Objective: The primary objective of this study was to compare the detection rate of high-risk human papillomavirus (HPV) infection between self-sampling to collect vaginal specimens and clinician sampling to collect cervical specimens, as well as the correlation between the two techniques. The secondary objective was to assess satisfaction with selfsampling for HPV testing. Methods: From October 2021 to September 2022, women positive for HPV 16/18 and other 12 high-risk HPV genotypes and cytological Ascus were enrolled. All participants were instructed on the method for self-collection of HPV samples. Self-collected vaginal samples and clinician-collected cervical samples were subjected to HPV DNA typing. Results: Paired self- and clinician-collected specimens were obtained from 104 women with positive HPV-positive results. The detection rate of high-risk HPV infection was comparable between the two techniques: 79/98 (80.6%) vs. 81/98 (82.7%) for the self-sampling and clinician-sampling techniques, respectively (McNemar’s test; P=0.774). The agreement in detecting HPV infection was substantial, with a kappa coefficient of 0.75. More than 90% of the participants rated self-collection as satisfactory to very satisfactory because of its convenience and safety. Regarding methods of further follow-up, 51% of the participants chose self-sampling, whereas the remaining participants preferred collection by clinicians. No intervention-related complications were observed. Conclusion The self-sampling technique for HPV testing was as effective as the clinician-sampling technique, and both techniques were substantially correlated in detecting high-risk HPV infection. The self-sampling method appears to be highly satisfactory and may provide better compliance for the detection of cervical HPV infection.

Objective: The primary objective of this study was to compare the detection rate of high-risk human papillomavirus (HPV) infection between self-sampling to collect vaginal specimens and clinician sampling to collect cervical specimens, as well as the correlation between the two techniques. The secondary objective was to assess satisfaction with selfsampling for HPV testing. Methods: From October 2021 to September 2022, women positive for HPV 16/18 and other 12 high-risk HPV genotypes and cytological Ascus were enrolled. All participants were instructed on the method for self-collection of HPV samples. Self-collected vaginal samples and clinician-collected cervical samples were subjected to HPV DNA typing. Results: Paired self- and clinician-collected specimens were obtained from 104 women with positive HPV-positive results. The detection rate of high-risk HPV infection was comparable between the two techniques: 79/98 (80.6%) vs. 81/98 (82.7%) for the self-sampling and clinician-sampling techniques, respectively (McNemar’s test; P=0.774). The agreement in detecting HPV infection was substantial, with a kappa coefficient of 0.75. More than 90% of the participants rated self-collection as satisfactory to very satisfactory because of its convenience and safety. Regarding methods of further follow-up, 51% of the participants chose self-sampling, whereas the remaining participants preferred collection by clinicians. No intervention-related complications were observed. Conclusion The self-sampling technique for HPV testing was as effective as the clinician-sampling technique, and both techniques were substantially correlated in detecting high-risk HPV infection. The self-sampling method appears to be highly satisfactory and may provide better compliance for the detection of cervical HPV infection.

Objective: The primary objective of this study was to compare the detection rate of high-risk human papillomavirus (HPV) infection between self-sampling to collect vaginal specimens and clinician sampling to collect cervical specimens, as well as the correlation between the two techniques. The secondary objective was to assess satisfaction with selfsampling for HPV testing. Methods: From October 2021 to September 2022, women positive for HPV 16/18 and other 12 high-risk HPV genotypes and cytological Ascus were enrolled. All participants were instructed on the method for self-collection of HPV samples. Self-collected vaginal samples and clinician-collected cervical samples were subjected to HPV DNA typing. Results: Paired self- and clinician-collected specimens were obtained from 104 women with positive HPV-positive results. The detection rate of high-risk HPV infection was comparable between the two techniques: 79/98 (80.6%) vs. 81/98 (82.7%) for the self-sampling and clinician-sampling techniques, respectively (McNemar’s test; P=0.774). The agreement in detecting HPV infection was substantial, with a kappa coefficient of 0.75. More than 90% of the participants rated self-collection as satisfactory to very satisfactory because of its convenience and safety. Regarding methods of further follow-up, 51% of the participants chose self-sampling, whereas the remaining participants preferred collection by clinicians. No intervention-related complications were observed. Conclusion The self-sampling technique for HPV testing was as effective as the clinician-sampling technique, and both techniques were substantially correlated in detecting high-risk HPV infection. The self-sampling method appears to be highly satisfactory and may provide better compliance for the detection of cervical HPV infection.

