Each year in the US, approximately 100 000 people are treated for cervical precancer, 14 000 people are diagnosed with cervical cancer, and 4000 die of cervical cancer.

Cytology identifies the women who are at higher risk of harboring high-grade cervical premalignant lesions or invasive cancer. However, a diagnostic test such as colposcopy is crucial for women with abnormal cytology for localization of the abnormality, confirmation of diagnosis, and appropriate management. To standardize this subjective technique and to minimize the interobserver variations, Swede scoring system was introduced. The revised colposcopic nomenclature of the International Federation of Cervical Pathology and Colposcopy in 2011 included various normal and abnormal colposcopic findings and gives a description of colposcopic features which improves its accuracy over the colposcopic indices. There is consensus agreement that cytology indicative of high-grade lesions (ASC-H and HSIL in the Bethesda system) should engender immediate referral for colposcopy and biopsy. The management of women who have equivocal or borderline cytology of low-grade abnormalities (ASCUS/LSIL) is still under deliberation. It is generally agreed to have an HPV triage for women with equivocal cytology. Based on the latest recommendations, the current chapter provides an extensive overview of the role of colposcopy in the management of women with various abnormalities reported on Pap smear.© 2022 Cytopathology Foundation Inc, Published by Scientific Scholar.

It has been suggested that the accuracy of colposcopy is less reliable than once presumed. The Reid colposcopic index is the most well-known scoring system designed to standardize colposcopic assessment and assist in the prediction of histological diagnosis. Strander et al. have devised a new scoring system, the Swede score, which includes lesion size as a variable. This evaluation aimed to validate the Swede score within a London teaching hospital colposcopy unit.An evaluation was carried out of women undergoing colposcopy at the Royal Free Hospital, London, UK. For 4 months, 200 women attending diagnostic colposcopy clinics or undergoing inpatient treatment of cervical intraepithelial neoplasia (CIN) were included. Participating colposcopists comprised both trained and trainee colposcopists. Swede scores were calculated at the time of colposcopy and recorded; they were compared with the final histological diagnosis after either directed or excisional cervical biopsy. Because this was an evaluation and not a research study, the Swede score was not used to influence the patient management in anyway.Swede scores of 8 or more had a sensitivity, specificity, and positive and negative predictive values of 38%, 95%, 83%, and 70%, respectively, for lesions where the final diagnosis was CIN 2 or higher. Using the same cutoff score of 8 or higher, the first 100 examinations had similar results compared with the second set, showing that no major learning curve existed when using the Swede score.Because the specificity when scoring 8 or higher was 95%, it is possible that higher scores within this system might be used to more accurately predict CIN 2 or higher. There was no obvious learning curve, and trainees showed comparable results compared with their trained colleagues.

Screening plays a key role in secondary prevention of cervical cancer. High-risk human papillomavirus (hrHPV) testing, a highly sensitive test but with limited specificity, has become the gold standard frontline for screening programs. Thus, the importance of effective triage strategies, including DNA methylation markers, has been emphasized. Despite the potential reported in individual studies, methylation markers still require validation before being recommended for clinical practice. This systematic review and meta-analysis aimed to evaluate the performance of DNA methylation-based biomarkers for detecting high-grade intraepithelial lesions (HSIL) in hrHPV-positive women.

Human papillomavirus (HPV) integration is recognized as a hallmark event in cervical carcinogenesis. However, it does not represent a routine phase of the viral life cycle but rather a stochastic occurrence, often constituting a dead-end pathway for the virus. High-risk human papillomavirus (hr-HPV) exhibits a greater propensity for integration. The progression from initial infection to genomic integration constitutes a dynamic multi-step oncogenic process in the development of cervical cancer (CC). This process involves viral entry, immune evasion, persistent infection, and ultimately integration. This article innovatively provides a comprehensive overview of this multi-stage mechanism: HPV, via the L1/L2 proteins, mediates internalization and establishes infection. Subsequently, under the influence of factors such as the host’s genetic background, vaginal microbiota imbalance, and immune evasion, the host’s DNA damage response (DDR) pathways are activated. Viral DNA integrates into host genome vulnerable sites (e.g., 3q28 and 8q24) through microhomology-mediated end joining (MMEJ) or other alternative pathways. Following integration, the expression of viral oncogenes persists, triggering host genomic rearrangements, aberrant epigenetic modifications, and immune microenvironment remodeling, all of which collectively drive cervical cancer progression. The study further reveals the clinical potential of HPV integration as a highly specific molecular biomarker, offering new perspectives for precision screening and targeted therapy. This dynamic model deepens our understanding of the HPV carcinogenic mechanism and provides a theoretical basis for intervention strategies.

