Validity and Reproducibility of Immunohistochemical Scoring by Trained Non-Pathologists on Tissue Microarrays

Scoring of immunohistochemistry (IHC) staining is often done by non-pathologists, especially in large-scale tissue microarray (TMA)-based studies. Studies on the validity and reproducibility of scoring results from non-pathologists are limited. Therefore, our main aim was to assess interobserver agreement between trained non-pathologists and an experienced histopathologist for three IHC markers with different subcellular localization (nucleus/membrane/cytoplasm).

Three non-pathologists were trained in recognizing adenocarcinoma and IHC scoring by a senior histopathologist. Kappa statistics were used to analyze interobserver and intraobserver agreement for 6,249 TMA cores from a colorectal cancer series.

Interobserver agreement between non-pathologists (independently scored) and the histopathologist was "substantial" for nuclear and membranous IHC markers (κ_range = 0.67-0.75 and κ_range = 0.61-0.69, respectively), and "moderate" for the cytoplasmic IHC marker (κ_range = 0.43-0.57). Scores of the three non-pathologists were also combined into a "combination score" (if at least two non-pathologists independently assigned the same score to a core, this was the combination score). This increased agreement with the pathologist (κ_nuclear = 0.74; κ_membranous = 0.73; κ_cytopasmic = 0.57). Interobserver agreement between non-pathologists was "substantial" (κ_nuclear = 0.78; κ_membranous = 0.72; κ_cytopasmic = 0.61). Intraobserver agreement of non-pathologists was "substantial" to "almost perfect" (κ_{nuclear,range} = 0.83-0.87; κ_{membranous,range} = 0.75-0.82; κ_cytopasmic = 0.69). Overall, agreement was lowest for the cytoplasmic IHC marker.

This study shows that adequately trained non-pathologists are able to generate reproducible IHC scoring results, that are similar to those of an experienced histopathologist. A combination score of at least two non-pathologists yielded optimal results.

Non-pathologists can generate reproducible IHC results after appropriate training, making analyses of large-scale molecular pathological epidemiology studies feasible within an acceptable time frame.