Program-Specific Cost-Effectiveness Analysis: Breast Cancer Screening Policies for a Safety-Net Program

Melnikow, Joy; Tancredi, Daniel J.; Yang, Zhuo; Ritley, Dominique; Jiang, Yun; Popova, Svetlana; Rylett, Phillip; Knutson, Kirsten; Smalley, Sherie

doi:10.1016/j.jval.2013.06.013

Cited by 16 publications

(18 citation statements)

References 40 publications

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“…The analyses were based in a number of countries including the USA (n = 18 239,257,263,267,271,272,274,275,277,278,283,[289][290][291][292][293]295,298 ), the UK (n = 15 241,243,246,247,249,253,261,265,273,276,279,287,297,299,303 ), the Netherlands (n = 4 242,244,256,259 ), Hong Kong (n = 4 [304][305][306][307] ), Australia (n = 3 254,262,302 ), Italy (n = 3 245,251,252 ), Japan (n = 2 284,…”

Section: Study Overviewmentioning

confidence: 99%

Improvement in risk prediction, early detection and prevention of breast cancer in the NHS Breast Screening Programme and family history clinics: a dual cohort study

Evans

Astley

Stavrinos³

et al. 2016

Programme Grants Appl Res

117

126

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BackgroundIn the UK, women are invited for 3-yearly mammography screening, through the NHS Breast Screening Programme (NHSBSP), from the ages of 47–50 years to the ages of 69–73 years. Women with family histories of breast cancer can, from the age of 40 years, obtain enhanced surveillance and, in exceptionally high-risk cases, magnetic resonance imaging. However, no NHSBSP risk assessment is undertaken. Risk prediction models are able to categorise women by risk using known risk factors, although accurate individual risk prediction remains elusive. The identification of mammographic breast density (MD) and common genetic risk variants [single nucleotide polymorphisms (SNPs)] has presaged the improved precision of risk models.ObjectivesTo (1) identify the best performing model to assess breast cancer risk in family history clinic (FHC) and population settings; (2) use information from MD/SNPs to improve risk prediction; (3) assess the acceptability and feasibility of offering risk assessment in the NHSBSP; and (4) identify the incremental costs and benefits of risk stratified screening in a preliminary cost-effectiveness analysis.DesignTwo cohort studies assessing breast cancer incidence.SettingHigh-risk FHC and the NHSBSP Greater Manchester, UK.ParticipantsA total of 10,000 women aged 20–79 years [Family History Risk Study (FH-Risk); UK Clinical Research Network identification number (UKCRN-ID) 8611] and 53,000 women from the NHSBSP [aged 46–73 years; Predicting the Risk of Cancer At Screening (PROCAS) study; UKCRN-ID 8080].InterventionsQuestionnaires collected standard risk information, and mammograms were assessed for breast density by a number of techniques. All FH-Risk and 10,000 PROCAS participants participated in deoxyribonucleic acid (DNA) studies. The risk prediction models Manual method, Tyrer–Cuzick (TC), BOADICEA (Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm) and Gail were used to assess risk, with modelling based on MD and SNPs. A preliminary model-based cost-effectiveness analysis of risk stratified screening was conducted.Main outcome measuresBreast cancer incidence.Data sourcesThe NHSBSP; cancer registration.ResultsA total of 446 women developed incident breast cancers in FH-Risk in 97,958 years of follow-up. All risk models accurately stratified women into risk categories. TC had better risk precision than Gail, and BOADICEA accurately predicted risk in the 6268 single probands. The Manual model was also accurate in the whole cohort. In PROCAS, TC had better risk precision than Gail [area under the curve (AUC) 0.58 vs. 0.54], identifying 547 prospective breast cancers. The addition of SNPs in the FH-Risk case–control study improved risk precision but was not useful inBRCA1(breast cancer 1 gene) families. Risk modelling of SNPs in PROCAS showed an incremental improvement from using SNP18 used in PROCAS to SNP67. MD measured by visual assessment score provided better risk stratification than automatic measures, despite wide intra- and inter-reader variability. Using a MD-adjusted TC model in PROCAS improved risk stratification (AUC = 0.6) and identified significantly higher rates (4.7 per 10,000 vs. 1.3 per 10,000;p < 0.001) of high-stage cancers in women with above-average breast cancer risks. It is not possible to provide estimates of the incremental costs and benefits of risk stratified screening because of lack of data inputs for key parameters in the model-based cost-effectiveness analysis.ConclusionsRisk precision can be improved by using DNA and MD, and can potentially be used to stratify NHSBSP screening. It may also identify those at greater risk of high-stage cancers for enhanced screening. The cost-effectiveness of risk stratified screening is currently associated with extensive uncertainty. Additional research is needed to identify data needed for key inputs into model-based cost-effectiveness analyses to identify the impact on health-care resource use and patient benefits.Future workA pilot of real-time NHSBSP risk prediction to identify women for chemoprevention and enhanced screening is required.FundingThe National Institute for Health Research Programme Grants for Applied Research programme. The DNA saliva collection for SNP analysis for PROCAS was funded by the Genesis Breast Cancer Prevention Appeal.

