Hubungan antara Tingkat Ketergantungan Nikotin dengan Hasil LDCT pada Individu Risiko Tinggi Kanker Paru yang Menjalani Skrining Kanker Paru di RS Adam Malik Medan

Abstract

Background: Lung cancer is one of the leading causes of cancer-related mortality in Indonesia, with a high prevalence particularly among smokers. Low Dose Computed Tomography (LDCT), as demonstrated in the National Lung Screening Trial (NLST), has been proven to reduce lung cancer mortality by 20% through early detection of pulmonary nodules at an early stage. Heavy nicotine dependence, which is frequently observed among smokers, is hypothesized to be closely associated with LDCT findings, given that smoking is the primary risk factor for lung cancer. However, empirical evidence in the Indonesian population remains limited. Objective: To assess the association between the level of nicotine dependence and LDCT results in high-risk individuals undergoing lung cancer screening Adam Malik General Hospital, Medan. Methods: This was an analytical cross-sectional study involving 30 subjects aged over 40 years who met the criteria for high lung cancer risk. The degree of nicotine dependence was determined using the Fagerstrom Test for Nicotine Dependence (FTND). LDCT results were classified as positive if nodules ≥4 mm or Lung-RADS >1 were identified. Data analysis was performed using Firth logistic regression to account for small sample size and data separation issues. Results: The majority of respondents demonstrated a high level of nicotine dependence. Subjects with higher FTND scores tended to have more positive LDCT results compared to those with low or moderate dependence. However, this association did not reach statistical significance. The analysis showed non-significant associations between nicotine dependence and positive LDCT findings at all FTND levels (mild p = 0.055; moderate p = 0.623; severe p = 0.828). Conclusion: No statistically significant association was found between the level of nicotine dependence and LDCT results in this high-risk population. However, due to the small sample size and potential data separation, further investigation is warranted.