| Literature DB >> 31114629 |
Miriam Nakalembe1, Philippa Makanga1, Frank Mubiru1, Megan Swanson2, Jeffrey Martin3, Megan Huchko4.
Abstract
BACKGROUND: New strategies are needed to combat the high incidence of cervical cancer in resource-limited settings such as sub-Saharan Africa. Screening for high-risk human papillomavirus (hrHPV) DNA is sensitive for pre-cancer, but its lack of specificity results in substantial overtreatment in low resource settings where additional testing (e.g., colposcopy) is rarely available. Testing for hrHPV E6/E7 mRNA may enhance specificity, but little is known about its performance characteristics in resource-limited settings.Entities:
Keywords: Africa; Cervical cancer; Community-based screening; Human papillomavirus; Predictive value; Uganda; mRNA testing
Year: 2019 PMID: 31114629 PMCID: PMC6515623 DOI: 10.1186/s13027-019-0230-0
Source DB: PubMed Journal: Infect Agent Cancer ISSN: 1750-9378 Impact factor: 2.965
Characteristics of 1892 women from two rural districts of Uganda participating in a community-based study of cervical cancer screening
| Characteristic | Percentage |
|---|---|
| Age, in years | |
| 20–29 | 32% |
| 30–39 | 41% |
| ≥ 40 | 27% |
| Marital statusa | |
| Never married | 2.7% |
| Married | 83% |
| Separated/divorced/widowed | 14% |
| Educationa | |
| None | 18% |
| At least some primary | 61% |
| At least some secondary | 20% |
| At least some tertiary | 1.0% |
| Occupationa | |
| Unemployed | 79% |
| Employed, non-professional | 14% |
| Employed, professional | 7.4% |
| Distance of home from screening venuea | |
| | 60% |
| 3–5 km | 29% |
| > 5 km | 11% |
| Transport to screening venueb | |
| Walked | 89% |
| Other transport | 11% |
| Paritya | |
| 0 | 3.0% |
| 1–3 | 34% |
| 4–6 | 40% |
| > 6 | 23% |
| Pregnanta | 10% |
| Prior cervical cancer screeninga | 5.0% |
| HIV-infected, via self-reportc | 9.6% |
| Using antiretroviral therapyd | 98% |
amissing in 2 participants
bmissing in 19 participants
c225 participants reported never testing
damong those self-reporting to be HIV-infected
hrHPV prevalence, by self-reported HIV infection status, among women from two rural districts of Uganda participating in a community-based study of cervical cancer screening
| hrHPV Type Detected | HIV-infectedc Participants ( | HIV-uninfected Participants ( | HIV-untested Participants ( | All Participants ( |
|---|---|---|---|---|
| Any hrHPV | 40% (32 to 48%) | 19% (17 to 21%) | 17% (12 to 22%) | 21% (19 to 23%) |
| At least one of HPV-16, 18 and 45a | 11% (6.3 to 16%) | 4.0% (3.1 to 5.2%) | 4.0% (1.8 to 7.5%) | 4.6% (3.7 to 5.6%) |
| HPV-16a, b | 4.4% (1.8 to 8.8%) | 2.7% (1.9 to 3.6%) | 2.2% (0.7 to 5.1%) | 2.7% (2.1 to 3.6%) |
| HPV-18 and/or 45a, b | 6.9% (3.5 to 12%) | 1.5% (0.9 to 2.2% | 1.8% (0.5 to 4.5%) | 1.8% (1.3 to 2.6%) |
| At least one of HPV-31, 33, 35, 39, 51, 52, 56, 58, 59, 66 and 68 but without 16, 18 and 45 | 29% (22 to 36%) | 15% (13 to 17%) | 13% (8.8 to 18%) | 16% (14 to 18%) |
amay also include HPV-31, 33, 35, 39, 51, 52, 56, 58, 59, 66 and 68
bIncludes 2 patients who were positive for HPV-16 and HPV-18/45
cHIV infection status ascertained by self-report
Fig. 1A directed acyclic graph (DAG) depicting our hypothesized conception of the system under investigation. We sought to estimate the independent contribution of age, marital status, education, occupation (proxy for socioeconomic status), pregnancy, and HIV Infection status to the prevalence of HPV infection in Ugandan women. Exposure to HPV-infected sexual partners and immune status were not directly measured by our study and hence could not be evaluated. The DAG was used to guide which variables to control for when assessing the independent contribution of the various constructs
Evaluation of potential independent correlates of hrHPV E6/E7 mRNA-positivity among Ugandan women participating in a community-based study of cervical cancer screening. Separate analyses are shown for correlates of any hrHPV type and for a restricted set of HPV 16 or 18/45
| Characteristic | Any hrHPV Type | HPV 16 or 18/45 | ||||||
