In this paper a decision support system for the diagnosis of a very serious respiratory disease caused by tobacco and named the chronic obstructive pulmonary disease is presented. The system is based on case-based reasoning principles and gathers the experience of experts of the pneumology department of Dorban Hospital (Annaba, Algeria). A critical issue about the case base is that some values of the features are missing in most cases. Five approaches for managing this problem of missing data are proposed. Three of them allow evaluating the similarity despite the missing information. The two other approaches are proposed for filling the voids by plausible values using a statistical method and the principle of case-based reasoning itself.