Dataset Information

Cervical cancer screening coverage, management of squamous intraepithelial lesions and related costs in France.

ABSTRACT: Until 2018, cervical cancer screening in France was an unorganized individual screening, with the exception of some pilot programs in some territories. We aimed to assess, before the implementation of organized cervical cancer screening and human papillomavirus (HPV) nonavalent vaccine introduction in the vaccination schedule in 2018, (i) the individual cervical cancer screening coverage, (ii) the management of squamous intraepithelial lesions (SIL) and (iii) the related costs. We used the Système National des Données de Santé (SNDS) (Echantillon Généraliste de Bénéficiaires [EGB] and Programme de Médicalisation des systèmes d'information [PMSI]) to assess the cervical screening coverage rate in France between January 1st, 2012 and December 31st, 2014, and to describe diagnostic investigations and therapeutic management of SIL in 2013. After extrapolation to the general population, a total of 10,847,814 women underwent at least one smear test over the 3-year study period, corresponding to a coverage rate of 52.4% of the women aged 25 to 64 included. In 2013, 126,095 women underwent HPV test, 327,444 women underwent colposcopy, and 9,653 underwent endocervical curettage; 31,863 had conization and 12,162 had laser ablation. Besides, 34,067 women experienced hospital stays related to management of SIL; 25,368 (74.5%) had high-grade lesions (HSIL) and 7,388 (21.7%) low-grade lesions (LSIL). Conization was the most frequent in-hospital therapeutic procedure: 89.5% (22,704) of women with an in-hospital procedure for HSIL and 64.7% (4,781) for LSIL. Mean cost of smear test, colposcopy and HPV tests were around 50€. Total cost for hospital stays in 2013 was estimated at M41€, or a mean cost of 1,211€ per woman; 76% were due to stays with HSIL. This study highlights the low coverage rate of individual cervical cancer screening and a high burden related to SIL management.

SUBMITTER: de Rycke Y

PROVIDER: S-EPMC7018036 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Cervical cancer screening coverage, management of squamous intraepithelial lesions and related costs in France.

de Rycke Yann Y Tubach Florence F Lafourcade Alexandre A Guillo Sylvie S Dalichampt Marie M Dahlab André A Bresse Xavier X Uhart Mathieu M Bergeron Christine C Borne Hélène H Cancalon Charlotte C Lajoinie Audrey A Bénard Stève S

PloS one 20200213 2

Until 2018, cervical cancer screening in France was an unorganized individual screening, with the exception of some pilot programs in some territories. We aimed to assess, before the implementation of organized cervical cancer screening and human papillomavirus (HPV) nonavalent vaccine introduction in the vaccination schedule in 2018, (i) the individual cervical cancer screening coverage, (ii) the management of squamous intraepithelial lesions (SIL) and (iii) the related costs. We used the Systè ...[more]

PMID: 32053648

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Project description:It is crucial to classify cervical lesions into high-grade squamous intraepithelial lesions (HSILs) and low-grade SILs (LSILs), as LSILs are conservatively treated by observation, based on an expectation of natural regression, whereas HSILs usually require electrosurgical excision. In the present study, peripheral blood gene expression profiles were analyzed to identify transcriptomic biomarkers distinguishing HSILs from LSILs. A total of 102 blood samples were collected from women with cervical SILs (66 HSIL and 36 LSIL) for microarray hybridization. Candidate gene signatures were identified using AdaBoost algorithms, and a predictive model was constructed using logistic regression to differentiate HSILs from LSILs. To correct for possible bias as a result of the limited sample size and to verify the stability of the predictive model, a two-fold cross validation and null set analysis was conducted over 1,000 iterations. The functions of the transcriptomic biomarkers were then analyzed to elucidate the pathogenesis of cervical SIL. A total of 10 transcriptomic genes (STMN3, TRPC4AP, DYRK2, AGK, KIAA0319L, GRPEL1, ZFC3H1, LYL1, ITGB1 and ARHGAP18) were identified. The predictive model based on the 10-gene panel exhibited well-discriminated power. A cross validation process using known disease status exhibited almost the same performance as that of the predictive model, whereas null-set analysis with randomly reassigned disease status exhibited much lower predictive performance for distinguishing HSILs from LSILs. These biomarkers were involved in the 'Rho GTPase cycle', 'mitochondrial protein import', 'oncogenic MAPK signaling', 'integrin cell surface interaction' and 'signaling by BRAF and RAF fusions'. In conclusion, peripheral blood gene expression analysis is a promising method for distinguishing HSILs from LSILs. The present study proposes 10 candidate genes that could be used in the future as diagnostic biomarkers and potential therapeutic targets for cervical SILs. A simple, non-invasive blood test would be clinically useful in the diagnosis and classification of patients with cervical SILs.

