FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2894912068> ?p ?o ?g. }

• W2894912068 endingPage "e3" @default.
• W2894912068 startingPage "e2" @default.
• W2894912068 abstract "In May, 2018, at the World Health Assembly, the Director-General of WHO made a global call for action towards the elimination of cervical cancer as a public health problem.1WHOWHO Director-General calls for all countries to take action to help end the suffering caused by cervical cancer.http://www.who.int/reproductivehealth/call-to-action-elimination-cervical-cancer/en/Date: May 19, 2018Date accessed: September 18, 2018Google Scholar The present focus of this initiative is to develop a global strategy and supporting approaches that can achieve this ambitious goal in every country within the 21st century. In their Article in The Lancet Public Health, Michaela Hall and colleagues2Hall MT Simms KT Lew JB et al.The projected timeframe until cervical cancer elimination in Australia: a modelling study.Lancet Public Health. 2018; (published online Oct 2.)http://dx.doi.org/10.1016/S2468-2667(18)30183-XScopus (204) Google Scholar take advantage of an extensively validated dynamic model of human papillomavirus (HPV) vaccination, natural history, and cervical screening3Hall MT Simms KT Lew JB Smith MA Saville M Canfell K Projected future impact of HPV vaccination and primary HPV screening on cervical cancer rates from 2017–2035: example from Australia.PLoS One. 2018; 13: e0185332Crossref PubMed Scopus (46) Google Scholar to estimate the timeframe until cervical cancer elimination in Australia. Depending on the incidence threshold used to define public health elimination, cervical cancer will be eliminated by 2020 (based on a rare cancer threshold of fewer than six new cases per 100 000 women annually) or by 2028 (based on a lower threshold of four new cases per 100 000 women annually). The authors also predict that the mortality associated with cervical cancer could decrease below one death per 100 000 women by 2034. Beyond the specific merit of modelling cervical cancer elimination in Australia, the study by Hall and colleagues exemplifies a process that is likely to be replicated in most countries when they address elimination of cervical cancer. Worldwide, mathematical modelling has become a standard approach in the planning and evaluation of public health interventions.4Garnett GP Cousens S Hallett TB Steketee R Walker N Mathematical models in the evaluation of health programmes.Lancet. 2011; 378: 515-525Summary Full Text Full Text PDF PubMed Scopus (157) Google Scholar To be reliable, model based-projections must use valid data and realistic assumptions. From that perspective, the Australian modelling team had access to the best possible sets of data that were essential to make their projections.3Hall MT Simms KT Lew JB Smith MA Saville M Canfell K Projected future impact of HPV vaccination and primary HPV screening on cervical cancer rates from 2017–2035: example from Australia.PLoS One. 2018; 13: e0185332Crossref PubMed Scopus (46) Google Scholar Furthermore, the routine monitoring of the prevalence of HPV, precancerous lesion detection rates, cervical cancer incidence, and the performance of HPV vaccination and screening programmes will enable adjustments of the predictions where necessary. At the global level, countries seeking to design, plan, and evaluate their own programmes for cervical cancer elimination can, in theory, rely on model-based projections that are informed by local datasets. However, in most low-income and middle-income countries (LMIC), where elimination remains a more distant prospect than predicted in Australia by Hall and colleagues, access to modelling is not to be taken for granted. Most published models have been primarily developed by international or academic institutions and have been used to assess the effects of preventing cervical cancer in high-income countries.5Brisson M Bénard É Drolet M et al.Population-level impact, herd immunity, and elimination after human papillomavirus vaccination: a systematic review and meta-analysis of predictions from transmission-dynamic models.Lancet Public Health. 2016; 1: e8-e17Summary Full Text Full Text PDF PubMed Scopus (166) Google Scholar In some cases, these models have been adapted to predict the expected effects of preventing cervical cancer in LMIC.6Baussano I Lazzarato F Ronco G Dillner J Franceschi S Benefits of catch-up in vaccination against human papillomavirus in medium- and low-income countries.Int J Cancer. 2013; 133: 1876-1881Crossref PubMed Scopus (13) Google Scholar, 7Campos NG Tsu V Jeronimo J Mvundura M Lee K Kim JJ To expand coverage, or increase frequency: quantifying the tradeoffs between equity and efficiency facing cervical cancer screening programs in low-resource settings.Int J Cancer. 