Evaluation of Systemic Inflammation- and Nutrition-Based Indices in the Prediction of HPV Persistence

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Although systemic inflammation and nutritional indices such as the Hemoglobin, Albumin, Lymphocyte, and Platelet (HALP) score and Prognostic Nutritional Index (PNI) have prognostic value in various malignancies, their role in predicting HPV persistence remains unclear. This study aimed to evaluate the predictive value of HALP and PNI scores for one-year HPV persistence. Methods: This retrospective study included 470 HPV-positive women aged 31–67 years, followed for at least one year between January 2021 and March 2025. Participants were divided into Group N (HPV clearance, n=271) and Group P (HPV persistence, n=199) based on one-year HPV results. Baseline demographic, clinical, histopathological, and laboratory data were recorded. HALP and PNI scores were calculated from hemoglobin, albumin, lymphocyte, and platelet counts. Group comparisons were performed using appropriate statistical tests, and predictive performance was assessed via receiver operating characteristic (ROC) analysis. Results: There were no significant differences between groups in age, marital status, smoking, contraceptive use, parity, delivery mode, or chronic diseases. HPV16 (44.7%) and HPV18 (27.1%) positivity were significantly higher in the persistence group (p<0.001 and p=0.0006, respectively). Histopathological findings and p16/Ki-67 expression did not differ significantly. Post-diagnosis HPV vaccination did not affect clearance rates (p=0.604). Median HALP scores were 49.11 (IQR 35.87–60.42) in Group N and 46.97 (IQR 35.49–59.23) in Group P (p=0.361). Median PNI scores were 55.30 (IQR 51.40–58.40) and 55.00 (IQR 51.10–58.20), respectively (p=0.637). ROC analysis indicated poor predictive performance (AUC=0.531 for HALP; AUC=0.516 for PNI). Conclusions: HALP and PNI scores were not predictive of one-year HPV persistence, indicating limited influence of systemic inflammation and nutritional status on viral clearance in localized cervical HPV infections. HPV16 and HPV18 positivity was strongly associated with persistence, supporting their known immune evasion mechanisms. These findings highlight the need for prognostic markers targeting local mucosal immune responses to improve risk stratification and management of HPV-related disease. Human papillomavirus HPV persistence HALP score Prognostic Nutritional Index cervical cancer prognostic biomarkers Figures Figure 1 Figure 2 Figure 3 Introduction Cervical cancer is the fourth most prevalent type of cancer-related death for women globally [ 1 ]. Cervical cancer is among the rare malignancies associated with a viral etiology, specifically Human papillomavirus (HPV) infection [ 2 ]. Cervical cancer is a type of cancer for which screening is possible through cervical cytology (CVC) and HPV testing. The natural history of most HPV infections is characterized by spontaneous resolution, typically occurring within 12 to 24 months without any notable clinical manifestations [ 3 ]. It is estimated that only 10–20% of infected women develop a persistent infection lasting longer than 24 months [ 4 ]. The failure of HPV to be eradicated from the body can result in a persistent infection, which is a significant contributor to the onset of Cervical Intraepithelial Neoplasia (CIN) and cervical cancer [ 5 ]. The formation of preinvasive lesions and the progression to malignant transformation can vary significantly at the individual level, depending on factors such as age, the type of HPV infection, smoking, and HIV infection [ 3 , 6 – 8 ] Nutritional status is known to significantly influence the immune system’s ability to mount an effective response against infections [ 9 ]. Hemoglobin, albumin, lymphocyte count, and platelet count values (HALP) and the Prognostic Nutritional Index (PNI) scores are noninvasive, low-cost prognostic indicators that comprehensively evaluate inflammation, nutritional status, and immune function based on hematological and immunological parameters. HALP and PNI scores are commonly used tools for predicting prognosis and immune response in progressive and malignant diseases, as well as for assessing nutritional and immunological status [ 9 – 11 ]. The immune response has been shown to be effective not only in the local context but also on a systemic scale. Moreover, it has the potential to play a decisive role in the elimination of cervical HPV infection. Predicting HPV persistence may be a crucial tool for managing and keeping a watch on high-risk patients. The assessment of disease risk commonly employs a range of scientific approaches, including pathological techniques, medical imaging, laboratory analyses, and demographic data. However, the accuracy of these techniques in predicting HPV persistence remains unclear. These services have several important limitations, such as high costs, specialized knowledge, and the requirement for customized approaches. A noninvasive, simple-to-use, cost-effective, and standardized prognostic prediction tool is ideal. The purpose of this research is to assess the PNI and HALP scores' potential utility in predicting HPV persistence at a one-year follow-up. Patients And Methods The present study was conducted in accordance with the Helsinki Declaration and approved by the Ethics Committee of the Faculty of Medicine, Ordu University (Approval No. 2025/152). Prior to analysis, all data were anonymized. From January 2021 to March 2025, a total of 581 HPV-positive female patients aged 31–67 years who had been subjects in the study for a minimum of one year were included in the analysis. We excluded 111 patients who underwent excisional treatment during the follow-up period, leaving a total of 470 patients in the study. The patients' initial HPV tests were conducted as part of the Turkish National Cervical Cancer Screening Program, using DNA-based testing methods [SPF10, PCR-DEIA-LiPA25] and positive high-risk HPV tests [Hybrid Capture II (HC2)]. The initial HPV tests of the patients included in the study were performed within the scope of this program, and individuals with positive HPV results were referred to our center. All patients underwent colposcopic examination with cervical and endocervical sampling at the time of admission. Routine blood tests (lymphocyte, hemoglobin, WBC, albumin) were requested during the day-long hospitalization to assess the risk of potential infection, allergic reactions, or hematological complications. The laboratory data utilized in this retrospective study were obtained from the hospital information system. The demographic information collected included age, marital status, smoking status, chronic disease, contraceptive method, and mode of delivery. The laboratory parameters recorded included Hb, WBC, lymphocyte, platelet, and albumin. The results of the HPV test were then compared at the initial presentation and for one year. Initial HPV tests were evaluated using PCR, while cytology was assessed using the ThinPrep method (Hologic Inc., USA). A total of 15 HPV DNA genotypes, including HPV16, HPV18, and other high-risk genotypes (31, 33, 35, 39, 45, 51, 52, 56, 58, 59, 66, 68, and others), were detected using the Roche Cobas system. Cases that were HPV-positive at baseline were divided into two groups based on whether the HPV test became negative or remained positive at the first-year follow-up. The HALP and PNI scores were subsequently calculated and compared for both groups. Cases that were HPV-positive at baseline were divided into two groups based on whether the HPV test became negative or remained positive at the first-year follow-up. A comparative analysis was conducted on the HALP and PNI scores between the two groups. To this end, both scores were calculated and subjected to statistical analysis to discern intergroup differences. The HALP score, which is based on hemoglobin, albumin, lymphocyte, and platelet values, was calculated as follows: HALP = (Hemoglobin [g/L] × Albumin [g/L] × Lymphocytes [/L]) / Platelets [/L]. The PNI score was calculated as follows: PNI = (10 × Albumin [g/dL]) + (0.005 × Lymphocyte count [/mm³]) [ 9 , 12 ]. The exclusion criteria are as follows: having an immune system disease, a diagnosis or history of malignancy, undergoing long-term glucocorticoid or immunosuppressive treatment, receiving treatment for another concurrent malignancy, possessing incomplete test data, being diagnosed with new cancer during follow-up that leads to the initiation of chemotherapy, and having a control HPV test performed more than one year ago. Statistics: We used SPSS (Statistical Package for the Social Sciences) 18.0 software to do the statistical analyses. The descriptive statistics encompassed both categorical and numerical variables. Counts and percentages were used to show categorical variables, and means ± standard deviations were used to show numerical variables. The chi-square test was used for categorical data when comparing groups, and Fisher's exact test was used when the expected cell counts were less than five. The statistical analysis of the data utilized Student's t-test under the condition that the data distribution adhered to the normal distribution assumption, and employed the Mann–Whitney U test when the data failed to conform to a normal distribution. For situations with more than one group, the Kruskal–Wallis test was used when the normal distribution condition was not met, and the one-way analysis of variance (One-Way ANOVA) was used when it was. All statistical tests had a level of significance of p < 0.05. Results Of the total 470 HPV-positive patients included in the study, 271 patients tested negative for HPV at the one-year follow-up, while 199 patients remained HPV-positive. Consequently, the patients were divided into two groups: The subjects were divided into two groups, designated Group N and Group P, based on their HPV status. A comparative analysis was conducted among the groups in terms of demographic characteristics, laboratory parameters, and calculated HALP and PNI scores. The factors that influence HPV persistence include HPV genotype, patient age, smoking, and diseases affecting the immune system. The mean ages in Group P and Group N were 47.50 ± 9.79 and 46.77 ± 9.58 years, respectively, with no statistically significant difference (p = 0.477). The present study revealed that there were no statistically significant differences between Group P and Group N with regard to age, marital status, smoking status, contraceptive method, pregnancy history, mode of delivery, and presence of chronic diseases (Table 1 ). Table 1 Comparison of Demographic Characteristics Between Groups Variable Test Group N (Mean ± SD or %) Group P (Mean ± SD or %) p-value Age U† 46.77 ± 9.58 47.50 ± 9.79 0.4773 Marital status F‡ {0: 17.3, 1: 82.7} {0: 15.6, 1: 84.4} 0.7068 Smoking F‡ {0: 73.1, 1: 26.9} {0: 75.9, 1: 24.1} 0.5228 Contraceptive method χ²§ {0: 62.0, 1: 9.6, 2: 13.3, 3: 5.5, 4: 2.6, 5: 7.0} {0: 63.3, 1: 11.1, 2: 15.1, 3: 1.0, 4: 3.5, 5: 6.0} 0.183 Gravidity χ²§ {0: 5.9, 1: 11.1, 2: 34.7, 3: 29.2, 4: 12.9, 5: 4.1, 6: 1.5, 7: 0.7, 8: 0.0, 9: 0.0} {0: 3.5, 1: 7.5, 2: 32.7, 3: 29.6, 4: 14.6, 5: 7.5, 6: 3.0, 7: 0.5, 8: 0.5, 9: 0.5} 0.3651 Parity χ²§ {0: 5.9, 1: 13.7, 2: 41.7, 3: 25.5, 4: 10.0, 5: 1.8, 6: 1.5} {0: 3.5, 1: 11.6, 2: 40.2, 3: 28.1, 4: 10.6, 5: 4.0, 6: 2.0} 0.6367 Mode of delivery χ²§ {0: 6.3, 1: 56.5, 2: 30.3, 3: 7.0} {0: 5.0, 1: 54.8, 2: 25.6, 3: 14.6} 0.0535 Chronic