Development and internal validation of a pragmatic nomogram for predicting treatment-refractory outcomes in pediatric tic disorders: a single-center retrospective cohort study

Development and internal validation of a pragmatic nomogram for predicting treatment-refractory outcomes in pediatric tic disorders: a single-center retrospective cohort study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Development and internal validation of a pragmatic nomogram for predicting treatment-refractory outcomes in pediatric tic disorders: a single-center retrospective cohort study Zhenyu Lu, Huiyang Hu, Chunsong Yang, Dan Yu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9327833/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Background A clinically important subgroup of children and adolescents with tic disorders develops persistent symptoms and functional impairment despite treatment, yet practical tools for early risk stratification in outpatient care are lacking. We aimed to develop and internally validate a pragmatic nomogram to predict treatment-refractory outcomes in pediatric tic disorders. Methods In this single-center retrospective cohort study, we included patients younger than 18 years with DSM-5 tic disorders who attended West China Second University Hospital between October 2021 and October 2023 and completed follow-up between April and August 2025. Treatment-refractory outcome at the end of follow-up was adjudicated using a prespecified framework that explicitly excluded pseudo-refractoriness. Vitamin D, the only substantially incomplete variable, was handled with multiple imputation. Predictors were selected using LASSO with 10-fold cross-validation and preference for the lambda.1se rule, followed by multivariable logistic regression with pooled estimates across imputed datasets. We assessed discrimination, calibration, internal validation, clinical utility, and prespecified sensitivity analyses. Results Among 806 participants, 82 (10.2%) met criteria for treatment-refractory outcome. Four predictors were retained in the final model: tic type, comorbidity burden, adverse pregnancy and perinatal factors, and psychosocial stressors. Concurrent mixed tics, greater comorbidity burden, adverse pregnancy and perinatal factors, and psychosocial stressors were independently associated with higher risk. The model showed good apparent discrimination (AUC 0.820), limited optimism after bootstrap correction (optimism-corrected AUC 0.802), acceptable calibration, and net benefit across clinically relevant threshold probabilities. Sensitivity analyses supported the robustness of the main findings. Conclusions This internally validated nomogram may help identify children and adolescents with tic disorders who are at increased risk of a treatment-refractory course. Beyond risk prediction, it may help child and adolescent mental health outpatient services identify patients who need earlier comorbidity-focused assessment, psychosocial intervention, family-school coordination, and intensified follow-up. External validation, recalibration, and prospective implementation studies are needed before routine use. tic disorders treatment-refractory outcomes prediction model nomogram comorbidity burden psychosocial stress perinatal adversity Figures Figure 2 Figure 3 Figure 4 Background Tic disorders (TDs), including provisional tic disorder, persistent motor or vocal tic disorder, and Tourette syndrome (TS), are childhood-onset neurodevelopmental conditions[ 1 – 3 ]. Although symptoms improve over time in many affected children, [ 4 , 5 ] a clinically important subgroup has persistent symptoms despite treatment and continues to experience psychiatric comorbidity, psychosocial stress, functional impairment, and reduced quality of life[ 2 , 4 , 6 , 7 ]. After excluding pseudo-refractoriness due to inadequate treatment exposure, poor adherence, or predominantly uncontrolled comorbidity, this unfavorable course can be conceptualized as treatment-refractory[ 8 – 11 ]. This issue has direct relevance to child and adolescent mental health services. In routine practice, the burden associated with TD rarely depends on tic symptoms alone; rather, it reflects the combined effects of tic phenotype, psychiatric comorbidity, psychosocial adversity, and developmental vulnerability[ 1 , 2 , 4 , 12 ]. Co-occurring attention-deficit/hyperactivity disorder, obsessive-compulsive symptoms, anxiety, and depression may amplify impairment and complicate management [ 6 , 7 , 13 , 14 ]. Psychosocial stress may further exacerbate tic fluctuation, undermine coping, and disrupt family and school functioning[ 15 – 18 ]. Population-based evidence linking tic disorders to self-harm and premature mortality further underscores the need to identify young patients at risk of a more adverse course[ 19 , 20 ]. Despite this need, early identification of children likely to develop a treatment-refractory course still depends largely on clinical judgment. Existing studies have focused mainly on definitions, treatment strategies, or comparisons between refractory and non-refractory groups[ 10 , 11 , 21 , 22 ] or on predictors of long-term tic severity and response to behavioral therapy[ 23 – 25 ], rather than on directly usable prediction tools for treatment-refractory outcomes in pediatric TD. A pragmatic outpatient model based on routinely collected baseline information could support earlier comorbidity-focused