ArticleBMC cancer2014
Modeling optimal cervical cancer prevention strategies in Nigeria.
Article in BMC cancer, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 3 of them syntheses that pooled 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.
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.
Who cites it
15 citing papers in PubMed, 3 syntheses or guidelines pooled it, 30 citations in OpenAlex.
- The cost-effectiveness of bivalent, quadrivalent, and nine-valent HPV vaccination in Asia: a systematic review.Archives of gynecology and obstetrics · 2022Pooled it
- Barriers to uptake of cervical cancer screening among women in Nigeria: a systematic review.African health sciences · 2022Pooled it
- Cervical cancer prevention and treatment research in Africa: a systematic review from a public health perspective.BMC women's health · 2016Pooled it
- Vaccine Development, Its Implementation and Price Setting: A Historical Perspective with Proposed Ways to Move Forward.Journal of market access & health policy · 2025Article
- Modelling epidemiological and economics processes - the case of cervical cancer.Health economics review · 2025Review
- Modeling optimal combination of breast and cervical cancer screening strategies in China.BMC women's health · 2025Article
- Examining barriers and facilitators of HPV vaccination in Nigeria, in the context of an innovative delivery model: a mixed-methods study.BMJ public health · 2023Article
- Identification of an Optimal COVID-19 Booster Allocation Strategy to Minimize Hospital Bed-Days with a Fixed Healthcare Budget.Vaccines · 2023Article
- Effect of a community-based multicomponent intervention on cervical cancer behavior among women - A randomized controlled trial.Journal of education and health promotion · 2022Article
- Reducing dengue fever cases at the lowest budget: a constrained optimization approach applied to Thailand.BMC public health · 2021Article
- Awareness, Knowledge and Attitudes Towards Cervical Cancer Amongst HIV-Positive Women Receiving Care in a Tertiary Hospital in Nigeria.Journal of cancer education : the official journal of the American Association for Cancer Education · 2018Article
- Projected cervical Cancer incidence in Swaziland using three methods and local survey estimates.BMC cancer · 2018Article
- Cost-effectiveness of Human Papilloma Virus (HPV) vaccination in Nigeria: a decision analysis using pragmatic parameter estimates for cost and programme coverage.BMC health services research · 2017Article
- The Need for Societal Investment to Improve Cervical Cancer Outcomes in Nigeria: A commentary.African journal of reproductive health · 2017Article
- Operations research in global health: a scoping review with a focus on the themes of health equity and impact.Health research policy and systems · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThis study aims to assess the most efficient combinations of vaccination and screening coverage for the prevention of cervical cancer (CC) at different levels of expenditure in Nigeria.
methodsAn optimization procedure, using a linear programming approach and requiring the use of two models (an evaluation and an optimization model), was developed. The evaluation model, a Markov model, estimated the annual number of CC cases at steady state in a population of 100,000 women for four alternative strategies: screening only; vaccination only; screening and vaccination; and no prevention. The results of the Markov model for each scenario were used as inputs to the optimization model determining the optimal proportion of the population to receive screening and/or vaccination under different scenarios. The scenarios varied by available budget, maximum screening and vaccination coverage, and overall reachable population.
resultsIn the base-case optimization model analyses, with a coverage constraint of 20% for one lifetime screening, 95% for vaccination and a budget constraint of $1 per woman per year to minimize CC incidence, the optimal mix of prevention strategies would result in a reduction of CC incidence of 31% (3-dose vaccination available) or 46% (2-dose vaccination available) compared with CC incidence pre-vaccination. With a 3-dose vaccination schedule, the optimal combination of the different strategies across the population would be 20% screening alone, 39% vaccination alone and 41% with no prevention, while with a 2-dose vaccination schedule the optimal combination would be 71% vaccination alone, and 29% with no prevention. Sensitivity analyses indicated that the results are sensitive to the constraints included in the optimization model as well as the cervical intraepithelial neoplasia (CIN) and CC treatment cost.
conclusionsThe results of the optimization model indicate that, in Nigeria, the most efficient allocation of a limited budget would be to invest in both vaccination and screening with a 3-dose vaccination schedule, and in vaccination alone before implementing a screening program with a 2-dose vaccination schedule.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.