Objective: To develop a novel machine learning-based preoperative prediction model for pelvic lymph node metastasis (PLNM) in early-stage cervical cancer by combining the clinical findings and preoperative computerized tomography (CT) of the whole abdomen and pelvis. Methods: Patients diagnosed with International Federation of Gynecology and Obstetrics stage IA2-IIA1 squamous cell carcinoma, adenocarcinoma, and adenosquamous carcinoma of the cervix who had primary radical surgery with bilateral pelvic lymphadenectomy from January 1, 2003 to December 31, 2020, were included. Seven supervised machine learning algorithms, including logistic regression, random forest, support vector machine, adaptive boosting, gradient boosting, extreme gradient boosting, and category boosting, were used to evaluate the risk of PLNM. Results: PLNM was found in 199 (23.9%) of 832 patients included. Younger age, larger tumor size, higher stage, no prior conization, tumor appearance, adenosquamous histology, and vaginal metastasis as well as the CT findings of larger tumor size, parametrial metastasis, pelvic lymph node enlargement, and vaginal metastasis, were significantly associated with PLNM. The models’ predictive performance, including accuracy (89.1%–90.6%), area under the receiver operating characteristics curve (86.9%–91.0%), sensitivity (77.4%–82.4%), specificity (92.1%–94.3%), positive predictive value (77.0%–81.7%), and negative predictive value (93.0%–94.4%), appeared satisfactory and comparable among all the algorithms.After optimizing the model’s decision threshold to enhance the sensitivity to at least 95%, the ‘highly sensitive’ model was obtained with a 2.5%–4.4% false-negative rate of PLNM prediction. Conclusion We developed prediction models for PLNM in early-stage cervical cancer with promising prediction performance in our setting. Further external validation in other populations is needed with potential clinical applications.

Objective: To develop a novel machine learning-based preoperative prediction model for pelvic lymph node metastasis (PLNM) in early-stage cervical cancer by combining the clinical findings and preoperative computerized tomography (CT) of the whole abdomen and pelvis. Methods: Patients diagnosed with International Federation of Gynecology and Obstetrics stage IA2-IIA1 squamous cell carcinoma, adenocarcinoma, and adenosquamous carcinoma of the cervix who had primary radical surgery with bilateral pelvic lymphadenectomy from January 1, 2003 to December 31, 2020, were included. Seven supervised machine learning algorithms, including logistic regression, random forest, support vector machine, adaptive boosting, gradient boosting, extreme gradient boosting, and category boosting, were used to evaluate the risk of PLNM. Results: PLNM was found in 199 (23.9%) of 832 patients included. Younger age, larger tumor size, higher stage, no prior conization, tumor appearance, adenosquamous histology, and vaginal metastasis as well as the CT findings of larger tumor size, parametrial metastasis, pelvic lymph node enlargement, and vaginal metastasis, were significantly associated with PLNM. The models’ predictive performance, including accuracy (89.1%–90.6%), area under the receiver operating characteristics curve (86.9%–91.0%), sensitivity (77.4%–82.4%), specificity (92.1%–94.3%), positive predictive value (77.0%–81.7%), and negative predictive value (93.0%–94.4%), appeared satisfactory and comparable among all the algorithms.After optimizing the model’s decision threshold to enhance the sensitivity to at least 95%, the ‘highly sensitive’ model was obtained with a 2.5%–4.4% false-negative rate of PLNM prediction. Conclusion We developed prediction models for PLNM in early-stage cervical cancer with promising prediction performance in our setting. Further external validation in other populations is needed with potential clinical applications.

Objective: The primary objective of this study was to compare the detection rate of high-risk human papillomavirus (HPV) infection between self-sampling to collect vaginal specimens and clinician sampling to collect cervical specimens, as well as the correlation between the two techniques. The secondary objective was to assess satisfaction with selfsampling for HPV testing. Methods: From October 2021 to September 2022, women positive for HPV 16/18 and other 12 high-risk HPV genotypes and cytological Ascus were enrolled. All participants were instructed on the method for self-collection of HPV samples. Self-collected vaginal samples and clinician-collected cervical samples were subjected to HPV DNA typing. Results: Paired self- and clinician-collected specimens were obtained from 104 women with positive HPV-positive results. The detection rate of high-risk HPV infection was comparable between the two techniques: 79/98 (80.6%) vs. 81/98 (82.7%) for the self-sampling and clinician-sampling techniques, respectively (McNemar’s test; P=0.774). The agreement in detecting HPV infection was substantial, with a kappa coefficient of 0.75. More than 90% of the participants rated self-collection as satisfactory to very satisfactory because of its convenience and safety. Regarding methods of further follow-up, 51% of the participants chose self-sampling, whereas the remaining participants preferred collection by clinicians. No intervention-related complications were observed. Conclusion The self-sampling technique for HPV testing was as effective as the clinician-sampling technique, and both techniques were substantially correlated in detecting high-risk HPV infection. The self-sampling method appears to be highly satisfactory and may provide better compliance for the detection of cervical HPV infection.