assessment, psychosocial intervention, family-school coordination, and more efficient use of specialist follow-up resources[ 12 ]. We therefore developed and internally validated a pragmatic clinic-based nomogram to predict treatment-refractory outcomes in a single-center pediatric TD cohort. Methods Study design and participants This single-center retrospective cohort study used consecutive outpatient electronic medical records from West China Second University Hospital, Sichuan University, supplemented by standardized telephone follow-up. Eligible participants were younger than 18 years, attended the outpatient clinic between October 2021 and October 2023, and met DSM-5 diagnostic criteria for a tic disorder. All included participants underwent telephone follow-up during a prespecified window (April 2025 to August 2025) for outcome ascertainment. Clinical and follow-up information used for outcome adjudication and variable collection was obtained from structured guardian telephone interviews together with outpatient electronic medical records, laboratory records, prescription history, and clinician assessment. We excluded patients with secondary or symptomatic tics or uncertain diagnoses, those with severe neurodevelopmental disorders that precluded reliable assessment, those lost to follow-up or with insufficient outcome information, and pseudo-refractory cases (defined below). This study was approved by the Ethics Committee of West China Second University Hospital, Sichuan University (No. 2025 − 241). Written informed consent was waived for the retrospective chart review. Before telephone follow-up, verbal informed consent was obtained from guardians and documented, and all data were de-identified before analysis. Outcome and group definitions The primary outcome was treatment-refractory outcome at the end of follow-up. Outcome adjudication followed a prespecified pragmatic framework derived from expert consensus on treatment failure in persistent tic disorders, integrating illness duration, adequacy of treatment exposure, persistent clinical burden, and explicit exclusion of pseudo-refractoriness[ 8 ]. Because the Yale Global Tic Severity Scale was not collected systematically in this cohort, endpoint severity and improvement were assessed using the Clinical Global Impressions scales for severity (CGI-S) and improvement relative to baseline (CGI-I), pragmatic instruments for retrospective chart review and telephone follow-up[ 26 – 28 ]. Participants were classified as having a treatment-refractory outcome if all of the following criteria were met: tic duration > 12 months; after exclusion of pseudo-refractoriness, failure of at least two adequately delivered anti-tic medications with different mechanisms; treatment trials of adequate dose and duration (generally 8–12 weeks, including at least 4–8 weeks within the maximum tolerated dose range)[ 8 , 29 ]; and persistence at follow-up of at least moderate severity or poor response together with functional impairment, defined as CGI-S ≥ 4, or CGI-I ≥ 4 plus documentation of academic, social, or family impairment in the medical record or follow-up interview[ 8 , 26 – 28 ]. Treatment discontinuation because of documented adverse effects could also count as failure when tolerability precluded an adequate therapeutic course. Pseudo-refractoriness was defined as apparent treatment failure attributable to inadequate treatment exposure or poor adherence, including missed doses, self-discontinuation, clearly insufficient dose or duration, or labeling a regimen ineffective before an adequate trial had been completed. It also included cases in which an uncontrolled comorbidity was judged to be the principal driver of impairment or symptom fluctuation in the absence of sufficient evidence of tic-specific treatment failure. To reduce circularity, baseline comorbidity burden was retained as a candidate predictor but was not itself used to define treatment-refractory outcome or pseudo-refractoriness, and cases were not excluded solely because of a higher baseline comorbidity count[ 8 ]. The non-RTD group included patients who did not meet criteria for treatment-refractory outcome and had a favorable status at follow-up, defined as CGI-I ≤ 3 or CGI-S ≤ 3 without the need for further intensification of anti-tic treatment[ 26 ]. Variable collection and measurement Candidate predictors were prespecified on the basis of previous literature and clinical interpretability. They included demographic and clinical characteristics, tic phenotype (type, site of onset, age at onset, and age at symptom peak), comorbidity burden, family history, family environment, parenting style, adverse pregnancy and perinatal factors, psychosocial stressors, recurrent respiratory infections, allergy history, screen time, and vitamin D values. Family-reported follow-up information was collected using an investigator-developed structured guardian telephone interview (Additional file 3). Study variables were documented and coded using a study-specific information extraction form (Additional file 4). Baseline clinical, laboratory, and treatment-related data were obtained from outpatient electronic medical records, laboratory records, and prescription records; missing historical information was supplemented by guardian interview where applicable. CGI-S and CGI-I were rated by clinicians on the basis of interview data, chart review, and clinical