## 4 Discussion  
PIH is a common skin complication in patients after treatment with lasers and other light sources [6]. As no objective prediction model is available at present, this side effect is predicted based on medical history. However, we found that PIH can be predicted in laser toning patients using the LASSO-based PIHCP model with cross-validation. The incidence of PIH in laser toning patients in this study was 16.8% (NPV = 84%). Similar reports by [PERSON] et al. [2] and [PERSON] et al. [21] showed that pigmented disorders can be easily controlled by laser toning therapy, but complications may occur. The incidence of rebound hyperpigmentation or hypopigmentation associated with laser toning was reported to range from 0% to 16.8% [2; 3; 5; 21]. For the PIHCP model with the LASSO algorithm, the most important risk factors for PIHCP were IEL, AHA peel, FSPT, acne, and melanoma. The AUC improved from 0.62 to 0.79 when the number of risk predictive factors used was increased from one (IEL) to five (AHA peel, FSPT, acne, and melanoma; Table 4). An appropriate set of predictive factors can limit the risk of PIH in patients treated with Q-switched Nd-YAG laser toning. Risk prediction models for PIH could optimize current laser toning therapies and indicate which risk factors are the most important to limit the rate of complications. The incidence of PIH could be reduced if the risk factors are handled appropriately. Among the predictive factors tested in our models, the most significant was IEL. The major negative outcome of laser treatment is early tissue reactions occurring immediately after laser treatment, which provide a reliable indication of tissue injury. [PERSON] et al. reported that IEL is an indicator of laser-tissue reaction and PIH is caused by inflammation [4; 19]. Thus, the occurrence of immediate-onset laser-tissue reaction is a strong indicator of the possibility of PIH [4; 19]. A similar report by [PERSON] et al. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Predictive Factors Selected** & **HL** & **SB-S** & \(\mathbf{R^{2}}\) & **Omnibus** & **AUC** \\ \hline IEL, & 1.00 & 0.06 & 0.08 & 0.06 & 0.62 (0.48–0.77) \\ IEL, AHA Peels & 0.60 & 0.09 & 0.13 & 0.02 & 0.67 (0.53–0.81) \\ IEL, AHA Peels, FSPT & 0.82 & 0.10 & 0.16 & 0.03 & 0.73 (0.60–0.85) \\ IEL, AHA Peels, FSPT, Acnes & 0.44 & 0.12 & 0.18 & 0.03 & 0.75 (0.63–0.87) \\ IEL, AHA Peels, FSPT, Acnes, Melasma & 0.29 & 0.11 & 0.20 & 0.02 & 0.79 (0.70–0.88) \\ \hline \hline \end{tabular} Abbreviations: FSPT: Fitzpatrick skin phototype; IEL: Immediately Endpoints of Laser; AHA: \(\alpha\)-hydroxy acid; Nevus. AUC: Area under the receiver operating characteristic curve; HL: Hosmer–Lemeshow test SB-S: Scaled Brier score; the first five predictive factors were IEL, AHA Peels, FSPT, Acnes, and Melasma.  
\end{table} 
Table 4: System performance evaluation. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Predictive Factors** & \(\beta\) & \(\mathbf{p}\)**-Value** & **Odds Ratio** & **95\% CI** \\ \hline \multicolumn{5}{c}{(\(n=5\))} \\ \multicolumn{5}{c}{Immediately Endpoints of} \\ \multicolumn{5}{c}{Laser (IEL)} \\ \multicolumn{5}{c}{Erythema (0)} \\ \multicolumn{5}{c}{Petechiae (1)} \\ \multicolumn{5}{c}{Léythema mild Petechiae (2)} \\ \multicolumn{5}{c}{AHA Peels} \\ \multicolumn{5}{c}{FSPT} \\ \multicolumn{5}{c}{Type III (0)} \\ \multicolumn{5}{c}{Type IV (1)} \\ \multicolumn{5}{c}{} \\ \multicolumn{5}{c}{Type V (2)} \\ \multicolumn{5}{c}{Acnes} \\ \multicolumn{5}{c}{Yes (1)} \\ \multicolumn{5}{c}{Melasma} \\ \multicolumn{5}{c}{Yes (1)} \\ \multicolumn{5}{c}{Yes (1)} \\ \multicolumn{5}{c}{Melasma} \\ \multicolumn{5}{c}{Yes (1)} \\ \multicolumn{5}{c}{Constant (\(\beta_{0}\))} \\ \multicolumn{5}{c}{Abbreviations: FSPT: Fitzpatrick skin phototype; AHA: \(\alpha\)-hydroxy acid; CI: Confidence Interval; n: selected predictive risk factors.} \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Multivariate logistic regression coefficients and odds ratios.