2017; 140: 1293-1305Crossref PubMed Scopus (12) Google Scholar Evidently, access to open-source, validated, and well documented models to quantify the long-term medical, societal, and economic benefits of vaccination and screening in LMIC is essential. Technical guidance and transfer of modelling skills to LMIC must also be addressed. A more basic concern is the poor availability of data on cervical cancer incidence worldwide, particularly in LMIC. Although the feasibility of cervical cancer elimination, the definition of aspirational targets, and tailored in-country strategies might be driven by mathematical models, sensitivity analyses indicate that trends in the incidence of cervical cancer have a greater effect on future global estimates of elimination than other model parameters. At present, the likely future of the incidence of cervical cancer in most LMIC remains unknown. Taking the 47 constituent countries of sub-Saharan Africa as a regional example, only Uganda (Kampala) and Zimbabwe (Harare) have longstanding high-quality population-based cancer registries that are capable of providing such crucial information, and both report increasing trends in the incidence of cervical cancer.8Chokunonga E Borok MZ Chirenje ZM Nyakabau AM Parkin DM Trends in the incidence of cancer in the black population of Harare, Zimbabwe 1991–2010.Int J Cancer. 2013; 133: 721-729Crossref PubMed Scopus (131) Google Scholar, 9Wabinga HR Nambooze S Amulen PM Okello C Mbus L Parkin DM Trends in the incidence of cancer in Kampala, Uganda 1991–2010.Int J Cancer. 2014; 135: 432-439Crossref PubMed Scopus (123) Google Scholar On a global scale, about a third of countries (68 countries) have high-quality national (or subnational) data on cancer incidence10Bray F Colombet M Mery L et al.Cancer incidence in five continents, vol 11 (electronic version). International Agency for Research on Cancer, Lyon, France2017Google Scholar and about a quarter of countries (51 countries) can report all-cause mortality data to WHO;11WHOWorld Health Statistics 2018: monitoring health for the SDGs.http://www.who.int/gho/publications/world_health_statistics/2018/en/Date: 2018Date accessed: September 18, 2018Google Scholar in both instances, most of these countries are classified as high-income. Given the global status of recorded health data in general, a compelling case for a shift away from the ongoing investments in global health estimations and towards building the capacity of countries to collect and analyse their own data was made in 2018 by Ties Boerma and colleagues.12Boerma T Victora C Abouzahr C Monitoring country progress and achievements by making global predictions: is the tail wagging the dog?.Lancet. 2018; 392: 607-609Summary Full Text Full Text PDF PubMed Scopus (39) Google Scholar The growing burden of cancer worldwide reinforces the need for national implementation of tailored surveillance, with incidence—alongside risk factor and mortality data—as a core indicator of cancer surveillance programmes that are built around population-based cancer registries. These data systems permit governments to effectively monitor progress in national cancer control programmes. Cancer data inequities also need to be addressed in LMIC. Registries are often overlooked at the planning phase of cancer control, and their sustainable development requires their complete integration into broader political commitments, including the 2017 WHO Cancer Resolution, which was unanimously adopted by governments in 2017, to scale up and implement national cancer control programmes. Technical assistance is available to governments that seek to instigate surveillance plans, through the Global Initiative for Cancer Registry Development, which is a partnership of leading cancer organisations that aims to radically increase the quality, comparability, and use of cancer data in developing countries in informing their cancer policies and cancer research. In conclusion, the study by Hall and colleagues is a clear example of how modelling can contribute to assessing national progress in cancer control. Access to models and high-quality data are key in enabling countries to plan and effectively monitor health problems generally, and in tailoring preventative actions that one day will lead to the global elimination of cervical cancer as a major public health problem. For the Global Initiative for Cancer Registry Development see http://gicr.iarc.fr For the Global Initiative for Cancer Registry Development see http://gicr.iarc.fr IB reports grants from the Bill & Melinda Gates Foundation and the European Commission (CoheaHr). FB declares no competing interests. The projected timeframe until cervical cancer elimination in Australia: a modelling studyIf high-coverage vaccination and screening is maintained, at an elimination threshold of four new cases per 100 000 women annually, cervical cancer could be considered to be eliminated as a public health problem in Australia within the next 20 years. However, screening and vaccination initiatives would need to be maintained thereafter to maintain very low cervical cancer incidence and mortality rates. Full-Text PDF Open Access" @default.
