A fundamental challenge in the design of objective models for estimation of speech signal quality lies in the shortage of subjectively labelled databases. This problem is particularly relevant when developing quality assessment models for wide-band (16 kHz sampling rate) signals where databases are scarce. We explore the possibility for seamlessly integrating a quality prior in the form of a narrow-band quality estimate into the framework of a non-intrusive wide-band quality assessment algorithm. Experimental results confirm that the proposed approach can be used to improve performance over a baseline wide-band system without a narrow-band prior.