Several studies have explored the correlation between HPV genotypes, viral load, and different grades of cervical lesions; however, further prospective research is needed to validate these findings. Recently, Professor Lina Zhang and her research team from Changzhou Maternal and Child Health Care Hospital published a study titled “Human Papillomavirus Genotyping and Viral Load as a Predictor of Cervical Lesions: A Prospective Study” in the Journal of Medical Virology (Impact Factor: 6.8). This prospective study aims to examine the impact of changes in viral load on the occurrence of cervical lesions and to evaluate viral load as a biomarker for predicting cervical lesions and triaging HPV-positive patients.

Conclusion

It can be concluded that high viral load persistent infection is related to cervical lesions. HPV genotype and viral load may be able to predict cervical lesions progress. The application of HPV viral load to the first screening of cervical cancer can better predict and identify cervical lesions.

Methods

From September 2022 to August 2023, women who visited the cervical disease diagnosis and treatment center at Changzhou Maternal and Child Health Hospital for their first cervical cancer screening were included in the study. Follow-up was conducted by the research team 6 months later. All patients in the cohort (N = 1150) were notified to attend follow-up visits. This resulted in 1012 follow-ups being successfully completed. During the follow-up, the subjects underwent HPV quantitative typing tests. If the virus was cleared, colposcopy was deemed unnecessary. However, if the HPV quantitative typing test was positive, colposcopy was required. If colposcopy results indicated CIN2+ lesions, appropriate treatment was administered.

Figure 1 Study flowchart.

Results

The baseline cohort included a total of 1150 patients, with 816 (71.0%) single-infected and 334 (29.0%) multiple-infected. The participants had a median age of 40 years (range, 33–48), with those whose HPV infection had cleared being younger than those whose HPV infection had persisted (p < 0.001). The HPV quantitative typing results showed that 1030 (89.6%) women had high-risk HPV infection, 236 (20.5%) had medium- and low-risk HPV infection, 597 (51.9%) were infected with α-9 HPV, 249 (21.7%) had HPV16 infection, and 264 (23.0%) had HPV52 infection. Only 95 (8.3%) women were infected with HPV18. At baseline, the average viral load for different HPV types was 4.30 ± 1.58 (HPV16), 3.63 ± 1.40 (HPV18), 4.15 ± 1.19 (HPV52), 4.25 ± 1.40 (α-9 HPV), 4.26 ± 1.48 (high-risk HPV), and 4.19 ± 1.66 (medium- and low-risk HPV). Follow-up results showed that the virus was cleared in 293 cases (29.0%). The average viral load of each HPV genotype during the follow-up period was slightly higher than that at baseline, but only the change in high-risk HPV (HR-HPV) viral load was statistically significant (p = 0.024). Pathological findings included 471 cases of inflammation, 237 cases of LSIL, and 14 cases of HSIL.

Compared with the baseline, 293 individuals experienced HPV virus clearance, 469 individuals exhibited persistent HPV infection without cervical lesions, and 250 individuals had persistent HPV infection with low-or high-grade lesions. These patients were categorized into the virus clearance group, maintenance group, and progression group. The baseline viral load among the three groups exhibited an increasing trend across different HPV genotypes. Significant statistical differences (p < 0.001) were observed among the virus clearance, maintenance, and progression groups for 21 HPV types, medium- and low-risk HPV, high-risk HPV, HPV16, and α-9 HPV. However, for HPV52, no significant difference in viral load was detected between the virus clearance and maintenance groups. In contrast, the viral load in the progression group was significantly higher than that in both the virus clearance and maintenance groups (p < 0.001) (Figure 2).

Figure 2 Differences in baseline viral load of different outcomes during the follow-up. (A) 21 HPV types; (B) Alpha 9 group; (C) High-risk HPV; (D) Medium/Low-risk HPV; (E) HPV16; (F) HPV52.

Table 1 Correlation between viral load and cervical lesions in follow-up.

The study employed a one-to-one self-pairing method to compare changes in viral load between baseline and follow-up. Among women diagnosed with CIN during follow-up, a significant increase in viral load was observed from baseline to follow-up. The specific HPV types showing this increase were 21 HPV types (p=0.001), α-9 HPV (p=0.043), HR-HPV (p=0.011), and M/LR-HPV (p=0.032). For patients who remained lesion-free during follow-up, the viral load decreased from baseline to follow-up. A statistically significant reduction in viral load was observed for high-risk HPV and α-9 HPV (p=0.047, p=0.028). However, the reduction in viral load for 21 HPV types did not reach statistical significance (p=0.13) (Table 2). This indicates that the progression from lesion-free status to cervical lesions is accompanied by an increase in HPV viral load, consistent with previous research findings. Conversely, when HPV infection persists without cervical lesions, the viral load decreases, which may be influenced by the body's immune response.

Table 2 Changes in viral load from baseline to follow-up.

Baseline and follow-up HPV viral loads were used to predict and diagnose the progression of cervical lesions (Figure 3). According to the ROC curve analysis, the optimal cut-off values for the viral loads of 21 HPV types at baseline and follow-up were 5.01 (Se=55.38%, Sp=73.32%) and 4.90 (Se=68.80%, Sp=69.08%), respectively. For high-risk HPV viral loads, the optimal cut-off values at baseline and follow-up were 4.56 (Se=71.25%, Sp=62.78%) and 5.04 (Se=62.78%, Sp=75.98%), respectively. The optimal cut-off values for α-9 HPV's viral loads were 4.16 (Se=80.40%, Sp=58.90%) and 4.87 (Se=66.67%, Sp=75.13%) at baseline and follow-up, respectively. The appropriate cut-off values for M/LR-HPV viral loads were 4.46 (Se=72.41%, Sp=75.71%) and 5.33 (Se=73.08%, Sp=83.93%) at baseline and follow-up, respectively. Similarly, the optimal cut-off values for HPV 16 viral loads were 4.81 (Se=67.74%, Sp=69.31%) and 3.91 (Se=78.38%, Sp=56.25%), while for HPV 52 viral loads, they were 4.18 (Se=82.35%, Sp=63.39%) and 4.87 (Se=72.97%, Sp=80.00%) (Table 3).

Figure 3 The performance and cut-off values of viral loads in predicting CIN. (A) 21 HPV types; (B) Alpha 9 group; (C) High-risk HPV; (D) Medium/Low-risk HPV; (E) HPV16; (F) HPV52.

Table 3 Screening efficiency of different types of viral load.

Reference：Zhou Y, Liu J, Chen S, et al. Human Papillomavirus Genotyping and Viral Load as a Predictor of Cervical Lesions: A Prospective Study[J]. Journal of Medical Virology, 2025, 97(6): e70386.