• W2894912068 created "2018-10-12" @default.
• W2894912068 creator A5055346148 @default.
• W2894912068 creator A5064215217 @default.
• W2894912068 date "2019-01-01" @default.
• W2894912068 modified "2023-09-30" @default.
• W2894912068 title "Modelling cervical cancer elimination" @default.
• W2894912068 cites W1567352500 @default.
• W2894912068 cites W1878172041 @default.
• W2894912068 cites W2095718569 @default.
• W2894912068 cites W2104123633 @default.
• W2894912068 cites W2528304237 @default.
• W2894912068 cites W2559936830 @default.
• W2894912068 cites W2788982635 @default.
• W2894912068 cites W2797987669 @default.
• W2894912068 cites W2894633078 @default.
• W2894912068 doi "https://doi.org/10.1016/s2468-2667(18)30189-0" @default.
• W2894912068 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/30291039" @default.
• W2894912068 hasPublicationYear "2019" @default.
• W2894912068 type Work @default.
• W2894912068 sameAs 2894912068 @default.
• W2894912068 citedByCount "10" @default.
• W2894912068 countsByYear W28949120682019 @default.
• W2894912068 countsByYear W28949120682020 @default.
• W2894912068 countsByYear W28949120682021 @default.
• W2894912068 countsByYear W28949120682022 @default.
• W2894912068 countsByYear W28949120682023 @default.
• W2894912068 crossrefType "journal-article" @default.
• W2894912068 hasAuthorship W2894912068A5055346148 @default.
• W2894912068 hasAuthorship W2894912068A5064215217 @default.
• W2894912068 hasBestOaLocation W28949120681 @default.
• W2894912068 hasConcept C121608353 @default.
• W2894912068 hasConcept C126322002 @default.
• W2894912068 hasConcept C2778220009 @default.
• W2894912068 hasConcept C71924100 @default.
• W2894912068 hasConceptScore W2894912068C121608353 @default.
• W2894912068 hasConceptScore W2894912068C126322002 @default.
• W2894912068 hasConceptScore W2894912068C2778220009 @default.
• W2894912068 hasConceptScore W2894912068C71924100 @default.
• W2894912068 hasIssue "1" @default.
• W2894912068 hasLocation W28949120681 @default.
• W2894912068 hasLocation W28949120682 @default.
• W2894912068 hasOpenAccess W2894912068 @default.
• W2894912068 hasPrimaryLocation W28949120681 @default.
• W2894912068 hasRelatedWork W1998409886 @default.
• W2894912068 hasRelatedWork W1998885523 @default.
• W2894912068 hasRelatedWork W2081064592 @default.
• W2894912068 hasRelatedWork W2110269574 @default.
• W2894912068 hasRelatedWork W2384708512 @default.
• W2894912068 hasRelatedWork W2385052163 @default.
• W2894912068 hasRelatedWork W2514884906 @default.
• W2894912068 hasRelatedWork W3088389503 @default.
• W2894912068 hasRelatedWork W3097205217 @default.
• W2894912068 hasRelatedWork W4235306126 @default.
• W2894912068 hasVolume "4" @default.
• W2894912068 isParatext "false" @default.
• W2894912068 isRetracted "false" @default.
• W2894912068 magId "2894912068" @default.
• W2894912068 workType "article" @default.