High-Risk HPV Genotype Distribution in Karnataka, India: Implications for Screening and Vaccination Strategies

Background: Cervical cancer remains a major cause of cancer mortality among women in India, driven primarily by persistent infection with high-risk human papillomavirus (HPV) genotypes. While HPV 16 and 18 are globally recognised as the most oncogenic, the prevalence of other high-risk types varies regionally, influencing prevention strategies. Methods: We conducted a cross-sectional study involving 923 women aged ≥30 years from diverse socio-economic backgrounds across urban and rural Karnataka. Cervical swabs were collected using the HC2 DNA Collection Device following counselling by obstetricians and gynaecologists in their respective hospitals. All positive samples underwent extended genotyping. Co-testing with Pap smear cytology was performed for all participants. Women with normal cytology were advised to repeat HPV testing after one year and offered HPV vaccination if <45 years. Those with abnormal cytology were referred for colposcopy, biopsy, and further management. Results: Of the 923 women screened, 35 (3.79%) tested positive for high-risk HPV genotypes. The most prevalent types were HPV 66 (54.3%) and HPV 33 (34.3%), followed by HPV 16 (14.3%) and HPV 58 (14.3%). HPV 18, 35, 45, 51, and 52 were detected in ≤4 cases each. This pattern represents a marked deviation from the globally dominant HPV 16/18 profile. Conclusions: The predominance of HPV 33 and 66 in this cohort highlights the need for region-specific HPV surveillance, extended genotyping in screening programmes, and reconsideration of vaccination strategies to ensure coverage of locally prevalent oncogenic strains.

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Publication Details

Journal
British journal of healthcare and medical research
Published
2025-07-25
DOI
https://doi.org/10.14738/bjhr.1204.19304
Primary Topic
Geochemistry and Geologic Mapping
Type
article
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article

High-Risk HPV Genotype Distribution in Karnataka, India: Implications for Screening and Vaccination Strategies

British journal of healthcare and medical research
Geochemistry and Geologic Mapping
article

High-Risk HPV Genotype Distribution in Karnataka, India: Implications for Screening and Vaccination Strategies

article en

Abstract

Background: Cervical cancer remains a major cause of cancer mortality among women in India, driven primarily by persistent infection with high-risk human papillomavirus (HPV) genotypes. While HPV 16 and 18 are globally recognised as the most oncogenic, the prevalence of other high-risk types varies regionally, influencing prevention strategies. Methods: We conducted a cross-sectional study involving 923 women aged ≥30 years from diverse socio-economic backgrounds across urban and rural Karnataka. Cervical swabs were collected using the HC2 DNA Collection Device following counselling by obstetricians and gynaecologists in their respective hospitals. All positive samples underwent extended genotyping. Co-testing with Pap smear cytology was performed for all participants. Women with normal cytology were advised to repeat HPV testing after one year and offered HPV vaccination if <45 years. Those with abnormal cytology were referred for colposcopy, biopsy, and further management. Results: Of the 923 women screened, 35 (3.79%) tested positive for high-risk HPV genotypes. The most prevalent types were HPV 66 (54.3%) and HPV 33 (34.3%), followed by HPV 16 (14.3%) and HPV 58 (14.3%). HPV 18, 35, 45, 51, and 52 were detected in ≤4 cases each. This pattern represents a marked deviation from the globally dominant HPV 16/18 profile. Conclusions: The predominance of HPV 33 and 66 in this cohort highlights the need for region-specific HPV surveillance, extended genotyping in screening programmes, and reconsideration of vaccination strategies to ensure coverage of locally prevalent oncogenic strains.

British journal of healthcare and medical researchVol. 12(04)
Tamil Nadu Government Multi Super Speciality Hospital (IN)
Good health and well-being
Openalex Percentile: Top 39%
Geochemistry and Geologic Mapping
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