Effect of Pap smear screening on cervical cancer stage at diagnosis: results from the Korean National Cancer Screening Program

Exploring Cervical Cancer Screening Uptake among Women in the United States: Impact of Social Determinants of Health and Psychosocial Determinants

Several non-medical factors, such as income, education, and access to care, directly or indirectly affect adherence to cancer screening guidelines. We examined the impact of social determinants of health (SDOH) and psychosocial factors on screening behavior in a nationally representative sample of women in the US. A retrospective population-level cross-sectional sample was extracted from the 2022 Health Information National Trends Survey. The dependent variables were the interest in cervical cancer screening and the screening behavior. The independent variables included SDOH and psychosocial factors. Descriptive statistics were calculated for demographics and covariates, and population-based estimates with 95% confidence intervals (CI) were produced for Pap testing behaviors. Logistic regression models assessed differences in Pap testing based on SDOH and psychosocial factors, adjusting for covariates. The study included 2224 women with a mean age of 46.96. Results showed that 90% of women were interested in cervical cancer screening, with an 80% screening rate. Screening rates varied by age and rurality. SDOH and psychosocial factors influenced both interest and actual screening, with 3% and 1% impacts, respectively. These findings suggest that SDOH and psychosocial factors are associated with cervical cancer screening uptake, highlighting the need for policies to address these disparities. Policies must be directed at bridging the gap created by these SDOHs. Public health professionals and researchers can design interventions using the SDOH and psychosocial frameworks to increase cervical cancer screening uptake.

HO-SsNF: heap optimizer-based self-systematized neural fuzzy approach for cervical cancer classification using pap smear images

Cervical cancer is a significant concern for women, necessitating early detection and precise treatment. Conventional cytological methods often fall short in early diagnosis. The proposed innovative Heap Optimizer-based Self-Systematized Neural Fuzzy (HO-SsNF) method offers a viable solution. It utilizes HO-based segmentation, extracting features via Gray-Level Co-Occurrence Matrix (GLCM) and Local Binary Pattern (LBP). The proposed SsNF-based classifier achieves an impressive 99.6% accuracy in classifying cervical cancer cells, using the Herlev Pap Smear database. Comparative analyses underscore its superiority, establishing it as a valuable tool for precise cervical cancer detection. This algorithm has been seamlessly integrated into cervical cancer diagnosis centers, accessible through smartphone applications, with minimal resource demands. The resulting insights provide a foundation for advancing cancer prevention methods.

Comparing the Diagnostic Performance of Quantitative PCR, Digital Droplet PCR, and Next-Generation Sequencing Liquid Biopsies for Human Papillomavirus-Associated Cancers

Human papillomavirus (HPV)-associated cancers, including oropharyngeal squamous cell carcinoma (HPV + OPSCC), cervical cancer, and squamous cell carcinoma of the anus (HPV + SCCA), release circulating tumor HPV DNA (ctHPVDNA) into the blood. The diagnostic performance of ctHPVDNA detection depends on the approaches used and the individual assay metrics. A comparison of these approaches has not been systematically performed to inform expected performance, which in turn affects clinical interpretation. A meta-analysis was performed using Ovid MEDLINE, Embase, and Web of Science Core Collection databases to assess the diagnostic accuracy of ctHPVDNA detection across cancer anatomic sites, detection platforms, and blood components. The population included patients with HPV + OPSCC, HPV-associated cervical cancer, and HPV + SCCA with pretreatment samples analyzed by quantitative PCR (qPCR), digital droplet PCR (ddPCR), or next-generation sequencing (NGS). Thirty-six studies involving 2986 patients met the inclusion criteria. The sensitivity, specificity, and quality of each study were assessed and pooled for each analysis. The sensitivity of ctHPVDNA detection was greatest with NGS, followed by ddPCR and then qPCR when pooling all studies, whereas specificity was similar (sensitivity: ddPCR > qPCR, P < 0.001; NGS > ddPCR, P = 0.014). ctHPVDNA from OPSCC was more easily detected compared with cervical cancer and SCCA, overall (P = 0.044). In conclusion, detection platform, anatomic site of the cancer, and blood component used affects ctHPVDNA detection and must be considered when interpreting results. Plasma NGS-based testing may be the most sensitive approach for ctHPVDNA overall.

A Diagnostic Nomogram Incorporating Prognostic Nutritional Index for Predicting Vaginal Invasion in Stage IB - IIA Cervical Cancer

INTRODUCTION

With the advancements in cancer prevention and diagnosis, the proportion of newly diagnosed early-stage cervical cancers has increased. Adjuvant therapies based on high-risk postoperative histopathological factors significantly increase the morbidity of treatment complications and seriously affect patients' quality of life.

OBJECTIVES

Our study aimed to establish a diagnostic nomogram for vaginal invasion (VI) among early-stage cervical cancer (CC) that can be used to reduce the occurrence of positive or close vaginal surgical margins.

