Risk prediction of cervical abnormalities: The value of sociodemographic and lifestyle factors in addition to HPV status

Acceptability of risk-based triage in cervical cancer screening: A focus group study

BACKGROUND

Compared to the previous cytology-based program, the introduction of primary high-risk human papillomavirus (hrHPV) based screening in 2017 has led to an increased number of referrals. To counter this, triage of hrHPV-positive women in cervical cancer screening can potentially be optimized by taking sociodemographic and lifestyle risk factors for cervical abnormalities into account. Therefore, it is essential to gain knowledge of the views of women (30-60 years) eligible for cervical cancer screening.

OBJECTIVE

The main goal of this qualitative study was to gain insight in the aspects that influence acceptability of risk-based triage in cervical cancer screening.

DESIGN

A focus group study in which participants were recruited via four general medical practices, and purposive sampling was used to maximize heterogeneity with regards to age, education level, and cervical cancer screening experiences.

APPROACH

The focus group discussions were transcribed verbatim and analyzed using reflexive thematic analysis.

PARTICIPANTS

A total of 28 women (average age: 45.2 years) eligible for cervical cancer screening in The Netherlands participated in seven online focus group discussions. Half of the participants was higher educated, and the participants differed in previous cervical cancer screening participation and screening result.

KEY RESULTS

In total, 5 main themes and 17 subthemes were identified that determine the acceptability of risk-stratified triage. The main themes are: 1) adequacy of the screening program: an evidence-based program that is able to minimize cancer incidence and reduce unnecessary referrals; 2) personal information (e.g., sensitive topics and stigma); 3) emotional impact: fear and reassurance; 4) communication (e.g., transparency); and 5) autonomy (e.g., prevention).

CONCLUSION

The current study highlights several challenges regarding the development and implementation of risk-based triage that need attention in order to be accepted by the target group. These challenges include dealing with sensitive topics and a transparent communication strategy.

APOBEC3A/B Polymorphism Is Not Associated with Human Papillomavirus Infection and Cervical Carcinogenesis

The persistence of a high-risk Human papillomavirus (HPV-HR) infection of the cervix results in different manifestations of lesions depending on the immunologic capacity of the host. Variations in apolipoprotein B mRNA editing enzyme catalytic polypeptide (APOBEC)-like genes, such as the APOBEC3A/B deletion hybrid polymorphism (A3A/B), may contribute to cervical malignancy in the presence of HPV. The aim of this study was to investigate the association between the A3A/B polymorphism and HPV infection and the development of cervical intraepithelial lesions and cervical cancer in Brazilian women. The study enrolled 369 women, who were categorized according to the presence of infection and subdivided according to the degree of intraepithelial lesion and cervical cancer. APOBEC3A/B was genotyped by allele-specific polymerase chain reaction (PCR). As for the A3A/B polymorphism, the distribution of genotypes was similar between groups and among the analyzed subgroups. There were no significant differences in the presence of infection or development of lesions, even after exclusion of confounding factors. This is the first study to show that the A3A/B polymorphism is not associated with HPV infection and the development of intraepithelial lesions and cervical cancer in Brazilian women.

Sociodemographic Characteristics and Screening Outcomes of Women Preferring Self-Sampling in the Dutch Cervical Cancer Screening Programme: A Population-Based Study

BACKGROUND

In the Netherlands, lower high-risk human papillomavirus (hrHPV) positivity but higher cervical intraepithelial neoplasia (CIN) 2+ detection were found in self-collected compared with clinician-collected samples. To investigate the possible reason for these differences, we compared sociodemographic and screening characteristics of women and related these to screening outcomes.

METHODS

We extracted data from PALGA on all primary hrHPV screens and associated follow-up tests for 857,866 screened women, invited in 2017 and 2018. We linked these data with sociodemographic data from Statistics Netherlands. Logistic regression was performed for hrHPV positivity and CIN 2+/3+ detection.