15% of women treated for high-grade cervical intraepithelial neoplasia (CIN grade 2 or 3) develop residual or recurrent CIN grade 2 or 3 or cervical cancer, most of which are diagnosed within 2 years of treatment. To gain more insight into the long-term predictive value of different post-treatment strategies, we assessed the long-term cumulative risk of post-treatment CIN grade 2 or 3 or cancer and different follow-up algorithms to identify women at risk of residual or recurrent disease.Women who were included in three studies in the Netherlands and who were treated for CIN grade 2 or 3 between July, 1988, and November, 2004, were followed up by cytology and testing for high-risk human papillomavirus (hrHPV) at 6, 12, and 24 months after treatment, and subsequently received cytological screening every 5 years. The primary endpoint was the cumulative risk of post-treatment CIN grade 2 or higher by December, 2009. We also assessed the cumulative risk of CIN grade 2 or higher in women with three consecutive negative cytological smears and women with negative co-testing with cytology and hrHPV at months 6 and 24. This study is registered in the Dutch trial register, NTR1468.435 women were included, 76 (17%) of whom developed post-treatment CIN grade 2 or higher, of which 39 were CIN grade 3 or higher. The 5-year risk of developing post-treatment CIN grade 2 or higher was 16·5% (95% CI 13·0-20·7) and the 10-year risk was 18·3% (13·8-24·0). The 5-year risk of developing post-treatment CIN grade 3 or higher was 8·6% (95% CI 6·0-12·1) and the 10-year risk was 9·2% (5·8-14·2). Women with three consecutive negative cytological smears had a CIN grade 2 or higher risk of 2·9% (95% CI 1·2-7·1) in the next 5 years and of 5·2% (2·1-12·4) in the next 10 years. The 5-year risk of CIN grade 3 or higher was 0·7% (95% CI 0·0-3·9) and the 10-year risk was 0·7% (0·0-6·3). Women with negative results for co-testing had a 5-year risk of CIN grade 2 or higher of 1·0% (95% CI 0·2-4·6) and a 10-year risk of 3·6% (1·1-10·7). The 5-year risk of CIN grade 3 or higher was 0·0% (95% CI 0·0-3·0) and the 10-year risk was 0·0% (0·0-5·3).The 5-year risk of post-treatment CIN grade 2 or higher in women with three consecutive negative cytological smears or negative co-testing for cytology and hrHPV at 6 and 24 months was similar to that of women with normal cytology in population-based screening and therefore justifies their return to regular screening.VU University Medical Center, Erasmus University Medical Center, Netherlands.Copyright © 2011 Elsevier Ltd. All rights reserved.

A deep learning classifier that improves the accuracy of colposcopic impression.Colposcopy images taken 56 seconds after acetic acid application were processed by a cervix detection algorithm to identify the cervical region. We optimized models based on the SegFormer architecture to classify each cervix as high-grade or negative/low-grade. The data were split into histologically stratified, random training, validation, and test subsets (80%-10%-10%). We replicated a 10-fold experiment to align with a prior study utilizing expert reviewer analysis of the same images. To evaluate the model's robustness across different cameras, we retrained it after dividing the dataset by camera type. Subsequently, we retrained the model on a new, histologically stratified random data split and integrated the results with patients' age and referral data to train a Gradient Boosted Tree model for final classification. Model accuracy was assessed by the receiver operating characteristic area under the curve (AUC), Youden's index (YI), sensitivity, and specificity compared to the histology.Out of 5,485 colposcopy images, 4,946 with histology and a visible cervix were used. The model's average performance in the 10-fold experiment was AUC = 0.75, YI = 0.37 (sensitivity = 63%, specificity = 74%), outperforming the experts' average YI of 0.16. Transferability across camera types was effective, with AUC = 0.70, YI = 0.33. Integrating image-based predictions with referral data improved outcomes to AUC = 0.81 and YI = 0.46. The use of model predictions alongside the original colposcopic impression boosted overall performance.Deep learning cervical image classification demonstrated robustness and outperformed experts. Further improved by including additional patient information, it shows potential for clinical utility complementing colposcopy.Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the ASCCP.