Lung cancer screening with CT scans is leading to a significant increase in the number of patients diagnosed with lung nodules

  • Over 95% of positive CT scans are false positives, i.e. not cancer
  • About 50% of larger CT detected nodules are Intermediate1 risk level (10-65% risk, circa 8mm to 20mm in diameter)

EarlyCDT-Lung significantly aids the assessment of malignancy risk in pulmonary nodules

  • A positive EarlyCDT-Lung result can be used to ‘rule-in’ lung nodules as malignant: nearly 4 out of 5 positive results are a true cancer with a High Level result, and 1 in 1.7 for a Moderate Level result
  • EarlyCDT-Lung can help reduce the number of patients in ‘watchful waiting’ and aid early lung cancer detection, leading to earlier intervention and better patient outcomes
  • A High Level EarlyCDT-Lung result has high Specificity (98%), PPV > 78% and Accuracy 84% in patients with nodules2
  • A Moderate Level EarlyCDT-Lung result also has high Specificity (93%), PPV 59% and Accuracy 83%2
  • A High Level EarlyCDT-Lung result shifts all Intermediate Risk level (10-65%, circa 8-20mm in diameter) nodules to Intervention1 risk (>65%)
  • A ‘Moderate Level’ EarlyCDT-Lung result adds more than 25% to the calculated malignancy risk of a nodule, shifting some nodules from Intermediate to Intervention1 risk level
  • A ‘No Significant Level of Autoantibodies Detected’ EarlyCDT-Lung result should not change the clinical management of lung nodules

EarlyCDT-Lung significantly improves Positive Predictive value (PPV) for the assessment of risk of lung nodule malignancy3

1Gould MK, et al. Evaluation of individuals with pulmonary nodules: when is it lung cancer? Diagnosis and management of lung cancer, 3rd ed: American College of Chest Physicians evidence-based clinical practice guidelines. Chest 2013; 143(5):e93S-e120S, https://www.ncbi.nlm.nih.gov/pubmed/23649456
2 Based on lung cancer prevalence of 20%
3 Massion PP, Healey GF, Peek LJ, Fredericks L, Sewell HF, Murray A, Robertson JF. Autoantibody Signature Enhances the Positive Predictive Power of Computed Tomography and Nodule-Based Risk Models for Detection of Lung Cancer. J Thorac Oncol. 2017 Mar;12(3):578-584. doi: 10.1016/j.jtho.2016.08.143. Epub 2016 Sep 8


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