Triage of women with positive HPV: comparing DNA ploidy analysis with HPV 16/18 genotyping and cervical cytology

Introduction

Cervical cancer remains a significant public health concern globally as it is the fourth most common cancer affecting women worldwide after breast, colorectal, and lung cancers. It accounts for approximately 660,000 new cases and 350,000 deaths annually (1). It arises from the cervix and is primarily driven by persistent infection with high-risk human papillomavirus (HPV). Early detection through effective screening programs, such as those utilizing HPV testing to detect oncogenic HPV DNA, has proven crucial for reducing both the incidence and mortality of cervical cancer. In 2019, China reported 109,759 new cases, underscoring the widespread impact of the disease (2). The shift toward HPV testing has enhanced the precision of screening programs compared to cytology-based methods alone. This has been pivotal in identifying at-risk women earlier and more reliably, thereby allowing for timely interventions and management. Moreover, advances in HPV vaccination have begun to alter the landscape of cervical cancer incidence, promising a future decrease in its prevalence. Nonetheless, challenges remain, including the integration of these tools into coordinated screening efforts worldwide, particularly in regions where access to healthcare is limited and disease burden is the highest (3-5).

The risk of cervical cancer or precancerous lesions is closely associated with the type and duration of HPV infection. Persistent infection with high-risk HPV types is responsible for more than 99% of the cervical cancer cases. HPV 16/18 are of particular concern and account for more than 70% of all cervical cancer cases (6). Cervical cancer progression is characterized by a series of cellular and molecular alterations (7). Cervical cytology using the ThinPrep cytology test (TCT) aids in the collection of exfoliated cells from the cervix using a liquid-based method and an automated processing system, facilitating cytological examination to detect potential cancerous changes. Currently, the integrated use of HPV testing and the TCT constitutes the foundation of cervical cancer screening strategies (8).

The updated guidelines recommend that negative HPV screening results be followed up at intervals of 5 years, reflecting the low 5-year risk of cervical intraepithelial neoplasia (CIN) III+ for HPV-negative and co-screening-negative cases, which are recorded at 0.14% [95% confidence interval (CI), 0.13–0.15%] and 0.12% (95% CI, 0.12–0.13%), respectively (9). These risks are below the threshold of 0.15%. However, the primary challenge in cervical screening is not the risk of CIN III+ among women with a negative HPV DNA test but the test’s low specificity, which necessitates further triage. Current strategies, such as partial genotyping for HPV 16/18 and cytological triage for women with non-HPV 16/18 positive tests, are hampered by the limited sensitivity and specificity of genotyping and the subjective and error-prone nature of cytological assessments. Therefore, it is crucial to develop more accurate and reliable triage methods to effectively identify women at significant risk after a positive HPV DNA test, thereby enhancing the efficacy of cervical cancer screening programs.

At the molecular level, cervical carcinogenesis involves mutations in multiple genes, including the activation of oncogenes and the inactivation of tumor suppressor genes. Concurrently, alterations in the signaling pathways related to cell growth, apoptosis, and DNA damage repair disrupt the regulation of cell proliferation, facilitating the growth and survival of cancer cells. Quantitative DNA ploidy analysis, which detects abnormal DNA content in the nuclei of cervical epithelial cells, provides insight into the proliferative potential of tumor cells and has emerged as a valuable diagnostic tool for identifying cervical cancer and its precursors (10,11). Given the need for more objective biomarkers in the triage of women with a positive HPV test in primary screening, to better balance benefits and harms, this study aimed to evaluate the clinical utility of DNA ploidy analysis as a triage test for women with a positive HPV test in primary screening, comparing it to HPV 16/18 genotyping and TCT.

This study employed a retrospective cross-sectional design. We collected demographics, diagnoses, colposcopy and biopsy results, and other laboratory tests, including HPV, TCT, and DNA ploidy, which were performed as part of the cervical cancer or precancerous lesion screening program at Ruijin Hospital. The data collection period spanned from November 2021 to February 2022, as detailed in Table S1. Logistic regression was used to evaluate the association between screening tests and the detection rates of high-grade squamous intraepithelial lesions (HSIL) and cervical cancer, as confirmed using colposcopy and biopsy. We present this article in accordance with the TRIPOD reporting checklist (available at https://tcr.amegroups.com/article/view/10.21037/tcr-24-1455/rc).