disease F‡ {0: 78.6, 1: 21.4} {0: 72.4, 1: 27.6} 0.127 Statistical Test Symbols:† Mann–Whitney U Test ‡ Fisher’s Exact Test § Chi-Square Test In contrast, when the HPV genotypes at the patients' initial visits were examined, statistically significant differences were observed between the groups in terms of HPV16 (44.7%) and HPV18 (27.1%) positivity (p < 0.001 and p = 0.0006, respectively). No significant differences were identified for other high- and low-risk HPV types (Fig. 1 ). The findings suggest a substantial variation between the two groups, characterized by the presence or absence of persistent HPV positivity, with respect to the types of high- and low-risk HPV they initially carried. All patients who initially presented to our center with HPV positivity underwent cervical and endocervical sampling, accompanied by colposcopic evaluation. Cervical biopsies revealed normal cervical epithelium in 294 patients, koilocytosis in 46 patients, and low-grade squamous intraepithelial lesions (LSIL; CIN1) in 130 patients. No high-grade squamous intraepithelial lesions (HSIL) were detected. Endocervical curettage (ECC) results showed normal endocervical tissue in 372 patients, koilocytosis in 18 patients, LSIL (CIN1) in 76 patients, and HSIL (CIN2) in 4 patients. The four patients diagnosed with CIN2 on ECC refused excisional treatment and were instead placed under close clinical surveillance. Subsequent comparisons between Group P (HPV persistence) and Group N (HPV clearance) revealed no statistically significant differences in cervical biopsy or ECC outcomes (p > 0.05). Similarly, immunohistochemical analyses of P16 and Ki-67 expression did not yield significant differences between the two groups (p = 0.131 for P16, p = 0.176 for Ki-67) (Table 2 ). Table 2 Histopathologic and Immunohistochemical Findings According to Sampling Method and Group Type Diagnosis Total n = 470 Group N n = 271 Group N (%) Group P N = 199 Group P (%) p-value Cervical Biopsy Koilocytosis 46 30 11.070 16 8.040 0.250 Cervical Biopsy LSIL (CIN1) 130 68 25.092 62 31.156 0.250 Cervical Biopsy Normal Cervical Tissue 294 173 63.838 121 60.804 0.250 ECC Normal Endocervical Tissue 372 221 81.550 151 75.879 0.269 ECC Koilocytosis 18 8 2.952 10 5.025 0.269 ECC LSIL (CIN1) 76 41 15.129 35 17.588 0.269 ECC Endometrial Tissue 4 1 0.369 3 1.508 0.269 P16 Staining Negative 407 242 89.299 165 82.915 0.061 P16 Staining Superficial 63 29 10.701 34 17.085 0.061 Ki-67 Staining Negative 379 224 82.657 155 77.889 0.240 Ki-67 Staining Superficial 91 47 17.343 44 22.111 0.240 CIN1: Cervical Intraepithelial Neoplasia Grade 1, ECC: Endocervical Curettage, LSIL: Low-Grade Squamous Intraepithelial Lesion, P16: Tumor suppressor protein p16 (INK4a), Ki-67: Cellular proliferation marker Ki-67, Group N: Patients who became HPV-negative at one-year follow-up, Group P: Patients with persistent HPV infection at one-year follow-up All patients were informed about the vaccine, regardless of HPV positivity and type; vaccination was left to the patients' discretion. The study population comprised patients who had completed the vaccination series, received incomplete doses, and were still undergoing the vaccination process. In Group P, 137 patients received no vaccine, 2 received 1 dose, 3 received 2 doses, and 38 received 3 doses. In Group N, 193 patients received no vaccine, 1 received 1 dose, 3 received 2 doses, and 74 received 3 doses. A subsequent statistical analysis revealed no statistically significant difference between the two groups (p = 0.604). At the conclusion of the one-year follow-up period, a comparison was made between HALP and PNI scores in patients with persistent HPV infection (Group P, n = 199) and those with negative results (Group N, n = 271). The median HALP score was determined to be 49.11 (with an interquartile range of 35.87–60.42) in Group N, while it was 46.97 (with an interquartile range of 35.49–59.23) in Group P. The median PNI score was found to be 55.30 (with an interquartile range of 51.40–58.40) in Group N and 55.00 (with an interquartile range of 51.10–58.20) in Group P. The Mann-Whitney U test performed on the groups yielded U = 25,064.5, p = 0.361 for the HALP score and U = 26,106.5, p = 0.637 for the PNI score. No statistically significant difference was detected between the groups for either biomarker (p > 0.05). The results indicate that HALP and PNI scores do not significantly influence HPV infection persistence or clearance (Table 3 ). Table 3 Comparison of HALP and PNI Scores Between Groups Score Group N (n = 271) Median (IQR) Group P (n = 199) Median (IQR) p-value HALP 49.11 (35.52–61.48) 46.97 (35.77–58.40) 0.361 PNI 55.30 (52.50–58.23) 55.00 (52.20–58.10) 0.637 Statistical comparison was performed using the Mann–Whitney U test. IQR: Interquartile Range The predictive power of HPV infection persistence was evaluated using the area under the curve (AUC) of the receiver operating characteristic (ROC) curve analysis. The AUC was 0.531 for HALP and 0.516 for PNI, both of which are close to 0.5. These results indicate that the predictive performance of HALP and PNI scores in distinguishing between HPV persistence and clearance was no better than chance, underscoring their limited utility as prognostic tools in this context (Fig. 2 , Fig. 3 ). Discussion In this study, the predictive roles of the HALP score and the PNI were evaluated in the natural course of HPV infection. Specifically, it was investigated whether there was a significant difference in these two biomarkers between individuals whose HPV infection persisted (Group P) and those whose infection cleared (Group N) within one year. The findings revealed that HALP and PNI scores did not differ significantly between the two groups. This result suggests that these indices, which reflect systemic inflammation and nutritional status, may have a limited impact on HPV clearance over a one-year period. The HALP score has become a frequently utilized metric for evaluating systemic inflammatory processes in solid tumors recent years [ 13 ]. The HALP calculation, which incorporates hemoglobin and albumin, has enabled the correlation between nutritional status and immune response, particularly in the context of gastrointestinal malignancies. This calculation has revealed the relationship between nutrition and immunity [ 14 ]. In a prospective study involving more than 20,000 healthy individuals, a decrease in platelet count after the age of 60 was shown to be associated with immune response [ 15 ]. The inclusion of platelet count in the denominator of the HALP score suggests a potential correlation between this score and age. Furthermore, studies that have evaluated the relationship between age and HPV infection prevalence and clearance have demonstrated that HPV clearance decreases with increasing age. In addition, these studies have indicated that there is an inverse relationship between these two variables. [ 16 , 17 ]. In the present study, the age variable, which has the potential to affect the HALP score and HPV persistence, exhibited a comparable distribution between Group P and Group N and did not demonstrate a statistically significant difference. Consequently, age was not considered a confounding variable in the analyses. HPV infection can spontaneously resolve within 12 to 24 months in the immune systems of most healthy individuals; however, in some cases, the virus persists and can lead to the development of cervical preinvasive lesions [ 18 ]. A multitude of factors contribute to the development of persistent infection, including the oncogenicity of the HPV type, age, immunosuppression, smoking, and co-infections [ 19 ]. The expression of E6 and E7 oncoproteins in high-risk types, such as HPV16 and HPV18, has been demonstrated to suppress the host immune response at various levels, thereby hindering viral elimination. This contributes to the persistence of HPV infection [ 20 ]. In the present study, it was also determined that the HPV persistence rate was significantly higher in cases positive for HPV 16 and HPV 18. It has been established that these high-risk types suppress the host immune response through E6 and E7 oncoproteins, thereby preventing viral clearance. The findings of this study are consistent with the clinical implications of the immune evasion mechanisms described in the extant literature. They also support the notion that HPV16/18 positivity may serve as an independent risk factor for persistence. The PNI is a score calculated based on albumin and lymphocyte levels that reflects an individual's nutritional and immune status [ 21 ]. In cancer patients, systemic infections, and intensive care patients, these ratings offer considerable predictive advantages by concurrently measuring immune response and nutritional status [ 22 – 24 ]. HPV infection has been found to be closely linked to both the systemic immune response and the mucosal local immunological response [ 25 ]. The indices that evaluate systemic responses, such as HALP and PNI, provide a limited amount of information regarding the process of virus elimination. This limitation is due to the fact that they only reflect inflammation and nutritional status. This study's findings indicate that systemic response alone cannot fully explain HPV infection, and local immunity also plays a crucial role. These scores have been shown to be prognostic in many malignancies and chronic diseases; however, they may only become predictive when infection reaches systemic inflammatory response levels [ 26 – 28 ]. However, these scores can only be used to make predictions once an infection or disease has reached a stage that triggers a systemic inflammatory response. In contrast, cervical HPV infection is characterized as a localized mucosal infection, with the potential to manifest without eliciting a systemic response. Previous cervical HPV infection typically does not result in the development of systemic antibodies; therefore, it maintains the risk of reinfection with the same HPV strain. Nevertheless, HPV infection has been found to be closely associated with both the systemic immune response and the mucosal local immunological response [ 29 ]. It is unexpected that systemic indicators like HALP and PNI demonstrate comparable levels in preinvasive HPV infections, making them ineffective for predicting persistence. Both scores demonstrated poor predictive performance in ROC analysis, with AUC values approximating 0.5, indicating no meaningful discriminatory capacity. These findings highlight the limited prognostic value of HALP and PNI in HPV infection. In localized HPV infections of the cervix and vagina, the immune response is influenced by microimmunological variables, including epithelial defense, local antigen presentation, and cytokine networks [ 30 , 31 ]. Consequently, in subsequent studies, it is essential to formulate therapeutic approaches that target the local immune microenvironment. We should achieve this aim by conducting a comprehensive evaluation of the cervical and vaginal local immune responses, along with systemic parameters. Consequently, a concerted effort to understand the dynamics of the local immune system in the context of HPV persistence holds promise in identifying more specific biomarkers and treatment targets. In our study, we evaluated the relationship between immune-based mechanisms and histopathological and immunohistochemical markers associated with cervical preinvasive lesions and HPV persistence. P16 and Ki-67 are frequently used markers