1565P - Improving lung cancer screening selection: Hunt Lung Cancer Model (HUNT LCM) versus PLCOm2012, early results after two rounds of screening in a prospective screening pilot study in Norway (TIDL)

Background

There is international consensus that risk models are more effective than fixed criteria as pack-years and age to select high-risk subjects for lung cancer screening. Here we tested the HUNT LCM against the PLCOm2012, in a Norwegian prospective lung cancer screening study. Both models were thoroughly validated in external large dataset. These risk models have not been compared to each other directly by all participants answering questions from both models. This is of interest for implementation of screening in several countries.

Methods

In the Norwegian prospective lung cancer screening pilot TIDL, 1004 subjects with age 60-79 and > 35 packyears or PLCOm2012 risk > 2.6% were screened in 2023 and re-screened in 2024. All were asked to provide the variables needed for the HUNT LCM and PLCOm2012 calculators. Risk scores for both models were calculated for all subjects at inclusion. The performance of the models was tested by area under the ROC curve (AUC) and by ranking of risk by sample-level risk scores versus the cumulative number of lung cancers diagnosed provided by the two models with the Kolgomorov-Smirnov test.

Results

Out of the 1004 included in the screening trial, 884 had had signed consent to be included in this risk study. In total at 1st and 2nd screening round, 25 individuals were diagnosed with lung cancer. Median pack-years was 41.5 and 43.8 among cases and controls respectively (p=0.44). Median risk score of all screened and the lung cancer cases was 3.7% and 4.4% versus 2.15% and 2.19% by the PLCOm2012 and the HUNT LCM respectively (p>0.05). The AUC for lung cancer diagnosis in one year was 0.522 and 0.546 in the PLCO and HUNT LCM respectively. When ranked according to risk score, the HUNT LCM had a higher detection rate (p<0.001).

Conclusions

In this Norwegian pilot screening study of very high risk individuals, none of the two methods were able to predict lung cancer at the first two screening rounds correctly according to AUC. However, HUNT LCM was statistically superior over PLCOm2012 in ranking and predicting lung cancer diagnosis two years after inclusion. We will follow this up with yearly updates to assess the usefulness of the two models.

Clinical trial identification

Editorial acknowledgement

Legal entity responsible for the study

Akershus University Hospital, Lørenskog, Norway.

Funding

Has not received any funding.

Disclosure

All authors have declared no conflicts of interest.