The NYCKidSeq randomized controlled trial: Impact of GUÍA digitally enhanced genetic results disclosure in diverse families

Abstract

Digital solutions are needed to support rapid increases in the application of genetic/genomic tests (GTs) in diverse clinical settings and patient populations. We developed GUÍA, a bilingual digital application that facilitates disclosure of GT results. The NYCKidSeq randomized controlled trial enrolled diverse children with neurologic, cardiac, and immunologic conditions who underwent GTs. The trial evaluated GUÍA's impact on understanding the GT results by randomizing families to results disclosure genetic counseling with GUÍA (intervention) or standard of care (SOC). Parents/legal guardians (participants) completed surveys at baseline, post-results disclosure, and 6 months later. Survey measures assessed the primary study outcomes of participants' perceived understanding of and confidence in explaining their child's GT results and the secondary outcome of objective understanding. The analysis included 551 diverse participants, 270 in the GUÍA arm and 281 in SOC. Participants in the GUÍA arm had significantly higher perceived understanding post-results (OR = 2.8, CI[1.004, 7.617], p = 0.049) and maintained higher objective understanding over time (OR = 1.1, CI[1.004, 1.127], p = 0.038) compared to SOC. There was no impact on perceived confidence. Hispanic/Latino(a) individuals in the GUÍA arm maintained higher perceived understanding (OR = 3.9, CI[1.603, 9.254], p = 0.003), confidence (OR = 2.7, CI[1.021, 7.277], p = 0.046), and objective understanding (OR = 1.1, CI[1.009, 1.212], p = 0.032) compared to SOC. This trial demonstrates that GUÍA positively impacts understanding of GT results in diverse parents of children with suspected genetic conditions and builds a case for utilizing GUÍA to deliver complex results. Continued development and evaluation of digital applications in diverse populations are critical for equitably scaling GT offerings in specialty clinics.

Keywords: digital solutions; digital tools; diverse populations; genetic counseling; genetic testing; genome sequencing; genomic medicine.

Graphical abstract

Figure 1

Consort diagram for the NYCKidSeq randomized controlled trial A total of n = 1,017 children were assessed for eligibility in NYCKidSeq. Of n = 888 who were eligible for enrollment, n = 38 were assigned to the Lead-In Phase and n = 622 were included in the RCT with n = 312 randomized to the GUÍA arm and n = 310 to the standard of care (SOC) arm. Note, ^∗one participant in the GUÍA arm did not complete the baseline survey. Excluding the Lead-In Phase (n = 38), n = 613 provided a sample and enrolled in the RCT: n = 308 in the GUÍA arm and n = 305 in SOC. In the GUÍA arm, n = 281 completed the ROR1 survey (∼3 months from enrollment) and n = 255 completed the ROR2 survey (∼9 months from enrollment and ∼6 months post-disclosure). In the SOC arm, n = 294 completed the ROR1 survey and n = 268 completed the ROR2 survey. The final analytic sample was n = 551 (n = 270 in the GUÍA arm, n = 281 in the SOC arm) for ROR1 and n = 487 (n = 238 in the GUÍA arm, n = 249 in the SOC arm) for ROR2. RCT, randomized controlled trial; LTFU, lost to follow-up; SOC, standard of care; GC, genetic counseling; GS, genome sequencing; TGP, targeted gene panel; ROR1, results disclosure time point; ROR2, 6-month post-disclosure time point.

Figure 2

Forest plots displaying results of the longitudinal analyses using repeated measures for the entire cohort (ALL) and stratified by sociodemographic and clinical characteristics The stratified analyses were conducted with six characteristics: population group, health literacy, case-level result interpretation, neurological phenotype, poverty level, and interpreter use at results disclosure. The separate panels show differences in perceived understanding, perceived confidence, and objective understanding between GUÍA and SOC arms for ALL randomized participants and stratified by characteristic subgroups. We analyzed perceived understanding and confidence using alternating logistic regression, and we used Poisson regression to analyze the objective understanding summary score. The following covariates were included in all models: parent age, education level, language, child’s insurance, and case-level interpretation. In addition, genetic counselor was added as a covariate for perceived understanding and confidence, and health system was added as a covariate for objective understanding. The p value is shown for every characteritic subgroup, and the bars around the odds ratio point designate the 95% confidence interval. SOC, standard of care; IDD, intellectual developmental disability.

Figure 3

Forest plots displaying results of the longitudinal analyses using repeated measures of the H/L population by interpreter use and health literacy level The panels display differences in perceived understanding, perceived confidence, and objective understanding between GUÍA and SOC arms for H/L participants stratified by medical interpreter use at result disclosure and health literacy level. We analyzed perceived understanding and confidence using alternating logistic regression and Poisson regression to analyze the objective understanding summary score. The following covariates were included in all models: parent age, education level, language, child’s insurance, and case-level interpretation. In addition, genetic counselor was added as a covariate for perceived understanding and confidence, and health system was added as a covariate for objective understanding. The p value is shown for every characteritic subgroup, and the bars around the odds ratio point designate the 95% confidence interval. SOC, standard of care; H/L, Hispanic/Latino(a).