Lung Cancer Small Cell Lung Cancer (SCLC)

Background: In Canada, lung cancer accounts for approximately 25% of cancer deaths each year. There are also known sociodemographic and racial inequities in the diagnosis and treatment of lung cancer. Studies have consistently found that patients with cancer have a high number of unmet needs, including psychological, physical, and informational. Navigation programs represent a potentially promising, equitable, and cost-effective approach to address the unmet needs of patients with lung cancer, but there is limited evidence about their effectiveness in patients with lung cancer. The investigators developed and have implemented a volunteer lay navigator program, Care and Connect (C\&C), which aims to proactively reduce distress in patients, provide information and support, and increase access to treatment and supportive care resources. The proposed pilot randomized controlled trial (RCT) project plans to 1) assess the feasibility and acceptability of referral to C\&C and, 2) examine the preliminary effectiveness of C\&C. Methods: The current study is a 2-arm, parallel group, mixed methods, pilot RCT with a 1:1 allocation ratio and 3 timepoints: baseline (T0), 3 months (T1), 6 months (T2). It is designed to test the trial feasibility and acceptability of the C\&C intervention in patients with lung cancer. In total, 50 participants will be randomized to receive the C\&C intervention or usual care only (25 per arm). At each timepoint, data will be collected on participants' access to psychosocial (PSO) services, psychological wellbeing, and satisfaction with care through participant medical record and a survey. To gain additional insights regarding the acceptability, feasibility, and impact of C\&C, a subset of 15 participants from the intervention group will be contacted for qualitative exit interviews. Expected outcomes: There is limited evidence about the effects of lay navigation programs on access to PSO services among patients with lung cancer. This work addresses this knowledge gap by evaluating the feasibility, acceptability, and preliminary impact of C\&C on patients with lung cancer. The findings of the proposed work will expand the body of evidence supporting lay navigation to the lung cancer population, contributing to the evidence base for patient-centred care.

Lung cancer can be divided into two major categories: small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC), with NSCLC accounting for about 85% and SCLC about 15%. The prognoses of different types of lung cancer vary significantly. Early identification of different pathological types of lung cancer is crucial to the patient's prognosis. Raman Spectrum (RS), as a non-invasive and highly specific molecular detection technique, can obtain information at the molecular level, thereby sensitively detecting changes in biomolecules related to tumor metabolism such as proteins, nucleic acids, lipids, and sugars. Surface-enhanced Raman spectroscopy (SERS), developed based on this technology, is one of the feasible methods for high-sensitivity biomolecular analysis. In preliminary study, the investigators collected serum Raman spectral data from a cohort of 233 patients with malignant lung tumors and built a Raman intelligent diagnostic system for SCLC and NSCLC based on a machine learning model, achieving an accuracy rate of 80%. To obtain the highest level of clinical evidence and truly achieve clinical translation, this prospective, multicenter clinical study aims to validate the use of this intelligent diagnostic system for the early diagnosis of SCLC.