Objective: To develop a novel machine learning-based preoperative prediction model for pelvic lymph node metastasis (PLNM) in early-stage cervical cancer by combining the clinical findings and preoperative computerized tomography (CT) of the whole abdomen and pelvis. Methods: Patients diagnosed with International Federation of Gynecology and Obstetrics stage IA2-IIA1 squamous cell carcinoma, adenocarcinoma, and adenosquamous carcinoma of the cervix who had primary radical surgery with bilateral pelvic lymphadenectomy from January 1, 2003 to December 31, 2020, were included. Seven supervised machine learning algorithms, including logistic regression, random forest, support vector machine, adaptive boosting, gradient boosting, extreme gradient boosting, and category boosting, were used to evaluate the risk of PLNM. Results: PLNM was found in 199 (23.9%) of 832 patients included. Younger age, larger tumor size, higher stage, no prior conization, tumor appearance, adenosquamous histology, and vaginal metastasis as well as the CT findings of larger tumor size, parametrial metastasis, pelvic lymph node enlargement, and vaginal metastasis, were significantly associated with PLNM. The models’ predictive performance, including accuracy (89.1%–90.6%), area under the receiver operating characteristics curve (86.9%–91.0%), sensitivity (77.4%–82.4%), specificity (92.1%–94.3%), positive predictive value (77.0%–81.7%), and negative predictive value (93.0%–94.4%), appeared satisfactory and comparable among all the algorithms.After optimizing the model’s decision threshold to enhance the sensitivity to at least 95%, the ‘highly sensitive’ model was obtained with a 2.5%–4.4% false-negative rate of PLNM prediction. Conclusion We developed prediction models for PLNM in early-stage cervical cancer with promising prediction performance in our setting. Further external validation in other populations is needed with potential clinical applications.

Objective: The primary objective of this study was to compare the detection rate of high-risk human papillomavirus (HPV) infection between self-sampling to collect vaginal specimens and clinician sampling to collect cervical specimens, as well as the correlation between the two techniques. The secondary objective was to assess satisfaction with selfsampling for HPV testing. Methods: From October 2021 to September 2022, women positive for HPV 16/18 and other 12 high-risk HPV genotypes and cytological Ascus were enrolled. All participants were instructed on the method for self-collection of HPV samples. Self-collected vaginal samples and clinician-collected cervical samples were subjected to HPV DNA typing. Results: Paired self- and clinician-collected specimens were obtained from 104 women with positive HPV-positive results. The detection rate of high-risk HPV infection was comparable between the two techniques: 79/98 (80.6%) vs. 81/98 (82.7%) for the self-sampling and clinician-sampling techniques, respectively (McNemar’s test; P=0.774). The agreement in detecting HPV infection was substantial, with a kappa coefficient of 0.75. More than 90% of the participants rated self-collection as satisfactory to very satisfactory because of its convenience and safety. Regarding methods of further follow-up, 51% of the participants chose self-sampling, whereas the remaining participants preferred collection by clinicians. No intervention-related complications were observed. Conclusion The self-sampling technique for HPV testing was as effective as the clinician-sampling technique, and both techniques were substantially correlated in detecting high-risk HPV infection. The self-sampling method appears to be highly satisfactory and may provide better compliance for the detection of cervical HPV infection.

Objective: To compare survival outcomes, posttreatment complications, and quality of life (QoL) of early-stage cervical cancer patients with intermediate-risk factors between those who received adjuvant pelvic radiation and those without adjuvant treatment. Methods: Stages IB–IIA cervical cancer patients classified as having intermediate-risk following primary radical surgery were included. After propensity score weighted adjustment, all baseline demographic and pathological characteristics of 108 women who received adjuvant radiation and 111 women who had no adjuvant treatment were compared. The primary outcomes were progression-free survival (PFS) and overall survival (OS). The secondary outcomes included treatment-related complications and QoL. Results: Median follow-up time was 76.1 months in the adjuvant radiation group and 95.4 months in the observation group. The 5-year PFS (91.6% in the adjuvant radiation group and 88.4% in the observation group, p=0.42) and OS (90.1% in the adjuvant radiation group and 93.5% in the observation group, p=0.36) were not significantly different between the groups. There was no significant association between adjuvant treatment and overall recurrence/death in the Cox proportional hazard model. However, a substantial reduction in pelvic recurrence was observed in participants with adjuvant radiation (hazard ratio=0.15; 95% confidence interval=0.03–0.71). Grade 3/4 treatment-related morbidities and QoL scores were not significantly different between the groups. Conclusion Adjuvant radiation was associated with a lower risk of pelvic recurrence. However, its significant benefit in reducing overall recurrence and improving survival in early-stage cervical cancer patients with intermediate-risk factors could not be demonstrated.