in the diagnosis of cervical lesions because they are associated with cellular proliferation and viral oncoprotein activity [ 32 ]. In the scientific literature, these two markers are considered highly specific, especially for distinguishing high-grade cervical lesions (CIN2 and above), when they are positive together [ 33 ]. However, the present study revealed no statistically significant difference in p16 and Ki-67 expression between the groups that became negative and remained positive according to the HPV test results in the first year. This finding may be associated with the observation that the majority of cases included in the present study consisted of patients with low-grade lesions or normal histopathological findings that did not require excisional procedures. In the present study, CIN2 lesions were detected in a sample of four patients. However, these patients were placed under follow-up as they refused excisional treatment. In the majority of the other cases, the biopsy and ECC results were limited to chronic cervicitis, koilocytosis, or low-grade lesions such as CIN1. Consequently, it is imperative to acknowledge that tissue markers such as p16 and Ki-67 exhibit greater diagnostic and prognostic significance in preinvasive or invasive processes as contrasted with transient infections. Evaluating dynamic processes such as persistent HPV infections requires a comprehensive approach that includes not only histopathological but also immunological and molecular responses. The preponderance of cervical cancer cases worldwide has been linked to persistent HPV 16 and 18 infections [ 25 , 34 ]. HPV vaccines, which have been utilized since 2006, are effective only before exposure to the virus, as they prevent infection; they have no therapeutic effect on existing or established HPV infections [ 34 ]. HPV vaccines are not included in the national immunization program in our country and are administered based on individual preferences. In the present study, all patients who received the HPV vaccine did so subsequent to a positive HPV test result and in accordance with their individual preferences. In the present study, among patients who tested HPV-negative at the first-year follow-up, there were also individuals who were vaccinated subsequent to receiving a positive HPV diagnosis. However, the rates of HPV negativity were similar between the vaccinated and unvaccinated groups, which supports the findings in the literature indicating that HPV vaccines have limited efficacy in clearing existing infections. This study's strength is that it is the first to assess the potential of common, calculable clinical biomarkers like HALP and PNI in predicting HPV infection persistence. On the other hand, the limitations of the study include a relatively small sample size, the inability to assess more specific parameters, such as mucosal immune responses, and a single-center design with a follow-up period limited to a minimum of one year. In conclusion, this study demonstrated that PNI and HALP scores are not reliable predictors of the clinical course of HPV infection, suggesting that systemic inflammation and nutritional status may exert only a limited influence on HPV persistence. The findings indicate that these indices may be insufficient to reflect viral clearance accurately, thereby underscoring the need to investigate more specific immunological and molecular markers in predicting the prognosis of HPV-related disease. Given their limited predictive performance in this study, the clinical applicability of HALP and PNI scores in HPV persistence appears minimal and requires further investigation before routine use can be recommended. The authors declare that there are no conflicts of interest related to this study. The findings, interpretations, and conclusions presented in this article reflect solely the views of the authors and were not influenced by any external organization or financial support. Throughout the research process, we upheld the integrity of the study and the objectivity of the analyses. Conclusions The present study demonstrated that HPV persistence over a one-year period was not predicted by systemic inflammation- and nutrition-based indices such as HALP and PNI scores. The significant association between high-risk HPV types 16 and 18 and persistence is consistent with the mechanisms by which these types suppress host immunity. The administration of vaccination following a positive HPV diagnosis did not affect the rates of HPV clearance. These findings underscore the necessity for more specific biomarkers, including those reflecting local immune responses, to improve the prognostic assessment of HPV-related disease. Abbreviations HPV: Human papillomavirus CVC: Cervical cytology CIN: Cervical Intraepithelial Neoplasia PNI: Prognostic Nutritional Index HALP: Hemoglobin, albumin, lymphocyte count, and platelet count values LSIL: Low-grade squamous intraepithelial lesions HSIL: High-grade squamous intraepithelial lesions ECC: Endocervical curettage AUC: Area under the curve ROC: Receiver operating characteristic Declarations Author contributions FO: Conceptualization, validation and formal analysis, data collection, statistical analysis, writing original draft preparation, funding acquisition. BO: Data collection, writing original draft preparation. BE: Data collection, writing. Funding No funding. Ethics approval The study was conducted in accordance with the principles of the Helsinki Declaration. The study was approved by the Ethics Committee of the Faculty of Medicine at Ordu University (approval no. 2025/152). Due to the retrospective nature of the study, informed consent was not required by the ethics committee. Conflict of interest The authors have no relevant financial or non-financial interests to disclose. Acknowledgement Not applicable. Availability of data and materials The data generated in the present study may be requested from the corresponding author. References Pimple S, Mishra G. Cancer cervix: Epidemiology and disease burden. Cytojournal. 2022;19:21. Rahangdale L, Mungo C, O’Connor S, Chibwesha CJ, Brewer NT. Human papillomavirus vaccination and cervical cancer risk. BMJ 2022, 379. de Sanjose S, Brotons M, Pavon MA. The natural history of human papillomavirus infection. Best Pract Res Clin Obstet Gynecol. 2018;47:2–13. Huber J, Mueller A, Sailer M, Regidor P-A. Human papillomavirus persistence or clearance after infection in reproductive age. What is the status? Review of the literature and new data of a vaginal gel containing silicate dioxide, citric acid, and selenite. Women's Health. 2021;17:17455065211020702. Aerssens A, Claeys P, Beerens E, Garcia A, Weyers S, Van Renterghem L, Praet M, Temmerman M, Velasquez R, Cuvelier C. Prediction of recurrent disease by cytology and HPV testing after treatment of cervical intraepithelial neoplasia. Cytopathology. 2009;20(1):27–35. Carreon JD, Sherman ME, Guillén D, Solomon D, Herrero R, Jerónimo J, Wacholder S, Rodríguez AC, Morales J, Hutchinson M. CIN2 is a much less reproducible and less valid diagnosis than CIN3: results from a histological review of population-based cervical samples. Int J Gynecol Pathol. 2007;26(4):441–6. Catalán-Castorena O, Garibay-Cerdenares OL, Illades-Aguiar B, Rodríguez-Ruiz HA, Zubillaga-Guerrero MI, Leyva-Vázquez MA, Encarnación-Guevara S. del Carmen Alarcón-Romero L: The role of HR-HPV integration in the progression of premalignant lesions into different cancer types. Heliyon 2024. Gutierrez-Xicotencatl L, Salazar-Piña DA, Pedroza-Saavedra A, Chihu-Amparan L, Rodriguez-Ocampo AN, Maldonado-Gama M, Esquivel-Guadarrama FR. Humoral immune response against human papillomavirus as source of biomarkers for the prediction and detection of cervical cancer. Viral Immunol. 2016;29(2):83–94. Yan L, Nakamura T, Casadei-Gardini A, Bruixola G, Huang Y-L, Hu Z-D. Long-term and short-term prognostic value of the prognostic nutritional index in cancer: a narrative review. Annals Translational Med. 2021;9(21):1630. Kim Y-J, Sung MK, Kim C-S, Lee J, Kim J-H, Sim J-H, Jeong S-M. Impact of prognostic nutritional index on survival in periampullary/pancreatic cancer patients undergoing pylorus-preserving pancreaticoduodenectomy: A propensity score-matched analysis. Hepatobiliary & Pancreatic Diseases International; 2025. Erol MF, Ay OF, Karademir E. Evaluating the role of pre-operative hemoglobin, albumin, lymphocyte, and platelet scores in predicting perioperative morbidity in rectal cancer patients. Cirugía y Cir 2025, 93(3). Shen X-B, Zhang Y-X, Wang W, Pan Y-Y. The hemoglobin, albumin, lymphocyte, and platelet (HALP) score in patients with small cell lung cancer before first-line treatment with etoposide and progression-free survival. Med Sci monitor: Int Med J experimental Clin Res. 2019;25:5630. Farag CM, Antar R, Akosman S, Ng M, Whalen MJ. What is hemoglobin, albumin, lymphocyte, platelet (HALP) score? A comprehensive literature review of HALP’s prognostic ability in different cancer types. Oncotarget. 2023;14:153. Chen X-L, Xue L, Wang W, Chen H-N, Zhang W-H, Liu K, Chen X-Z, Yang K, Zhang B, Chen Z-X. Prognostic significance of the combination of preoperative hemoglobin, albumin, lymphocyte and platelet in patients with gastric carcinoma: a retrospective cohort study. Oncotarget. 2015;6(38):41370. Bonaccio M, Di Castelnuovo A, Costanzo S, De Curtis A, Donati MB, Cerletti C, de Gaetano G, Iacoviello L. Age-and sex-based ranges of platelet count and cause-specific mortality risk in an adult general population: prospective findings from the Moli-sani study. Platelets. 2018;29(3):312–5. Baseman JG, Koutsky LA. The epidemiology of human papillomavirus infections. J Clin Virol. 2005;32:16–24. Rositch AF, Koshiol J, Hudgens MG, Razzaghi H, Backes DM, Pimenta JM, Franco EL, Poole C, Smith JS. Patterns of persistent genital human papillomavirus infection among women worldwide: a literature review and meta-analysis. Int J Cancer. 2013;133(6):1271–85. Schiffman M, Castle PE, Jeronimo J, Rodriguez AC, Wacholder S. Human papillomavirus and cervical cancer. lancet. 2007;370(9590):890–907. Schichl K, Doorbar J. Regulation and Deregulation of Viral Gene Expression During High-Risk HPV Infection. Viruses. 2025;17(7):937. Mohammed MM, Al-Khafaji ZAI, Al-Hilli NM. An exploration of the natural and acquired immunological mechanisms to high-risk human papillomavirus infection and unmasking immune escape in cervical cancer: A concise synopsis. Tzu Chi Med J. 2025;37(1):28–41. Mohri Y, Inoue Y, Tanaka K, Hiro J, Uchida K, Kusunoki M. Prognostic nutritional index predicts postoperative outcome in colorectal cancer. World J Surg. 2013;37(11):2688–92. Zhang L, Ma W, Qiu Z, Kuang T, Wang K, Hu B, Wang W. Prognostic nutritional index as a prognostic biomarker for gastrointestinal cancer patients treated with immune checkpoint inhibitors. Front Immunol. 2023;14:1219929. Yilmaz E, Sarier IF, Arsava EM, Topcuoglu MA. Prognostic importance of multiple objective nutrition screening Indexes in acute ischemic stroke patients treated with intravenous tissue plasminogen activator: A retrospective observational study. Clin Nutr ESPEN. Ertuğrul ÖZ, Karaaslan F, Yılmaz R, Tuncer MC. Relationship Between Nutritional Indexes and Clinical Outcomes in Stroke Patients Undergoing Mechanical Thrombectomy. Brain Sci. 2025;15(7):704. Zottnick S, Voß AL, Riemer AB. Inducing immunity where it matters: orthotopic HPV tumor models and therapeutic vaccinations. Front Immunol. 