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Simulation modeling for stratified breast cancer screening - a systematic review of cost and quality of life assumptions.

ABSTRACT: The economic evaluation of stratified breast cancer screening gains momentum, but produces also very diverse results. Systematic reviews so far focused on modeling techniques and epidemiologic assumptions. However, cost and utility parameters received only little attention. This systematic review assesses simulation models for stratified breast cancer screening based on their cost and utility parameters in each phase of breast cancer screening and care.A literature review was conducted to compare economic evaluations with simulation models of personalized breast cancer screening. Study quality was assessed using reporting guidelines. Cost and utility inputs were extracted, standardized and structured using a care delivery framework. Studies were then clustered according to their study aim and parameters were compared within the clusters.Eighteen studies were identified within three study clusters. Reporting quality was very diverse in all three clusters. Only two studies in cluster 1, four studies in cluster 2 and one study in cluster 3 scored high in the quality appraisal. In addition to the quality appraisal, this review assessed if the simulation models were consistent in integrating all relevant phases of care, if utility parameters were consistent and methodological sound and if cost were compatible and consistent in the actual parameters used for screening, diagnostic work up and treatment. Of 18 studies, only three studies did not show signs of potential bias.This systematic review shows that a closer look into the cost and utility parameter can help to identify potential bias. Future simulation models should focus on integrating all relevant phases of care, using methodologically sound utility parameters and avoiding inconsistent cost parameters.

SUBMITTER: Arnold M

PROVIDER: S-EPMC5712150 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

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Simulation modeling for stratified breast cancer screening - a systematic review of cost and quality of life assumptions.

Arnold Matthias M

BMC health services research 20171202 1

<h4>Background</h4>The economic evaluation of stratified breast cancer screening gains momentum, but produces also very diverse results. Systematic reviews so far focused on modeling techniques and epidemiologic assumptions. However, cost and utility parameters received only little attention. This systematic review assesses simulation models for stratified breast cancer screening based on their cost and utility parameters in each phase of breast cancer screening and care.<h4>Methods</h4>A litera ...[more]

PMID: 29197417

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Project description:ImportanceThe age-based or "one-size-fits-all" breast screening approach does not take into account the individual variation in risk. Mammography screening reduces death from breast cancer at the cost of overdiagnosis. Identifying risk-stratified screening strategies with a more favorable ratio of overdiagnoses to breast cancer deaths prevented would improve the quality of life of women and save resources.ObjectiveTo assess the benefit-to-harm ratio and the cost-effectiveness of risk-stratified breast screening programs compared with a standard age-based screening program and no screening.Design, setting, and populationA life-table model was created of a hypothetical cohort of 364 500 women in the United Kingdom, aged 50 years, with follow-up to age 85 years, using (1) findings of the Independent UK Panel on Breast Cancer Screening and (2) risk distribution based on polygenic risk profile. The analysis was undertaken from the National Health Service perspective.InterventionsThe modeled interventions were (1) no screening, (2) age-based screening (mammography screening every 3 years from age 50 to 69 years), and (3) risk-stratified screening (a proportion of women aged 50 years with a risk score greater than a threshold risk were offered screening every 3 years until age 69 years) considering each percentile of the risk distribution. All analyses took place between July 2016 and September 2017.Main outcomes and measuresOverdiagnoses, breast cancer deaths averted, quality-adjusted life-years (QALYs) gained, costs in British pounds, and net monetary benefit (NMB). Probabilistic sensitivity analyses were used to assess uncertainty around parameter estimates. Future costs and benefits were discounted at 3.5% per year.ResultsThe risk-stratified analysis of this life-table model included a hypothetical cohort of 364 500 women followed up from age 50 to 85 years. As the risk threshold was lowered, the incremental cost of the program increased linearly, compared with no screening, with no additional QALYs gained below 35th percentile risk threshold. Of the 3 screening scenarios, the risk-stratified scenario with risk threshold at the 70th percentile had the highest NMB, at a willingness to pay of £20 000 (US $26 800) per QALY gained, with a 72% probability of being cost-effective. Compared with age-based screening, risk-stratified screening at the 32nd percentile vs 70th percentile risk threshold would cost £20 066 (US $26 888) vs £537 985 (US $720 900) less, would have 26.7% vs 71.4% fewer overdiagnoses, and would avert 2.9% vs 9.6% fewer breast cancer deaths, respectively.Conclusions and relevanceNot offering breast cancer screening to women at lower risk could improve the cost-effectiveness of the screening program, reduce overdiagnosis, and maintain the benefits of screening.