Methods

This was a retrospective, cross-sectional study. Demographics, diagnosis, colposcopy, and other laboratory tests, including HPV, TCT, and DNA ploidy, which were used for cervical cancer or precancerous lesion screening of eligible women who visited Shanghai Ruijin Hospital between November 2021 and February 2022 for the cervical cancer screening program were collected (Table S1). The association between the screening tests and degree of cervical malignancy confirmed using colposcopy was evaluated using logistic regression. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). This retrospective study was exempt from review by the Ethics Committee of Ruijin Hospital because this type of study is a non-human subject research, and the need for informed consent was waived.

Participants

Women aged ≥18 years who had visited or were in the periodic follow-up of the Department of Gynecology of Shanghai Ruijin Hospital, China for a cervical cancer screening program between November 1, 2021 and February 28, 2022 were retrospectively identified from the in-house electronic medical record system in June 2024. All participants underwent human-performed HPV testing, cervical ThinPrep liquid-based cytology testing, and cervical DNA ploidy analysis during recruitment. Patients whose TCT results were reported using the Papanicolaou system, were diagnosed with intrauterine adhesions, had a history of cervical cancer, or had incomplete colposcopy information were excluded from the analysis (Figure 1). The degree of malignancy of the cervical epithelial cells was detected using colposcopy. Cervical biopsy was considered the gold standard method for all participants. Information recorded at the date of the hospital visit, such as demographics including age, smoking history, menopausal status, number of pregnancies, abortion information, delivery information, screening test results, and colposcopy or biopsy results, was collected (Table S2). To minimize systematic errors induced during testing, the same clinician was responsible for sample collection and the same technician was responsible for HPV, TCT, and DNA ploidy testing.

Figure 1 Flow chart of the screening process.

HPV testing

An endocervical brush was placed on the cervix and rotated 2–3 times to collect cervical tissue for HPV E6/E7 mRNA detection. The HPV test (Health Gene Technologies, Inc., Shanghai, China) utilizes multiplex polymerase chain reaction (PCR) and capillary electrophoresis to detect 25 different HPV types based on the length of specific amplification fragments. The high-risk HPV genotypes were 16, 18, 26, 31, 33, 35, 39, 45, 51, 52, 53, 56, 58, 59, 66, 68, 73, and 82. The low-risk HPV types were 6, 11, 42, 43, 44, 81, and 83. HPV 16/18 positivity was defined as the presence of 16 or 18 HPV genotypes.

TCT

Participant’s endocervical brush sample was rinsed in a vial filled with 20 mL of PreservCyt^® Solution (PreservCyt). The ThinPrep sample vials were processed using a ThinPrep 5000 Processor (Hologic, Inc., Shanghai, China). The cells were collected from the exterior surface of the membrane and transferred to a thin cell smear with a diameter of 2 cm. Smears were fixed with 95% alcohol, stained with xylene, and sealed. All smears were reviewed by a pathologist according to the Bethesda system. TCT diagnoses were divided into negative for intraepithelial lesions or malignancy (NILM), atypical squamous cells of undetermined significance (ASCUS), low-grade squamous intraepithelial lesions (LSIL), HSIL, and squamous cell carcinomas (SCC). The TCT-positive outcomes were defined as ASCUS, LSIL, HSIL, or SCC.

Cervical DNA ploidy analysis

The specimens prepared through endocervical brushing were stained using a stoichiometric DNA staining method (Feulgen-Thionin) according to the method described by Feulgen. DNA image cytometry was performed using a DNA Ploidy Analysis System (Landing Medical Hi-Tech Co., Ltd., Shanghai, China) by measuring the nuclear characteristics and DNA distribution in all nucleated cells. The DNA ploidy result was expressed as a “c” value for chromosome. The DNA ploidy value of 2c was identical to that of normal diploid cells. Most studies have used 5c as the cut-off value to define aneuploidy. DNA ploidy positivity was defined as the presence of three or more cells with a DNA ploidy value greater than 5c.