2020;11:1750. Çolak M, Çoban H, Sarıoğlu N, Şenel MY, Erel F. Prognostic significance of HALP score in İdiopathic Pulmonary Fibrosis-related mortality. Sarcoidosis Vasculitis Diffuse Lung Dis. 2025;42(2):16003. Li Q, Chen M, Zhao H, Zeng J. The prognostic and clinicopathological value of HALP score in non-small cell lung cancer. Front Immunol. 2025;16:1576326. Lin L, Huang H, Wu M, Chen F, Li C. The modified HALP score is associated with short-term mortality in critically ill patients with sepsis–A cohort study. J Infect Developing Ctries. 2025;19(06):924–33. Yokoji K, Giguère K, Malagón T, Rönn MM, Mayaud P, Kelly H, Delany-Moretlwe S, Drolet M, Brisson M, Boily M-C. Association of naturally acquired type-specific HPV antibodies and subsequent HPV re-detection: systematic review and meta-analysis. Infect Agents Cancer. 2023;18(1):70. Cui M, Wu Y, Liu Z, Liu Y, Fan L. Advances in the interrelated nature of vaginal microecology, HPV infection, and cervical lesions. Front Cell Infect Microbiol. 2025;15:1608195. Ntuli L, Mtshali A, Mzobe G, Liebenberg LJ, Ngcapu S. Role of immunity and vaginal microbiome in clearance and persistence of human papillomavirus infection. Front Cell Infect Microbiol. 2022;12:927131. Pinto PP, Zanine RM. Diagnostic value of p16 and Ki-67 expression in cervical glandular intraepithelial disease: A review. Annals Diagn Pathol. 2023;62:152054. Clarke MA, Cheung LC, Castle PE, Schiffman M, Tokugawa D, Poitras N, Lorey T, Kinney W, Wentzensen N. Five-year risk of cervical precancer following p16/Ki-67 dual-stain triage of HPV-positive women. JAMA Oncol. 2019;5(2):181–6. Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. Cancer J Clin. 2018;68(6):394–424. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 17 Dec, 2025 Read the published version in BMC Women's Health → Version 1 posted Editorial decision: Revision requested 18 Sep, 2025 Reviews received at journal 17 Sep, 2025 Reviews received at journal 17 Sep, 2025 Reviews received at journal 14 Sep, 2025 Reviews received at journal 11 Sep, 2025 Reviewers agreed at journal 08 Sep, 2025 Reviewers agreed at journal 04 Sep, 2025 Reviews received at journal 03 Sep, 2025 Reviewers agreed at journal 02 Sep, 2025 Reviewers agreed at journal 02 Sep, 2025 Reviewers agreed at journal 02 Sep, 2025 Reviewers invited by journal 02 Sep, 2025 Editor invited by journal 13 Aug, 2025 Editor assigned by journal 12 Aug, 2025 Submission checks completed at journal 12 Aug, 2025 First submitted to journal 08 Aug, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7328319","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":510377982,"identity":"3f234367-f53f-4940-9e37-3f80a7db45c2","order_by":0,"name":"Fatma OZMEN","email":"data:image/png;base64,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","orcid":"","institution":"Ordu University","correspondingAuthor":true,"prefix":"","firstName":"Fatma","middleName":"","lastName":"OZMEN","suffix":""},{"id":510377983,"identity":"9808e362-ab18-44b4-b3fe-506391c987fb","order_by":1,"name":"Burcu OZATA","email":"","orcid":"","institution":"Ordu University","correspondingAuthor":false,"prefix":"","firstName":"Burcu","middleName":"","lastName":"OZATA","suffix":""},{"id":510377987,"identity":"c8950792-7f88-430b-9b2b-704b7bccbe70","order_by":2,"name":"Burcu EROL","email":"","orcid":"","institution":"Ordu University","correspondingAuthor":false,"prefix":"","firstName":"Burcu","middleName":"","lastName":"EROL","suffix":""}],"badges":[],"createdAt":"2025-08-08 14:38:34","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7328319/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7328319/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12905-025-04147-7","type":"published","date":"2025-12-17T15:57:18+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":90899679,"identity":"a25ed192-ec39-446d-8d84-252c7d671307","added_by":"auto","created_at":"2025-09-09 12:02:38","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":164703,"visible":true,"origin":"","legend":"\u003cp\u003eHPV genotype positivity Rates.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7328319/v1/1b97996dfb267abbeb6a25fd.png"},{"id":90898697,"identity":"7fd60019-9009-4712-ba80-7770aeed3191","added_by":"auto","created_at":"2025-09-09 11:54:38","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":137832,"visible":true,"origin":"","legend":"\u003cp\u003eROC Curve HALP Score.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7328319/v1/1fe1edb38610a1ed11ef174a.png"},{"id":90898694,"identity":"0b223ca6-2365-4ec7-97ff-64e88e9f3d8d","added_by":"auto","created_at":"2025-09-09 11:54:38","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":145599,"visible":true,"origin":"","legend":"\u003cp\u003eROC Curve PNI Score.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7328319/v1/9224d907a5a1ee7286dfe1dc.png"},{"id":98813967,"identity":"a54d5c59-b6e8-4eda-a22a-caf3fa49fd89","added_by":"auto","created_at":"2025-12-22 16:08:41","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":840468,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7328319/v1/d64cd977-ce28-4e25-9caa-5514ef0bcec5.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Evaluation of Systemic Inflammation- and Nutrition-Based Indices in the Prediction of HPV Persistence","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCervical cancer is the fourth most prevalent type of cancer-related death for women globally [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Cervical cancer is among the rare malignancies associated with a viral etiology, specifically Human papillomavirus (HPV) infection [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Cervical cancer is a type of cancer for which screening is possible through cervical cytology (CVC) and HPV testing.\u003c/p\u003e\u003cp\u003eThe natural history of most HPV infections is characterized by spontaneous resolution, typically occurring within 12 to 24 months without any notable clinical manifestations [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. It is estimated that only 10\u0026ndash;20% of infected women develop a persistent infection lasting longer than 24 months [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The failure of HPV to be eradicated from the body can result in a persistent infection, which is a significant contributor to the onset of Cervical Intraepithelial Neoplasia (CIN) and cervical cancer [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The formation of preinvasive lesions and the progression to malignant transformation can vary significantly at the individual level, depending on factors such as age, the type of HPV infection, smoking, and HIV infection [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/p\u003e\u003cp\u003eNutritional status is known to significantly influence the immune system\u0026rsquo;s ability to mount an effective response against infections [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Hemoglobin, albumin, lymphocyte count, and platelet count values (HALP) and the Prognostic Nutritional Index (PNI) scores are noninvasive, low-cost prognostic indicators that comprehensively evaluate inflammation, nutritional status, and immune function based on hematological and immunological parameters. HALP and PNI scores are commonly used tools for predicting prognosis and immune response in progressive and malignant diseases, as well as for assessing nutritional and immunological status [\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The immune response has been shown to be effective not only in the local context but also on a systemic scale. Moreover, it has the potential to play a decisive role in the elimination of cervical HPV infection.\u003c/p\u003e\u003cp\u003ePredicting HPV persistence may be a crucial tool for managing and keeping a watch on high-risk patients. The assessment of disease risk commonly employs a range of scientific approaches, including pathological techniques, medical imaging, laboratory analyses, and demographic data. However, the accuracy of these techniques in predicting HPV persistence remains unclear. These services have several important limitations, such as high costs, specialized knowledge, and the requirement for customized approaches. A noninvasive, simple-to-use, cost-effective, and standardized prognostic prediction tool is ideal. The purpose of this research is to assess the PNI and HALP scores' potential utility in predicting HPV persistence at a one-year follow-up.\u003c/p\u003e"},{"header":"Patients And Methods","content":"\u003cp\u003e The present study was conducted in accordance with the Helsinki Declaration and approved by the Ethics Committee of the Faculty of Medicine, Ordu University (Approval No. 2025/152). Prior to analysis, all data were anonymized.\u003c/p\u003e\u003cp\u003eFrom January 2021 to March 2025, a total of 581 HPV-positive female patients aged 31\u0026ndash;67 years who had been subjects in the study for a minimum of one year were included in the analysis. We excluded 111 patients who underwent excisional treatment during the follow-up period, leaving a total of 470 patients in the study.\u003c/p\u003e\u003cp\u003eThe patients' initial HPV tests were conducted as part of the Turkish National Cervical Cancer Screening Program, using DNA-based testing methods [SPF10, PCR-DEIA-LiPA25] and positive high-risk HPV tests [Hybrid Capture II (HC2)]. The initial HPV tests of the patients included in the study were performed within the scope of this program, and individuals with positive HPV results were referred to our center. All patients underwent colposcopic examination with cervical and endocervical sampling at the time of admission. Routine blood tests (lymphocyte, hemoglobin, WBC, albumin) were requested during the day-long hospitalization to assess the risk of potential infection, allergic reactions, or hematological complications. The laboratory data utilized in this retrospective study were obtained from the hospital information system.\u003c/p\u003e\u003cp\u003eThe demographic information collected included age, marital status, smoking status, chronic disease, contraceptive method, and mode of delivery. The laboratory parameters recorded included Hb, WBC, lymphocyte, platelet, and albumin. The results of the HPV test were then compared at the initial presentation and for one year.\u003c/p\u003e\u003cp\u003eInitial HPV tests were evaluated using PCR, while cytology was assessed using the ThinPrep method (Hologic Inc., USA). A total of 15 HPV DNA genotypes, including HPV16, HPV18, and other high-risk genotypes (31, 33, 35, 39, 45, 51, 52, 56, 58, 59, 66, 68, and others), were detected using the Roche Cobas system. Cases that were HPV-positive at baseline were divided into two groups based on whether the HPV test became negative or remained positive at the first-year follow-up. The HALP and PNI scores were subsequently calculated and compared for both groups.\u003c/p\u003e\u003cp\u003eCases that were HPV-positive at baseline were divided into two groups based on whether the HPV test became negative or remained positive at the first-year follow-up. A comparative analysis was conducted on the HALP and PNI scores between the two groups. To this end, both scores were calculated and subjected to statistical analysis to discern intergroup differences. The HALP score, which is based on hemoglobin, albumin, lymphocyte, and platelet values, was calculated as follows: HALP = (Hemoglobin [g/L] \u0026times; Albumin [g/L] \u0026times; Lymphocytes [/L]) / Platelets [/L]. The PNI score was calculated as follows: PNI = (10 \u0026times; Albumin [g/dL]) + (0.005 \u0026times; Lymphocyte count [/mm\u0026sup3;]) [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe exclusion criteria are as follows: having an immune system disease, a diagnosis or history of malignancy, undergoing long-term glucocorticoid or immunosuppressive treatment, receiving treatment for another concurrent malignancy, possessing incomplete test data, being diagnosed with new cancer during follow-up that leads to the initiation of chemotherapy, and having a control HPV test performed more than one year ago.