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Table 1 Decision tree chance nodes with estimates

From: The optimal timing of FDG-PET/CT in non-small cell lung cancer diagnosis and staging in an Australian centre

Variable

Estimate (%)

Plausible range/95% confidence interval

Data source

CT first decision tree

 Supraclavicular lymphadenopathy

1.7%

0.3–6.7%

Study cohort

 USS-guided lymph node biopsy sensitivity

93%

90–96%

Extrapolated from Han et al. [12]

 HAL model eTable 8 > 10%

51%

42–60%

Study cohort

 Nodule accessible by radial EBUS

57%

44–69%

Study cohort

 Radial and Linear EBUS sensitivity

73%

70–76%

Published data [13]

 Linear EBUS sensitivity

89%

46–97%

Published data [14, 15]

 Ct-guided lung biopsy sensitivity

93%

90–97%

Published data [12]

 Distant metastatic disease on FDG PET

38%

27–51%

Study cohort

 Full HAL model > 10

21%

10–37%

Study cohort

 Accessible met disease OR FDG PET positive hilar LN OR Nodule accessible with radial EBUS

51%

38–64%

Study cohort

PET first decision tree

 Accessible metastatic disease

7.9%

4.2–14%

Study cohort

 Percutaneous image-guided biopsy sensitivity

93%

90–96%

Published data [16]

 FDG PET positive hilar LN OR HAL > 10%

42%

33–52%

Study cohort

 Nodule accessible by radial EBUS

64%

50–77%

Study cohort

 Radial and linear EBUS sensitivity

73%

70–76%

Published data [13]

 Linear EBUS sensitivity

89%

46–97%

Published data [14, 15]

 CT-guided lung biopsy sensitivity

93%

90–97%

Published data [12]

 Full HAL model > 10%

3.3%

0.9–11%

Study cohort

 Nodule accessible by radial EBUS

44%

33–57%

Study cohort

  1. CT Computed tomography, EBUS Endobronchial ultrasound, HAL Help with Assessment of Lymphadenopathy Model6. USS Ultrasound