Abstract Objectives: To develop a clinical prediction model of contribution of chronic obstructive pulmonary disease (COPD) to the pathogenesis of lung cancer, by reporting the estimated prevalence and severity by GOLD criteria in a single-institution cohort of patients with newly diagnosed lung cancer. Primary objective was investigating the effects of impaired lung function with various histological cell types on crude survival, while considering the initial staging of disease extent. Materials & methods: A total of 441 patients, in this historical cohort from electronic medical records, completed spirometry prior to invasive diagnostic procedures and initial treatment of their lung cancer. All statistical analyses, including ANOVA and survival analysis, were performed using SAS version 9.1 software. Results: Estimated prevalence of COPD was 79.1% (95% confidence interval: 71.3%-82.9%). Lung function as measured by spirometry was a significant predictor of survival time in months (p<.0001) both with and without adjusting for tumor-cell-type, age, and stage of disease. Median survival was similar (p=0.32) and longer among those patients with normal pulmonary function, those with restrictive disease patterns, and those with COPD–GOLD-1 defects. Median survival was shortest among patients with COPD–GOLD-4 impairment (p=0.001). Those patients with COPD–GOLD-2 and COPD-GOLD-3 impairment levels had intermediate survival times (p=0.003). Conclusions: This investigation suggests that strategies for early detection and slowing the progression of COPD before the development of lung cancer might increase patient survival. As demonstrated in this study, the presence and severity of COPD in lung cancer patients is an independent predictor of survival time, different from the established staging of initial extent of disease.
Keywords: COPD; pulmonary disease; lung cancer; prevalence; common pathogenesis

Abstract Objective: To identify the system and other non-clinical factors that may influence a General Practitioners’ decision on whether to refer a patient who may have cancer. Study design: Expert group discussion and consensus formation. Methods: A group of eight General Practitioner (GP) researchers from Croatia, England, Slovenia, Spain, Sweden and Switzerland used brainstorming to identify the non-clinical factors that could affect GPs’ decision-making when faced with patients that might have cancer. The group refined and came to a consensus on these factors. Results: Many non-clinical factors are likely to have a significant impact on referral decisions. These include levels of gatekeeping responsibility, funding systems, access to special investigations, fear of litigation, and relationships with specialist colleagues. Conclusions: Many patients with cancer present without red-flag symptoms, but nevertheless still cause a feeling of concern in their GPs. How a health system is organised is likely to influence on how GPs act on those concerns.
Keywords: health care systems; primary health care; cancer; decision making; early detection of cancer