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStatistics:\u003c/h2\u003e\u003cp\u003eWe used SPSS (Statistical Package for the Social Sciences) 18.0 software to do the statistical analyses. The descriptive statistics encompassed both categorical and numerical variables. Counts and percentages were used to show categorical variables, and means\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviations were used to show numerical variables. The chi-square test was used for categorical data when comparing groups, and Fisher's exact test was used when the expected cell counts were less than five. The statistical analysis of the data utilized Student's t-test under the condition that the data distribution adhered to the normal distribution assumption, and employed the Mann\u0026ndash;Whitney U test when the data failed to conform to a normal distribution. For situations with more than one group, the Kruskal\u0026ndash;Wallis test was used when the normal distribution condition was not met, and the one-way analysis of variance (One-Way ANOVA) was used when it was. All statistical tests had a level of significance of p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eOf the total 470 HPV-positive patients included in the study, 271 patients tested negative for HPV at the one-year follow-up, while 199 patients remained HPV-positive. Consequently, the patients were divided into two groups: The subjects were divided into two groups, designated Group N and Group P, based on their HPV status. A comparative analysis was conducted among the groups in terms of demographic characteristics, laboratory parameters, and calculated HALP and PNI scores.\u003c/p\u003e\u003cp\u003eThe factors that influence HPV persistence include HPV genotype, patient age, smoking, and diseases affecting the immune system. The mean ages in Group P and Group N were 47.50\u0026thinsp;\u0026plusmn;\u0026thinsp;9.79 and 46.77\u0026thinsp;\u0026plusmn;\u0026thinsp;9.58 years, respectively, with no statistically significant difference (p\u0026thinsp;=\u0026thinsp;0.477). The present study revealed that there were no statistically significant differences between Group P and Group N with regard to age, marital status, smoking status, contraceptive method, pregnancy history, mode of delivery, and presence of chronic diseases (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of Demographic Characteristics Between Groups\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTest\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGroup N (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD or %)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGroup P (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD or %)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eU\u0026dagger;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e46.77\u0026thinsp;\u0026plusmn;\u0026thinsp;9.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e47.50\u0026thinsp;\u0026plusmn;\u0026thinsp;9.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.4773\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarital status\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eF\u0026Dagger;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e{0: 17.3, 1: 82.7}\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e{0: 15.6, 1: 84.4}\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.7068\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSmoking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eF\u0026Dagger;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e{0: 73.1, 1: 26.9}\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e{0: 75.9, 1: 24.1}\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.5228\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eContraceptive method\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eχ\u0026sup2;\u0026sect;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e{0: 62.0, 1: 9.6, 2: 13.3, 3: 5.5, 4: 2.6, 5: 7.0}\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e{0: 63.3, 1: 11.1, 2: 15.1, 3: 1.0, 4: 3.5, 5: 6.0}\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.183\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGravidity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eχ\u0026sup2;\u0026sect;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e{0: 5.9, 1: 11.1, 2: 34.7, 3: 29.2, 4: 12.9, 5: 4.1, 6: 1.5, 7: 0.7, 8: 0.0, 9: 0.0}\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e{0: 3.5, 1: 7.5, 2: 32.7, 3: 29.6, 4: 14.6, 5: 7.5, 6: 3.0, 7: 0.5, 8: 0.5, 9: 0.5}\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.3651\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eχ\u0026sup2;\u0026sect;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e{0: 5.9, 1: 13.7, 2: 41.7, 3: 25.5, 4: 10.0, 5: 1.8, 6: 1.5}\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e{0: 3.5, 1: 11.6, 2: 40.2, 3: 28.1, 4: 10.6, 5: 4.0, 6: 2.0}\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.6367\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMode of delivery\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eχ\u0026sup2;\u0026sect;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e{0: 6.3, 1: 56.5, 2: 30.3, 3: 7.0}\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e{0: 5.0, 1: 54.8, 2: 25.6, 3: 14.6}\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.0535\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChronic\u003c/p\u003e\u003cp\u003edisease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eF\u0026Dagger;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e{0: 78.6, 1: 21.4}\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e{0: 72.4, 1: 27.6}\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.127\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cem\u003eStatistical Test Symbols:\u0026dagger; Mann\u0026ndash;Whitney U Test \u0026Dagger; Fisher\u0026rsquo;s Exact Test \u0026sect; Chi-Square Test\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eIn contrast, when the HPV genotypes at the patients' initial visits were examined, statistically significant differences were observed between the groups in terms of HPV16 (44.7%) and HPV18 (27.1%) positivity (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 and p\u0026thinsp;=\u0026thinsp;0.0006, respectively). No significant differences were identified for other high- and low-risk HPV types (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The findings suggest a substantial variation between the two groups, characterized by the presence or absence of persistent HPV positivity, with respect to the types of high- and low-risk HPV they initially carried.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAll patients who initially presented to our center with HPV positivity underwent cervical and endocervical sampling, accompanied by colposcopic evaluation. Cervical biopsies revealed normal cervical epithelium in 294 patients, koilocytosis in 46 patients, and low-grade squamous intraepithelial lesions (LSIL; CIN1) in 130 patients. No high-grade squamous intraepithelial lesions (HSIL) were detected. Endocervical curettage (ECC) results showed normal endocervical tissue in 372 patients, koilocytosis in 18 patients, LSIL (CIN1) in 76 patients, and HSIL (CIN2) in 4 patients. The four patients diagnosed with CIN2 on ECC refused excisional treatment and were instead placed under close clinical surveillance. Subsequent comparisons between Group P (HPV persistence) and Group N (HPV clearance) revealed no statistically significant differences in cervical biopsy or ECC outcomes (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Similarly, immunohistochemical analyses of P16 and Ki-67 expression did not yield significant differences between the two groups (p\u0026thinsp;=\u0026thinsp;0.131 for P16, p\u0026thinsp;=\u0026thinsp;0.176 for Ki-67) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eHistopathologic and Immunohistochemical Findings According to Sampling Method and Group\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eType\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDiagnosis\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003cp\u003en\u0026thinsp;=\u0026thinsp;470\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGroup N\u003c/p\u003e\u003cp\u003en\u0026thinsp;=\u0026thinsp;271\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eGroup N (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eGroup P\u003c/p\u003e\u003cp\u003eN\u0026thinsp;=\u0026thinsp;199\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eGroup P (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCervical Biopsy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eKoilocytosis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e11.070\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e8.040\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.250\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCervical Biopsy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLSIL (CIN1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e130\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e25.092\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e31.156\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.250\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCervical Biopsy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNormal Cervical Tissue\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e294\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e173\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e63.838\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e121\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e60.804\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.250\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eECC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNormal Endocervical Tissue\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e372\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e221\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e81.550\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e151\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e75.879\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.269\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eECC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eKoilocytosis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2.952\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e5.025\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.269\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eECC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLSIL (CIN1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e15.129\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e17.588\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.269\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eECC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEndometrial