Abstract
OBJECTIVE: This study addresses the following 3 questions posed by the US Preventive Services Task Force: (1) at what age should screening for cervical cancer begin; (2) at what age should screening for cervical cancer end; and (3) how do the benefits and potential harms of screening strategies that use human papillomavirus DNA testing in conjunction with cytology (cotesting) compare with those strategies that use cytology only? MATERIALS AND METHODS: A Markov model was updated and used to quantify clinical outcomes (i.e., colposcopies, cancers, and life expectancy) associated with different screening strategies. RESULTS: Screening in the teenaged years is associated with a high number of colposcopies (harms), small differences in cancers detected and, as a result, small gains in life expectancy (benefits). Screening women beginning in the early 20s provides a reasonable balance of the harms and benefits of screening. Among women who have been screened according to the current recommendations for cervical cancer (beginning at age 21 years and conducted every 3 years with cytology), screening beyond 65 years is associated with small additional gains in life expectancy but large increases in colposcopies. For cotesting, a strategy of cytology only conducted every 3 years, followed by cotesting conducted every 5 years (for women ≥30 years), is associated with fewer colposcopies and greater gains in life expectancy compared with screening with cytology only conducted every 3 years. CONCLUSIONS: The results of this modeling study support current US Preventive Services Task Force recommendations for cervical cancer screening.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 193-202 |
| Number of pages | 10 |
| Journal | Journal of lower genital tract disease |
| Volume | 17 |
| Issue number | 2 |
| DOIs | |
| State | Published - Apr 2013 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Cervical cancer screening
- Decision
- Modeling
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