Project description:Cervical cancer is an important health concern worldwide and is one of the leading causes of death in Mexican women. Previous studies have shown changes in the female genital tract microbe community related to human papillomavirus (HPV) infection and cervical cancer; yet, this link remains unexplored in many human populations. This study evaluated the vaginal bacterial community among Mexican women with precancerous squamous intraepithelial lesions (SIL). We sequenced the V3 region of the 16S rRNA gene in cervical samples from 228 Mexican women, including 121 participants with SIL, most of which were HPV positive, and 107 healthy women without HPV infection or SIL. The presence of SIL was associated with changes in composition (beta diversity) and with a higher species richness (Chao1). A comparison of HPV-positive women with and without SIL showed that microbiota changes occurred even in the absence of SIL. Multivariate association with linear models (MaAsLin) analysis yielded independent associations between HPV infection and an increase in the relative abundance of Brachybacterium conglomeratum and Brevibacterium aureum as well as a decrease in two Lactobacillus iners operational taxonomic units (OTUs). We also identified a positive independent association between HPV-16, the most common HPV subtype linked to SIL, and Brachybacterium conglomeratum. Our work indicates that HPV infection leading to SIL is primarily associated with shifts in vaginal microbiota composition, some of which may be specific to this human population. IMPORTANCE Human papillomavirus (HPV) plays a critical role in cervical carcinogenesis but is not sufficient for cervical cancer development, indicating the involvement of other factors. The vaginal microbiota is an important factor in controlling infections caused by HPV, and, depending on its composition, it can modulate the microenvironment in vaginal mucosa against viral infections. Ethnic and sociodemographic factors influence differences in vaginal microbiome composition, which underlies the dysbiotic patterns linked to HPV infection and cervical cancer across different populations of women. Here, we provide evidence for associations between vaginal microbiota patterns and HPV infection linked to ethnic and sociodemographic factors. To our knowledge, this is the first report of the species Brevibacterium aureum and Brachybacterium conglomeratum linked to HPV infection or squamous intraepithelial lesions (SIL).

Project description:Background Deep learning has presented considerable potential and is gaining more importance in computer assisted diagnosis. As the gold standard for pathologically diagnosing cervical intraepithelial lesions and invasive cervical cancer, colposcopy-guided biopsy faces challenges in improving accuracy and efficiency worldwide, especially in developing countries. To ease the heavy burden of cervical cancer screening, it is urgent to establish a scientific, accurate and efficient method for assisting diagnosis and biopsy. Methods The data were collected to establish three deep-learning-based models. For every case, one saline image, one acetic image, one iodine image and the corresponding clinical information, including age, the results of human papillomavirus testing and cytology, type of transformation zone, and pathologic diagnosis, were collected. The dataset was proportionally divided into three subsets including the training set, the test set and the validation set, at a ratio of 8:1:1. The validation set was used to evaluate model performance. After model establishment, an independent dataset of high-definition images was collected to further evaluate the model performance. In addition, the comparison of diagnostic accuracy between colposcopists and models weas performed. Results The sensitivity, specificity and accuracy of the classification model to differentiate negative cases from positive cases were 85.38%, 82.62% and 84.10% respectively, with an AUC of 0.93. The recall and DICE of the segmentation model to segment suspicious lesions in acetic images were 84.73% and 61.64%, with an average accuracy of 95.59%. Furthermore, 84.67% of high-grade lesions were detected by the acetic detection model. Compared to colposcopists, the diagnostic system performed better in ordinary colposcopy images but slightly unsatisfactory in high-definition images. Implications The deep learning-based diagnostic system could help assist colposcopy diagnosis and biopsy for HSILs.

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Cervical cancer screening coverage, management of squamous intraepithelial lesions and related costs in France.

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Cervical cancer screening coverage, management of squamous intraepithelial lesions and related costs in France.

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