Tissue\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.369\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.508\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.269\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eP16 Staining\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNegative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e407\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e242\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e89.299\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e165\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e82.915\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.061\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eP16 Staining\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSuperficial\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e10.701\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e17.085\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.061\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKi-67 Staining\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNegative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e379\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e224\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e82.657\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e155\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e77.889\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.240\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKi-67 Staining\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSuperficial\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e17.343\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e22.111\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.240\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003cem\u003eCIN1: Cervical Intraepithelial Neoplasia Grade 1, ECC: Endocervical Curettage, LSIL: Low-Grade Squamous Intraepithelial Lesion, P16: Tumor suppressor protein p16 (INK4a), Ki-67: Cellular proliferation marker Ki-67, Group N: Patients who became HPV-negative at one-year follow-up, Group P: Patients with persistent HPV infection at one-year follow-up\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eAll patients were informed about the vaccine, regardless of HPV positivity and type; vaccination was left to the patients' discretion. The study population comprised patients who had completed the vaccination series, received incomplete doses, and were still undergoing the vaccination process. In Group P, 137 patients received no vaccine, 2 received 1 dose, 3 received 2 doses, and 38 received 3 doses. In Group N, 193 patients received no vaccine, 1 received 1 dose, 3 received 2 doses, and 74 received 3 doses. A subsequent statistical analysis revealed no statistically significant difference between the two groups (p\u0026thinsp;=\u0026thinsp;0.604).\u003c/p\u003e\u003cp\u003eAt the conclusion of the one-year follow-up period, a comparison was made between HALP and PNI scores in patients with persistent HPV infection (Group P, n\u0026thinsp;=\u0026thinsp;199) and those with negative results (Group N, n\u0026thinsp;=\u0026thinsp;271). The median HALP score was determined to be 49.11 (with an interquartile range of 35.87\u0026ndash;60.42) in Group N, while it was 46.97 (with an interquartile range of 35.49\u0026ndash;59.23) in Group P. The median PNI score was found to be 55.30 (with an interquartile range of 51.40\u0026ndash;58.40) in Group N and 55.00 (with an interquartile range of 51.10\u0026ndash;58.20) in Group P. The Mann-Whitney U test performed on the groups yielded U\u0026thinsp;=\u0026thinsp;25,064.5, p\u0026thinsp;=\u0026thinsp;0.361 for the HALP score and U\u0026thinsp;=\u0026thinsp;26,106.5, p\u0026thinsp;=\u0026thinsp;0.637 for the PNI score. No statistically significant difference was detected between the groups for either biomarker (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). The results indicate that HALP and PNI scores do not significantly influence HPV infection persistence or clearance (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of HALP and PNI Scores Between Groups\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eScore\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGroup N (n\u0026thinsp;=\u0026thinsp;271)\u003c/p\u003e\u003cp\u003eMedian (IQR)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGroup P (n\u0026thinsp;=\u0026thinsp;199)\u003c/p\u003e\u003cp\u003eMedian (IQR)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHALP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e49.11 (35.52\u0026ndash;61.48)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e46.97 (35.77\u0026ndash;58.40)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.361\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePNI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e55.30 (52.50\u0026ndash;58.23)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e55.00 (52.20\u0026ndash;58.10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.637\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cem\u003eStatistical comparison was performed using the Mann\u0026ndash;Whitney U test.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cem\u003eIQR: Interquartile Range\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe predictive power of HPV infection persistence was evaluated using the area under the curve (AUC) of the receiver operating characteristic (ROC) curve analysis. The AUC was 0.531 for HALP and 0.516 for PNI, both of which are close to 0.5. These results indicate that the predictive performance of HALP and PNI scores in distinguishing between HPV persistence and clearance was no better than chance, underscoring their limited utility as prognostic tools in this context (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, the predictive roles of the HALP score and the PNI were evaluated in the natural course of HPV infection. Specifically, it was investigated whether there was a significant difference in these two biomarkers between individuals whose HPV infection persisted (Group P) and those whose infection cleared (Group N) within one year. The findings revealed that HALP and PNI scores did not differ significantly between the two groups. This result suggests that these indices, which reflect systemic inflammation and nutritional status, may have a limited impact on HPV clearance over a one-year period.\u003c/p\u003e\u003cp\u003eThe HALP score has become a frequently utilized metric for evaluating systemic inflammatory processes in solid tumors recent years [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The HALP calculation, which incorporates hemoglobin and albumin, has enabled the correlation between nutritional status and immune response, particularly in the context of gastrointestinal malignancies. This calculation has revealed the relationship between nutrition and immunity [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In a prospective study involving more than 20,000 healthy individuals, a decrease in platelet count after the age of 60 was shown to be associated with immune response [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The inclusion of platelet count in the denominator of the HALP score suggests a potential correlation between this score and age. Furthermore, studies that have evaluated the relationship between age and HPV infection prevalence and clearance have demonstrated that HPV clearance decreases with increasing age. In addition, these studies have indicated that there is an inverse relationship between these two variables. [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. In the present study, the age variable, which has the potential to affect the HALP score and HPV persistence, exhibited a comparable distribution between Group P and Group N and did not demonstrate a statistically significant difference. Consequently, age was not considered a confounding variable in the analyses.\u003c/p\u003e\u003cp\u003eHPV infection can spontaneously resolve within 12 to 24 months in the immune systems of most healthy individuals; however, in some cases, the virus persists and can lead to the development of cervical preinvasive lesions [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. A multitude of factors contribute to the development of persistent infection, including the oncogenicity of the HPV type, age, immunosuppression, smoking, and co-infections [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. The expression of E6 and E7 oncoproteins in high-risk types, such as HPV16 and HPV18, has been demonstrated to suppress the host immune response at various levels, thereby hindering viral elimination. This contributes to the persistence of HPV infection [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. In the present study, it was also determined that the HPV persistence rate was significantly higher in cases positive for HPV 16 and HPV 18. It has been established that these high-risk types suppress the host immune response through E6 and E7 oncoproteins, thereby preventing viral clearance. The findings of this study are consistent with the clinical implications of the immune evasion mechanisms described in the extant literature. They also support the notion that HPV16/18 positivity may serve as an independent risk factor for persistence.\u003c/p\u003e\u003cp\u003eThe PNI is a score calculated based on albumin and lymphocyte levels that reflects an individual's nutritional and immune status [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. In cancer patients, systemic infections, and intensive care patients, these ratings offer considerable predictive advantages by concurrently measuring immune response and nutritional status [\u003cspan additionalcitationids=\"CR23\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. HPV infection has been found to be closely linked to both the systemic immune response and the mucosal local immunological response [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The indices that evaluate systemic responses, such as HALP and PNI, provide a limited amount of information regarding the process of virus elimination. This limitation is due to the fact that they only reflect inflammation and nutritional status. This study's findings indicate that systemic response alone cannot fully explain HPV infection, and local immunity also plays a crucial role.\u003c/p\u003e\u003cp\u003eThese scores have been shown to be prognostic in many malignancies and chronic diseases; however, they may only become predictive when infection reaches systemic inflammatory response levels [\u003cspan additionalcitationids=\"CR27\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. However, these scores can only be used to make predictions once an infection or disease has reached a stage that triggers a systemic inflammatory response. In contrast, cervical HPV infection is characterized as a localized mucosal infection, with the potential to manifest without eliciting a systemic response. Previous cervical HPV infection typically does not result in the development of systemic antibodies; therefore, it maintains the risk of reinfection with the same HPV strain. Nevertheless, HPV infection has been found to be closely associated with both the systemic immune response and the mucosal local immunological response [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. It is unexpected that systemic indicators like HALP and PNI demonstrate comparable levels in preinvasive HPV infections, making them ineffective for predicting persistence. Both scores demonstrated poor predictive performance in ROC analysis, with AUC values approximating 0.5, indicating no meaningful discriminatory capacity. These findings highlight the limited prognostic value of HALP and PNI in HPV infection. In localized HPV infections of the cervix and vagina, the immune response is influenced by microimmunological variables, including epithelial defense, local antigen presentation, and cytokine networks [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Consequently, in subsequent studies, it is essential to formulate therapeutic approaches that target the local immune microenvironment. We should achieve this aim by conducting a comprehensive evaluation of the cervical and vaginal local immune responses, along with systemic parameters. Consequently, a concerted effort to understand the dynamics of the local immune system in the context of HPV persistence holds promise in identifying more specific biomarkers and treatment targets.