Why intrinsic reduced susceptibility in rare fungal pathogens should be differentiated from intrinsic resistance: an ISHAM conceptual framework and narrative review

Accurate interpretation of antifungal minimum inhibitory concentrations (MICs) requires distinguishing species-level intrinsic phenotypes from isolate-level acquired resistance. Many fungi exhibit intrinsic reduced susceptibility (IRS) reflected by wild-type (WT) MIC distributions that are shifted toward higher values (uniformly or with a high-MIC tail). This may lead to the misclassification of high-end WT isolates as resistant and compromise surveillance and cross-center comparability, particularly for rare fungi lacking established breakpoints. In this review, we propose a pragmatic and standardized framework to distinguish intrinsic phenotypes (normal susceptibility, IRS, intrinsic resistance) from acquired resistance based on species-specific WT MIC distributions and standardized WT/non-wild-type (NWT) reporting. This framework is specifically intended to guide interpretation in data-limited settings where WT distributions and epidemiological cut-off values (ECOFFs) are not yet established. MICs within the unimodal species-specific WT range, even if high, should be interpreted as potentially reflecting IRS and not as acquired resistance. Only MICs clearly right-shifted beyond the WT range should be classified as NWT by epidemiological cut-off values or, if unavailable, as putative NWT, and considered candidates for acquired resistance. When breakpoints are lacking, WT versus NWT reporting with explicit comments on IRS/intrinsic resistance is preferable to forced susceptible/resistant (S/R) categorization. In the absence of established WT distributions or ECOFFs, such classification remains provisional and should rely on descriptive MIC patterns, available data sets, and clinical context. Integrating these biological interpretations with pharmacokinetics/pharmacodynamics and clinical context supports optimized dosing, avoids inappropriate drug exclusion, and enables consistent surveillance and multicenter comparisons.