Year: 2023
Type: article
Abstract: Prognostic models in cancer use patient demographic and tumor characteristics to predict survival and dynamic disease prognosis. Past work in breast cancer has shown that cancer detection method, screen-detected or symptom-detected, has prognostic significance. We investigate this phenomenon in the lung component of the Prostate, Lung, Colorectal, and Ovarian (PLCO) screening trial. Patients were randomized to intervention, receiving four annual chest x-rays (CXRs), or to control, receiving usual care. Patients were followed for a total of approximately 13 years. In PLCO, lung cancer detection method has independent prognostic value exceeding that of variables commonly used in lung cancer prognostic models, including sex, histology, and age. Results are robust to cohort selection and type of predictive model. These results imply that detection method should be considered when developing prognostic models in lung cancer studies, and cancer registries should routinely collect cancer detection method.
Source: Scientific Reports
Authors: James P. Long, Yu Shen
Institution: The University of Texas MD Anderson Cancer Center
Language: English
Subfield: Pulmonary and Respiratory Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,390
Awards: G10598100, G111615301, G1527481403, G1572863790, G2851546738, G3015541426, G4745782215, G486457145, Addressing COVID-19 Testing Disparities in Vulnerable Populations Using a Community JITAI (Just in Time Adaptive Intervention) Approach - Phase II, CCSG supplement: HOPE/CARE, G9000034222, G9000134271, G9000206034, Statistical Methods for Integration of Multiple Data Sources toward Precision Cancer Medicine
OpenAlex ID: W4385954247