Purpose: To assess the expected value (EVPI and EVSI and EVIC) of a proposed clinical trial of patients with early-stage breast cancer with the following aims (1) surveillance using currently available CA15-3/CA 27.29 biomarkers to detect recurrence (2) biobank creation of serial blood specimens that could be used to discover more accurate biomarkers for detecting breast cancer recurrence.
Method: We developed a decision-analytic model comparing the addition tumor biomarker to standard surveillance in patients with early-stage breast cancer. Model parameters and uncertainties, including quality-of-life indicators, were derived from literature values, clinical experts and multidisciplinary stakeholders. Our model also incorporated uncertainties in patient/provider adherence to recommended guidelines. The affected population was estimated from SEER data and discounted over a 10-year time horizon. Expected values were assessed at a $150K/QALY threshold in the base-case. The expected-value-of-individualized care (EVIC) i.e. total potential value of a biobank, was estimated by evaluating the impact of developing an improved diagnostic using biobank samples. Limiting assumptions were then applied to the EVIC to obtain a range of conservative biobank values.
Result: The standard care strategy was found to be cost-effective. However, the acceptability probability was only 55% with individual and population EVPI values of $4,600 and $1.7 billion (10-year time horizon). The EVSI for the trial ranged from $0.25 to $1.3 billion for trial sizes from 100 to 9,000 patients. Key uncertainties dominating EVPI and EVSI magnitudes were impact on survival through earlier detection of breast cancer, and quality-of-life impacts of testing including false positives, burden of increased testing, and deviations of uptake from clinical guidelines. The value of a biobank ranged from $136–700 million under a range of scenarios.
Conclusion: Our findings indicate that additional research assessing the use of breast cancer recurrence biomarkers and consequent earlier treatment could be highly valuable. Given the paucity of prior clinical data evaluating the effectiveness of existing markers, even a relatively small trial could provide substantial societal value. Model analysis suggests that trials focused on reducing uncertainty in survival and quality-of-life impact associated with breast cancer tumor marker testing, represent the most effective investments. Efforts to increase adherence to guidelines in real-world settings can also offer substantial healthcare system dividends. Considerable value may also be derived through trial patient samples stored in a biobank.
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