RESULTS

Out of the 857,866 women, 6.8% chose to use a self-sampling device. A higher proportion of self-sampling users was ages 30 to 35 years, was not previously screened, was living in a one-person household, or was the breadwinner in the household. After adjustment for these factors self-sampling had lower hrHPV positivity (aOR, 0.65; 95% CI, 0.63-0.68)) as compared with clinician-collected sampling, as well as lower odds of CIN 2+ (aOR, 0.76; 95% CI, 0.70-0.82) and CIN 3+ (aOR, 0.86; 95% CI, 0.78-0.95) detection.

CONCLUSIONS

It is likely that the observed differences between the two sampling methods are not only related to sociodemographic differences, but related to differences in screening test accuracy and/or background risk.

IMPACT

Self-sampling can be used for targeting underscreened women, as a more convenient screening tool. Further investigation is required to evaluate how to implement self-sampling, when it is used as a primary instrument in routine screening. See related commentary by Arbyn et al., p. 159.

Towards a data-driven system for personalized cervical cancer risk stratification

Mass-screening programs for cervical cancer prevention in the Nordic countries have been effective in reducing cancer incidence and mortality at the population level. Women who have been regularly diagnosed with normal screening exams represent a sub-population with a low risk of disease and distinctive screening strategies which avoid over-screening while identifying those with high-grade lesions are needed to improve the existing one-size-fits-all approach. Machine learning methods for more personalized cervical cancer risk estimation may be of great utility to screening programs shifting to more targeted screening. However, deriving personalized risk prediction models is challenging as effective screening has made cervical cancer rare and the exam results are strongly skewed towards normal. Moreover, changes in female lifestyle and screening habits over time can cause a non-stationary data distribution. In this paper, we treat cervical cancer risk prediction as a longitudinal forecasting problem. We define risk estimators by extending existing frameworks developed on cervical cancer screening data to incremental learning for longitudinal risk predictions and compare these estimators to machine learning methods popular in biomedical applications. As input to the prediction models, we utilize all the available data from the individual screening histories.Using data from the Cancer Registry of Norway, we find in numerical experiments that the models are strongly biased towards normal results due to imbalanced data. To identify females at risk of cancer development, we adapt an imbalanced classification strategy to non-stationary data. Using this strategy, we estimate the absolute risk from longitudinal model predictions and a hold-out set of screening data. Comparing absolute risk curves demonstrate that prediction models can closely reflect the absolute risk observed in the hold-out set. Such models have great potential for improving cervical cancer risk stratification for more personalized screening recommendations.

Association Between GSDMB Gene Polymorphism and Cervical Cancer in the Northeast Chinese Han Population

Objective: The purpose of this study was to investigate the relationship between GSDMB gene polymorphism and genetic susceptibility to cervical cancer in the Han population in Northeast China. Methods: In this case-control study, the genotypes and alleles of rs8067378 in the GSDMB gene were analyzed by multiplex polymerase chain reaction (PCR) and next-generation sequencing methods in 482 cervical cancer (CC) patients, 775 cervical squamous intraepithelial lesion (SIL) patients, and 495 healthy women. The potential relationships between the SNP of the GSDMB gene with SIL and CC were analyzed by multivariate logistic regression analysis combined with 10,000 permutation tests. Results: In the comparison between the SIL group and the control group, the genotype and allele distribution frequencies of rs8067378 SNP of the GSDMB gene were statistically significant (p = 0.0493 and p = 0.0202, respectively). The allele distribution frequencies of rs8067378 were also statistically significant in the comparison between high-grade cervical squamous intraepithelial lesion (HSIL) and low-grade cervical squamous intraepithelial lesion (LSIL) groups with control group ( p = 0.0483 and p = 0.0330, respectively). Logistic regression analysis showed that after adjusting for age, the rs8067378 SNP of the GSDMB gene was significantly associated with the reduced risk of SIL under the dominant model (p = 0.0213, OR = 0.764, CI = 0.607-0.961) and the additive model (p = 0.0199, OR = 0.814, and CI = 0.684-0.968), and its mutant gene G may play a role in the progression of healthy people to LSIL and even HSIL as a protective factor. However, there was no significant association between cervical cancer and its subtypes with the control group (p > 0.05). After 10,000 permutations, there was still no correlation that has provided evidence for the accuracy of our study. Conclusion: The results of this study showed that rs8067378 single nucleotide polymorphism of the GSDMB gene may reduce the risk of SIL and protect the susceptibility to cervical precancerous lesions in the Northeast Chinese Han population, but it has no significant correlation with the progression of cervical cancer.