\u003c/p\u003e\u003cp\u003eIn our study, we evaluated the relationship between immune-based mechanisms and histopathological and immunohistochemical markers associated with cervical preinvasive lesions and HPV persistence. P16 and Ki-67 are frequently used markers in the diagnosis of cervical lesions because they are associated with cellular proliferation and viral oncoprotein activity [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. In the scientific literature, these two markers are considered highly specific, especially for distinguishing high-grade cervical lesions (CIN2 and above), when they are positive together [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. However, the present study revealed no statistically significant difference in p16 and Ki-67 expression between the groups that became negative and remained positive according to the HPV test results in the first year. This finding may be associated with the observation that the majority of cases included in the present study consisted of patients with low-grade lesions or normal histopathological findings that did not require excisional procedures. In the present study, CIN2 lesions were detected in a sample of four patients. However, these patients were placed under follow-up as they refused excisional treatment. In the majority of the other cases, the biopsy and ECC results were limited to chronic cervicitis, koilocytosis, or low-grade lesions such as CIN1. Consequently, it is imperative to acknowledge that tissue markers such as p16 and Ki-67 exhibit greater diagnostic and prognostic significance in preinvasive or invasive processes as contrasted with transient infections. Evaluating dynamic processes such as persistent HPV infections requires a comprehensive approach that includes not only histopathological but also immunological and molecular responses.\u003c/p\u003e\u003cp\u003eThe preponderance of cervical cancer cases worldwide has been linked to persistent HPV 16 and 18 infections [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. HPV vaccines, which have been utilized since 2006, are effective only before exposure to the virus, as they prevent infection; they have no therapeutic effect on existing or established HPV infections [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. HPV vaccines are not included in the national immunization program in our country and are administered based on individual preferences. In the present study, all patients who received the HPV vaccine did so subsequent to a positive HPV test result and in accordance with their individual preferences. In the present study, among patients who tested HPV-negative at the first-year follow-up, there were also individuals who were vaccinated subsequent to receiving a positive HPV diagnosis. However, the rates of HPV negativity were similar between the vaccinated and unvaccinated groups, which supports the findings in the literature indicating that HPV vaccines have limited efficacy in clearing existing infections.\u003c/p\u003e\u003cp\u003eThis study's strength is that it is the first to assess the potential of common, calculable clinical biomarkers like HALP and PNI in predicting HPV infection persistence. On the other hand, the limitations of the study include a relatively small sample size, the inability to assess more specific parameters, such as mucosal immune responses, and a single-center design with a follow-up period limited to a minimum of one year. In conclusion, this study demonstrated that PNI and HALP scores are not reliable predictors of the clinical course of HPV infection, suggesting that systemic inflammation and nutritional status may exert only a limited influence on HPV persistence. The findings indicate that these indices may be insufficient to reflect viral clearance accurately, thereby underscoring the need to investigate more specific immunological and molecular markers in predicting the prognosis of HPV-related disease. Given their limited predictive performance in this study, the clinical applicability of HALP and PNI scores in HPV persistence appears minimal and requires further investigation before routine use can be recommended.\u003c/p\u003e\u003cp\u003eThe authors declare that there are no conflicts of interest related to this study. The findings, interpretations, and conclusions presented in this article reflect solely the views of the authors and were not influenced by any external organization or financial support. Throughout the research process, we upheld the integrity of the study and the objectivity of the analyses.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe present study demonstrated that HPV persistence over a one-year period was not predicted by systemic inflammation- and nutrition-based indices such as HALP and PNI scores. The significant association between high-risk HPV types 16 and 18 and persistence is consistent with the mechanisms by which these types suppress host immunity. The administration of vaccination following a positive HPV diagnosis did not affect the rates of HPV clearance. These findings underscore the necessity for more specific biomarkers, including those reflecting local immune responses, to improve the prognostic assessment of HPV-related disease.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eHPV: Human papillomavirus\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCVC: Cervical cytology\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCIN: Cervical Intraepithelial Neoplasia\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePNI: Prognostic Nutritional Index\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHALP: Hemoglobin, albumin, lymphocyte count, and platelet count values\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLSIL: Low-grade squamous intraepithelial lesions\u003c/p\u003e\n\u003cp\u003eHSIL: High-grade squamous intraepithelial lesions\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eECC: Endocervical curettage\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAUC: Area under the curve\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eROC: Receiver operating characteristic\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFO: Conceptualization, validation and formal analysis, data collection, statistical analysis, writing original draft preparation, funding acquisition. BO: Data collection, writing original draft preparation. BE: Data collection, writing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was conducted in accordance with the principles of the Helsinki Declaration. The study was approved by the Ethics Committee of the Faculty of Medicine at Ordu University (approval no. 2025/152). Due to the retrospective nature of the study, informed consent was not required by the ethics committee.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data generated in the present study may be requested from the corresponding author.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003ePimple S, Mishra G. Cancer cervix: Epidemiology and disease burden. Cytojournal. 2022;19:21.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRahangdale L, Mungo C, O\u0026rsquo;Connor S, Chibwesha CJ, Brewer NT. Human papillomavirus vaccination and cervical cancer risk. BMJ 2022, 379.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ede Sanjose S, Brotons M, Pavon MA. The natural history of human papillomavirus infection. Best Pract Res Clin Obstet Gynecol. 2018;47:2\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHuber J, Mueller A, Sailer M, Regidor P-A. Human papillomavirus persistence or clearance after infection in reproductive age. What is the status? Review of the literature and new data of a vaginal gel containing silicate dioxide, citric acid, and selenite. Women's Health. 2021;17:17455065211020702.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAerssens A, Claeys P, Beerens E, Garcia A, Weyers S, Van Renterghem L, Praet M, Temmerman M, Velasquez R, Cuvelier C. Prediction of recurrent disease by cytology and HPV testing after treatment of cervical intraepithelial neoplasia. Cytopathology. 2009;20(1):27\u0026ndash;35.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCarreon JD, Sherman ME, Guill\u0026eacute;n D, Solomon D, Herrero R, Jer\u0026oacute;nimo J, Wacholder S, Rodr\u0026iacute;guez AC, Morales J, Hutchinson M. CIN2 is a much less reproducible and less valid diagnosis than CIN3: results from a histological review of population-based cervical samples. Int J Gynecol Pathol. 2007;26(4):441\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCatal\u0026aacute;n-Castorena O, Garibay-Cerdenares OL, Illades-Aguiar B, Rodr\u0026iacute;guez-Ruiz HA, Zubillaga-Guerrero MI, Leyva-V\u0026aacute;zquez MA, Encarnaci\u0026oacute;n-Guevara S. del Carmen Alarc\u0026oacute;n-Romero L: The role of HR-HPV integration in the progression of premalignant lesions into different cancer types. \u003cem\u003eHeliyon\u003c/em\u003e 2024.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGutierrez-Xicotencatl L, Salazar-Pi\u0026ntilde;a DA, Pedroza-Saavedra A, Chihu-Amparan L, Rodriguez-Ocampo AN, Maldonado-Gama M, Esquivel-Guadarrama FR. Humoral immune response against human papillomavirus as source of biomarkers for the prediction and detection of cervical cancer. Viral Immunol. 2016;29(2):83\u0026ndash;94.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYan L, Nakamura T, Casadei-Gardini A, Bruixola G, Huang Y-L, Hu Z-D. Long-term and short-term prognostic value of the prognostic nutritional index in cancer: a narrative review. Annals Translational Med. 2021;9(21):1630.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKim Y-J, Sung MK, Kim C-S, Lee J, Kim J-H, Sim J-H, Jeong S-M. Impact of prognostic nutritional index on survival in periampullary/pancreatic cancer patients undergoing pylorus-preserving pancreaticoduodenectomy: A propensity score-matched analysis. Hepatobiliary \u0026amp; Pancreatic Diseases International; 2025.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eErol MF, Ay OF, Karademir E. Evaluating the role of pre-operative hemoglobin, albumin, lymphocyte, and platelet scores in predicting perioperative morbidity in rectal cancer patients. Cirug\u0026iacute;a y Cir 2025, 93(3).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShen X-B, Zhang Y-X, Wang W, Pan Y-Y. The hemoglobin, albumin, lymphocyte, and platelet (HALP) score in patients with small cell lung cancer before first-line treatment with etoposide and progression-free survival. Med Sci monitor: Int Med J experimental Clin Res. 2019;25:5630.