Rasch analysis for assessing unidimensionality and identifying measurement biases of malignancy scores in oncology. The example of the Weiss histopathological system for the diagnosis of adrenocortical cancer

AbstractPurpose alignancy scores have been developed without comprehensive statistical or measurement validation, and in particular without verification of the necessary property of unidimensionality. Here, we used Rasch analysis to assess unidimensionality and identify measurement biases of malignancy scores. s iss histopathological system (WHS), summing nine items of histopathological alteration, was used to evaluate 247 adrenocortical tumors. Rasch model analysis was implemented and compared to classical factor analytic methods to investigate the validity of item-score summation for both the original and modified WHS, to assess differential functioning of the WHS items across various factors related to patient and tumors, and to identify items or subtypes of tumors that could be considered for removal or exclusion from the WHS with the aims of improving measurement and relieving the burden on pathologists. s S does not meet the necessary property of unidimensionality and is severely affected by differential item functioning in relation to size and weight of the tumor. Moreover, items are not well distributed along the spectrum of malignancy, most being located in the upper part and several at the same place. sion S in its present form should be applied only to small or moderate size tumors, and better scoring systems could be developed by using more appropriately distributed items. Rasch analysis is a powerful method for developing, evaluating, refining and simplifying malignancy scores.