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Abstract
<p>ObjectiveMany cancer patients exhibit cognitive problems in memory, working memory, attention, and executive function. The outcome measures of traditional neuropsychological tests do not fully capture how underlying cognitive processes are impaired and interconnected. We integrate hierarchical Bayesian cognitive process models with network analysis to examine these relationships, accounting for measurement error and distinguishing between test scores and cognitive processes.MethodWe compared 244 breast cancer patients (58% previously systemically treated) with 125 controls without cancer using Verbal Learning, Digit Span, and Block Tapping tests. Cognitive process models decomposed performance into processes we labeled as Working Memory, Manipulation Decline, Maintenance Decline, Retrieval, and Learning processes. We constructed networks of these processes.ResultsAnalyses of traditional outcome measures showed cancer patients performed significantly worse than controls on Digit Span Backward (d=0.40), Block Tapping (d=.23), and Verbal Learning tests (d=0.47 and d=0.40 for Immediate and Delayed Recall). Process model analysis revealed more selective impairments: Patients showed lower performance in Verbal Working Memory Capacity (d=0.49) and Retrieval processes (Short-term Retrieval d=0.66, Learned Retrieval d=0.44, Delayed Retrieval d=0.80), while Learning processes remained intact. Network analysis showed Visual- and Verbal Working Memory processes clustered together. Verbal Working Memory connected Visual Working Memory and Short-term Retrieval, with patient status showing negative associations with Retrieval processes and Verbal Working Memory.ConclusionsProcess-level analysis reveals more selective cognitive deficit patterns than traditional test outcomes. Network analysis indicates that working memory plays a connecting role across neuropsychological tests. This approach shows how cognitive processes are related.</p>