Colposcope and pathological examination

Experienced gynecologists performed electronic colposcopy. The examinees were placed in the lithotomy position. After cervical exposure using a vaginal speculum, cervical secretions were removed using dry cotton balls for preliminary observation. Subsequently, 3% acetic acid was applied to the cervix and colposcopic images were carefully observed, recorded, and archived. In cases in which abnormalities were suspected, cervical biopsies were collected under colposcopic guidance and fixed in 1% formalin solution for subsequent histological examination.

Statistical analysis

Data were independently entered by two researchers (W.S. and H.L.) and cross-checked to avoid information bias. The sample size was calculated by using the equation of N = Z_α/2 * P * (1 − P) / d². Z_α/2 indicates the Z score under the precise level of α/2. P values indicate the sensitivity or specificity of the screening tools used in this study. d indicates margin of error. In this study, 0.05 was used for α and d. As the sensitivity and specificity of the screening tool may vary in different populations, 0.8 and 0.5 were used as P to obtain a range of target sample size, which were from 246 to 385. Continuous variables were presented as the mean [standard deviation (SD)], whereas count or categorical variables were presented as numbers (%). The crude and adjusted odds ratio (OR) and 95% confidence interval (CI) were calculated using univariate and multivariate logistic regression models. Missing value was presented as “unknown” in Table 1 and considered as one level for certain variable in the regression model. Age, number of induced abortions, menopausal status, and squamocolumnar junction (SCJ) visibility might be related to cervical malignant lesions and were adjusted for in the regression model. All data were analyzed using the R statistics package (R version 4.4.1; R: The R Project for Statistical Computing, Vienna, Austria).

Results

Overall description

Between November 1, 2021, and February 28, 2022, 388 women visited the Department of Gynecology at Ruijin Hospital for screening. After excluding 16 women with non-standard TCT results, 3 with intrauterine adhesions, 19 with a history of cervical cancer, and 15 with incomplete colposcopy or screening test information, 335 women were included in the analysis. Their mean age was 43.5 years (SD 12.3). Of these patients, 48 (14.3%) were diagnosed with cervical cancer or HSIL on biopsy (Table 1). Among the participants, 20 (6%) had a history of smoking, 79 (23.6%) were postmenopausal, and the majority (205, 61.2%) had been pregnant 1–3 times. Miscarriages occurred in 171 (67.6%) of those who had been pregnant, predominantly through induced abortion (154, 90.0%). High-risk HPV 16/18 was found in 85 (25.4%) participants, whereas 303 (90.4%) tested positive for other high-risk HPV types with some coinfection. DNA ploidy testing revealed abnormalities in 66 patients (19.7%). The TCT results showed that 85.7% of the participants had NILM, 22 (6.5%) had LSIL, and only one (0.3%) had HSIL.

Classification model (Table 2)

HPV 16/18 infection, TCT, and DNA ploidy tests are critical for predicting cervical cancer and precancerous lesions. Individually, these predictors showed varying sensitivities and specificities (Table 2 and Figure 2). HPV 16/18 and TCT demonstrated low sensitivities of 35.4% and 29.2% but relatively high specificities of 76.1% and 88.2%, respectively. The positive predictive values (PPVs) were modest, at 20.0% for HPV 16/18 and 29.2% for TCT, whereas the negative predictive values (NPVs) were close to 90%. Their classification accuracies were 70.3% and 79.7%, respectively, with Youden Indices ranging from 11% to 18%. In contrast, the DNA ploidy test exhibited high sensitivity and specificity, exceeding 90%, with PPV and NPV of 68.2% and 98.9%, respectively, resulting in a predictive accuracy of 92.8% and a Youden Index of 86.4%.

