TS Triage of HR-HPV Positive Population and Its Accuracy Study

Using cervical biopsy pathology as the gold standard, the study participants were stratified into 6 detailed subgroups based on HR-HPV genotype (HPV 16/18 and other 12 genotypes) and viral load gradients (low: 1.00-99.99; medium: 100-999.99; high: ≥1000.00) to form six detailed subgroups. The percentage of TS-positive cases among pathologically confirmed patients was calculated for each subgroup to determine the differences in diagnostic sensitivity when using TS as a screening tool.

Using the pathological diagnosis of cervical biopsy as the gold standard, the study subjects were stratified into 6 detailed subgroups based on HR-HPV genotype (HPV 16/18 and other 12 genotypes) and viral load gradients (low: 1.00-99.99; medium: 100-999.99; high: ≥1000.00) to form six detailed subgroups. The percentage of TS-negative cases among pathologically negative (non-lesional) patients was calculated for each subgroup to clarify the differences in clinical efficacy of the test as a triage tool in excluding non-lesional individuals and reducing unnecessary referral rates.

Using cervical biopsy pathology as the gold standard, the study participants were stratified into 6 detailed subgroups based on HR-HPV genotype (HPV 16/18 and other 12 genotypes) and viral load gradients (low: 1.00-99.99; medium: 100-999.99; high: ≥1000.00) to form six detailed subgroups. The percentage of TS-positive subjects in each subgroup who were pathologically confirmed to have lesions was calculated to assess the predictive ability of TS-positive results for cervical high-grade lesions and their clinical diagnostic value across different viral load levels.

Using cervical biopsy pathology as the gold standard, the study participants were stratified into 6 detailed subgroups based on HR-HPV genotype (HPV 16/18 and other 12 genotypes) and viral load gradients (low: 1.00-99.99; medium: 100-999.99; high: ≥1000.00) to form six detailed subgroups. The percentage of subjects with a normal/non-lesional pathological diagnosis among those with a negative TS test result was calculated for each subgroup to assess the reliability of TS-negative results in ruling out cervical lesions and to determine the safety of using TS as a triage tool at different viral load levels.

Using the pathological diagnosis of cervical biopsy as the gold standard, the study subjects were stratified into 6 detailed subgroups based on HR-HPV genotyping (HPV types 16/18 and other 12 types) and viral load gradients (low: 1.00-99.99; medium: 100-999.99; high: ≥1000.00) to form six detailed subgroups. By plotting receiver operating characteristic (ROC) curves and calculating the area under the curve (AUC), we comprehensively evaluated the overall diagnostic performance of TS in distinguishing between women with and without cervical lesions across different viral load levels. The closer the AUC value is to 1.0, the higher the accuracy of TS in classifying patients within that subgroup.

This study used pathological diagnosis based on cervical biopsy as the gold standard. Patients with positive TS test results but pathological diagnoses of normal or inflammation were defined as the TS false-positive group, while the TS true-positive group-in which TS and pathological results were consistent-served as the control group. Univariate and multivariate logistic regression analyses were performed on the two groups, examining factors such as age, cervical conditions (e.g., columnar epithelium ectopia, hypertrophy, polyps), history of cervical conization, and vaginal microbiome (various types of vaginal inflammation and pathogen infections), with the aim of identifying independent risk factors contributing to false-positive interference in TS results.

This study used the pathological diagnosis of cervical biopsy as the gold standard, defining patients with negative TS test results but a pathological diagnosis of lesions as the TS false-negative group, and using the TS true-negative group-in which TS and pathological results were consistent-as the control group. Through univariate and multivariate logistic regression analyses of indicators such as age, cervical anatomical status, and vaginal microbiome composition in both patient groups, the study aims to identify independent risk factors leading to TS missed diagnosis (false negatives) and provide clinical evidence to optimize screening strategies.

This indicator uses the pathological diagnoses from the second and third cervical biopsies during the 1-year follow-up period as the gold standard. For the specific population of patients who were "TS-positive but biopsy-negative" at the initial visit, it calculates the percentage of patients in this group who tested positive on subsequent TS screening during the follow-up period out of the total number of patients in this group who were ultimately pathologically confirmed to have lesions. This indicator is designed to evaluate the ability of TS to detect missed diagnoses at the initial visit, occult lesions, or newly developed lesions during long-term monitoring, to clarify its safety as a follow-up management tool, and to prevent the missed diagnosis of high-grade lesions.

This indicator uses the pathological diagnoses from the second and third cervical biopsies during a 1-year follow-up period as the gold standard. For a specific subgroup of patients who were "TS-positive but biopsy-negative" at their initial visit, it calculates the percentage of patients in this subgroup who maintained a consistently negative TS result during follow-up, relative to the total number of patients in this subgroup who ultimately maintained a normal or inflammatory pathological diagnosis. This indicator aims to evaluate the ability of TS to rule out transient risks and identify non-lesional cases, thereby demonstrating its clinical efficacy in reducing unnecessary repeat biopsies and optimizing the allocation of medical resources during the follow-up process.

This indicator uses the pathological diagnoses from the second and third cervical biopsies during the 1-year follow-up period as the gold standard. For the specific subgroup of patients who were "TS-positive but biopsy-negative" at the initial visit, it calculates the percentage of patients among all those with positive TS results during follow-up who were ultimately pathologically confirmed to have lesions. This indicator aims to evaluate the predictive value of TS "false-positive" results in identifying actual lesions during follow-up, thereby providing data to support clinical decisions regarding the timing of intervention.

This indicator uses the pathological diagnoses from the second and third cervical biopsies during the 1-year follow-up period as the gold standard. For the specific subgroup of patients who were "TS-positive but biopsy-negative" at the initial visit, it calculates the percentage of patients who maintained a normal/negative pathological result throughout the follow-up period among those with negative TS results on all follow-up tests. This indicator is used to evaluate the safety of TS-negative results in follow-up management, providing a basis for using it as a decision-making tool to extend follow-up intervals and reduce monitoring frequency.

This metric uses the pathological diagnoses from the second and third cervical biopsies during the 1-year follow-up period as the gold standard. For the specific subgroup of patients who were "TS-positive but biopsy-negative" at the initial visit, a ROC curve is plotted and the area under the curve (AUC) is calculated by integrating dynamic testing data collected over the 1-year follow-up period. This indicator aims to comprehensively evaluate the overall predictive accuracy of TS regarding long-term disease outcomes in this population and to compare the monitoring efficacy of TS alone versus TS combined with HPV testing.