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Section: Study Overviewmentioning

confidence: 99%

Improvement in risk prediction, early detection and prevention of breast cancer in the NHS Breast Screening Programme and family history clinics: a dual cohort study

Evans

Astley

Stavrinos³

et al. 2016

Programme Grants Appl Res

117

126

View full text Add to dashboard Cite

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“…These screening approaches have shown to be more cost-effective than no screening [8,9]. The US Preventive Services Task Force (USPSTF) recommends that women between 50 and 74 years of age should receive mammography screenings every two years, while those between 21 and 65 years of age should receive a Pap smear every 3 years [10].…”

Section: Introductionmentioning

confidence: 99%

The relationship between four health-related quality-of-life indicators and use of mammography and Pap test screening in US women

et al. 2015

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Purpose Limited evidence is available to explain the role of four components of health-related quality of life (HRQoL) on breast and cervical cancer screening. The objective of this study was to determine the relationship between four HRQoL aspects and use of mammography and Pap test screening in US women. Methods Data were obtained from the 2012 Behavioral Risk Factor Surveillance System (BRFSS). The outcome variables were receiving mammogram <2 versus ≥2 years in women aged 50-74 years, and receiving Pap test <3 versus ≥3 years in women aged 18-64 years. Eight logistic regression models were conducted to test the role of four HRQoL aspects (general health status, physical HRQoL, mental HRQoL, and activity limitation) on the two screening variables, after adjusting for covariates. Statistical analysis accounted for the complex sampling design of the BRFSS and the a priori alpha error was set at p ≤ 0.05. Results Among respondents, approximately 74% and 78% of the women received mammography and Pap test, respectively. Three HRQoL aspects (general health status, physical HRQoL, and activity limitation) were significantly associated with mammography use (all p-values<0.05), whereas two HRQoL aspects (general health status and physical HRQoL) were significantly associated with Pap test (p-values≤0.05). All significant relationships demonstrated higher cancer screening rates among individuals with better HRQoL. Conclusions HRQoL is an important factor associated with use of mammography and Pap test. Future studies should explore the mechanisms associated with an individual's HRQoL and use HRQoL assessment as an avenue to influence adherence to use of mammography and Pap tests.

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“…This will have the effect of underestimating both the effectiveness and the cost of screening; however, the difference is unlikely to be large. Previous studies have reported ICERs for digital mammography versus film of $180,333/LYG [34] and $331,000/QALY [35], suggesting that digital mammography may negatively impact the cost-effectiveness of screening programs. Lastly, our model assumes full participation and perfect adherence to screening schedules.…”

Section: Discussionmentioning

confidence: 99%

Cost-effectiveness of population-based mammography screening strategies by age range and frequency

Pataky

Phillips

Peacock

et al. 2014

Journal of Cancer Policy

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a b s t r a c tThere is little cost-effectiveness evidence for breast cancer screening with mammography in women under the age of 50 years, or over the age of 70 years, and available estimates vary widely. The Canadian Task Force on Preventive Health Care (CTFPHC) took cost-effectiveness into account in their recent recommendations on breast cancer screening, but no data are available from a Canadian setting. We constructed a microsimulation model using data from the Screening Mammography Program of British Columbia (BC) and the BC Cancer Registry. Eight screening strategies with varying age ranges and frequencies were compared to a reference strategy of no screening. Local screening, diagnostic, and treatment costs, and utility weights from the literature were applied to health states. Cost-effectiveness was expressed as incremental cost-effectiveness ratios (ICER) and cost-effectiveness acceptability curves, using the results of probabilistic sensitivity analysis. The most cost-effective strategies were biennial screening from ages 50 to 69, with an ICER of $28,921/QALY, and biennial screening from 40 to 69, with an ICER of $86,029/QALY. Screening women ages 40-49 was more cost-effective than screening women ages 70-74, which conflicts with the recommendations of the CTFPHC. There was, however, considerable uncertainty around these cost-effectiveness results. Regardless of willingness-to-pay, no single strategy was significantly more likely to be cost effective than the others. There is value in reducing the uncertainty around these cost-effectiveness estimates, to better inform future screening policy.

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Program-Specific Cost-Effectiveness Analysis: Breast Cancer Screening Policies for a Safety-Net Program

Cited by 16 publications

References 40 publications

Improvement in risk prediction, early detection and prevention of breast cancer in the NHS Breast Screening Programme and family history clinics: a dual cohort study

Improvement in risk prediction, early detection and prevention of breast cancer in the NHS Breast Screening Programme and family history clinics: a dual cohort study

The relationship between four health-related quality-of-life indicators and use of mammography and Pap test screening in US women

Cost-effectiveness of population-based mammography screening strategies by age range and frequency

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