripheral venous blood in breast Cancer[J]. Onco Targets Ther. 2020;13:1397–412.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Zhang Y, Sun Y, Zhang Q. Prognostic value of the systemic immune-inflammation index in patients with breast cancer: a meta-analysis[J]. Cancer Cell Int. 2020;20:224.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Zhu M, Chen L, Kong X, et al. The systemic Immune-inflammation index is an independent predictor of survival in breast Cancer Patients[J]. Cancer Manag Res. 2022;14:775–820.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Hu C, Bai Y, Li J, et al. Prognostic value of systemic inflammatory factors NLR, LMR, PLR and LDH in penile cancer[J]. BMC Urol. 2020;20(1):57.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Zhu X, Song H, Chen Y et al. Neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio in blood to Distinguish Lung Cancer patients from healthy Subjects[J]. Dis Markers, 2020,2020:8844698.

  32. Nøst TH, Alcala K, Urbarova I, et al. Systemic inflammation markers and cancer incidence in the UK Biobank[J]. Eur J Epidemiol. 2021;36(8):841–8.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Tian T, Lu J, Zhao W, et al. Associations of systemic inflammation markers with identification of pulmonary nodule and incident lung cancer in Chinese population[J]. Cancer Med. 2022;11(12):2482–91.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Tas M, Yavuz A, Ak M, et al. Neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio in discriminating precancerous pathologies from cervical Cancer[J]. J Oncol. 2019;2019:2476082.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Noh JJ, Lim MC, Kim MH et al. The Prognostic Model of Pre-treatment Complete Blood Count (CBC) for recurrence in early cervical Cancer[J]. J Clin Med, 2020,9(9).

  36. Bogani G, Sopracordevole F, Ciavattini A, et al. HPV persistence after cervical surgical excision of high-grade cervical lesions[J]. Cancer Cytopathol. 2024;132(5):268–9.

    Article  CAS  PubMed  Google Scholar 

  37. Buskwofie A, David-West G, Clare CA. A review of Cervical Cancer: incidence and Disparities[J]. J Natl Med Assoc. 2020;112(2):229–32.

    PubMed  Google Scholar 

  38. Sadri NJ, Moghoofei M, Salmaninejad A, et al. Pathogenic role of exosomes and microRNAs in HPV-mediated inflammation and cervical cancer: a review[J]. Int J Cancer. 2020;146(2):305–20.

    Article  Google Scholar 

  39. Ilhan ZE, Łaniewski P, Thomas N, et al. Deciphering the complex interplay between microbiota, HPV, inflammation and cancer through cervicovaginal metabolic profiling[J]. EBioMedicine. 2019;44:675–90.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Vitkauskaite A, Urboniene D, Celiesiute J, et al. Circulating inflammatory markers in cervical cancer patients and healthy controls[J]. J Immunotoxicol. 2020;17(1):105–9.

    Article  CAS  PubMed  Google Scholar 

  41. Taguchi A, Nakajima Y, Furusawa A, et al. High neutrophil-to-lymphocyte ratio is a predictor of short-term survival for patients with recurrent cervical cancer after radiation-based therapy[J]. J Obstet Gynaecol Res. 2021;47(5):1862–70.

    Article  CAS  PubMed  Google Scholar 

  42. Trinh H, Dzul SP, Hyder J, et al. Prognostic value of changes in neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and lymphocyte-to-monocyte ratio (LMR) for patients with cervical cancer undergoing definitive chemoradiotherapy (dCRT)[J]. Clin Chim Acta. 2020;510:711–6.

    Article  CAS  PubMed  Google Scholar 

  43. Wang B, Huang Y, Lin T. Prognostic impact of elevated pre-treatment systemic immune-inflammation index (SII) in hepatocellular carcinoma: a meta-analysis[J]. Med (Baltim). 2020;99(1):e18571.

    Article  CAS  Google Scholar 

  44. Gao Y, Guo W, Cai S, et al. Systemic immune-inflammation index (SII) is useful to predict survival outcomes in patients with surgically resected esophageal squamous cell carcinoma[J]. J Cancer. 2019;10(14):3188–96.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Holub K, Biete A. Impact of systemic inflammation biomarkers on the survival outcomes of cervical cancer patients[J]. Clin Transl Oncol. 2019;21(7):836–44.

    Article  CAS  PubMed  Google Scholar 

  46. Zhu M, Feng M, He F, et al. Pretreatment neutrophil-lymphocyte and platelet-lymphocyte ratio predict clinical outcome and prognosis for cervical Cancer[J]. Clin Chim Acta. 2018;483:296–302.

    Article  CAS  PubMed  Google Scholar 

  47. Origoni M, Cantatore F, Candotti G et al. Prognostic Significance of Neutrophil/Lymphocytes Ratio (NLR) in Predicting recurrence of cervical Dysplasia[J]. Biomed Res Int, 2022,2022:1149789.

  48. Hajizadeh N, Baghestani AR, Pourhoseingholi MA, et al. Evaluation of the factors affecting the cure rate of cervical intra-epithelial neoplasia recurrence using defective Models[J]. J Res Health Sci. 2021;21(3):e524.

    Article  Google Scholar 

  49. Xu L, Song J. Elevated neutrophil-lymphocyte ratio can be a biomarker for predicting the development of cervical intraepithelial neoplasia[J]. Med (Baltim). 2021;100(28):e26335.

    Article  CAS  Google Scholar 

  50. Taguchi A, Furusawa A, Ito K, et al. Postradiotherapy persistent lymphopenia as a poor prognostic factor in patients with cervical cancer receiving radiotherapy: a single-center, retrospective study[J]. Int J Clin Oncol. 2020;25(5):955–62.

    Article  PubMed  Google Scholar 

  51. Lee HJ, Kim JM, Chin YJ, et al. Prognostic value of hematological parameters in locally advanced cervical Cancer patients treated with concurrent Chemoradiotherapy[J]. Anticancer Res. 2020;40(1):451–8.

    Article  PubMed  Google Scholar 

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Acknowledgements

The authors gratefully acknowledge the patients and the guardian. We also thankful to my workmates for their invaluable contribution to this study.

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  1. Senior Department of Obstetrics & Gynecology, the Seventh Medical Center of PLA General Hospital, Beijing, China

    Lin Qin & Lina Zhang

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  1. Lin Qin
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Lin Q. wrote the main manuscript text and Lina Z. prepared the figures. All authors reviewed the manuscript.

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Correspondence to Lin Qin.

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This study was approved by the ethics committees of Senior Department of Obstetrics & Gynecology of PLA General Hospital having approval no 2024KY007-KS001 and study was conducted in accordance with the Declaration of Helsinki. This study informed consent was obtained from all subjects and/or their legal guardian(s).

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Qin, L., Zhang, L. The predictive value of serum inflammatory markers for the severity of cervical lesions. BMC Cancer 24, 780 (2024). https://doi.org/10.1186/s12885-024-12561-7

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BMC Cancer

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