judgment. Statistical analysis and model development All analyses were performed in R version 4.5.2. Continuous variables were summarized as medians (IQRs) and categorical variables as counts (%), as appropriate. Baseline comparisons in Table 1 were descriptive and were not used to screen predictors for model development. Group comparisons used the chi-square test or Fisher’s exact test for categorical variables and the Mann-Whitney U test for continuous variables, as appropriate. Vitamin D values (vd_value) had missing data (approximately 27%) and were handled using multiple imputation by chained equations (m = 5)[ 30 ]. No other variables had missing values, and the outcome was not imputed. Predictive mean matching was used for continuous variables, logistic regression for binary variables, and polytomous regression for multicategory variables within the imputation model. As a pragmatic workflow, least absolute shrinkage and selection operator regression (glmnet package) with 10-fold cross-validation and preference for the lambda.1se rule was performed in the first completed imputed dataset. Selected variables were then refit across all five imputed datasets using multivariable logistic regression, and adjusted odds ratios (ORs) with 95% confidence intervals (CIs) were pooled using Rubin’s rules[ 31 ]. To assess robustness, we performed two prespecified sensitivity analyses. First, we repeated the multivariable analysis using complete cases only, without multiple imputation. Because complete-case analysis reduced the sample size, this analysis was intended to assess the stability of the main associations rather than to redefine the final model. Second, because some categories were sparse, we refit the model after collapsing comorbidity burden into 0, 1, and ≥ 2 and tic type into concurrent mixed versus all other tic types. For comparability, multivariable logistic regression was repeated using the same core predictors as in the primary model; for the sparse-category analysis, pooled estimates were again obtained across imputed datasets. Discrimination in sensitivity analyses was assessed using the area under the receiver operating characteristic curve (AUC). Detailed results are provided in Supplementary Tables S1 and S2. Model performance, internal validation, calibration, and clinical utility A nomogram was constructed from the final logistic model. For presentation and potential clinical application, the nomogram, forest plot, receiver operating characteristic (ROC) analyses, calibration plot, decision curve analysis, clinical impact curve, and bootstrap internal validation were generated from the first completed imputed dataset using the final four-variable model. Apparent discrimination was assessed with the area under the ROC curve (AUC), and bootstrap resampling (B = 1000) was used to estimate optimism-corrected discrimination and calibration. Calibration was evaluated using a bootstrap calibration plot, the calibration slope, calibration-in-the-large (CITL), the Hosmer-Lemeshow test, and the Brier score. The apparent optimal classification threshold was identified from the ROC curve. Decision curve analysis and the clinical impact curve were used to assess net benefit and the expected number of high-risk classifications across threshold probabilities[ 32 ]. Results Study population and baseline characteristics A total of 806 children and adolescents with TD were included, comprising 724 non-RTD and 82 RTD cases. Baseline characteristics are summarized in Table 1 . Compared with the non-RTD group, the RTD group differed significantly in tic phenotype (P < 0.001), comorbidity burden (P < 0.001), poor family environment (P = 0.008), adverse pregnancy and perinatal factors (P = 0.002), psychosocial stressors (P < 0.001), allergy history (P = 0.047), and vitamin D level (P = 0.004). The RTD group had a substantially higher proportion of concurrent mixed tics (45.1% vs 10.2%), a greater comorbidity burden (≥ 1 comorbidity, 86.6% vs 46.0%), and lower vitamin D levels [22.80 (17.68, 27.08) vs 25.10 (20.58, 30.30)]. Sex, site of onset, age at onset, age at symptom peak, family history, parenting style, recurrent respiratory infection, and screen time did not differ significantly between groups. Table 1 Comparison of baseline characteristics between the non-RTD and RTD groups Characteristics Non-RTD (n = 724) RTD (n = 82) P value Gender (male) 536 (74.0%) 68 (82.9%) 0.104 Tic type < 0.001** Simple Motor 326 (45.0%) 22 (26.8%) Simple Vocal 20 (2.8%) 1 (1.2%) Mixed (non-concurrent) 304 (42.0%) 22 (26.8%) Mixed (concurrent) 74 (10.2%) 37 (45.1%) Site of onset 0.614 Face 547 (75.6%) 59 (72.0%) Head/Neck 53 (7.3%) 6 (7.3%) Shoulder 22 (3.0%) 4 (4.9%) Trunk 22 (3.0%) 2 (2.4%) Limbs 12 (1.7%) 0 (0.0%) Vocal/throat 68 (9.4%) 11 (13.4%) Comorbidity burden < 0.001** 0 391 (54.0%) 11 (13.4%) 1 290 (40.1%) 51 (62.2%) 2 37 (5.1%) 16 (19.5%) ≥ 3 6 (0.8%) 4 (4.9%) Family history 106 (14.6%) 19 (23.2%) 0.063 Poor family environment 81 (11.2%) 18 (22.0%) 0.008** Poor parenting style 164 (22.7%) 18 (22.0%) 0.996 Perinatal factors 84 (11.6%) 20 (24.4%) 0.002** Psychosocial stress 12 (1.7%) 9 (11.0%) < 0.001** Respiratory infection 422 (58.3%) 52 (63.4%) 0.438 Allergy history 178 (24.6%) 29 (35.4%) 0.047* Screen time 0.126 4 h 15 (2.1%) 5 (6.1%) Age at onset 6.00 [4.75, 8.00] 6.00 [5.00, 7.00] 0.502 Age at symptom peak 6.42 [5.00, 8.25] 6.50 [5.33, 8.00] 0.992 Vitamin D level 