[en] Recently, analytical sensitivity methods has been applied to obtain fuel cycle cost implications of data uncertainties. To perform exposure dependent sensitivity analysis without repeating expensive spectrum calculations, simple correlations of the spectrum averaged cross sections (SAXS) were constructed. The correlation coefficients were obtained by fitting the SAXS calculated by direct methods over a wide range of LMFBR core designs. In this paper the procedure has been extended to study sensitivity of fuel cycle cost and breeding ratio to design variation. The method involves using the correlations to construct both the SAXS and the sensitivity coefficients. Composition dependent correlations have been found to be accurate for the core while both composition and position have to be included in analysing the blanket