👤 Ethan Basch

The PRO-CTCAE provides patient-reported data on symptomatic AEs. A summary metric-the ACS-reflecting total AE burden can be calculated by averaging AE-level composite scores at a given timepoint for each participant. This study investigated the psychometric properties and interpretability of this PRO-CTCAE ACS in patients with breast, lung, or head/neck cancers. We conducted a secondary analysis of a PRO-CTCAE validation dataset comprising 940 adults undergoing chemotherapy or radiation therapy (clinicaltrials.gov: NCT02158637). We focused on empirically recommended symptom terms for three cancer sites. Analyses included Spearman's correlations, coefficient alpha, and eigenvalues from the correlation matrices, confirmatory factor analysis (CFA), and principal component analysis (PCA). Latent profile analysis (LPA) was used to assess ACS interpretability in the lung cohort. Mean composite score inter-correlations were moderate (0.30-0.35), and coefficient alphas were high (0.81-0.91). Eigenvalue ratios and CFA supported retention of a single factor/component, with suitable model fit indices. ACS correlated highly with factor scores and the first principal component from the PCA. Reduced sets of terms produced reliable scores that closely approximated the full set scores and aligned with external criteria. LPA in the lung subgroup identified four latent classes; ACS differentiated high vs. low symptom burden groups but did not distinguish the two groups expressing distinct symptom profiles. The ACS demonstrated structural validity through adequately fitting linear factor models and effectively summarized symptomatic AE burden. However, similar ACS values may mask clinically distinct symptomatic AE profiles, underscoring the value of both summary metrics and profile-based approaches. Show less

The organ of Corti, the auditory organ of the inner ear, contains two types of sensory hair cells and at least seven types of supporting cells. Most of these supporting cell types rely on Notch-dependent expression of Hes/Hey transcription factors to maintain the supporting cell fate. Here, we show that Notch signaling is not necessary for the differentiation and maintenance of pillar cell fate, that pillar cells are distinguished by Hey2 expression, and that-unlike other Hes/Hey factors-Hey2 expression is Notch independent. Hey2 is activated by FGF and blocks hair cell differentiation, whereas mutation of Hey2 leaves pillar cells sensitive to the loss of Notch signaling and allows them to differentiate as hair cells. We speculate that co-option of FGF signaling to render Hey2 Notch independent also liberated pillar cells from the need for direct contact with surrounding hair cells, and enabled evolutionary remodeling of the complex cellular mosaic of the inner ear. Show less