Evidence map›Paper›PMID 22409292›Full record

ArticlePharmacoEconomics2012

Selecting a mix of prevention strategies against cervical cancer for maximum efficiency with an optimization program.

Nadia Demarteau, Thomas Breuer, Baudouin Standaert

Open access · bronzeAbstract readComparative Study
PubMed Publisher
In one paragraph

Article in PharmacoEconomics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
2.7field-weighted citation impact, top 10% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

24 citing papers in PubMed, 43 citations in OpenAlex.

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  12. 2. How is the economic assessment of vaccines performed today?Journal of market access & health policy · 2017
    Review
  13. 3. How comprehensive can we be in the economic assessment of vaccines?Journal of market access & health policy · 2017
    Review
  14. Article
  15. Promise of cancer stem cell vaccine.Human vaccines & immunotherapeutics · 2015
    Article
  16. Article
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  20. Budget constraint and vaccine dosing: a mathematical modelling exercise.Cost effectiveness and resource allocation : C/E · 2014
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 2 countries.

Nadia DemarteauHealth Economics, Global Vaccine Development, GlaxoSmithKline Biologicals, Wavre, Belgium. nadia.x.demarteau@gskbio.com
Thomas Breuer
Baudouin Standaert
GlaxoSmithKline (Belgium) · BEGlaxoSmithKline (United Kingdom) · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundScreening and vaccination against human papillomavirus (HPV) can protect against cervical cancer. Neither alone can provide 100% protection. Consequently it raises the important question about the most efficient combination of screening at specified time intervals and vaccination to prevent cervical cancer.

objectiveOur objective was to identify the mix of cervical cancer prevention strategies (screening and/or vaccination against HPV) that achieves maximum reduction in cancer cases within a fixed budget.

methodsWe assessed the optimal mix of strategies for the prevention of cervical cancer using an optimization program. The evaluation used two models. One was a Markov cohort model used as the evaluation model to estimate the costs and outcomes of 52 different prevention strategies. The other was an optimization model in which the results of each prevention strategy of the previous model were entered as input data. The latter model determined the combination of the different prevention options to minimize cervical cancer under budget, screening coverage and vaccination coverage constraints. We applied the model in two countries with different healthcare organizations, epidemiology, screening practices, resource settings and treatment costs: the UK and Brazil. 100,000 women aged 12 years and above across the whole population over a 1-year period at steady state were included. The intervention was papanicolaou (Pap) smear screening programmes and/or vaccination against HPV with the bivalent HPV 16/18 vaccine (Cervarix® [Cervarix is a registered trademark of the GlaxoSmithKline group of companies]). The main outcome measures were optimal distribution of the population between different interventions (screening, vaccination, screening plus vaccination and no screening or vaccination) with the resulting number of cervical cancer and associated costs.

resultsIn the base-case analysis (= same budget as today), the optimal prevention strategy would be, after introducing vaccination with a coverage rate of 80% in girls aged 12 years and retaining screening coverage at pre-vaccination levels (65% in the UK, 50% in Brazil), to increase the screening interval to 6 years (from 3) in the UK and to 5 years (from 3) in Brazil. This would result in a reduction of cervical cancer by 41% in the UK and by 54% in Brazil from pre-vaccination levels with no budget increase. Sensitivity analysis shows that vaccination alone at 80% coverage with no screening would achieve a cervical cancer reduction rate of 20% in the UK and 43% in Brazil compared with the pre-vaccination situation with a budget reduction of 30% and 14%, respectively. In both countries, the sharp reduction in cervical cancer is seen when the vaccine coverage rate exceeds the maximum screening coverage rate, or when screening coverage rate exceeds the maximum vaccine coverage rate, while maintaining the budget. As with any model, there are limitations to the value of predictions depending upon the assumptions made in each model.

conclusionsSpending the same budget that was used for screening and treatment of cervical cancer in the pre-vaccination era, results of the optimization program show that it would be possible to substantially reduce the number of cases by implementing an optimal combination of HPV vaccination (80% coverage) and screening at pre-vaccination coverage (65% UK, 50% Brazil) while extending the screening interval to every 6 years in the UK and 5 years in Brazil.

Indexed as

AdolescentAdultAgedBrazilChildFemaleHumansMarkov ChainsMass ScreeningMiddle AgedModels, TheoreticalPapillomavirus InfectionsPapillomavirus VaccinesTime FactorsUnited StatesUterine Cervical Neoplasmshuman papillomavirus vaccine, L1 type 16, 18Papillomavirus Vaccines

Identifiers

PMID22409292
OpenAlexW2050700128

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.