25.1 [20.6, 30.3] 22.8 [17.7, 27.1] 0.004** Note: *p < 0.05; **p < 0.01. Variable selection and independent predictors of RTD LASSO regression was used for variable reduction and predictor selection. In the first completed imputed dataset, 10-fold cross-validation favored the lambda.1se criterion as the more parsimonious solution, and four variables retained non-zero coefficients: tic type, comorbidity burden, adverse pregnancy and perinatal factors, and psychosocial stressors (Fig. 1 ). The four LASSO-selected variables were then entered into multivariable logistic regression across the five imputed datasets, and pooled estimates are shown in Fig. 2 . Using simple motor tics as the reference, concurrent mixed tics were independently associated with a higher risk of RTD (OR = 4.28, 95% CI 2.27–8.20, P < 0.001), whereas simple vocal tics (OR = 0.75, P = 0.792) and sequential mixed tics (OR = 0.88, P = 0.701) were not. Comorbidity burden showed a clear dose-response association: compared with no comorbidity, one comorbidity (OR = 4.79, 95% CI 2.44–10.20, P < 0.001), two comorbidities (OR = 11.06, 95% CI 4.52–27.77, P < 0.001), and three or more comorbidities (OR = 24.62, 95% CI 5.20–106.32, P < 0.001) were associated with progressively higher risk. Adverse pregnancy and perinatal factors (OR = 2.10, 95% CI 1.09–3.91, P = 0.028) and psychosocial stressors (OR = 5.30, 95% CI 1.77–15.57, P = 0.004) were also independent predictors. Nomogram construction A nomogram based on the final four-variable model was constructed and visualized in the first completed imputed dataset (Fig. 3 ). In practice, points are assigned for tic type, comorbidity burden, adverse pregnancy and perinatal factors, and psychosocial stressors, and the total score corresponds to an individualized predicted probability of RTD. Model discrimination, calibration, internal validation, and clinical utility The nomogram was evaluated for discrimination, calibration, internal validation, and potential clinical utility in the first completed imputed dataset (Fig. 4 ). Apparent discrimination was good, with an AUC of 0.820 (Fig. 4 A). Bootstrap internal validation suggested limited optimism, with an optimism-corrected AUC of 0.802 (Fig. 4 B). At the apparent optimal threshold of 0.114, sensitivity was 0.659 and specificity was 0.826. Calibration was acceptable, with a calibration slope of 0.876 and a CITL of -0.214; the bias-corrected curve remained close to the ideal line (Fig. 4 C). The Hosmer-Lemeshow test was non-significant (P = 0.916), and the Brier score was 0.0752. Decision curve analysis showed net benefit across an approximate threshold range of 5%–75% compared with treat-all and treat-none strategies (Fig. 4 D). The clinical impact curve suggested acceptable classification efficiency across clinically relevant thresholds; around the apparent optimal threshold (~ 0.11), about 223 per 1000 patients would be classified as high risk, including about 67 true RTD events per 1000 (Fig. 4 E). Sensitivity analyses Sensitivity analyses supported the robustness of the primary findings. In the complete-case analysis (n = 574; 60 events), the direction of association for the four main predictors remained unchanged. Concurrent mixed tics, greater comorbidity burden, adverse pregnancy and perinatal factors, and psychosocial stressors all remained associated with higher odds of treatment-refractory outcome, and model discrimination remained similar to that of the primary model (AUC 0.815). Similar findings were observed after collapsing sparse categories. In the sparse-category merged analysis, concurrent mixed tic type versus all other tic types (OR 4.61, 95% CI 2.67–7.94, P < 0.001) and higher comorbidity burden (OR 4.37, 95% CI 2.09–9.12, P < 0.001 for one comorbidity; OR 11.50, 95% CI 4.71–28.05, P < 0.001 for ≥ 2 comorbidities) remained strongly associated with treatment-refractory outcome; adverse pregnancy and perinatal factors (OR 2.09, 95% CI 1.12–3.93, P = 0.021) and psychosocial stressors (OR 4.91, 95% CI 1.67–14.41, P = 0.004) also remained significant. Discrimination in the sparse-category merged model was similar to that of the primary model (AUC 0.817). Overall, these analyses indicate that the primary findings were not materially driven by the imputation strategy or sparse category structure. Discussion Principal findings In this single-center retrospective pediatric outpatient cohort, we developed and internally validated a pragmatic clinic-based nomogram that estimates the probability of treatment-refractory outcome by the end of a prespecified follow-up window using four routinely available baseline variables: tic type, comorbidity burden, adverse pregnancy and perinatal factors, and psychosocial stressors. The model showed good apparent discrimination with limited optimism after bootstrap correction, acceptable calibration, favorable net benefit across clinically plausible thresholds, and stable results in prespecified sensitivity analyses. Together, these findings suggest that routinely collected baseline clinical information can be translated into an interpretable early risk estimate for children and adolescents with tic disorders. Relation to previous work and interpretation This study extends previous work by moving from descriptive identification of higher-risk features to individualized risk prediction. The existing literature on refractory TS/TD has focused largely on conceptual