|
Title
|
|
|
|
Human papillomavirus load and genotype analysis improves the prediction of invasive cervical cancer
| |
|
Author
|
|
|
|
| |
|
Abstract
|
|
|
|
| Human papillomavirus (HPV)-based cervical screening is a globally recommended health policy. Different HPV types have different risk for cervical cancer. For optimal HPV screening, the sensitivity and specificity for each HPV type at different viral loads should be known in a screening setting. HPV test results in about 1 million cervical samples analyzed during 2006 to 2014 were compared for 319 women who had developed invasive cervical cancer up to 8.5 years later and for 1911 matched control women. Detection including low viral loads resulted in markedly increased sensitivity for cervical cancer only for HPV types 16 and 18. Testing for HPV types 31, 33, 45 and 52 also increased the sensitivity for prediction of cervical cancer, but for these viruses, detection of low viral load did not further increase sensitivity. HPV types 35, 39, 51, 56, 58, 59, 66 and 68 only predicted occasional additional cervical cancer cases. Testing for HPV16/18 at low viral load plus testing for HPV31, 33, 45 and 52 at >3000 copies/mu L predicted 86.5% of cancers occurring within a year after testing, similar to the 89.4% that were predicted by testing for 14 HPV types. By contrast, the type and viral load-restricted testing greatly increased specificity: 6.3% of healthy women tested positive as compared to 11.7% of healthy women testing positive for the 14 HPV types commonly screened for today. Adequate HPV screening sensitivity, with considerable increase in specificity, can be obtained by testing only for HPV16/18/31/33/45/52, with detection of low viral load required only for HPV16/18. |
| |
|
Language
|
|
|
|
English
| |
|
Source (journal)
|
|
|
|
International journal of cancer. - New York, N.Y.
| |
|
Publication
|
|
|
|
Hoboken
:
Wiley
,
2021
| |
|
ISSN
|
|
|
|
0020-7136
| |
|
DOI
|
|
|
|
10.1002/IJC.33519
| |
|
Volume/pages
|
|
|
|
149
:3
(2021)
, p. 684-691
| |
|
ISI
|
|
|
|
000621634900001
| |
|
Pubmed ID
|
|
|
|
33586149
| |
|
Full text (Publisher's DOI)
|
|
|
|
| |
|
Full text (open access)
|
|
|
|
| |
|