Abstract Rationale To evaluate the association between participation in the Combined Lung cancer Identification Program (CLIP) and stage at diagnosis among patients with newly diagnosed lung cancer between 2022 and early 2023. Methods This retrospective analysis included patients diagnosed with lung cancer within the Frederick Health System between January 1, 2022, and March 20, 2023, based on tissue-confirmed biopsy results. Patients were categorized into two cohorts: those who participated in CLIP, a coordinated early-detection initiative integrating low-dose CT screening, incidental nodule tracking, and multidisciplinary case review, and those diagnosed outside the program (nonCLIP). Stage at diagnosis was determined according to the American Joint Committee on Cancer (AJCC) 8th edition and abstracted from electronic medical records. Aggregate data were analyzed to compare stage distribution between groups. Results A total of 133 patients met inclusion criteria, including 74 CLIP and 59 nonCLIP patients. Stage distribution varied significantly between cohorts. Among CLIP participants, 67.6% were diagnosed at stage 1, 9.5% at stage 2, 16.2% at stage 3, and 6.8% at stage 4. In contrast, nonCLIP patients presented with 13.6% at stage 1, 5.1% at stage 2, 25.4% at stage 3, and 55.9% at stage 4. The proportion of early-stage disease (stages 1-2) was markedly higher among CLIP patients (77.0%) compared with nonCLIP (18.6%), while late-stage diagnoses (stages 3-4) were substantially lower (23.0% vs 81.4%, respectively). Conclusion Participation in the Combined Lung cancer Identification Program (CLIP) was associated with a striking shift toward earlier lung cancer detection compared with patients diagnosed outside the program. Most CLIP participants were identified at stage 1, indicating that structured, multidisciplinary early-detection programs integrating low-dose CT screening, risk stratification blood-based tests, and coordinated follow-up can significantly alter stage distribution. Expanding CLIP-like programs and incorporating complementary blood-based risk assessment tools may further enhance early diagnosis, reduce late-stage presentations, and improve outcomes in community health systems. This abstract is funded by: None
Smith et al. (Fri,) studied this question.