definitions[ 10 , 11 ], treatment strategies[ 10 ], or comparisons between refractory and non-refractory groups[ 21 , 22 ]. Some longitudinal studies have identified predictors of later tic severity[ 23 , 24 ] or response to behavioral therapy[ 25 ], but directly usable clinic-based prediction models for treatment-refractory outcomes in pediatric TD remain scarce. By restricting the model to a small set of routinely available variables, we sought to balance parsimony, interpretability, and clinical usefulness in real-world outpatient practice. The retained predictors appear to capture complementary dimensions of vulnerability: symptom complexity, psychiatric burden, developmental vulnerability, and psychosocial context. Concurrent mixed tics may mark more complex disease expression[ 2 , 33 , 34 ], whereas the clear gradient across comorbidity categories suggests that adverse outcome in TD is shaped not only by tic manifestations themselves but also by accumulated neuropsychiatric burden[ 13 , 14 ]. Adverse pregnancy and perinatal factors are best interpreted as markers of neurodevelopmental vulnerability rather than as a single direct cause[ 35 , 36 ], and psychosocial stressors may represent potentially modifiable contextual factors that intensify symptom fluctuation[ 15 , 16 ], strain coping capacity, and complicate longer-term management[ 6 , 7 , 17 , 18 ]. The model therefore appears to capture a multidimensional clinical phenotype rather than a single severity axis. Implications for child and adolescent mental health services Importantly, the value of this model lies not only in predicting a more adverse clinical course, but also in supporting service delivery in child and adolescent mental health settings[ 37 , 38 ]. In routine outpatient practice, the model may help clinicians identify children who are more likely to require earlier comorbidity-focused assessment[ 12 ], psychosocial intervention[ 38 ], family-school coordination[ 6 , 7 , 37 ], and intensified follow-up[ 12 , 37 ], rather than relying solely on symptom-focused management. In this sense, the model should be viewed as a pragmatic decision-support and risk-stratification tool that may help prioritize multidisciplinary care for higher-risk patients, rather than as a substitute for clinical judgment. The practical value of the model lies less in the exact numerical probability than in its potential to support stratified outpatient management. Threshold probabilities around the observed optimal threshold (~ 0.11) may be most useful for identifying children who warrant enhanced follow-up, earlier screening for co-occurring psychiatric problems[ 13 , 14 ], more timely psychosocial review[ 15 , 16 ], and closer coordination across family, school, and specialist services[ 6 , 7 , 37 ]. The model may therefore help move care beyond a narrow focus on tic symptoms alone toward a broader child and adolescent mental health service framework that addresses comorbidity, psychosocial adversity, and functional impairment in an integrated way. Low-risk patients may continue routine follow-up and standard education, whereas children at moderate or high predicted risk may benefit from earlier multidisciplinary review, including screening for attention-deficit/hyperactivity disorder, obsessive-compulsive symptoms, anxiety, depression, sleep problems, and school maladaptation[ 13 , 14 ], together with strengthened family guidance and psychosocial support[ 6 , 7 , 38 ]. Whether this form of risk-stratified care improves real-world outcomes should be tested prospectively. Strengths, limitations, and next steps This study has several strengths. It addresses a clinically under-recognized yet important outcome, uses a relatively large pediatric outpatient cohort, and derives a parsimonious model from variables usually available in routine care, which supports feasibility. The model also integrates symptom phenotype, comorbidity burden, developmental vulnerability, and psychosocial context, reflecting the multidimensional nature of tic disorder management. The main findings were further supported by prespecified sensitivity analyses, which showed similar directions and magnitudes of association after complete-case analysis and simplification of sparse categories. Several limitations should be acknowledged. First, this was a single-center retrospective study and is therefore vulnerable to selection bias; external validation is still lacking. Second, some historical exposure information was supplemented retrospectively from guardians during telephone follow-up and may therefore be subject to recall bias. Third, outcome classification relied mainly on CGI together with integrated assessment of illness duration, treatment exposure, and functional impairment, rather than on a uniformly collected quantitative scale such as the Yale Global Tic Severity Scale. Fourth, because the outcome was defined at the end of a prespecified follow-up window rather than at a single uniform time horizon, some heterogeneity in follow-up duration may remain. Fifth, in retrospective clinical data, true refractoriness and pseudo-refractoriness may not be fully separable, particularly in the presence of severe comorbidity. Sixth, variable selection and graphical or internal-validation procedures were performed in the first completed imputed dataset, whereas coefficient estimates for inference were pooled across all five imputed datasets; this