Cost-effectiveness of a new autoantibody test added to Computed Tomography (CT) compared to CT surveillance alone in the diagnosis of lung cancer amongst patients with indeterminate pulmonary nodules.

Oncimmune's EarlyCDT®-Lung is a simple ELISA blood test that measures seven lung cancer specific autoantibodies and is used in the assessment of malignancy risk in patients with indeterminate pulmonary nodules (IPNs). The objective of this study was to examine the cost-effectiveness of EarlyCDT-Lung in the diagnosis of lung cancer amongst patients with IPNs in addition to CT surveillance, compared to CT surveillance alone which is the current recommendation by the British Thoracic Society guidelines. A model consisting of a combination of a decision tree and Markov model was developed using the outcome measure of the quality adjusted life year (QALY). A life-time time horizon was adopted. The model was parameterized using a range of secondary sources. At £70 per test, EarlyCDT-Lung and CT surveillance was found to be cost-effective compared to CT surveillance alone with an incremental cost-effectiveness ratio (ICER) of less than £2,500 depending on the test accuracy parameters used. It was also found that EarlyCDT-Lung can be priced up to £1,177 and still be cost-effective based on cost-effectiveness acceptance threshold of £20,000 / QALY. Further research to resolve parameter uncertainty, was not found to be of value. The results here demonstrate that at £70 per test the EarlyCDT-Lung will have a positive impact on patient outcomes and coupled with CT surveillance is a cost-effective approach to the management of patients with IPNs. The conclusions drawn from this analysis are robust to realistic variation in the parameters used in the model.

Cost-effectiveness of an autoantibody test (EarlyCDT-Lung) as an aid to early diagnosis of lung cancer in patients with incidentally detected pulmonary nodules.

OBJECTIVE: Patients who have incidentally detected pulmonary nodules and an estimated intermediate risk (5-60%) of lung cancer frequently are followed via computed tomography (CT) surveillance to detect nodule growth, despite guidelines for a more aggressive diagnostic strategy. We examined the cost-effectiveness of an autoantibody test (AABT)-Early Cancer Detection Test-Lung (EarlyCDT-LungTM)-as an aid to early diagnosis of lung cancer among such patients. METHODS: We developed a decision-analytic model to evaluate use of the AABT versus CT surveillance alone. In the model, patients with a positive AABT-because they are at substantially enhanced risk of lung cancer-are assumed to go directly to biopsy, resulting in diagnosis of lung cancer in earlier stages than under current guidelines (a beneficial stage shift). Patients with a negative AABT, and those scheduled for CT surveillance alone, are assumed to have periodic CT screenings to detect rapid growth and thus to have their lung cancers diagnosed-on average-at more advanced stages. RESULTS: Among 1,000 patients who have incidentally detected nodules 8-30 mm, have an intermediate-risk of lung cancer, and are evaluated by CT surveillance alone, 95 (9.5%) are assumed to have lung cancer (local, 73.6%; regional, 22.0%; distant, 4.4%). With use of the AABT set at a sensitivity/specificity of 41%/93% (stage shift = 10.8%), although expected costs would be higher by $949,442 ($949 per person), life years would be higher by 53 (0.05 per person), resulting in a cost per life-year gained of $18,029 and a cost per quality-adjusted life year (QALY) gained of $24,330. With use of the AABT set at a sensitivity/specificity of 28%/98% (stage shift = 7.4%), corresponding cost-effectiveness ratios would be $18,454 and $24,833. CONCLUSIONS: Under our base-case assumptions, and reasonable variations thereof, using AABT as an aid in the early diagnosis of lung cancer in patients with incidentally detected pulmonary nodules who are estimated to be at intermediate risk of lung cancer and are scheduled for CT surveillance alone is likely to be a cost-effective use of healthcare resources.

Signal stratification of autoantibody levels in serum samples and its application to the early detection of lung cancer.

BACKGROUND: Further signal stratification for the EarlyCDT®-Lung test should facilitate interpretation of the test, leading to more precise interventions for particular patients. METHODS: Samples were measured for the presence of autoantibodies to seven tumor-associated antigens (TAAs) (p53, NY-ESO-1, CAGE, GBU4-5, SOX2, MAGE A4, and HuD). In addition to the current test cut-offs (determined using a previously reported Validation case-control sample set, set A; n=501), new high and low cut-offs were set in order to maximize the test's positive and negative predictive values (PPV and NPV, respectively). All three sets of cut-offs were applied to two confirmatory datasets: (I) the case-control set B (n=751), and (II) Population-derived set C (n=883), and all three datasets combined (n=2,135). RESULTS: For the Validation dataset, cancer/non-cancer positivity for current cut-offs was 41%/9% (PPV =0.109, 1 in 9). The high positive stratum improved this to 25%/2% (PPV =0.274, 1 in 4). The low negative stratum improved this to 8%/23% (NPV =0.990, 1 in 105). This provides a 25-fold difference in lung cancer probability between the highest and lowest groups. The test performs equally well in subjects who fulfilled the entry risk criteria for the National Lung Screening Trial (NLST) and subjects who did not meet the NLST criteria. CONCLUSIONS: The EarlyCDT®-Lung test has been converted to a four-stratum test by the addition of high and low sets of cut-offs: patients are thus stratified into four risk categories. This stratification will enable personalization of subsequent screening and treatment programs for high risk individuals or patients with lung nodules.

EarlyCDT®-Lung test: improved clinical utility through additional autoantibody assays.

Tumor-associated autoantibodies (AAbs) have been described in patients with lung cancer, and the EarlyCDT®-Lung test that measures such AAbs is available as an aid for the early detection of lung cancer in high-risk populations. Improvements in specificity would improve its cost-effectiveness, as well as reduce anxiety associated with false positive tests. Samples from 235 patients with newly diagnosed lung cancer and matched controls were measured for the presence of AAbs to a panel of six (p53, NY-ESO-1, CAGE, GBU4-5, Annexin I, and SOX2) or seven (p53, NY-ESO-1, CAGE, GBU4-5, SOX2, HuD, and MAGE A4) antigens. Data were assessed in relation to cancer type and stage. The sensitivity and specificity of these two panels were also compared in two prospective consecutive series of 776 and 836 individuals at an increased risk of developing lung cancer. The six-AAb panel gave a sensitivity of 39% with a specificity of 89 %, while the seven-AAb panel gave a sensitivity of 41 % with a specificity of 91 % which, once adjusted for occult cancers in the population, resulted in a specificity of 93 %. Analysis of these AAb assays in the at-risk population confirmed that the seven-AAb panel resulted in a significant increase in the specificity of the test from 82 to 90 %, with no significant change in sensitivity. The change from a six- to a seven-AAb assay can improve the specificity of the test and would result in a PPV of 1 in 8 and an overall accuracy of 92 %.