METHODS

We assembled the medical data of early-stage CC patients between January 2013 and December 2021 from the Fujian Cancer Hospital. Data on demographics, laboratory tests, MRI features, physical examination (PE), and pathological outcomes were collected. Univariate and multivariate logistic regression analyses were employed to estimate the diagnostic variables for VI in the training set. Finally, the statistically significant factors were used to construct an integrated nomogram.

RESULTS

In this retrospective study, 540 CC patients were randomly divided into training and validation cohorts according to a 7:3 ratio. Multivariate logistic analyses showed that age [odds ratio (OR) = 2.41, 95% confidence interval (CI), 1.29-4.50, P = 0.006], prognostic nutritional index (OR = 0.18, 95% CI, 0.04-0.77, P = 0.021), histological type (OR = 0.28, 95% CI, 0.08-0.94, P = 0.039), and VI based on PE (OR = 3.12, 95% CI, 1.52-6.45, P = 0.002) were independent diagnostic factors of VI. The diagnostic nomogram had a robust ability to predict VI in the training [area under the receiver operating characteristic curve (AUC) = 0.76, 95% CI: 0.70-0.82] and validation (AUC = 0.70, 95% CI: 0.58-0.83) cohorts, and the calibration curves, decision curve analysis, and confusion matrix showed good prediction power.

CONCLUSION

Our diagnostic nomograms could help gynaecologists quantify individual preoperative VI risk, thereby optimizing treatment options, and minimizing the incidence of multimodality treatment-related complications and the economic burden.

Effect of Pap smears on the long-term survival of cervical cancer patients: a nationwide population-based cohort study in Korea

OBJECTIVES

This study aimed to investigate the effect of cervical cancer screening by Papanicolaou (Pap) smears on the long-term survival of cervical cancer patients.

METHODS

We constructed a retrospective cohort of 14,903 women diagnosed with invasive cancer or carcinoma in situ in 2008 and 2009 and followed up until December 31, 2019, by using individual-level data from 3 national databases of the Korean National Cancer Screening Program, the Korean Central Cancer Registry, and death certificates. Cox proportional-hazards regression was used to investigate the effect of cervical cancer screening on mortality.

RESULTS

In total, 12,987 out of 14,867 patients (87.4%) were alive at the end of the follow-up period (median: 10.5 years). Screened patients had a 38% lower risk of cervical cancer death than never-screened patients (hazard ratio [HR], 0.62; 95% confidence interval [CI], 0.54 to 0.70). Screening was associated with 59% and 35% lower risks of death, respectively, in screened patients with localized and regional stages. Furthermore, lower HRs among women who received screening were observed in all age groups, especially women aged 50-59 years (HR, 0.54; 95% CI, 0.42 to 0.69). The lowest HR for cervical cancer death was reported among patients screened within the past 2 years (HR, 0.54; 95% CI, 0.47 to 0.63), and the HRs increased with increasing time intervals.

CONCLUSIONS

Pap smear screening significantly reduced the risk of cervical cancer-specific death in Korean women across all cancer stages.

Diagnosis of Cervical Intraepithelial Neoplasia and Invasive Cervical Carcinoma by Cervical Biopsy under Colposcopy and Analysis of Factors Influencing

Objective

To explore the diagnosis of cervical intraepithelial neoplasia (CIN) and invasive cervical carcinoma (ICC) by cervical biopsy under colposcopy and analyze the factors influencing the detection.

Methods

The clinical data of 134 CIN confirmed by colposcopy biopsy in our hospital from June 2018 to October 2019 and subsequent LEEP treatment were analyzed retrospectively. All patients were diagnosed pathologically after the operation. The diagnosis of CIN by cervical biopsy under colposcopy was observed. The influencing factors of CIN and ICC detected by colposcopy biopsy were analyzed by the pathological results of loop electrosurgical excision procedure (LEEP) as the gold standard.

Results

After LEEP, the number of the no intraepithelial or malignant lesions (NILM) or ICC were higher than that of colposcopy biopsy, and CIN-III was lower than that of colposcopy biopsy, the differences were all statistically significant (P < 0.05). Among the 134 patients, the coincidence rate between colposcopy biopsy and LEEP examination results was 79.10% (106/134), and postoperative pathological findings showed that there were 13 cases (9.70%) with the pathological upgrade and 19 cases (14.18%) with pathological decrease. Multivariate logistic analysis showed that the image quality of colposcopy image, atypical blood vessels, biopsy sampling method, and visible lesion area of the cervix were the independent influencing factors for the detection of CIN and ICC by colposcopy biopsy (P < 0.05).

Conclusion

CIN and ICC can be diagnosed by colposcopy cervical biopsy and postoperative histopathology. However, there are still some missed and misdiagnosed cervical biopsies under colposcopy, and the combined detection of the two can further ensure the diagnosis rate. The clinical registration number is E2018091.