Morton, Cynthia C.

Objective: To compare 12-month post-treatment health-related quality of life (HR-QoL) and symptom severity (SS) changes among patients with symptomatic uterine fibroids (SUF) not seeking fertility and undergo a hysterectomy, abdominal myomectomy (AM), or uterine artery embolization (UAE). Materials and Methods: The Comparing Options for Management: Patient-Centered Results for Uterine Fibroids (COMPARE-UF) Registry is a multi-institutional prospective observational cohort study of patients treated for SUF. A subset of 1465 women 31–45 years of age, who underwent either hysterectomy ( n = 741), AM ( n = 446), or UAE ( n = 155) were included in this analysis. Demographics, fibroid history, and symptoms were obtained by baseline questionnaires and at 1 year post-treatment. Results were stratified by all treatments and propensity score weighting to adjust for differences in baseline characteristics. Results: Women undergoing UAE reported the lowest baseline HR-QoL and highest SS scores (mean = 40.6 [standard deviation (SD) = 23.8]; 62.3 [SD = 24.2]) followed by hysterectomy (44.3 [24.3]; 59.8 [SD = 24.1]). At 12 months, women who underwent a hysterectomy experienced the largest change in both HR-QoL (48.7 [26.2]) and SS (51.9 [25.6]) followed by other uterine-sparing treatments. Propensity score weighting revealed all treatments produced substantial improvement, with hysterectomy patients reporting the highest HR-QoL score (92.0 [17.8]) compared with myomectomy (86.7 [17.2]) and UAE (82.6 [21.5]) ( p < 0.0001). Similarly, hysterectomy patients reported the lowest SS scores (8.2 [15.1]) compared with myomectomy (16.5 [15.1]) and UAE (19.6 [17.5]) ( p < 0.0001). Conclusion: All procedures showed improvement in HR-QoL and reduction in SS score at 12 months, hysterectomy showing maximum improvement. Of importance, at 12 months, patients who underwent either a myomectomy or UAE reported comparable symptom relief and HR-QoL. Clinicaltrials.Gov Identifier: NCT02260752.

AbstractBalanced and apparently balanced chromosome abnormalities (BCAs) have long been known to generate disease through position effects, either by altering local networks of gene regulation or by positioning genes in architecturally different chromosome domains. Despite these observations, identification of genes distally affected by BCAs is often neglected, especially when predicted gene disruptions are found elsewhere in the genome. In this article, we provide detailed instructions on how to run a computational pipeline that identifies relevant candidates for non‐coding BCA position effects. This methodology facilitates quick identification of genes potentially involved in disease by non‐coding BCAs and other types of rearrangements, and expands on the importance of considering the long‐range consequences of genomic lesions. © 2018 by John Wiley & Sons, Inc.