Abstract 213P
Background
Lifestyle, environmental or mood factors may influence cancer outcomes. To harness these complex data for clinical decision-making, we propose building a PDT using a multidimensional and longitudinal data capture approach in prevalent cancers. We report the feasibility at the 10% planned accrual (N=30/300).
Methods
Prospective, multicentric (n=9) observational study. Inclusion criteria: treatment-naïve women >18 y.o. with metastatic lung or colorectal cancer eligible for any first-line treatment or hormone-positive breast cancer eligible for first-line endocrine + CDK4/6 inhibitor. Patients are profiled at baseline (V1), 1 month (m; V2), 3m (V3), and every 3m (V4…Vn), including an e-CRF with 24 clinical, 18 demographic, and 96 bloodwork fields; body CT; plasma (Pl) metabolomics and proteomics, germline methylome, stool (St) metabolomics and metagenomics; and V1 tumor (T) and germline genomics. Continuous physiological monitoring is captured via smartwatch (HR, pO2, sleep, activity). EORTCQ30, GH28, PRO-CTCAE and diet PDAQ questionnaires V1 to Vn, spontaneous reporting of emotional states (from a list of 20), and pain (VAS, daily) are captured via App. Coverage is computed as % of obtained vs. planned data. Sample quality is assessed based on pre-established QC parameters.
Results
N=30 pts (14 breast, 12 lung, 4 colon). Median(range) time on study: 202 days (2-350 d): 4 pts for > 9 m, 25 for >6 m and 29 for >4m. Clinical and analytical fields completed at 86%, and 93% (V1); 89% and 96% (V2); 81% and 93% (V3); 74% and 78% (V4); 100% and 100% (V5). Samples: V1: 93% T, 100% Pl and 80% St; V2: 100% Pl, 82% St; V3: 92% Pl, 78% St; V4: 87% Pl, 61% St; V5: 100% Pl, 100% St samples were obtained. 100% T, Pl and St samples met DNA QC criteria, yielding 11.9 (0.29-70), 10.2 (0.4-59) and 9.0 (1.5-27) ug of DNA, respectively. 100% samples for methylomics and metabolomics met 5 and 4 QC criteria respectively. Physiologic monitoring captured 94%, 83%, 69% and 63% of the maximum expected activity, HR, pO2 and sleep quality data. 90% and 93% of ptes entered >1 emotion (median 0.56/day) and pain data (median 0.53/day). 250 of 328 (76%) planned questionnaires were filled.
Conclusions
High patient engagement and data/sample quality affirm the feasibility of constructing a PDT.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
Centro Nacional de Investigaciones Oncologicas (CNIO), Madrid, Spain.
Funding
Centro Nacional de Investigaciones Oncologicas (CNIO), Madrid, Spain.
Disclosure
All authors have declared no conflicts of interest.
Resources from the same session
1192P - Optimizing lung cancer screening: Independent verification of an AI/ML computer-aided detection and characterization software as medical device
Presenter: Sylvain Bodard
Session: Poster session 09
1194P - Development of a novel artificial intelligence (AI) algorithm to detect pulmonary nodules on chest radiography
Presenter: Mitsunori Higuchi
Session: Poster session 09
1195P - Whole-body magnetic resonance imaging (WB-MRI) screening in Li Fraumeni syndrome for early cancer diagnosis: The SIGNIFIED project
Presenter: Elena Cojocaru
Session: Poster session 09
1196P - Organoid growth-based oncological sensitivity test (OncoSensi) for predicting adjuvant therapy outcomes in ovarian cancer patients
Presenter: Dong Woo Lee
Session: Poster session 09
1197P - Ex vivo basket study reports patient-specific sensitivity to carboplatin versus cisplatin in lung, ovarian and bladder cancer
Presenter: Debbie Robbrecht
Session: Poster session 09
1198P - Analytical validation of an NGS panel-based ecDNA detection device for use as a clinical trial assay for the POTENTIATE clinical study of the novel CHK1 inhibitor, BBI-355
Presenter: Pontis Julien
Session: Poster session 09