Facilitating Early Diagnosis of Lung Cancer: Transdisciplinary Efforts Combining Data from Patient-Reports, Biomarkers and Imaging

This nursing science precision health project, focus on complex interactions among biological, social, and behavioural factors, and their effects on outcomes.

By researching patients’ experience of symptoms and linking these to biological data, we aim to increase the sensitivity and specificity of LC diagnosis and to aid in investigate molecular determinants of common symptoms, e.g. fatigue and cachexia. Furthermore, we aim to develop our measures for use to monitor treatment response in patients receiving immunotherapy.

With previous VR funding (2016-1712, 2019-1222), we developed an interactive questionnaire, Peklung, to generate detailed descriptions about early health changes in LC and used it to collect data from ∼700 patients at diagnostic LC work-up; in parallel we also collected plasma samples from  these patients.

We apply here for continued VR funding to link patient-reported data from Peklung with biomolecular and imaging profiles, to determine biomarkers of LC and other lung diseases, and to investigate new molecular determinants of symptoms with unclear aetiology and mechanism, e.g. fatigue, cachexia.

Establishing symptomatology related to early LC can: decrease diagnostic delay, with increased chance of curative treatment options and shorter time spans to curative or palliative treatment, thus reducing distress for patients/families; connect detailed symptom with omics data to increase understanding of mechanisms of poorly understood symptoms.