Analysis of Distributions of HPV Infection in Females with Cervical Lesions in the Western District of Beijing Chaoyang Hospital

Objective

To analyze the distribution of human papilloma virus (HPV) infection in women with cervical lesions of different grades and analyze the relationship of high-risk HPV and cervical lesions in order to facilitate targeted prevention.

Methods

The infection status of HPV subtype was statistically analyzed in patients who underwent colposcopy examination from April 2017 to June 2019.

Results

The infection rate of HPV was 81.4% in chronic cervicitis, 82.9% in 1ow-grade squamous intraepithelial lesion (LSIL), 63.7% in HSIL (high-grade squamous intraepithelial lesion), and 50% in cervical squamous cell carcinoma (CSCC). Among the 16 high-risk HPV types, the top six HPV types with the comprehensive infection rates were HPV16 > HPV52 > HPV58 > HPV18 > HPV51 > HPV53 in turn, and the infection rates were 23.3%, 14.8%, 13.3%, 9.8%, 9.2%, and 8.8%, respectively. The infection rates of HPV16 in chronic cervicitis group, LSIL group, and HSIL group were significantly different. There was no significant difference in the injection rates of HPV52, HPV58, and HPV18 among the three groups. HPV infection rates were highest in the 31–40 years old group, followed by the 41–50 years old group.

Conclusion

The distribution of different types of HPV varies in different tissue types, which can be used to develop relevant vaccines to achieve better prevention and treatment of cervical cancer.

Optimization of Cervical Cancer Screening: A Stacking-Integrated Machine Learning Algorithm Based on Demographic, Behavioral, and Clinical Factors

PURPOSE

The purpose is to accurately identify women at high risk of developing cervical cancer so as to optimize cervical screening strategies and make better use of medical resources. However, the predictive models currently in use require clinical physiological and biochemical indicators, resulting in a smaller scope of application. Stacking-integrated machine learning (SIML) is an advanced machine learning technique that combined multiple learning algorithms to improve predictive performance. This study aimed to develop a stacking-integrated model that can be used to identify women at high risk of developing cervical cancer based on their demographic, behavioral, and historical clinical factors.

METHODS

The data of 858 women screened for cervical cancer at a Venezuelan Hospital were used to develop the SIML algorithm. The screening data were randomly split into training data (80%) that were used to develop the algorithm and testing data (20%) that were used to validate the accuracy of the algorithms. The random forest (RF) model and univariate logistic regression were used to identify predictive features for developing cervical cancer. Twelve well-known ML algorithms were selected, and their performances in predicting cervical cancer were compared. A correlation coefficient matrix was used to cluster the models based on their performance. The SIML was then developed using the best-performing techniques. The sensitivity, specificity, and area under the curve (AUC) of all models were calculated.

RESULTS

The RF model identified 18 features predictive of developing cervical cancer. The use of hormonal contraceptives was considered as the most important risk factor, followed by the number of pregnancies, years of smoking, and the number of sexual partners. The SIML algorithm had the best overall performance when compared with other methods and reached an AUC, sensitivity, and specificity of 0.877, 81.8%, and 81.9%, respectively.

CONCLUSION

This study shows that SIML can be used to accurately identify women at high risk of developing cervical cancer. This model could be used to personalize the screening program by optimizing the screening interval and care plan in high- and low-risk patients based on their demographics, behavioral patterns, and clinical data.

