Utility of Scoring System for Screening and Early Warning of Cervical Cancer Based on Big Data Analysis

To explore the utility of the scoring system for screening and early warning of cervical cancer based on big data analysis.ObjectiveTo explore the utility of the scoring system for screening and early warning of cervical cancer based on big data analysis.A total of 420 women undergoing physical exam...

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Published inFrontiers in public health Vol. 10; p. 920956
Main Authors Hou, Dan, Yang, Binjie, Li, Yangdan, Sun, Ming
Format Journal Article
LanguageEnglish
Published Frontiers Media S.A 20.06.2022
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ISSN2296-2565
2296-2565
DOI10.3389/fpubh.2022.920956

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Summary:To explore the utility of the scoring system for screening and early warning of cervical cancer based on big data analysis.ObjectiveTo explore the utility of the scoring system for screening and early warning of cervical cancer based on big data analysis.A total of 420 women undergoing physical examination in Shenyang from January 2021 to January 2022 were screened by convenient sampling as the study subjects. All females accepted the human papilloma virus (HPV) tests and thin-prep cytology test (TCT), a Rating Questionnaire for Screening and Early Warning of Cervical Cancer was developed, and a warning threshold was derived according to the scores of the questionnaire and the goodness of fit for the results of HPV+TCT tests. The patients were graded according to the threshold, and corresponding intervention strategies for patients of different grades were developed.MethodsA total of 420 women undergoing physical examination in Shenyang from January 2021 to January 2022 were screened by convenient sampling as the study subjects. All females accepted the human papilloma virus (HPV) tests and thin-prep cytology test (TCT), a Rating Questionnaire for Screening and Early Warning of Cervical Cancer was developed, and a warning threshold was derived according to the scores of the questionnaire and the goodness of fit for the results of HPV+TCT tests. The patients were graded according to the threshold, and corresponding intervention strategies for patients of different grades were developed.Among the 420 people undergoing physical examination, 92 (21.90%) obtained scores ≥8 points, and 328 (78.10%) obtained scores < 8 points; in diagnosing cervical cancer, the Rating Questionnaire for Screening and Early Warning of Cervical Cancer had an AUC value of 0.848, specificity of 97.22%, and sensitivity of 86.46%; after scientific intervention, HPV test results showed a significant decrease in both high-risk positive cases and low-risk positive cases (p < 0.05), and TCT results showed that there was a significant difference in the number of patients with CIN I before and after intervention (p < 0.05).ResultsAmong the 420 people undergoing physical examination, 92 (21.90%) obtained scores ≥8 points, and 328 (78.10%) obtained scores < 8 points; in diagnosing cervical cancer, the Rating Questionnaire for Screening and Early Warning of Cervical Cancer had an AUC value of 0.848, specificity of 97.22%, and sensitivity of 86.46%; after scientific intervention, HPV test results showed a significant decrease in both high-risk positive cases and low-risk positive cases (p < 0.05), and TCT results showed that there was a significant difference in the number of patients with CIN I before and after intervention (p < 0.05).The scoring system for screening and early warning of cervical cancer based on big data analysis presents certain clinical value in the clinical screening of cervical cancer, which can further improve the screening coverage, is of great significance for the diagnosis and treatment of disease, and helps physician implement hierarchical diagnosis and treatment quickly and precisely.ConclusionThe scoring system for screening and early warning of cervical cancer based on big data analysis presents certain clinical value in the clinical screening of cervical cancer, which can further improve the screening coverage, is of great significance for the diagnosis and treatment of disease, and helps physician implement hierarchical diagnosis and treatment quickly and precisely.
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These authors have contributed equally to this work
This article was submitted to Digital Public Health, a section of the journal Frontiers in Public Health
Edited by: Thippa Reddy Gadekallu, VIT University, India
Reviewed by: Roshan Fernandes, Nitte Mahalinga Adyanthaya Memorial Institute of Technology, India; Sravan Kumar Reddy, R G M College of Engineering and Technology, India
ISSN:2296-2565
2296-2565
DOI:10.3389/fpubh.2022.920956