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Purpose <p>This study examined whether adults with Multiple Myeloma (MM) show measurable cognitive differences compared with neurologically healthy controls. The primary research question focused on identifying domain-specific cognitive deficits and determining whether standard screening tools adequately capture cognitive abilities.</p> Methods <p>A cross-sectional design compared 45 adults with MM to 40 controls. Participants completed 40–50&#xa0;min of cognitive and psychological assessments, including the Montreal Cognitive Assessment (MoCA), validated measures of mood and daily functioning, and a digitised cognitive battery assessing key cognitive domains. Group differences in reaction time (RTs) and accuracy were analysed using ANCOVAs adjusting for age and education. Bayesian analyses and EZ drift diffusion modelling (EZ-DDM) were used to characterise evidence strength, prevalence of domain-level inefficiencies, and latent decision-making processes.</p> Results <p>MoCA scores were lower in the MM group, although the group difference did not reach statistical significance. However, a higher proportion of MM participants met the criteria for possible cognitive impairment compared with controls. At the computerised task level, no significant group differences were observed in accuracy or mean RT. RT analyses showed significant effects of cognitive domain, age, and education, but no overall group effect or interaction. Despite this, threshold-based Bayesian analyses indicated that approximately 22% of MM participants exhibited multi-domain RT inefficiencies, with variability most evident in cognitive flexibility and semantic processing. Accuracy-based performance was largely preserved across both groups, with no participants exceeding impairment thresholds. EZ-DDM indicated that group differences were driven by reduced drift rates and prolonged non-decision times in MM, suggesting slower evidence accumulation with slower sensory encoding and/or motor execution.</p> Conclusion <p>Cognitive differences in MM appear subtle and primarily expressed in processing efficiency rather than accuracy. Conventional screening measures and standard group comparisons may not fully capture this variability, particularly at the individual level. These findings support the use of more sensitive analytic approaches to characterise heterogeneous cognitive profiles in MM. Longitudinal and neuroimaging studies may help clarify whether observed inefficiencies reflect underlying neural changes associated with disease and treatment, and how these relate to functional outcomes.</p>

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Cognitive speed–accuracy dissociation in multiple myeloma: a cross‑sectional study

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月10日

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  • Sumayyah Patel,
  • Christopher Parrish,
  • Frances Seymour,
  • Melanie Burke

摘要

Purpose

This study examined whether adults with Multiple Myeloma (MM) show measurable cognitive differences compared with neurologically healthy controls. The primary research question focused on identifying domain-specific cognitive deficits and determining whether standard screening tools adequately capture cognitive abilities.

Methods

A cross-sectional design compared 45 adults with MM to 40 controls. Participants completed 40–50 min of cognitive and psychological assessments, including the Montreal Cognitive Assessment (MoCA), validated measures of mood and daily functioning, and a digitised cognitive battery assessing key cognitive domains. Group differences in reaction time (RTs) and accuracy were analysed using ANCOVAs adjusting for age and education. Bayesian analyses and EZ drift diffusion modelling (EZ-DDM) were used to characterise evidence strength, prevalence of domain-level inefficiencies, and latent decision-making processes.

Results

MoCA scores were lower in the MM group, although the group difference did not reach statistical significance. However, a higher proportion of MM participants met the criteria for possible cognitive impairment compared with controls. At the computerised task level, no significant group differences were observed in accuracy or mean RT. RT analyses showed significant effects of cognitive domain, age, and education, but no overall group effect or interaction. Despite this, threshold-based Bayesian analyses indicated that approximately 22% of MM participants exhibited multi-domain RT inefficiencies, with variability most evident in cognitive flexibility and semantic processing. Accuracy-based performance was largely preserved across both groups, with no participants exceeding impairment thresholds. EZ-DDM indicated that group differences were driven by reduced drift rates and prolonged non-decision times in MM, suggesting slower evidence accumulation with slower sensory encoding and/or motor execution.

Conclusion

Cognitive differences in MM appear subtle and primarily expressed in processing efficiency rather than accuracy. Conventional screening measures and standard group comparisons may not fully capture this variability, particularly at the individual level. These findings support the use of more sensitive analytic approaches to characterise heterogeneous cognitive profiles in MM. Longitudinal and neuroimaging studies may help clarify whether observed inefficiencies reflect underlying neural changes associated with disease and treatment, and how these relate to functional outcomes.