Area-level socioeconomic deprivation and cause-specific survival after lung cancer diagnosis: a population-based cohort study in Naples, Italy

BackgroundLung cancer remains a major public health priority, with survival shaped by clinical, behavioral, socioeconomic, and organizational factors. Socioeconomic disadvantage may affect risk exposure, diagnosis, treatment access, continuity of care, and data completeness.ObjectiveTo assess the association between area-level socioeconomic deprivation and cause-specific survival in lung cancer and apply the M.A.S.T.E.R. (Methodological Approach for Strategic Transformation, Evaluation, and Redesign) framework to translate epidemiological evidence into organizational design and implementation planning.MethodsA retrospective population-based registry cohort study within ASL Napoli 1 Centro included incident malignant tumors of the trachea, lung, and bronchi recorded between 2010 and 2023. Cancer Registry data were integrated with the 2021 Socioeconomic Disadvantage Index (IDISE), Hospital Discharge Records, and progressi delle Aziende Sanitarie per la Salute in Italia (PASSI) 2022–2024 contextual smoking prevalence by sex and Primary Health Care District (DSB). Cause-specific survival was analyzed using multivariable Cox regression with district-clustered robust variance; Fine–Gray competing-risk regression was used as sensitivity analysis. M.A.S.T.E.R. comprised six phases: Mapping and contextualization, analysis and diagnosis, strategic design, testing and adaptive execution, embedding and sustainability, and resilience and renewal.ResultsOf 11,162 cases, 10,039 were included in the main analysis, totaling 207,600 person-months. There were 8,514 deaths, including 6,990 cause-specific deaths. In the primary model without contextual smoking prevalence, adjusted hazard ratios (HRs) increased across deprivation quintiles (Q5 vs. Q1: HR 1.11; 95% CI: 1.05–1.18; p < 0.001). Adding PASSI smoking prevalence attenuated the estimates (Q5 vs. Q1: HR 1.09; 95% CI: 0.99–1.19; p = 0.069); smoking prevalence was not statistically associated with mortality. M.A.S.T.E.R. outputs included a qualitative failure mode and effects analysis (FMEA), a plan, do, study, act (PDSA) protocol with control plan, a completeness dashboard, and plans for updates, audits, and strategic review.ConclusionsGreater area-level socioeconomic deprivation was associated with higher cause-specific mortality in the primary model; the association was attenuated and no longer statistically significant after adding contextual PASSI smoking prevalence. M.A.S.T.E.R. clarified the transition from epidemiological analysis to candidate interventions for prevention, smoking cessation, early diagnosis, patient navigation, and information integration. Outputs from the final four phases are design-oriented and require prospective implementation and validation.