Background: At least half of patients with lung cancer have comorbidities, which can affect treatment decisions and survival. Associated with comorbidity, polypharmacy can also have consequences on patient care. This study will evaluate both polypharmacy and comorbidities in a cohort of hospitalized patients on the administration of chemotherapy and survival.

Methods: In this monocentric retrospective study, patients diagnosed with lung cancer during their first hospitalization in thoracic oncology were included between 2011 and 2015.

Four datasets were obtained containing the variables of interest. Deterministic data linkage will be performed. The main objective will be to assess the impact of polypharmacy and comorbidities on chemotherapy administration within two months after the first hospitalization in thoracic oncology. The probability of chemotherapy administration will be estimated using the Kaplan Meier method. Prognostic factors will be identified using a Cox model. The Fine and Gray method will be used to analyze the competitive risk of death.

Expected results: We first aim to demonstrate the feasibility of working with real-life data and aggregate different databases. Then our goal is to assess impact of polypharmacy and comorbidities on chemotherapy administration and on the survival of lung cancer patients. This would help to understand the possibilities to aggregate several database for a protocol in view to help clinicians to rationalize treatment and define inappropriate medications for this population.