Abstract：
This study explores the reliability of four established legal age threshold estimation approaches in a Croatian sample. We applied Haavikko stages, Demirjian stages, Olze\'s third molar eruption stages, and second and third molar maturity indices measurement in 593 orthopantomograms of Croatian children and adolescents aged 11.00-20.99 years old. The left mandibular second and third molar were assessed. Logistic regression analysis was conducted to test the significance of predictive variables. Logistic Receiver operating characteristic (ROC) curves were performed to evaluate the classification ability of variables for estimating 14- and 16-year-old thresholds. The areas under the ROC curve (AUC), accuracy (Acc), sensitivity (Se), specificity (Sp), Positive Likelihood Ratio (LR +), Negative Likelihood Ratio (LR-), and Bayes post-test probability (Bayes PTP) were calculated to evaluate classification performance. Results suggest that the combination of I2M&I3M is the best classifier for the 14-year-old threshold (AUC = 0.879); for males alone, I2M is an even better classifier (AUC = 0.881). The highest Acc 80.1% (95%CI, 75.9%-83.9%), Bayes PTP 86.5% (95%CI, 82.8%-89.7%) and Sp 88.9% (95%CI, 83.0%-93.3%) were by I3M < 0.81 & I2M < 0.03 in total samples; the highest Acc 86.1% (80.6%- 90.6%), Bayes PTP 87.2% (95%CI, 81.7%- 91.4%) and Sp 87.8% (95%CI, 78.2%- 94.3%) were by I2M < 0.01 in males, Acc of Haavikko Ac and Demirjian H stage in second molar is very close with slightly lower Bayes PTP and Sp. I3M is a good classifier for 16-year-old threshold (AUC = 0.889). The cut-off value I3M < 0.34 can be used to classify the 16-year-old threshold with Acc of 80.6% (95%CI, 77.2%-83.7%), Sp of 83.4% (95%CI, 79.0%-87.3%), and 81.7% (95%CI, 78.4%-84.8%) Bayes PTP. In conclusion, to classify the 14-year-old threshold, a pair of cut-off values I3M < 0.81 & I2M < 0.03 can be used in Croatian females; I2M < 0.01, Demirjian H stage, Haavikko Ac stage in second molar, and the pair I3M < 0.81 & I2M < 0.03 can all be used in Croatian males. I3M < 0.34 can classify the 16-year-old threshold in Croatian populations.
摘要：
这项研究探讨了克罗地亚样本中四种既定的法定年龄阈值估计方法的可靠性。我们应用了Haavikko阶段，Demirjian舞台，Olze的第三磨牙喷发阶段，在11.00-20.99岁的克罗地亚儿童和青少年的593个正位体图中测量第二和第三磨牙的成熟度指数。评估左下颌第二磨牙和第三磨牙。采用Logistic回归分析检验预测变量的显著性。进行逻辑接收器工作特征（ROC）曲线以评估变量的分类能力，以估计14岁和16岁的阈值。ROC曲线下面积(AUC),准确度（Acc），灵敏度（Se），特异性（Sp），正似然比(LR+)，负似然比(LR-)，并计算贝叶斯后验概率(BayesPTP)来评估分类性能。结果表明，I2M和I3M的组合是14岁阈值的最佳分类器（AUC=0.879）；仅对于男性，I2M是甚至更好的分类器(AUC=0.881)。最高Acc80.1%（95CI，75.9%-83.9%），BayesPTP86.5%(95CI,82.8%-89.7%)和Sp88.9%(95CI,83.0%-93.3%)在总样本中的I3M<0.81&I2M<0.03;最高Acc86.1%(80.6%-90.6%),男性BayesPTP为87.2％（95CI，81.7％-91.4％）和Sp为87.8％（95CI，78.2％-94.3％），第二磨牙HaavikkoAc和DemirjianH阶段的Acc非常接近，贝叶斯PTP和Sp略低。I3M是16岁阈值(AUC=0.889)的良好分类器。截止值I3M<0.34可用于对16岁阈值进行分类，Acc为80.6％（95CI，77.2％-83.7％），Sp为83.4%（95CI，79.0%-87.3%），和81.7%（95CI，78.4%-84.8%）贝叶斯PTP。总之,为了对14岁的门槛进行分类，一对临界值I3M<0.81&I2M<0.03可用于克罗地亚女性；I2M<0.01，DemirjianH期，HaavikkoAc在第二磨牙阶段，对I3M<0.81和I2M<0.03都可以用于克罗地亚男性。I3M<0.34可以对克罗地亚人群的16岁阈值进行分类。
