Abstract 7453: Psychometric analysis of Neuro-QoL Perceived Cognitive Function tool in primary brain tumor patients
Bibliographic record
Abstract
Abstract Cognitive dysfunction is commonly reported but variable in course and severity in the primary brain tumor (PBT) population. Brief, reliable, and sensitive measures of patient-reported outcomes (PRO) of cognitive symptoms on function are needed for clinical care and research. This study aims to assess the reliability and validity of the Neuro-QoL Perceived Cognitive Function tool (NQC) and explore associations with symptoms and objective testing of cognitive dysfunction in a cohort of PBT patients enrolled in a natural history study (NCT02851706: PI T. Armstrong). Patient sample characteristics and PROs, including NQC (<40 = moderate/severe (MS) dysfunction), a symptom burden measure (MD Anderson Symptom Inventory-Brain Tumor (MDASI-BT), scores ≥5 = MS) and the Montreal Cognitive Assessment ((MoCA), scores ≤ 25 indicating cognitive impairment (range: 0-30)) were collected. Descriptive statistics and a psychometric analysis consisting of bivariate correlations, Cronbach’s alpha, and factor analyses using principal axis factoring with nonorthogonal rotation were performed. Cohen’s kappa and correlation were used to assess agreement between objective and subjective measures of cognitive function. The cohort included 327 patients who completed the NQC at study entry [median age: 47 years (range: 18-85), primarily white (78%) males (55%) with high-grade tumors (73%), 65% with a Karnofsky Performance Status (KPS) ≥ 90 (good), and 29% reporting MS cognitive dysfunction]. Factor analysis of the NQC identified two underlying factor groupings: concentration/focus and executive function with Cronbach’s alphas of 0.92 and 0.91 that are interpretable and provided adequate fit for the data. While the NQC was moderately correlated with several MDASI-BT symptom factors, it was highly associated with the cognitive factor (r = -.646). To assess agreement, a subset of patients also completed the MoCA (n=172). These were primarily male (58%), white (79%), had high-grade tumors (67%), and a good KPS score (67%). In this subset, 24% had MS cognitive dysfunction as measured by the NQC while 44% were cognitively impaired using the MoCA resulting in a kappa agreement of 0.07. The correlation between the MoCA score and NQC T-score was -0.292. Understanding the impact and prevalence of cognitive symptoms, objective cognitive testing, and perceived impact is essential for PBT patient care and identifying supportive care interventions. Select NQC psychometric properties demonstrate reliability and validity in this population, with strong agreement with self-report of cognitive symptoms but weaker correlation with objective testing, highlighting the variability in perceived impact. Future research in cognitive function will explore the use of objective testing and perceived impact, its predictors in select populations (i.e., IDH-mutant tumors), and examine its association with biomarkers. Citation Format: Morgan L. Johnson, Elizabeth Vera, Kimberly Reinhart, Hope Miller, Anna Choi, Tricia Kunst, Bennett McIver, Ewa Grajkowska, Michelle L. Wright, Terri S. Armstrong, Tito Mendoza. Psychometric analysis of Neuro-QoL Perceived Cognitive Function tool in primary brain tumor patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7453.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".