The effect of opting-in versus opting-out forming on the rate of reported variants of questionable significance in prenatal microarray

Int J Gynaecol Obstet. 2024 Dec;167(3):1231-1236. doi: 10.1002/ijgo.15805. Epub 2024 Jul 19.

Abstract

Objective: To examine the effect of patient-selected opt-in versus opt-out option on the rate of reported variants of uncertain clinical significance (VOUS) and high-frequency low-penetrant (HFLP) findings in prenatal microarray testing.

Methods: A standard microarray consent form in Israel includes a requirement to note patient choice to be or not to be informed about the presence of VOUS and HFLP variants. The original form was designed as an opting-out method, in which the women had to actively mark if they did not want to be informed about questionable findings. In the authors' Genetic Institute, the form was changed for an opting-in option in October 2019. In this study we have compared the rates of reported VOUS and HFLP variants between the opt-in and opt-out periods.

Results: Of the 1014 prenatal CMA tests, 590 (58.2%) were performed in the opt-out period. A significant decrease in the rate of women requesting to be informed of VOUS findings was noted (66.8% in opt-out period vs 34.0% in opt-in period), yielding a relative risk (RR) of 0.46 (95% confidence interval [CI] 0.39-0.53). Rate of women preferring to be informed of HFLP variants decreased from 75.3% to 48.1% (RR 0.52, 95% CI 0.45-0.60).

Discussion: We present a simple and effective method to decrease the rate of reported findings of questionable significance in the prenatal setting. These results are important not only for microarray results, but also for next-generation sequencing techniques, such as whole exome or genome sequencing.

Keywords: chromosomal microarray analysis; decision making; genetic counseling; prenatal diagnosis; variants of uncertain clinical significance.

MeSH terms

  • Adult
  • Female
  • Genetic Testing / methods
  • Genetic Testing / statistics & numerical data
  • Humans
  • Israel
  • Microarray Analysis*
  • Pregnancy
  • Prenatal Diagnosis* / methods