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFarag CM, Antar R, Akosman S, Ng M, Whalen MJ. What is hemoglobin, albumin, lymphocyte, platelet (HALP) score? A comprehensive literature review of HALP\u0026rsquo;s prognostic ability in different cancer types. Oncotarget. 2023;14:153.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChen X-L, Xue L, Wang W, Chen H-N, Zhang W-H, Liu K, Chen X-Z, Yang K, Zhang B, Chen Z-X. Prognostic significance of the combination of preoperative hemoglobin, albumin, lymphocyte and platelet in patients with gastric carcinoma: a retrospective cohort study. Oncotarget. 2015;6(38):41370.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBonaccio M, Di Castelnuovo A, Costanzo S, De Curtis A, Donati MB, Cerletti C, de Gaetano G, Iacoviello L. Age-and sex-based ranges of platelet count and cause-specific mortality risk in an adult general population: prospective findings from the Moli-sani study. Platelets. 2018;29(3):312\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBaseman JG, Koutsky LA. The epidemiology of human papillomavirus infections. J Clin Virol. 2005;32:16\u0026ndash;24.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRositch AF, Koshiol J, Hudgens MG, Razzaghi H, Backes DM, Pimenta JM, Franco EL, Poole C, Smith JS. Patterns of persistent genital human papillomavirus infection among women worldwide: a literature review and meta-analysis. Int J Cancer. 2013;133(6):1271\u0026ndash;85.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSchiffman M, Castle PE, Jeronimo J, Rodriguez AC, Wacholder S. Human papillomavirus and cervical cancer. lancet. 2007;370(9590):890\u0026ndash;907.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSchichl K, Doorbar J. Regulation and Deregulation of Viral Gene Expression During High-Risk HPV Infection. Viruses. 2025;17(7):937.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMohammed MM, Al-Khafaji ZAI, Al-Hilli NM. An exploration of the natural and acquired immunological mechanisms to high-risk human papillomavirus infection and unmasking immune escape in cervical cancer: A concise synopsis. Tzu Chi Med J. 2025;37(1):28\u0026ndash;41.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMohri Y, Inoue Y, Tanaka K, Hiro J, Uchida K, Kusunoki M. Prognostic nutritional index predicts postoperative outcome in colorectal cancer. World J Surg. 2013;37(11):2688\u0026ndash;92.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang L, Ma W, Qiu Z, Kuang T, Wang K, Hu B, Wang W. Prognostic nutritional index as a prognostic biomarker for gastrointestinal cancer patients treated with immune checkpoint inhibitors. Front Immunol. 2023;14:1219929.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYilmaz E, Sarier IF, Arsava EM, Topcuoglu MA. Prognostic importance of multiple objective nutrition screening Indexes in acute ischemic stroke patients treated with intravenous tissue plasminogen activator: A retrospective observational study. Clin Nutr ESPEN.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eErtuğrul \u0026Ouml;Z, Karaaslan F, Yılmaz R, Tuncer MC. Relationship Between Nutritional Indexes and Clinical Outcomes in Stroke Patients Undergoing Mechanical Thrombectomy. Brain Sci. 2025;15(7):704.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZottnick S, Vo\u0026szlig; AL, Riemer AB. Inducing immunity where it matters: orthotopic HPV tumor models and therapeutic vaccinations. Front Immunol. 2020;11:1750.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e\u0026Ccedil;olak M, \u0026Ccedil;oban H, Sarıoğlu N, Şenel MY, Erel F. Prognostic significance of HALP score in İdiopathic Pulmonary Fibrosis-related mortality. Sarcoidosis Vasculitis Diffuse Lung Dis. 2025;42(2):16003.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLi Q, Chen M, Zhao H, Zeng J. The prognostic and clinicopathological value of HALP score in non-small cell lung cancer. Front Immunol. 2025;16:1576326.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLin L, Huang H, Wu M, Chen F, Li C. The modified HALP score is associated with short-term mortality in critically ill patients with sepsis\u0026ndash;A cohort study. J Infect Developing Ctries. 2025;19(06):924\u0026ndash;33.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYokoji K, Gigu\u0026egrave;re K, Malag\u0026oacute;n T, R\u0026ouml;nn MM, Mayaud P, Kelly H, Delany-Moretlwe S, Drolet M, Brisson M, Boily M-C. Association of naturally acquired type-specific HPV antibodies and subsequent HPV re-detection: systematic review and meta-analysis. Infect Agents Cancer. 2023;18(1):70.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCui M, Wu Y, Liu Z, Liu Y, Fan L. Advances in the interrelated nature of vaginal microecology, HPV infection, and cervical lesions. Front Cell Infect Microbiol. 2025;15:1608195.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNtuli L, Mtshali A, Mzobe G, Liebenberg LJ, Ngcapu S. Role of immunity and vaginal microbiome in clearance and persistence of human papillomavirus infection. Front Cell Infect Microbiol. 2022;12:927131.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePinto PP, Zanine RM. Diagnostic value of p16 and Ki-67 expression in cervical glandular intraepithelial disease: A review. Annals Diagn Pathol. 2023;62:152054.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eClarke MA, Cheung LC, Castle PE, Schiffman M, Tokugawa D, Poitras N, Lorey T, Kinney W, Wentzensen N. Five-year risk of cervical precancer following p16/Ki-67 dual-stain triage of HPV-positive women. JAMA Oncol. 2019;5(2):181\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. Cancer J Clin. 2018;68(6):394\u0026ndash;424.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-womens-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmwh","sideBox":"Learn more about [BMC Women's Health](http://bmcwomenshealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmwh/default.aspx","title":"BMC Women's Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Human papillomavirus, HPV persistence, HALP score, Prognostic Nutritional Index, cervical cancer, prognostic biomarkers","lastPublishedDoi":"10.21203/rs.3.rs-7328319/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7328319/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAim: Persistent high-risk human papillomavirus (HPV) infection is the primary etiological factor in cervical cancer, with HPV16 and HPV18 posing the greatest oncogenic risk. Although systemic inflammation and nutritional indices such as the Hemoglobin, Albumin, Lymphocyte, and Platelet (HALP) score and Prognostic Nutritional Index (PNI) have prognostic value in various malignancies, their role in predicting HPV persistence remains unclear. This study aimed to evaluate the predictive value of HALP and PNI scores for one-year HPV persistence.\u003c/p\u003e\n\u003cp\u003eMethods: This retrospective study included 470 HPV-positive women aged 31–67 years, followed for at least one year between January 2021 and March 2025. Participants were divided into Group N (HPV clearance, n=271) and Group P (HPV persistence, n=199) based on one-year HPV results. Baseline demographic, clinical, histopathological, and laboratory data were recorded. HALP and PNI scores were calculated from hemoglobin, albumin, lymphocyte, and platelet counts. Group comparisons were performed using appropriate statistical tests, and predictive performance was assessed via receiver operating characteristic (ROC) analysis.\u003c/p\u003e\n\u003cp\u003eResults: There were no significant differences between groups in age, marital status, smoking, contraceptive use, parity, delivery mode, or chronic diseases. HPV16 (44.7%) and HPV18 (27.1%) positivity were significantly higher in the persistence group (p\u0026lt;0.001 and p=0.0006, respectively). Histopathological findings and p16/Ki-67 expression did not differ significantly. Post-diagnosis HPV vaccination did not affect clearance rates (p=0.604). Median HALP scores were 49.11 (IQR 35.87–60.42) in Group N and 46.97 (IQR 35.49–59.23) in Group P (p=0.361). Median PNI scores were 55.30 (IQR 51.40–58.40) and 55.00 (IQR 51.10–58.20), respectively (p=0.637). ROC analysis indicated poor predictive performance (AUC=0.531 for HALP; AUC=0.516 for PNI).\u003c/p\u003e\n\u003cp\u003eConclusions: HALP and PNI scores were not predictive of one-year HPV persistence, indicating limited influence of systemic inflammation and nutritional status on viral clearance in localized cervical HPV infections. HPV16 and HPV18 positivity was strongly associated with persistence, supporting their known immune evasion mechanisms. These findings highlight the need for prognostic markers targeting local mucosal immune responses to improve risk stratification and management of HPV-related disease.\u003c/p\u003e","manuscriptTitle":"Evaluation of Systemic Inflammation- and Nutrition-Based Indices in the Prediction of HPV Persistence","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-09 11:54:33","doi":"10.21203/rs.3.rs-7328319/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-18T05:52:24+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-18T03:52:26+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-17T23:06:41+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-14T12:48:36+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-11T11:13:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"63464880880141510283805452144602624416","date":"2025-09-08T20:14:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"71672076883622767267134473019320179990","date":"2025-09-04T06:55:28+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-03T17:58:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"79872518982704319030715073424523511465","date":"2025-09-02T13:20:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"288623763333061802448627020783240747285","date":"2025-09-02T11:23:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"72390151870797579837053525881711510685","date":"2025-09-02T10:07:39+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-02T06:50:52+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-08-13T13:28:39+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-12T23:49:12+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-12T23:48:39+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Women's Health","date":"2025-08-08T14:29:15+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-womens-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmwh","sideBox":"Learn more about [BMC Women's Health](http://bmcwomenshealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmwh/default.aspx","title":"BMC Women's Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8cd0fe41-9f6a-4a65-ba22-3486a030c5d9","owner":[],"postedDate":"September 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-22T16:02:05+00:00","versionOfRecord":{"articleIdentity":"rs-7328319","link":"https://doi.org/10.1186/s12905-025-04147-7","journal":{"identity":"bmc-womens-health","isVorOnly":false,"title":"BMC Women's Health"},"publishedOn":"2025-12-17 15:57:18","publishedOnDateReadable":"December 17th, 2025"},"versionCreatedAt":"2025-09-09 11:54:33","video":"","vorDoi":"10.1186/s12905-025-04147-7","vorDoiUrl":"https://doi.org/10.1186/s12905-025-04147-7","workflowStages":[]},"version":"v1","identity":"rs-7328319","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7328319","identity":"rs-7328319","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}