pragmatic workflow may underestimate selection uncertainty. Seventh, bootstrap validation was applied to the fixed final model rather than the full variable-selection process, so some residual optimism may remain. Finally, although optimism was modest, generalizability remains to be established. Future work should focus on external validation, recalibration when baseline risk differs across settings, and prospective implementation studies to determine whether risk-stratified care can improve outcomes and service efficiency. It will also be important to assess whether more standardized severity measures, adherence indicators, or longitudinal treatment variables can improve performance without sacrificing the simplicity that makes the current model potentially usable in routine outpatient care. Conclusions We developed an internally validated, pragmatic clinic-based nomogram for early estimation of treatment-refractory outcome risk in pediatric tic disorders. By integrating tic type, comorbidity burden, adverse pregnancy and perinatal factors, and psychosocial stressors, the model may support earlier comorbidity-focused assessment, psychosocial intervention, family-school coordination, and intensified follow-up in child and adolescent mental health outpatient services. External validation, recalibration, and implementation-focused prospective studies are needed before routine use. Abbreviations AUC Area under the receiver operating characteristic curve CGI-I Clinical Global Impression–Improvement CGI-S Clinical Global Impression–Severity CI Confidence interval CITL Calibration-in-the-large DSM-5 Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition IQR Interquartile range LASSO Least absolute shrinkage and selection operator OR Odds ratio ROC Receiver operating characteristic RTD Treatment-refractory tic disorder TD Tic disorder TS Tourette syndrome Declarations Ethics approval and consent to participate This study was approved by the Ethics Committee of West China Second University Hospital, Sichuan University (approval no. 2025 − 241). Written informed consent was waived for the retrospective chart review because this study used existing clinical records. Before telephone follow-up, verbal informed consent was obtained from guardians and documented. All data were de-identified before analysis. All procedures were performed in accordance with the Declaration of Helsinki and relevant institutional requirements. Consent for publication Not applicable. Competing interests The authors declare no competing interests. Funding This study was supported by the Tibet Autonomous Region Scientific and Technological Program (grant number XZ202501YD0006). Author Contribution ZL contributed to conceptualization, data curation, formal analysis, visualization, drafting of the manuscript, and revision of the manuscript. HH contributed to data collection and data verification. DY and CY contributed to study design, supervision, interpretation of the findings, and critical revision of the manuscript for important intellectual content. DY and CY jointly supervised the study and served as co-corresponding authors. All authors read and approved the final manuscript. Acknowledgements We thank the children and their guardians for their participation in the follow-up process. We also thank the clinicians and staff of West China Second University Hospital, Sichuan University, for their support in clinical data collection and follow-up coordination. Data Availability The datasets generated and/or analysed during the current study are not publicly available because they contain potentially identifiable clinical information from minors and are subject to institutional and ethical restrictions, but they are available from the corresponding author on reasonable request and with permission from the Ethics Committee of West China Second University Hospital, Sichuan University. References Robertson MM, Eapen V, Singer HS, Martino D, Scharf JM, Paschou P, et al. Gilles de la tourette syndrome. Nat Rev Dis Primers. 2017;3:16097. .https://doi.org/10.1038/nrdp.2016.97 . 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Capriotti MR, Brandt BC, Turkel JE, Lee H-J, Woods DW. Negative reinforcement and premonitory urges in youth with tourette syndrome: an experimental evaluation. Behav Modif. 2014;38:276–96. https://doi.org/10.1177/0145445514531015 . de la Fernández L, Rydell M, Runeson B, Brander G, Rück C, D’Onofrio BM, et al. Suicide in Tourette’s and Chronic Tic Disorders. Biol Psychiatry. 2017;82:111–8. https://doi.org/10.1016/j.biopsych.2016.08.023 . Hsu T-W, Chang W-H, Cheng C-M, Tsai S-J, Bai Y-M, Hsu J-W, et al. All-cause mortality and suicide mortality in patients with tic disorder: an entire population longitudinal study in taiwan. Suicide Life Threat Behav. 2025;55:e70023. https://doi.org/10.1111/sltb.70023 . Szejko N, Lombroso A, Bloch MH, Landeros-Weisenberger A, Leckman JF. Refractory gilles de la tourette syndrome-many pieces that define the puzzle. Front Neurol. 2020;11:589511. https://doi.org/10.3389/fneur.2020.589511 . Li Y, Yan J-J, Cui Y-H. Clinical characteristics of pediatric patients with treatment-refractory tourette syndrome: an evidence-based survey in a chinese population. World J Psychiatry. 2022;12:958–69. https://doi.org/10.5498/wjp.v12.i7.958 . Groth C, Skov L, Lange T, Debes NM. Predictors of the clinical course of tourette syndrome: a longitudinal study. J Child Neurol. 