Project description:ObjectiveTo assess the overall cost effectiveness of the NHS breast screening programme, based on findings of the Independent UK Panel on Breast Cancer Screening and taking into account the uncertainty of associated estimates of benefits, harms, and costs.DesignA life table model comparing data from two cohorts.SettingUnited Kingdom's health service.Participants and interventions364,500 women aged 50 years-the population of 50 year old women in England and Wales who would be eligible for screening-were followed up for 35 years without screening, compared with a similar cohort who had regular mammographic screening between ages 50 and 70 years and were then followed for another 15 years.Main outcome measuresBetween the cohorts, we compared the number of breast cancer diagnoses, number of deaths from breast cancer, number of deaths from other causes, person years of survival adjusted for health quality, and person years of survival with breast cancer. We also calculated the costs of treating primary and end stage breast cancer, and the costs of screening. Probabilistic sensitivity analysis explored the effect of uncertainty in key input parameters on the model outputs.ResultsUnder the base case scenario (using input parameters derived from the Independent Panel Review), there were 1521 fewer deaths from breast cancer and 2722 overdiagnosed breast cancers. Discounting future costs and benefits at a rate of 3.5% resulted in an additional 6907 person years of survival in the screened cohort, at a cost of 40,946 additional years of survival after a diagnosis of breast cancer. Screening was associated with 2040 additional quality adjusted life years (QALYs) at an additional cost of £42.5m (€49.8m; $64.7m) in total or £20,800 per QALY gained. The gain in person time survival over 35 years was 9.2 days per person and 2.7 quality adjusted days per person screened. Probabilistic sensitivity analysis showed that this incremental cost effectiveness ratio varied widely across a range of plausible scenarios. Screening was cost effective at a threshold of £20,000 per QALY gained in 2260 (45%) scenarios, but in 588 (12%) scenarios, screening was associated with a reduction in QALYs.ConclusionThe NHS breast screening programme is only moderately likely to be cost effective at a standard threshold. However, there is substantial uncertainty in the model parameter estimates, and further primary research will be needed for cost effectiveness studies to provide definitive data to inform policy.

Project description:BackgroundThe effectiveness of breast cancer screening is still under debate. Our objective was to systematically review studies assessing personalized breast cancer screening strategies based on women's individual risk and to conduct a risk of bias assessment.MethodsWe followed the standard methods of The Cochrane Collaboration and PRISMA declaration and searched the MEDLINE, EMBASE and Clinical Trials databases for studies published in English. The quality of the studies was assessed using the ISPOR-AMCP-NPC Questionnaire and The Cochrane Risk of Bias Tool. Two independent reviewers screened full texts and evaluated the risk of bias.ResultsOut of the 1533 initially retrieved citations, we included 13 studies. Three studies were randomized controlled trials, while nine were mathematical modeling studies, and one was an observational pilot study. The trials are in the recruitment phase and have not yet reported their results. All three trials used breast density and age to define risk groups, and two of them included family history, previous biopsies, and genetic information. Among the mathematical modeling studies, the main risk factors used to define risk groups were breast density, age, family history, and previous biopsies. Six studies used genetic information to define risk groups. The most common outcome measures were the gain in quality-adjusted life years (QALY), absolute costs, and incremental cost-effectiveness ratio (ICER), while the main outcome in the observational study was the detection rate. In all models, personalized screening strategies were shown to be effective. The randomized trials were of good quality. The modeling studies showed moderate risk of bias but there was wide variability across studies. The observational study showed a low risk of bias but its utility was moderate due to its pilot design and its relatively small scale.ConclusionsThere is some evidence of the effectiveness of screening personalization in terms of QUALYs and ICER from the modeling studies and the observational study. However, evidence is lacking on feasibility and acceptance by the target population.Review registrationPROSPERO: CRD42018110483.

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Simulation modeling for stratified breast cancer screening - a systematic review of cost and quality of life assumptions.

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Simulation modeling for stratified breast cancer screening - a systematic review of cost and quality of life assumptions.

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