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PanCan Lung Cancer Detection Model For Lung Cancer Screening

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The PanCan approach to lung cancer detection utility in lung cancer screening.

The Pan-Canadian Early Detection of Lung Cancer (PanCan) model is effective in identifying individuals who are subsequently diagnosed with early lung cancer, according to a study published in The Lancet Oncology.

Researchers from Canada performed a single-arm prospective study to determine whether the PanCan approach could detect patients with early, potentially curable, lung cancer.

Study participants were aged between 50 and 75 who had smoked at some point in their life (ever-smokers) and who did not have a self-reported history of lung cancer. Participants had at least a 2% 6-year risk of lung cancer as estimated by the PanCan model, a precursor to the validated PLCOm2012 model.

Risk variables in the model were:

• Age

• Smoking duration

• Pack-years

• Family history of lung cancer

• Education level

• Body-mass index

• Chest X-ray in the past 3 years

• History of chronic obstructive pulmonary disease (COPD)

Individuals were screened with low-dose CT at baseline (T0), and at 1 (T1), and 4 (T4) years post-baseline.

The findings showed there were 172 lung cancers diagnosed in 164 individuals of the 2,537 participants who were followed for a median of 5.5 years. There were 10 interval lung cancers (6% of lung cancers and 6% of individuals with cancer): one diagnosed between T0 and T1, and nine between T1 and T4. Cumulative incidence was significantly higher than that observed in the National Lung Screening Trial (NLST) (4.0%). Compared with 593 (57%) of 1,040 lung cancers observed in NLST, 133 (77%) of 172 lung cancers in the PanCan Study were early stage (I or II).

The researchers concluded the PanCan model was effective in identifying individuals who were subsequently diagnosed with early, potentially curable, lung cancer. “The incidence of cancers detected and the proportion of early stage cancers in the screened population was higher than observed in previous studies,” they wrote. The researchers suggested that the approach should be considered for adoption in lung cancer screening programs.

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