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Showing content from https://pubmed.ncbi.nlm.nih.gov/32007141/ below:

Impact of HPV vaccination and cervical screening on cervical cancer elimination: a comparative modelling analysis in 78 low-income and lower-middle-income countries

Comparative Study

. 2020 Feb 22;395(10224):575-590. doi: 10.1016/S0140-6736(20)30068-4. Epub 2020 Jan 30. Impact of HPV vaccination and cervical screening on cervical cancer elimination: a comparative modelling analysis in 78 low-income and lower-middle-income countries Jane J Kim², Karen Canfell³, Mélanie Drolet⁴, Guillaume Gingras⁴, Emily A Burger⁵, Dave Martin⁴, Kate T Simms⁶, Élodie Bénard⁴, Marie-Claude Boily⁷, Stephen Sy², Catherine Regan², Adam Keane⁶, Michael Caruana⁶, Diep T N Nguyen⁶, Megan A Smith⁶, Jean-François Laprise⁴, Mark Jit⁸, Michel Alary⁹, Freddie Bray¹⁰, Elena Fidarova¹¹, Fayad Elsheikh¹², Paul J N Bloem¹², Nathalie Broutet¹³, Raymond Hutubessy¹²

Affiliations

¹ Centre de recherche du CHU de Québec - Universite Laval, Québec, QC, Canada; Department of Social and Preventive Medicine, Universite Laval, Québec, QC, Canada; MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK. Electronic address: marc.brisson@crchudequebec.ulaval.ca.
² Center for Health Decision Science, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
³ Cancer Research Division, Cancer Council NSW, Sydney, NSW, Australia; School of Public Health, Sydney Medical School, University of Sydney, Sydney, NSW, Australia; Prince of Wales Clinical School, University of New South Wales, Sydney, NSW, Australia.
⁴ Centre de recherche du CHU de Québec - Universite Laval, Québec, QC, Canada.
⁵ Center for Health Decision Science, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Health Management and Health Economics, University of Oslo, Oslo, Norway.
⁶ Cancer Research Division, Cancer Council NSW, Sydney, NSW, Australia; School of Public Health, Sydney Medical School, University of Sydney, Sydney, NSW, Australia.
⁷ Centre de recherche du CHU de Québec - Universite Laval, Québec, QC, Canada; Department of Social and Preventive Medicine, Universite Laval, Québec, QC, Canada; MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
⁸ Centre for Mathematical Modelling of Infectious Disease, London School of Hygiene and Tropical Medicine, London, UK; Modelling and Economics Unit, Public Health England, London, UK; School of Public Health, University of Hong Kong, Hong Kong, China.
⁹ Centre de recherche du CHU de Québec - Universite Laval, Québec, QC, Canada; Department of Social and Preventive Medicine, Universite Laval, Québec, QC, Canada; Institut national de santé publique du Québec, Québec, QC, Canada.
¹⁰ Section of Cancer Surveillance, International Agency for Research on Cancer, Lyon, France.
¹¹ Department for the Management of Noncommunicable Diseases, Disability, Violence and Injury Prevention, World Health Organization, Geneva, Switzerland.
¹² Department of Immunization, Vaccines and Biologicals, World Health Organization, Geneva, Switzerland.
¹³ Department of Reproductive Health and Research, World Health Organization, Geneva, Switzerland.

PMID: 32007141
PMCID: PMC7043009
DOI: 10.1016/S0140-6736(20)30068-4

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Comparative Study

Impact of HPV vaccination and cervical screening on cervical cancer elimination: a comparative modelling analysis in 78 low-income and lower-middle-income countries

Marc Brisson et al. Lancet. 2020.

. 2020 Feb 22;395(10224):575-590. doi: 10.1016/S0140-6736(20)30068-4. Epub 2020 Jan 30. Authors Marc Brisson¹, Jane J Kim², Karen Canfell³, Mélanie Drolet⁴, Guillaume Gingras⁴, Emily A Burger⁵, Dave Martin⁴, Kate T Simms⁶, Élodie Bénard⁴, Marie-Claude Boily⁷, Stephen Sy², Catherine Regan², Adam Keane⁶, Michael Caruana⁶, Diep T N Nguyen⁶, Megan A Smith⁶, Jean-François Laprise⁴, Mark Jit⁸, Michel Alary⁹, Freddie Bray¹⁰, Elena Fidarova¹¹, Fayad Elsheikh¹², Paul J N Bloem¹², Nathalie Broutet¹³, Raymond Hutubessy¹² Affiliations

