Abstract
An early economic evaluation to inform the translation into clinical practice of a spectroscopic liquid biopsy for the detection of brain cancer. Two specific aims are (1) to update an existing economic model with results from a prospective study of diagnostic accuracy and (2) to explore the potential of brain tumor-type predictions to affect patient outcomes and healthcare costs. A cost-effectiveness analysis from a UK NHS perspective of the use of spectroscopic liquid biopsy in primary and secondary care settings, as well as a cost-consequence analysis of the addition of tumor-type predictions was conducted. Decision tree models were constructed to represent simplified diagnostic pathways. Test diagnostic accuracy parameters were based on a prospective validation study. Four price points (GBP 50-200, EUR 57-228) for the test were considered. In both settings, the use of liquid biopsy produced QALY gains. In primary care, at test costs below GBP 100 (EUR 114), testing was cost saving. At GBP 100 (EUR 114) per test, the ICER was GBP 13,279 (EUR 15,145), whereas at GBP 200 (EUR 228), the ICER was GBP 78,300 (EUR 89,301). In secondary care, the ICER ranged from GBP 11,360 (EUR 12,956) to GBP 43,870 (EUR 50,034) across the range of test costs. The results demonstrate the potential for the technology to be cost-effective in both primary and secondary care settings. Additional studies of test use in routine primary care practice are needed to resolve the remaining issues of uncertainty-prevalence in this patient population and referral behavior.
Highlights
Brain tumors have among the worst prognosis of all cancer types
In the base case of the cost-effectiveness analysis (Table 1), updated with prospective validation results, spectroscopic liquid biopsy testing would lead to a gain of 15.4 quality-adjusted life-years (QALY) per 10,000 patients in primary care use and 65.4 QALYs per 10,000 patients in secondary care use
Compared with the base case result in the previous iteration of the evaluation, effectiveness is reduced due to the attenuation of diagnostic accuracy in the prospective data
Summary
Brain tumors have among the worst prognosis of all cancer types. The symptoms experienced by patients with a brain tumor can be vague and nonspecific and, as such, have only a poor predictive value from a diagnostic perspective [2;3]. The most common symptom of brain tumors in adults, occurs in 4.4 percent of all primary care consultations but has a positive predictive value of only 0.09 percent [2]. A study of symptom-based referral pathways for suspected brain tumor reported a positive predictive value (PPV) of 2.8 percent for severe red flag symptoms in terms of detecting a brain tumor on subsequent brain imaging [4]. There is clinical need for new tests to support brain tumor diagnosis that reduce both diagnostic delay and unnecessary imaging
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