Normative tonsillectomy outcome inventory 14 values as a decision-making tool for tonsillectomy

Abstract

Purpose: The study aimed to determine normative values for the Tonsillectomy Outcome Inventory 14 (TOI-14) in a healthy middle-European cohort. We also compared these generated values with TOI-14 scores from a patient population with recurrent tonsillitis (RT) and explored the factorial structure of the TOI-14.

Methods: We systematically studied the responses of healthy individuals (reference cohort) and patients with RT (clinical cohort) to the TOI-14 survey. The reference cohort contained 1000 participants, who were recruited using the Respondi panel for market and social science research. This subsample was quoted to the population distribution of the German Microcensus and selected from a non-probability panel. Tonsillitis patients were assessed before and 6 and 12 months after tonsillectomy. Data were analysed using principal component and exploratory factor analyses.

Results: The PCA revealed three TOI-14 domains (physiological, psychological and socio-economic), which explained 73% of the total variance. The reference cohort perceived a good quality of life (QOL) with a TOI-14 total score of 11.8 (physiological: 8.0, psychological: 5.8, and socio-economic subscale score: 13.9). TOI-14 scores were higher in the patient cohort, indicating that the TOI-14 discriminates between patients with RT and healthy individuals with no RT. Age and female gender significantly influenced the total TOI-14 score, especially in the psychological (age) and socio-economic (gender) subscales.

Conclusion: We have developed a set of normative values that, together with the TOI-14, can determine the disease burden indicating tonsillectomy.

Keywords: EFA; Guidelines; Middle-european cohort; PCA; Quality of life; Recurrent tonsillitis; TOI-14.

Fig. 1

Non-graphical analysis as elbow figure. The black curve, illustrating the Eigenvalues in descending order, would suggest the inclusion of three main components since any further Eigenvalues are below one. However, the parallel analysis (triangles upward), comparing the actual matrix of Eigenvalues to a Monte-Carlo-simulated matrix of the same size, shows that only the EVs of two main-components are above the 95th percentile. The same number of components is suggested in regard to the EVs’ gradients and the optimal coordinates (triangles downward), whereas the Acceleration Factor

Fig. 2

An overview of TOI-14 sub-indices of the four different cohorts (control, preoperative, 6 months postoperative and 12 months postoperative) independent of the time point

Fig. 3

Boxplot illustration of the TOI-14 overall score (bottom) and the novel TOI-14 sub-indices of the reference cohort (a n = 1000), the preoperative patient cohort (b n = 108), the 6-month postoperative patient cohort (c n = 58), and the 12-month postoperative patient cohort (d n = 42). The red line represents the overall mean TOI-14 score of the non-clinical cohort (11.8). The bold line describes each distribution’s median whereas the box represents the interquartile range. Dots resemble outliers

Fig. 4

Forest plot showing the association between overall TOI-14 score and gender (a) and age (b) of the reference cohort (n = 1000). The questionnaire score is plotted on the Y-axis, the frequency of score responses on the X-axis