Objective

The Trans Woman Voice Questionnaire (TWVQ) is commonly used to quantify self-perceptions of voice for trans women seeking gender-affirming voice care, but the interpretation of TWVQ scores remains challenging. The objective of this study was to use item-response theory (IRT) to evaluate the relationship between TWVQ items and persons on a common scale and identify improvements to increase the meaningfulness of TWVQ scores.

Methods

A retrospective review of TWVQ scores from trans women patients between 2018-2020 was performed. Rasch-family models were used to generate item-person maps positioning respondent location and item difficulty estimates on a logit scale, which was then converted into a scaled score using linear transformations.

Results

TWVQ responses from 86 patients were analyzed. Initial item-person maps demonstrated that the middle response categories ("sometimes" and "often") performed inconsistently across items (poor threshold banding); interpretability improved when these ratings were scored as one category. The models were rerun using revised scoring, which retained high reliability (0.93) and supported a unidimensional construct. Updated item-person maps revealed four scaled score zones (≤54, >54 to ≤101, >101 to ≤140, and >140) that each corresponded to an increasing pattern of item thresholds (probability of selecting one response category vs. others). These ranges can be interpreted as minimal, low, moderate, and high, respectively.

Conclusions

Empiric data from Rasch analysis supports new interval scoring for the TWVQ that advances the clinical and research utility of the instrument and lays the foundation for future improvements in clinical care and outcomes assessment.

Level of evidence

NA Laryngoscope, 133:1197-1204, 2023.

A key aim of systems biology is the reconstruction of molecular networks. We do not yet, however, have networks that integrate information from all datasets available for a particular clinical condition. This is in part due to the limited scalability, in terms of required computational time and power, of existing algorithms. Network reconstruction methods should also be scalable in the sense of allowing scientists from different backgrounds to efficiently integrate additional data. We present a network model of acute myeloid leukemia (AML). In the current version (AML 2.1), we have used gene expression data (both microarray and RNA-seq) from 5 different studies comprising a total of 771 AML samples and a protein-protein interactions dataset. Our scalable network reconstruction method is in part based on the well-known property of gene expression correlation among interacting molecules. The difficulty of distinguishing between direct and indirect interactions is addressed by optimizing the coefficient of variation of gene expression, using a validated gold-standard dataset of direct interactions. Computational time is much reduced compared to other network reconstruction methods. A key feature is the study of the reproducibility of interactions found in independent clinical datasets. An analysis of the most significant clusters, and of the network properties (intraset efficiency, degree, betweenness centrality, and PageRank) of common AML mutations demonstrated the biological significance of the network. A statistical analysis of the response of blast cells from 11 AML patients to a library of kinase inhibitors provided an experimental validation of the network. A combination of network and experimental data identified CDK1, CDK2, CDK4, and CDK6 and other kinases as potential therapeutic targets in AML.

Purpose

The Programmed Death-1 (PD-1) immune checkpoint pathway may be usurped by tumors, including diffuse large B-cell lymphoma (DLBCL), to evade immune surveillance. The reconstituting immune landscape after autologous hematopoietic stem-cell transplantation (AHSCT) may be particularly favorable for breaking immune tolerance through PD-1 blockade.

Patients and methods

We conducted an international phase II study of pidilizumab, an anti-PD-1 monoclonal antibody, in patients with DLBCL undergoing AHSCT, with correlative studies of lymphocyte subsets. Patients received three doses of pidilizumab beginning 1 to 3 months after AHSCT.

Results

Sixty-six eligible patients were treated. Toxicity was mild. At 16 months after the first treatment, progression-free survival (PFS) was 0.72 (90% CI, 0.60 to 0.82), meeting the primary end point. Among the 24 high-risk patients who remained positive on positron emission tomography after salvage chemotherapy, the 16-month PFS was 0.70 (90% CI, 0.51 to 0.82). Among the 35 patients with measurable disease after AHSCT, the overall response rate after pidilizumab treatment was 51%. Treatment was associated with increases in circulating lymphocyte subsets including PD-L1E-bearing lymphocytes, suggesting an on-target in vivo effect of pidilizumab.

Conclusion

This is the first demonstration of clinical activity of PD-1 blockade in DLBCL. Given these results, PD-1 blockade after AHSCT using pidilizumab may represent a promising therapeutic strategy in this disease.