Figure 2 ROC curves of the single predictor. Blue line indicates participants with positive HPV subtype 16/18 detection. Green line indicates participants with positive TCT results (not NILM). Orange line indicates participants with DNA ploidy analysis over 5c. AUC, area under the curve; HPV, human papillomavirus; NILM, negative for intraepithelial lesions or malignancy; ROC, receiver operating characteristic; TCT, ThinPrep cytology test.

When combining HPV 16/18 and TCT, the sensitivity increased to 60.4%, but the specificity decreased to 65.7%. The overall accuracy of the combined model was only 65.0%, with a Youden index of 13.7%.

We also evaluated the performance of combinations involving single predictors, HPV 16/18 and TCT, using the better-performing DNA ploidy test (Table 2, Figure 3). The combined DNA ploidy and TCT model showed good sensitivity [93.8% (95% CI: 86.9–100%)] and specificity [82.6% (95% CI: 78.2–87.0%)] but did not perform better than DNA ploidy alone. Similarly, the DNA ploidy and HPV 16/18 models, as well as the tri-combination with all three predictors, yielded high sensitivity [97.9% (95% CI: 93.9–100%)] but low specificity, particularly in the three-way combination [62.2% (95% CI: 56.6–67.9%)] (Table 2, Figure 4). When applying DNA ploidy alone to classify cervical cancer or precancerous lesions in participants negative for HPV 16/18 and TCT (Table 2, Figure 4), both sensitivity and specificity reached 94.7%, with an accuracy and Youden index of 94.7% and 89.4%, respectively. This approach identified 18 additional cases (8.7% of 207) that were initially negative for HPV 16/18 and TCT and were subsequently confirmed by pathology.

Figure 3 ROC curves of two combined predictor. Blue line indicates participants with either positive results in HPV subtype 16/18 detection or TCT testing. Green line indicates participants with either positive results in HPV subtype 16/18 detection or DNA ploidy analysis over 5c. Orange line indicates participants with positive results in TCT testing and DNA ploidy analysis over 5c. AUC, area under the curve; HPV, human papillomavirus; ROC, receiver operating characteristic; TCT, ThinPrep cytology test.

Figure 4 ROC curves of three combined predictor. Light blue line indicates the performance of predicting value if one of the three test obtained positive result. The dark blue line indicates DNA ploidy analysis performance when negative results shown in HPV 16/18 and TCT. AUC, area under the curve; HPV, human papillomavirus; ROC, receiver operating characteristic; TCT, ThinPrep cytology test.

Risk factors of cervical cancer or precancerous lesions

Univariate analysis was initially used to estimate the crude OR for key predictive factors among the 48 HSIL or cervical cancer cases. HPV 16/18 did not show a statistically significant association with increased risk (OR: 1.75; 95% CI: 0.90–3.32), unlike the other factors where DNA ploidy demonstrated a strong association (OR: 190.0; 95% CI: 62.9–830.6) and TCT showed moderate significance (OR: 3.06; 95% CI: 1.46–6.21). Multivariable logistic regression adjusted for age, number of induced abortions, menstrual status, and SCJ results indicated that the influence of DNA ploidy remained robust (OR: 290.40; 95% CI: 7.89–1913.70). However, the association between HPV 16/18 and TCT was not significant in this adjusted model (HPV: OR, 1.87; 95% CI: 0.59–6.15; TCT: OR, 1.65; 95% CI: 0.49–5.82) (Table 3).

Discussion

The World Health Organization (WHO) 2021 guidelines recommend HPV-DNA detection as the primary screening method for cervical cancer prevention (12). In this study, the detection rate for high-risk HPV 16/18 subtypes was 25.5%, which is significantly higher than the 5–15% typically reported for first-time screening (13). This discrepancy may be attributed to the nature of our study population, which primarily consisted of symptomatic individuals rather than healthy participants who are routinely screened based on age. In our study, the sensitivity and specificity of HPV-16/18 testing were 35.4% and 76.1%, respectively. These figures are lower than those reported in other studies but may more accurately reflect real-world performance (14-16). A notable strength of our study is the consistency in sample collection, which was performed by the same clinician to minimize biases associated with sample preparation across the three tests.

