The incidence of CIN2 is high, with nearly half the number of CIN2 cases resolving within 2 years and less than 1/5 of the number progressing [18]. Additionally, some localized CIN2 lesions can be completely removed by biopsy during colposcopy. the use of traditional treatment methods often leads to postoperative downgrading, causing previously negative-tested patients to undergo invasive treatments, causing physical or psychological trauma and potentially excessive treatment [19].

Currently, there is limited research on post-biopsy pathological downgrading in patients with CIN2. Our study collected clinical information, LBC, HPV, and colposcopy findings, such as lesion area and acetic acid changes to establish a predictive model for post-biopsy pathological downgrading in patients with CIN2. Subsequently, single-factor logistic regression, LASSO regression, and multi-factor logistic regression were employed to identify five factors linked to CIN2 colposcopy post-biopsy downgrading, and then a prediction score model was constructed. The factors of the prediction scoring model were age at first intercourse, TCT, HPV, lesion area observed from colposcopy, and acetic acid changes. The prediction scoring model was internally validated and the results reveal that the model had good discriminative ability and calibration.

Several studies indicate that the safe age range for conservative treatment of CIN2 is < 25 years old [5, 20]. Among them, the meta-analysis by Zhang et al. of 1,481 female patients who underwent conservative treatment of CIN2 + for 15 months demonstrated a significantly negative correlation of age with regression [21]. Boulch observed 2,408 women with cervical cytological abnormalities for 24 months and reported that older women had longer-lasting prevalence of HPV infections (P = 0.008), but did not identify any correlation between new HPV infections and age [22]. However, Mancebo et al. studied CIN2 patients and found no relationship between the safety of conservative CIN2 treatment and age at diagnosis [23]. Our study also did not find any statistically significant difference in age and post-operative pathological upgrade or downgrade in patients with CIN2 who underwent LEEP or conization. Several cross-sectional studies have indicated that an early age of sexual debut is a confounding risk for HPV infection [24, 25]. Our study also reveals that a larger age of first intercourse was associated with post-operative pathological downgrading in patients with CIN2 who underwent LEEP or conization.

TCT and HPV are routine screening processes for cervical cancer and are often employed as predictive factors for cervical lesion progression. The global cytological HSIL positive predictive value for diagnosing CIN2 + is 77.5% [26]. Sedeno et al. analyzed 143 patients with low-grade squamous intraepithelial lesions (LSIL) and found that HPV16 LSIL is more likely to progress to CIN2 + and that HPV genotyping is a risk for patients with ASC-US or LSIL cytology [27]. Prior cytological examination showed HSIL as an independent risk factor for progression in CIN2 + women, and cytological examination results are helpful in more effective and personalized management of CIN2 [28, 29]. HPV16 and 18 are factors affecting post-operative pathological downgrading in LEEP or conization [30,31,32]. Persistent HPV16 infection is significantly more related to recurrence. Accordingly, CIN2 + caused by HPV16-positive infections is less likely to resolve than those due to other high-risk HPV or HPV16-negative CIN2 + cases. Other studies have further shown that compared to HPV16/18, the third most common genotype may be HPV58. HPV58 is 12.5% at 4–6 months after conization, but 0% at 8–12 months post-conization, indicating that HPV58 is not necessarily cleared and that the HPV58 clearance rate of may be just as ineffective as that of HPV16 [33,34,35]. Similarly, our study also reports that cytology (P < 0.0001) and HPV genotyping (P = 0.0121) are independent factors affecting post-operative pathological downgrading in CIN2 patients who underwent LEEP or conization.

Colposcopy is an important diagnostic approach for evaluating cervical lesions and performing biopsies following abnormal cytology and HPV genotyping [36, 37]. The lesion area and acetic acid epithelium under colposcopy are the primary colposcopy indicators for evaluating cervical lesions [38, 39]. Although acetic acid epithelium may not be identical to tumor tissue, nearly all cervical lesions exhibit variable transient and opaque white areas after the application of 3–5% acetic acid. Therefore, lesion area and the thickness of acetic acid epithelium under colposcopy may help in predicting the severity of cervical lesions. However, because of the subjectivity of the examination, the specificity of the colposcopy examination depends mainly on the experience and professional knowledge of the physician performing colposcopy. Our study shows that lesion area (P < 0.0001) and the thickness of acetic acid epithelium (P = 0.061) under colposcopy were critical factors affecting the post-operative pathological downgrade or upgrade in patients with CIN2.

Cervical cancer screening strategies need to consider overall costs, benefits, and cost-effectiveness [40]. According to estimates from the World Health Organization (WHO), between 1 and 2% of women are diagnosed with CIN2 + each year. In the United States, the incidence rate of CIN2/3 ranges from 120 to 160 cases per 100,000 women, while South Korea reports an incidence rate of CIN3 at 39.8 per 100,000. In China, the prevalence of histologically confirmed CIN2 + stands at 3%, with significantly higher rates observed in rural areas compared to urban centers; this figure also exceeds the prevalence seen in other Asian countries. The elevated incidence of CIN2 + clearly positions it as a critical public health concern, necessitating substantial resources for screening, diagnosis, and treatment. There is an urgent need to develop a predictive model for cervical lesions that is tailored for low- and middle-income countries. Our regression prediction model for patients with CIN2 incorporates several key factors, including TCT results, HPV infection types, the area of lesions detected through colposcopy, and the thickness of acetowhitening. These parameters can be obtained via cytology, HPV typing, and colposcopy, eliminating the requirement for additional tests such as immunohistochemistry, methylation analysis, or DNA ploidy analysis. This approach significantly reduces the economic burden on both patients and society. Moreover, by leveraging information technology, our disease prediction model can be effectively deployed in resource-limited settings. Primary healthcare providers can enter patient data into the model to estimate the likelihood of CIN2 regression. Low- and middle-income countries currently bear a substantial burden of cervical lesions. Our CIN2 prediction model, by avoiding the need for extra testing, offers a reliable means to assess the regression probability of CIN2 patients and can enhance the accuracy of treatment planning. This will ultimately contribute to reducing the incidence and mortality associated with cervical lesions.

This study followed the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis statement recommendations and used internal validation methods in calculating the C-index, time-dependent AUC, and calibration curves [41]. Overall, the prediction scoring model proposed by us may facilitate objective prediction of pathologic regression in patients with CIN2 and identify patients with CIN2 suitable for conservative treatment more conveniently, objectively, and practically in a clinical setting.

Nonetheless, despite the good performance of the prediction scoring model, this study had some limitations. The research design excluded patients with blood and digestive system diseases, immunocompromised patients, cervical gland lesions, etc. The sample size and follow-up time need to be increased to study the predictive value of the model in other CIN2 women. At the same time, further multi-center external validation will be carried out to explore the prediction model for predicting the regression of CIN2 patients.