Human Papillomavirus Vaccine Impact on Cervical Precancers in a Low-Vaccination Population

INTRODUCTION

Demonstrating human papillomavirus vaccine impact is critical for informing guidelines to increase vaccination and decrease human papillomavirus‒related outcomes, particularly in states with suboptimal vaccination coverage, such as Tennessee. This study examines the trends in high-grade cervical lesion incidence among Tennessee Medicaid-enrolled women aged 18-39 years and the subset of women who were screened for cervical cancer.

METHODS

Using a validated claims-based model to identify incident cervical intraepithelial neoplasia Grades 2 or 3 or adenocarcinoma in situ events, annual age group‒specific incidence rates from Tennessee Medicaid billing data, 2008-2018, were calculated. Significant trends were determined by Joinpoint. Analyses were conducted in 2020.

RESULTS

From 2008 to 2018, high-grade cervical lesion incidence significantly declined in women aged 18-20 years (average annual percentage change= -31.9, 95% CI= -38.6, -24.6), 21-24 years (average annual percentage change= -12.9, 95% CI= -22.3, -2.4), and 25-29 years (average annual percentage change= -6.4, 95% CI= -8.1, -4.6). Among screened women, rates significantly declined for ages 18-20 years (average annual percentage change= -20.3, 95% CI= -25.3, -15.0), 21-24 years (average annual percentage change= -10.2, 95% CI= -12.6, -7.8), and 25-29 years (average annual percentage change= -2.6, 95% CI= -3.9, -1.2). Trends from 2008 to 2018 were stable for older age groups (30-34 and 35-39 years).

CONCLUSIONS

Results show reductions in high-grade cervical lesion incidence among ages most likely to have benefited from the human papillomavirus vaccine. Declines among young, screened women suggest causes other than reduction in screening. Evidence of vaccine impact in populations with low-vaccination coverage, such as Tennessee, is promising.

Risk factors associated with HPV persistence after conization in high-grade squamous intraepithelial lesion

OBJECTIVE

Persistence of HPV infection in patients with high-grade squamous intraepithelial lesion (HSIL) undergoing cervical excision is considered strongly associated with the recurrence and progression of cervical dysplasia. This study aims to review potential risk factors for persistence of HPV infection in patients with HSIL, thus optimizing the postoperative monitoring program and clinical treatment.

METHODS

Through literature review, published data about estimated prognostic risk factors for persistence of HPV infection in patients with HSIL after conization within two decades were searched and analyzed, and their references were manually reviewed as well.

RESULTS

Women with persistence of HPV infection after cervical excision were at an extremely high risk of disease recurrence and progression to cervical cancer. Some clinicopathological and even physiological elements involving viral, organic human body and treatment factors, such as human papillomavirus (HPV) 16, high viral load, age older than 50 years and positive surgical margin were of prognostic significance in persistent HPV infection in patients with HSIL, yet some of which still remained controversial.

CONCLUSIONS

Monitoring prognostic factors in women with persistence of HPV infection who have underwent cervical excision for HSIL are of great significance, especially the follow-up within 2 years postoperatively, which significantly improves the clinical outcome.

Screening for cervical dysplasia and reproductive tract infections in Kerala, India: A multicentric study

Background:

Cancer of the uterine cervix is estimated to the second most frequently occurring malignancy among females in India. Cancer mortality profile in India estimates that 20.7% of cancer deaths in females are cervical cancer. This well elucidates the fatal aspect of the disease and the need for early detection.

Aims:

To screen for cervical dysplasias and reproductive tract infections in various parts of Kerala, India, and determine its associated factors.

Methods and Methodology:

This was a descriptive cross-sectional study conducted in various parts of Kerala, India. This study included an interview schedule to collect data and the procedures included per speculum examination along with a Pap smear test.

Results:

A total of 199 women were screened with mean age of 45.87 ± 9.84 years. Of these, 13.5% showed inflammatory smears, 1% showed infective pathology and 1.5% showed pre-malignant lesions.

Conclusion:

The increased rates of inflammation and infection show its importance in public health. Similar community-based screening as well as routine screening by physicians/gynaecologists is recommended for early detection of cervical cancer and reproductive tract infections. Community education among the population proves to be an important factor; especially regarding HPV vaccination.