Typically, individuals without HPV 16/18 infection but with a high risk of HPV infection, indicated as HPV subtypes 26, 31, 33, 35, 39, 45, 51, 52, 53, 56, 58, 59, 66, 68, 73, and 82, are recommended for validation by cytological testing such as TCT. The specificity of the TCT results in our study was 88.2%, which is consistent with other studies, ranging from 86–100% (17). Owing to limited reproducibility and sensitivity, the false-NPV of the TCT is quite high, mostly over 50% (18-21). In addition, low levels of infection may result in false-negative results for HPV detection. Taken together, under current clinical practice, individuals with negative results for HPV 16/18 and TCT are recommended for subsequent follow-up. Therefore, the false-negative portion of individuals misses the optimal screening and treatment period.

In this study, we evaluated DNA ploidy as a triage test for women with positive HPV DNA test results and compared it with partial HPV 16/18 genotyping and TCT triage. DNA ploidy demonstrated a higher sensitivity and specificity for HSIL+ than those demonstrated by the combination of HPV 16/18 and TCT (93.8% vs. 60.4% and 92.7% vs. 65.7%, respectively). Additionally, its lower positivity rate (19.7% vs. 37.9%) suggests a reduced referral rate for colposcopy, which is highly advantageous in triage settings.

These findings may be linked to biological processes associated with HPV infection. Previous studies have indicated that abnormal DNA ploidy is observed in women with squamous intraepithelial lesions (SILs) infected with high-risk HPV types (22,23). The severity of SIL is positively correlated with the proportion of heteroploid cells. This correlation could stem from HPV DNA fragments integrating into the host’s nuclear DNA within cervical epithelial cells, leading to aberrant cell division processes, such as multipolar mitosis and unbalanced chromosome division. These processes result in changes in chromosome number and structure, an increase in nuclear area, and alterations in DNA content and ploidy status. Therefore, DNA ploidy analysis may serve as an effective triage method for women with positive primary HPV test results.

There are several limitations in this study. First, the sample size was modest, with only 335 women participating, including 43 who were diagnosed with HSIL or cervical cancer. Second, detecting post-infection DNA ploidy requires a certain period of persistent high-risk HPV infection before changes in host cells become detectable. All tests in this study were conducted within a brief 2-month period, thus the optimal timing for follow-up testing from HPV detection to DNA ploidy assessment remains unclear. Women with transient HPV infections may have biased the results. Owing to its cross-sectional retrospective design, future longitudinal multicenter studies are required to address this limitation. Third, the study participants were recruited from a single hospital, which may not adequately represent a broader population, thus limiting the generalizability of the findings. Finally, the limited number of covariates collected restricted our ability to explore potential subgroups that might respond differently to the screening tools. To address these limitations and validate the reliability of our findings, larger multicenter studies with long-term events are required.

Conclusions

This study demonstrated that DNA ploidy analysis offers superior specificity and sensitivity in the triage of women with a positive HPV test for detecting HSIL and cervical cancer, compared to triage using partial genotyping (HPV 16/18) and TCT. Notably, the DNA ploidy analysis revealed a lower positivity rate for triage than that of both HPV 16/18 and TCT. These findings suggest that DNA ploidy testing could serve as a more effective triage test than the currently recommended in the guidelines.

Acknowledgments

The authors thank all the participants of this study and their families, and also thank the entire project team that participated in this study.

Footnote

Reporting Checklist: The authors have completed the TRIPOD reporting checklist. Available at https://tcr.amegroups.com/article/view/10.21037/tcr-24-1455/rc

Data Sharing Statement: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-24-1455/dss

Peer Review File: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-24-1455/prf

Funding: This study was supported by Shanghai Science and Technology funding (No. 19411961000).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tcr.amegroups.com/article/view/10.21037/tcr-24-1455/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). This retrospective study was exempt from review by the Ethics Committee of Ruijin Hospital because this type of study is a non-human subject research, and the need for informed consent was waived.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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