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. 2020 May 6;15(5):e0231388.
doi: 10.1371/journal.pone.0231388. eCollection 2020.

The past, present and future impact of HIV prevention and control on HPV and cervical disease in Tanzania: A modelling study

Affiliations

The past, present and future impact of HIV prevention and control on HPV and cervical disease in Tanzania: A modelling study

Michaela T Hall et al. PLoS One. .

Abstract

Background: Women with HIV have an elevated risk of HPV infection, and eventually, cervical cancer. Tanzania has a high burden of both HIV and cervical cancer, with an HIV prevalence of 5.5% in women in 2018, and a cervical cancer incidence rate among the highest globally, at 59.1 per 100,000 per year, and an estimated 9,772 cervical cancers diagnosed in 2018. We aimed to quantify the impact that interventions intended to control HIV have had and will have on cervical cancer in Tanzania over a period from 1995 to 2070.

Methods: A deterministic transmission-dynamic compartment model of HIV and HPV infection and natural history was used to simulate the impact of voluntary medical male circumcision (VMMC), anti-retroviral therapy (ART), and targeted pre-exposure prophylaxis (PrEP) on cervical cancer incidence and mortality from 1995-2070.

Findings: We estimate that VMMC has prevented 2,843 cervical cancer cases and 1,039 cervical cancer deaths from 1995-2020; by 2070 we predict that VMMC will have lowered cervical cancer incidence and mortality rates by 28% (55.11 cases per 100,000 women in 2070 without VMMC, compared to 39.93 with VMMC only) and 26% (37.31 deaths per 100,000 women in 2070 without VMMC compared to 27.72 with VMMC), respectively. We predict that ART will temporarily increase cervical cancer diagnoses and deaths, due to the removal of HIV death as a competing risk, but will ultimately further lower cervical cancer incidence and mortality rates by 7% (to 37.31 cases per 100,000 women in 2070) and 5% (to 26.44 deaths per 100,000 women in 2070), respectively, relative to a scenario with VMMC but no ART. A combination of ART and targeted PrEP use is anticipated to lower cervical cancer incidence and mortality rates to 35.82 and 25.35 cases and deaths, respectively, per 100,000 women in 2070.

Conclusions: HIV treatment and control measures in Tanzania will result in long-term reductions in cervical cancer incidence and mortality. Although, in the near term, the life-extending capability of ART will result in a temporary increase in cervical cancer rates, continued efforts towards HIV prevention will reduce cervical cancer incidence and mortality over the longer term. These findings are critical background to understanding the longer-term impact of achieving cervical cancer elimination targets in Tanzania.

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Conflict of interest statement

KC is a co-PI of an investigator-initiated trial of primary HPV screening in Australia (‘Compass’) which is conducted and funded by the VCS Foundation, a government-funded health promotion charity, which has received a funding contribution from Roche Molecular Systems and Roche Tissue Diagnostics, AZ, USA. Neither KC nor her institution on her behalf have received funding from industry for this or any other project. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Figures

Fig 1
Fig 1. State-space diagram for HIV disease progression.
Note that viral suppression was assumed to halt disease progression and that all states are subject to other cause mortality.
Fig 2
Fig 2. State space diagram for the natural history of HPV and cervical cancer carcinogenesis; note that all compartments are subject to natural mortality, and detected cancer (grey) compartments are subject to stage-specific cervical cancer mortality and survival rates; CIN = cervical intraepithelial neoplasia; CC = cervical cancer.
Fig 3
Fig 3. Calibrated HIV outcomes.
(A) and (B) male and female HIV prevalence from 1995 to 2015; (C) HIV incidence from 1995 to 2015; (D) number of HIV deaths from 1995 to 2015. Error bars are 95% CI of observed data. Training data sourced from UNAIDS [22, 30,31,57].
Fig 4
Fig 4. Calibrated (A) age-specific cervical cancer incidence and (B) mortality for the year 2018 compared to estimated data sourced from the International Agency for Research on Cancer IARC [23].
Fig 5
Fig 5. (A) and (B) Age-specific HIV prevalence for males and females in 2016 compared to observed data; (C) and (D: age-distribution of AIDS diagnoses for males and females in 2011 compared to observed data.
Observed data from the Tanzanian Ministry of Finance (no confidence intervals available) [26, 59].
Fig 6
Fig 6. (A), (B) and (C) Age-specific HPV prevalence in cervical cytology (all cytological results) of HPV 16/18, HPV H5 and HPV OHR compared to observed data.
Observed data from Dartell et al 2012 (no confidence intervals available) [58].
Fig 7
Fig 7. Age specific rates of HSIL (detected high-grade squamous intraepithelial lesion consistent with CIN2/3) prevalence for (A) HIV positive and (B) HIV negative women.
Observed data from Dartell et al 2012 (no confidence intervals available) [58].
Fig 8
Fig 8. (A) Annual cervical cancer cases averted due to VMMC and ART (negative values under ART denote additional cases rather than cases averted); (B) cumulative cervical cancer cases averted due to VMMC and ART; (C) annual cervical cancer deaths averted due to VMMC and ART; (D) cumulative cervical cancer deaths averted due to VMMC and ART.
Fig 9
Fig 9. (A) and (B) Male and female HPV prevalence; (C) and (D) male and female HIV prevalence from 1995 to 2070 under five intervention scenarios.
Fig 10
Fig 10. (A) and (B) Age-standardised cervical cancer incidence and mortality rates among all women aged 0–99 years; (C) and (D) cervical cancer incidence and mortality rates among HIV negative women aged 0–99 years; (E) and (F) cervical cancer incidence and mortality rates among HIV positive women aged 0–99 years.
Age-standardised rates are calculated using the 2015 World Female Population [35].
Fig 11
Fig 11. (A) and (B) Male and female HPV prevalence; (C) and (D) male and female HIV prevalence; (E) and (F) cervical cancer incidence and mortality among all women; (G) and (H) cervical cancer incidence and mortality among HIV negative women; (I) and (J) cervical cancer incidence and mortality among HIV positive women, simulated in the year 2070 (error bars correspond to the total variation generated by the sensitivity analysis).
Fig 12
Fig 12. Correlation strength of selected outputs (HIV and HPV prevalence for males and females, and cervical cancer incidence and mortality) against intervention and behavioural parameters varied in multivariate sensitivity analysis.
Partial rank correlation analysis was performed on the ‘VMMC, target ART and PrEP’ scenario, as it is the only scenario considering all modelled interventions.

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