¹ Centre de recherche du CHU de Québec - Universite Laval, Québec, QC, Canada; Department of Social and Preventive Medicine, Universite Laval, Québec, QC, Canada; MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK. Electronic address: marc.brisson@crchudequebec.ulaval.ca.
² Center for Health Decision Science, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
³ Cancer Research Division, Cancer Council NSW, Sydney, NSW, Australia; School of Public Health, Sydney Medical School, University of Sydney, Sydney, NSW, Australia; Prince of Wales Clinical School, University of New South Wales, Sydney, NSW, Australia.
⁴ Centre de recherche du CHU de Québec - Universite Laval, Québec, QC, Canada.
⁵ Center for Health Decision Science, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Health Management and Health Economics, University of Oslo, Oslo, Norway.
⁶ Cancer Research Division, Cancer Council NSW, Sydney, NSW, Australia; School of Public Health, Sydney Medical School, University of Sydney, Sydney, NSW, Australia.
⁷ Centre de recherche du CHU de Québec - Universite Laval, Québec, QC, Canada; Department of Social and Preventive Medicine, Universite Laval, Québec, QC, Canada; MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
⁸ Centre for Mathematical Modelling of Infectious Disease, London School of Hygiene and Tropical Medicine, London, UK; Modelling and Economics Unit, Public Health England, London, UK; School of Public Health, University of Hong Kong, Hong Kong, China.
⁹ Centre de recherche du CHU de Québec - Universite Laval, Québec, QC, Canada; Department of Social and Preventive Medicine, Universite Laval, Québec, QC, Canada; Institut national de santé publique du Québec, Québec, QC, Canada.
¹⁰ Section of Cancer Surveillance, International Agency for Research on Cancer, Lyon, France.
¹¹ Department for the Management of Noncommunicable Diseases, Disability, Violence and Injury Prevention, World Health Organization, Geneva, Switzerland.
¹² Department of Immunization, Vaccines and Biologicals, World Health Organization, Geneva, Switzerland.
¹³ Department of Reproductive Health and Research, World Health Organization, Geneva, Switzerland.

PMID: 32007141
PMCID: PMC7043009
DOI: 10.1016/S0140-6736(20)30068-4

Item in Clipboard

Abstract

Background: The WHO Director-General has issued a call for action to eliminate cervical cancer as a public health problem. To help inform global efforts, we modelled potential human papillomavirus (HPV) vaccination and cervical screening scenarios in low-income and lower-middle-income countries (LMICs) to examine the feasibility and timing of elimination at different thresholds, and to estimate the number of cervical cancer cases averted on the path to elimination.

Methods: The WHO Cervical Cancer Elimination Modelling Consortium (CCEMC), which consists of three independent transmission-dynamic models identified by WHO according to predefined criteria, projected reductions in cervical cancer incidence over time in 78 LMICs for three standardised base-case scenarios: girls-only vaccination; girls-only vaccination and once-lifetime screening; and girls-only vaccination and twice-lifetime screening. Girls were vaccinated at age 9 years (with a catch-up to age 14 years), assuming 90% coverage and 100% lifetime protection against HPV types 16, 18, 31, 33, 45, 52, and 58. Cervical screening involved HPV testing once or twice per lifetime at ages 35 years and 45 years, with uptake increasing from 45% (2023) to 90% (2045 onwards). The elimination thresholds examined were an average age-standardised cervical cancer incidence of four or fewer cases per 100 000 women-years and ten or fewer cases per 100 000 women-years, and an 85% or greater reduction in incidence. Sensitivity analyses were done, varying vaccination and screening strategies and assumptions. We summarised results using the median (range) of model predictions.

Findings: Girls-only HPV vaccination was predicted to reduce the median age-standardised cervical cancer incidence in LMICs from 19·8 (range 19·4-19·8) to 2·1 (2·0-2·6) cases per 100 000 women-years over the next century (89·4% [86·2-90·1] reduction), and to avert 61·0 million (60·5-63·0) cases during this period. Adding twice-lifetime screening reduced the incidence to 0·7 (0·6-1·6) cases per 100 000 women-years (96·7% [91·3-96·7] reduction) and averted an extra 12·1 million (9·5-13·7) cases. Girls-only vaccination was predicted to result in elimination in 60% (58-65) of LMICs based on the threshold of four or fewer cases per 100 000 women-years, in 99% (89-100) of LMICs based on the threshold of ten or fewer cases per 100 000 women-years, and in 87% (37-99) of LMICs based on the 85% or greater reduction threshold. When adding twice-lifetime screening, 100% (71-100) of LMICs reached elimination for all three thresholds. In regions in which all countries can achieve cervical cancer elimination with girls-only vaccination, elimination could occur between 2059 and 2102, depending on the threshold and region. Introducing twice-lifetime screening accelerated elimination by 11-31 years. Long-term vaccine protection was required for elimination.

Interpretation: Predictions were consistent across our three models and suggest that high HPV vaccination coverage of girls can lead to cervical cancer elimination in most LMICs by the end of the century. Screening with high uptake will expedite reductions and will be necessary to eliminate cervical cancer in countries with the highest burden.

Funding: WHO, UNDP, UN Population Fund, UNICEF-WHO-World Bank Special Program of Research, Development and Research Training in Human Reproduction, Canadian Institute of Health Research, Fonds de recherche du Québec-Santé, Compute Canada, National Health and Medical Research Council Australia Centre for Research Excellence in Cervical Cancer Control.