2019;34:913–21. https://doi.org/10.1177/0883073819867245 . Ricketts EJ, Woods DW, Espil FM, McGuire JF, Stiede JT, Schild J, et al. Childhood predictors of long-term tic severity and tic impairment in tourette’s disorder. Behav Ther. 2022;53:1251–64. https://doi.org/10.1016/j.beth.2022.07.002 . Sukhodolsky DG, Woods DW, Piacentini J, Wilhelm S, Peterson AL, Katsovich L, et al. Moderators and predictors of response to behavior therapy for tics in tourette syndrome. Neurology. 2017;88:1029–36. https://doi.org/10.1212/WNL.0000000000003710 . Busner J, Targum SD. The clinical global impressions scale: applying a research tool in clinical practice. Psychiatry (Edgmont). 2007;4:28–37. Walkup JT, Rosenberg LA, Brown J, Singer HS. The validity of instruments measuring tic severity in tourette’s syndrome. J Am Acad Child Adolesc Psychiatry. 1992;31:472–7. https://doi.org/10.1097/00004583-199205000-00013 . Jeon S, Walkup JT, Woods DW, Peterson A, Piacentini J, Wilhelm S, et al. Detecting a clinically meaningful change in tic severity in tourette syndrome: a comparison of three methods. Contemp Clin Trials. 2013;36:414–20. https://doi.org/10.1016/j.cct.2013.08.012 . Roessner V, Eichele H, Stern JS, Skov L, Rizzo R, Debes NM, et al. European clinical guidelines for tourette syndrome and other tic disorders-version 2.0. Part III: pharmacological treatment. Eur Child Adolesc Psychiatry. 2022;31:425–41. https://doi.org/10.1007/s00787-021-01899-z . van Buuren S, Groothuis-Oudshoorn K. mice: multivariate imputation by chained equations in R. J Stat Softw. 2011;45:1–67. https://doi.org/10.18637/jss.v045.i03 . Rubin DB. Multiple imputation for nonresponse in surveys. New York: Wiley; 1987. https://doi.org/10.1002/9780470316696 . Fitzgerald M, Saville BR, Lewis RJ. Decision curve analysis. JAMA. 2015;313:409–10. https://doi.org/10.1001/jama.2015.37 . Jackson GM, Draper A, Dyke K, Pépés SE, Jackson SR. Inhibition, disinhibition, and the control of action in tourette syndrome. Trends Cognit Sci. 2015;19:655–65. https://doi.org/10.1016/j.tics.2015.08.006 . Claudio-Campos K, Stevens D, Koo S-W, Valko A, Bienvenu OJ, Budman CB, et al. Is persistent motor or vocal tic disorder a milder form of tourette syndrome? Mov Disord. Off J Mov Disord Soc. 2021;36:1899–910. https://doi.org/10.1002/mds.28593 . Brander G, Rydell M, Kuja-Halkola R, Fernández de la Cruz L, Lichtenstein P, Serlachius E, et al. Perinatal risk factors in tourette’s and chronic tic disorders: a total population sibling comparison study. Mol Psychiatry. 2018;23:1189–97. https://doi.org/10.1038/mp.2017.31 . Dalsgaard S, Waltoft BL, Leckman JF, Mortensen PB. Maternal history of autoimmune disease and later development of tourette syndrome in offspring. J Am Acad Child Adolesc Psychiatry. 2015;54:495–e5011. https://doi.org/10.1016/j.jaac.2015.03.008 . Eapen V, Cavanna AE, Robertson MM. Comorbidities, social impact, and quality of life in tourette syndrome. Front Psychiatry. 2016;7:97. https://doi.org/10.3389/fpsyt.2016.00097 . Andrén P, Jakubovski E, Murphy TL, Woitecki K, Tarnok Z, Zimmerman-Brenner S, et al. European clinical guidelines for tourette syndrome and other tic disorders-version 2.0. Part II: psychological interventions. Eur Child Adolesc Psychiatry. 2022;31:403–23. https://doi.org/10.1007/s00787-021-01845-z . Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9327833","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":640541049,"identity":"70ffd7ec-254f-4cae-97d6-2ef654652d90","order_by":0,"name":"Zhenyu Lu","email":"","orcid":"","institution":"West China Second University Hospital of Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Zhenyu","middleName":"","lastName":"Lu","suffix":""},{"id":640541051,"identity":"4100c7dc-4c99-43fa-8664-88b8803e7925","order_by":1,"name":"Huiyang Hu","email":"","orcid":"","institution":"West China Second University Hospital of Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Huiyang","middleName":"","lastName":"Hu","suffix":""},{"id":640541053,"identity":"70251a59-6404-4142-99d0-e16181f3c860","order_by":2,"name":"Chunsong Yang","email":"","orcid":"","institution":"West China Second University Hospital of Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Chunsong","middleName":"","lastName":"Yang","suffix":""},{"id":640541054,"identity":"5ca51b30-00c3-4f29-a491-e83b4ecaf461","order_by":3,"name":"Dan Yu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA40lEQVRIie3RsWrDMBCA4TMHl+UckU2mxXkFgaFTH0YioC3Q0UOGQIM8lJDVj5ExYyDgSdk7ugS6NllKt1Z7gu1sHfTP98GdBBCL/cNo+nVptXpmQjCtLhf9ZAy6UOfS5mIEJ9X6pp/koJ8mtT8U2Sb5zD5WOGAx2FtMHZrtAW1plgSietPdJFk2p9RRIGTfze4RpD9uuwkmVZE6DoQD8QRKznsIIT2kTgYivl+MwwGEibLaqyJ7BQvDiGQMj6xzgTCT2jfce8u05iR85S+T2JvLT7nIRbXuJlfxfeOxWCwWu9kfCjRGlVVUcZgAAAAASUVORK5CYII=","orcid":"","institution":"West China Second University Hospital of Sichuan University","correspondingAuthor":true,"prefix":"","firstName":"Dan","middleName":"","lastName":"Yu","suffix":""}],"badges":[],"createdAt":"2026-04-05 17:39:53","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9327833/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9327833/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":109405617,"identity":"fc8797a8-d7ff-4a32-a914-a64e0f770c26","added_by":"auto","created_at":"2026-05-17 13:19:24","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":88308,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot of independent predictors of RTD from the multivariable logistic regression model.