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. Author manuscript; available in PMC: 2020 Jul 1.
Published in final edited form as: Genet Med. 2019 Jan 14;21(7):1548–1558. doi: 10.1038/s41436-018-0377-x

Figure 3. Developing and Validation of the Risk Prediction Model and Diagnostic Pipeline of TACS. (A) TACScore: risk predictive model for TACS.

Figure 3.

The final multivariate risk model was developed through a binary logistic regression analysis of detailed phenotypic data from Cohort 1. (B) The predictive efficacy of the TACScore. The X-axis shows the spectrum of TACScore and Y-axis shows the predicted TACS frequency and the percentage of TACS patients in all CS patients with each calculated score in Cohort 1 and Cohort 2. The TACScore presented excellent predictive efficacy by comparing the predicted TACS risk to the real TACS frequency. The cutoff point was selected as 3 to achieve the highest accuracy. (C) ROC Curve for the TACScore in Cohort 1 and Cohort 2. AUCs were 0.9 (P=1.6×10−15; 95% CI, 0.9–1.0) for the discovery cohort (Cohort 1) and 0.8 (P=1.5×10−4; 95% CI, 0.7–0.9) for the validation cohort (Cohort 2). (D) A proposed guideline for predicting and evaluating TACS. The risk of TACS evaluated by TACScore is suggested to perform prior to genetic testing. After the detection of TACS, a systemic evaluation, with early interventions and genetic consultation were recommended.

Abbreviation: CS, congenital scoliosis; TACS, TBX6-associated CS; ES, exome sequencing; CMA, chromosomal microarray analysis; GS, genome sequencing.

a TBX6 compound variant contains a 16p11.2 deletion/TBX6 loss-of-function variant in the compound heterozygous configuration with the risk haplotype providing a hypomorphic variant.

b VUS, variants with unknown significance.

c Evidence from large-scale case-control studies, pedigree analysis, and functional studies are needed.