{'fraction_non_alphanumeric': 0.024173806609547124, 'fraction_numerical': 0.007037943696450428, 'mean_word_length': 5.644308943089431, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Validation and Proficiency Testing of Biomarker Immunohistochemistry: Diagnostic Accuracy "Fit for Purpose" in a 3D World.

T analytic validation of clinical tests in the diagnostic immunohistochemistry laboratory, and the ongoing demonstration of laboratory proficiency in the performance of those tests, depends on the ability of a candidate test (optimized against well-defined controls and tested against an accepted limit of detection standard1) to perform at an acceptable level of analytic sensitivity and specificity against a comparator test or data set2 that reflects the intended purpose of the assay.3,4 Ideally, the comparator test would be a well-defined reference methodology or an assay that performs optimally against an appropriately designed proficiency testing challenge. However, for most practical purposes, these comparators are not readily available for diagnostic markers used in clinical practice. Hence, despite recommendations designed to enhance this process,2–4 I suspect that, in most laboratory settings, new immunohistochemical tests intended to identify targets of diagnostic value are often compared against an existing assay for the same general purpose or against archived cases with expected patterns of immunoreactivity. But inferring the presence of a specific immunohistochemical target through reproducible patterns of immunoreactivity in a selected patient population may not be sufficient to ensure the validity of tests designed to detect predictive biomarkers. Rather, despite the difficulty in identifying an appropriate reference standard for evaluation of sensitivity and specificity and the challenge in defining the appropriate sample set for technical validation, the direct link between immunoreactivity and the actual presence of the target predictive marker must be reasonably assured. The process begins, as with diagnostic markers, by evaluating the methodology in a manner that takes into account the intended diagnostic or clinical use of the test—the test must be “fit for purpose.” In addition, as introduced by Cheung et al5 in this issue (where the “fit for purpose” principle is applied to proficiency testing), the intended application of a given predictive biomarker must also take into account which drug will be used in a selected patient population with a given disease using the diagnostic assay designed and optimized to detect that biomarker. Cheung and associates refer to this as “fit for purpose 3D” (3D—drug, disease, diagnostic test). Why should our evaluation of predictive biomarker tests necessarily be so robust? The Clinical Laboratory Standards Institute (CLSI) designates diagnostic assays, such as immunohistochemistry, that effectively have only 2 outcomes (positive or negative), as qualitative tests.6 This designation also applies to tests with a semiquantitative read-out (eg, Her2 testing and the 0, 1+, 2+, 3+ scoring system or the Allred scoring system for estrogen and progesterone receptor proteins) when clinical action (treat or not treat) is based on a single cut-off value within that scoring system (eg, 3+ for Her2, or an Allred score of 3). In guideline EP12A2 “User Protocol for Evaluation of Qualitative Test Performance,” CLSI notes that certain qualitative tests