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Figures
Figure 1

Dynamics of cervical cancer incidence…

Figure 1

Dynamics of cervical cancer incidence after HPV vaccination and cervical screening Average age-standardised…

Figure 1

Dynamics of cervical cancer incidence after HPV vaccination and cervical screening Average age-standardised cervical cancer incidence per 100 000 women-years (A) and relative reduction in incidence (B) after HPV vaccination and screening ramp-up in low-income and lower-middle-income countries. Median prediction from the three models. Vaccination coverage=90% at age 9 years (and at ages 10–14 years in 2020). Vaccine efficacy=100% against HPV16, 18, 31, 33, 45, 52, and 58. Vaccine duration=lifetime. Screening=HPV testing. Screening uptake=45% (2023–29), 70% (2030–44), and 90% (2045 onwards). Screen and treat efficacy=100%. Loss to follow-up=10%. Equilibrium occurs 90–100 years after the introduction of HPV vaccination only (and earlier for the screening scenarios). HPV=human papillomavirus.

Figure 2

Variability in model predictions of…

Figure 2

Variability in model predictions of the impact of HPV vaccination and screening strategies…

Figure 2

Variability in model predictions of the impact of HPV vaccination and screening strategies The average age-standardised cervical cancer incidence per 100 000 women-years over time in low-income countries and lower-middle-income countries, by World Bank income level (A) and region (B). The solid line represents the median prediction and shaded area represents the minimum and maximum predictions of the three models. Vaccination coverage=90% at age 9 years (and at ages 10–14 years in 2020). Vaccine efficacy=100% against HPV types 16, 18, 31, 33, 45, 52, and 58. Vaccine duration=lifetime. Screening=HPV testing. Screening uptake=45% (2023–29), 70% (2030–44), and 90% (2045 onwards). Screen and treat efficacy=100%. Loss to follow-up=10%. Equilibrium occurs 90–100 years after the introduction of HPV vaccination only (and earlier for the screening scenarios). HPV=human papillomavirus.

Figure 3

Global map of cervical cancer…

Figure 3

Global map of cervical cancer elimination in 78 low-income and lower-middle-income countries Age-standardised…

Figure 3

Global map of cervical cancer elimination in 78 low-income and lower-middle-income countries Age-standardised incidence of cervical cancer at equilibrium (2100–20), assuming status quo (A), girls-only vaccination (B), and girls-only vaccination and two lifetime screens (C). Median prediction from the three models. Vaccination coverage=90% at age 9 years (and at ages 10–14 years in 2020). Vaccine efficacy=100% against HPV16, 18, 31, 33, 45, 52, and 58.Vaccine duration=lifetime. Screening=HPV testing. Screening uptake=45% (2023–29), 70% (2030–44), and 90% (2045 onwards). Screen and treat efficacy=100%. Loss to follow-up=10%. See videos 1–3 for the global maps of cervical cancer elimination over time and the appendix (p 6) for the change in the distribution of the country-specific age-standardised cervical cancer incidence over time. HPV=human papillomavirus.

Figure 4

Impact of current cervical cancer…

Figure 4

Impact of current cervical cancer incidence on elimination predictions The age-standardised incidence of…

Figure 4

Impact of current cervical cancer incidence on elimination predictions The age-standardised incidence of cervical cancer (A) and relative (B) and absolute (C) reduction in incidence at equilibrium (2100–20) following vaccination and screening, as a function of initial age-standardised incidence of cervical cancer for each low-income and lower-middle-income country. Median prediction from the three models. Vaccination coverage=90% at age 9 years (and at ages 10–14 years in 2020). Vaccine efficacy=100% against HPV16, 18, 31, 33, 45, 52, and 58. Vaccine duration=lifetime. Screening=HPV testing. Screening uptake=45% (2023–29), 70% (2030–44), and 90% (2045 onwards). Screen and treat efficacy=100%. Loss to follow-up=10%. HPV=human papillomavirus.

Figure 5

Cervical cancer cases averted Cumulative…

Figure 5

Cervical cancer cases averted Cumulative cases averted by girls-only vaccination or girls-only vaccination…

Figure 5

Cervical cancer cases averted Cumulative cases averted by girls-only vaccination or girls-only vaccination plus screening, and incremental cases averted by screening in addition to vaccination over time, for lower-middle-income countries (A), low-income countries (B), and by region (C). Median prediction from the three models. Error bars represent the minimum and maximum estimates from the three models. Vaccination coverage=90% at age 9 years (and at ages 10–14 years in 2020). Vaccine efficacy=100% against HPV types 16, 18, 31, 33, 45, 52, and 58. Vaccine duration=lifetime. Screening=HPV testing. Screening uptake=45% (2023–29), 70% (2030–44), and 90% (2045 onwards). Screen and treat efficacy=100%. Loss to follow-up=10%. HPV=human papillomavirus.

Comment in

Eliminating cervical cancer.
The Lancet. The Lancet. Lancet. 2020 Feb 1;395(10221):312. doi: 10.1016/S0140-6736(20)30247-6. Lancet. 2020. PMID: 32007146 No abstract available.