Exponential growth and slow-growing tumours in screen-detected lung cancers: findings from the NELCIN-B3 LDCT screening study in China

Background Volume doubling time (VDT) is central to lung cancer screening, yet its calculation assumes exponential growth, a model evaluated mainly in Western populations. We evaluated the exponential growth model and characterised tumour growth in a Chinese low-dose computed tomography (LDCT) screening cohort. Methods We used data from the NELCIN-B3 LDCT screening cohort (Tianjin, China) of a general population aged 40–74 years. Four candidate models (linear, exponential, power-law, monomolecular) were fitted to serial volume and mass measurements of lung cancer nodules with ≥3 pretreatment scans (n = 32). VDT and mass doubling time (MDT) were calculated for all nodules with ≥2 scans (n = 57, including the 32 with ≥3 scans). Slow-growing tumours were defined by VDT >400 days or negative VDT, with MDT-based classification assessed in parallel. Subgroup analyses were exploratory. Results The exponential model provided the best fit for both volume and mass trajectories (median R 2 = 0.99). Median VDT and MDT were 593 (interquartile range: 305–994) and 617 (291–991) days, respectively. Among the 57 screen-detected cancers with serial pretreatment imaging, 65% were slow-growing. Never-smokers had longer doubling times than ever-smokers, and non-solid nodules had the longest doubling times; non-solid morphology was independently associated with slow growth (VDT: odds ratio 4.63; MDT: 7.58). Conclusion The exponential model provided a good empirical fit to screen-detected lung cancers with ≥3 pretreatment scans in this Chinese cohort, and slow-growing tumours were highly prevalent among cancers with serial imaging. These findings provide preliminary empirical evidence for prospective evaluation of growth-informed, risk-adapted surveillance strategies.