|---|---|---|---|---|---|---|---|---|
| Unadjusted | Adjusted | Unadjusted | Adjusted | |||||
| Age, per additional yeara | 0.97 (0.96 to 0.99) | < 0.001 | 0.97 (0.96 to 0.99) | < 0.001 | 1.20 (0.92 to 1.58) | 0.18 | 0.96 (0.92 to 0.99) | 0.024 |
| Marital statusb | ||||||||
| Never married | Ref. | Ref. | Ref. | Ref. | ||||
| Married | 0.71 (0.45 to 1.13) | 0.15 | 0.87 (0.50 to 1.52) | 0.50 | 1.15 (0.28 to 4.55) | 0.84 | 1.19 (0.30 to 4.74) | 0.81 |
| Separated/divorced/widowed | 0.96 (0.59 to 1.57) | 0.17 | 1.02 (0.56 to 1.85) | 0.95 | 1.36 (0.32 to 5.81) | 0.68 | 1.30 (0.29 to 5.76) | 0.73 |
| Educational levelc | ||||||||
| None | Ref. | Ref. | Ref. | Ref. | ||||
| As least some primary | 1.28 (0.97 to 1.69) | 0.079 | 1.17 (0.86 to 1.58) | 0.32 | 0.94 (0.51 to 1.73) | 0.84 | 0.73 (0.38 to 1.38) | 0.33 |
| At least some secondary | 1.39 (1.01 to 1.91) | 0.041 | 1.12 (0.78 to 1.63) | 0.52 | 1.58 (0.82 to 3.08) | 0.17 | 0.99 (0.46 to 2.14) | 0.98 |
| At least some tertiary | 1.68 (0.77 to 3.69) | 0.19 | 1.36 (0.58 to 3.17) | 0.48 | 2.64 (0.64 to 10.4) | 0.17 | 1.69 (0.35 to 8.10) | 0.51 |
| Occupationd | ||||||||
| Unemployed | Ref: | Ref: | Ref. | Ref. | ||||
| Non-professional | 1.17 (0.89 to 1.56) | 0.26 | 1.08 (0.79 to 1.46) | 0.63 | 1.64 (0.90 to 2.99) | 0.11 | 1.35 (0.68 to 2.67) | 0.39 |
| Professional | 1.44 (1.12 to 1.84) | 0.004 | 1.33 (0.98 to 1.80) | 0.068 | 2.13 (1.25 to 3.63) | 0.005 | 1.56 (0.77 to 3.15) | 0.21 |
| Pregnancy statuse | ||||||||
| Not pregnant | Ref. | Ref. | Ref. | Ref. | ||||
| Pregnant | 1.31 (1.02 to 1.69) | 0.036 | 1.37 (1.04 to 1.80) | 0.026 | 1.14 (0.60 to 2.17) | 0.69 | 1.30 (0.67 to 2.52) | 0.43 |
| HIV infection statusf | ||||||||
| HIV-uninfected | Ref. | Ref. | Ref. | Ref. | ||||
| HIV-infected | 2.07 (1.67 to 2.57) | < 0.001 | 2.20 (1.74 to 2.78) | < 0.001 | 2.62 (1.57 to 4.38) | < 0.001 | 3.08 (1.77 to 5.35) | < 0.001 |
aAge was adjusted for education, HIV infection status, marital status, pregnancy, and occupation
bMarital status was adjusted for age, education, HIV infection status, pregnancy, and occupation
cEducation was adjusted for age, HIV infection status, marital status, pregnancy, and occupation
dOccupation was adjusted for age, education, HIV infection status, marital status, and pregnancy
ePregnancy was adjusted for age, education, HIV infection status, marital status and occupation
fHIV infection status was adjusted for age, education, marital status, pregnancy, and occupation
Positive predictive value, by self-reported HIV infection status, of detecting hrHPV E6/E7 mRNA for the presence of CIN 2+ among women from two rural districts of Uganda participating in a community-based study of cervical cancer screening
| hrHPV Type Detected | HIV-infectedb Participants | HIV-uninfected Participants | HIV-untested Participants | All Participants | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Total No. | No. with CIN 2+ | Positive predictive value % (95% CI) | Total No. | No. with CIN 2+ | Positive predictive value % (95% CI) | Total No. | No. with CIN 2+ | Positive predictive value % (95% CI) | Total No. | No. with CIN 2+ | Positive predictive value% (95% CI) | |
| Any hrHPV | 42 | 4 | 9.8% (2.7 to 23%) | 193 | 12 | 6.3% (3.3 to 11%) | 20 | 5 | 25% (8.7 to 49%) | 255 | 21 | 8.2% (5.1 to 12%) |
| At least one of HPV-16, 18 and 45a | 10 | 1 | 10% (0.25 to 45%) | 43 | 4 | 9.5% (2.7 to 23%) | 5 | 4 | 80% (28 to 99%) | 58 | 9 | 15% (7.3 to 27%) |
| HPV-16a | 4 | 0 | 0% (0 to 60%) | 28 | 3 | 11% (2.3 to 28%) | 2 | 2 | 100% (16 to 100%) | 34 | 5 | 15% (5.0 to 31%) |
| HPV-18 and/or 45a | 7 | 1 | 14% (0.36 to 58%) | 16 | 1 | 6.3% (0.15 to 30%) | 3 | 2 | 67% (9.4 to 99%) | 26 | 4 | 15% (4.4 to 35%) |
| At least one of HPV-31, 33, 35, 39, 51, 52, 56, 58, 59, 66 and 68 but without 16, 18 and 45 | 32 | 3 | 9.1% (1.9 to 24%) | 150 | 8 | 29% (22 to 37%) | 15 | 1 | 13% (1.7 to 40%) | 197 | 12 | 6.1% (3.2 to 10%) |
amay also include HPV-31, 33, 35, 39, 51, 52, 56, 58, 59, 66 and 68
bHIV infection status ascertained by self-report