Preoperative Decision-Making in Patients With Pulmonary Nodules Suspected of Lung Cancer

Pulmonary nodules that are highly suspected of malignancy represent a common and clinically challenging scenario in thoracic surgery. Before a definite pathological diagnosis is available, patients may need to make complex decisions regarding surgery, additional diagnostic procedures, active surveillance, or other management strategies. These decisions are often made under uncertainty and may be influenced by patients' understanding of medical information, perceived cancer risk, fear of treatment delay, concerns about unnecessary surgery, family involvement, and communication with clinicians.

This is a single-center, prospective observational study conducted at Sichuan Cancer Hospital. The study plans to enroll approximately 200 adult patients with pulmonary nodules highly suspected of lung cancer who are facing preoperative clinical decision-making. The study will not assign any treatment, diagnostic procedure, or behavioral intervention. All clinical management decisions will be made according to routine clinical practice and shared discussion between patients and their treating clinicians.

The primary aim of the study is to characterize preoperative decision-making among patients with pulmonary nodules suspected of lung cancer. Specifically, the study will assess decision self-efficacy, decisional conflict, and decision quality. Decision self-efficacy will be evaluated using the Decision Self-Efficacy Scale. Decisional conflict will be assessed using the Decisional Conflict Scale. Decision quality and shared decision-making experience will be evaluated using instruments such as the SDM-Q-9 and decision regret-related measures, as applicable.

The study will also explore the relationships among decision self-efficacy, decisional conflict, and decision quality. Potential associated factors may include demographic characteristics, clinical characteristics, health literacy, quality of doctor-patient communication, family involvement, emotional status, and patient preferences. Data will be collected using structured questionnaires during the preoperative outpatient or inpatient period.

Descriptive statistics will be used to summarize participant characteristics and questionnaire scores. Correlation analyses, multivariable regression models, and, if appropriate, structural equation modeling will be used to examine the associations and potential pathways linking decision self-efficacy, decisional conflict, and decision quality. The study is expected to provide evidence for identifying patients at risk of poor decision quality and for developing future decision support strategies in thoracic surgical practice.