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-9327833/v1/ee5962ca71223162ffbe270f.png"},{"id":109338056,"identity":"8ef7562f-0100-4e6e-a069-5f661b76a227","added_by":"auto","created_at":"2026-05-15 17:49:44","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":42446,"visible":true,"origin":"","legend":"\u003cp\u003eNomogram for predicting risk of treatment-refractory outcome in pediatric tic disorders. Points are assigned for tic type, comorbidity burden, adverse pregnancy and perinatal factors, and psychosocial stressors; the total score corresponds to the predicted probability of treatment-refractory outcome.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-9327833/v1/17a0dc3a796c64eb52110352.png"},{"id":109338059,"identity":"281cd655-ec87-4c5e-8d15-28f06b945809","added_by":"auto","created_at":"2026-05-15 17:49:44","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":149700,"visible":true,"origin":"","legend":"\u003cp\u003eModel performance. (A) Apparent ROC curve. (B) Optimism-corrected ROC curve after bootstrap internal validation. (C) Calibration plot showing the apparent and bias-corrected curves together with the calibration slope and calibration-in-the-large (CITL). (D) Decision curve analysis. (E) Clinical impact curve. (F) Validation summary.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-9327833/v1/a4e20cd93761a57b9ba41473.png"},{"id":109338053,"identity":"a1f123ec-8de4-4bd6-b6c7-45f145b29345","added_by":"auto","created_at":"2026-05-15 17:49:44","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":9592,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-9327833/v1/87c722a8bba94b9f643b04bf.xlsx"},{"id":109405424,"identity":"b19d44ff-5d49-484a-b17b-21ee742c8e4a","added_by":"auto","created_at":"2026-05-17 13:17:58","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":39842,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile4.docx","url":"https://assets-eu.researchsquare.com/files/rs-9327833/v1/4c85485a5e78f1f6983b5ccc.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Development and internal validation of a pragmatic nomogram for predicting treatment-refractory outcomes in pediatric tic disorders: a single-center retrospective cohort study","fulltext":[{"header":"Background","content":"\u003cp\u003eTic disorders (TDs), including provisional tic disorder, persistent motor or vocal tic disorder, and Tourette syndrome (TS), are childhood-onset neurodevelopmental conditions[\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Although symptoms improve over time in many affected children, [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] a clinically important subgroup has persistent symptoms despite treatment and continues to experience psychiatric comorbidity, psychosocial stress, functional impairment, and reduced quality of life[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. After excluding pseudo-refractoriness due to inadequate treatment exposure, poor adherence, or predominantly uncontrolled comorbidity, this unfavorable course can be conceptualized as treatment-refractory[\u003cspan additionalcitationids=\"CR9 CR10\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis issue has direct relevance to child and adolescent mental health services. In routine practice, the burden associated with TD rarely depends on tic symptoms alone; rather, it reflects the combined effects of tic phenotype, psychiatric comorbidity, psychosocial adversity, and developmental vulnerability[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Co-occurring attention-deficit/hyperactivity disorder, obsessive-compulsive symptoms, anxiety, and depression may amplify impairment and complicate management [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Psychosocial stress may further exacerbate tic fluctuation, undermine coping, and disrupt family and school functioning[\u003cspan additionalcitationids=\"CR16 CR17\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Population-based evidence linking tic disorders to self-harm and premature mortality further underscores the need to identify young patients at risk of a more adverse course[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite this need, early identification of children likely to develop a treatment-refractory course still depends largely on clinical judgment. Existing studies have focused mainly on definitions, treatment strategies, or comparisons between refractory and non-refractory groups[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] or on predictors of long-term tic severity and response to behavioral therapy[\u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], rather than on directly usable prediction tools for treatment-refractory outcomes in pediatric TD. A pragmatic outpatient model based on routinely collected baseline information could support earlier comorbidity-focused assessment, psychosocial intervention, family-school coordination, and more efficient use of specialist follow-up resources[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. We therefore developed and internally validated a pragmatic clinic-based nomogram to predict treatment-refractory outcomes in a single-center pediatric TD cohort.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and participants\u003c/h2\u003e \u003cp\u003eThis single-center retrospective cohort study used consecutive outpatient electronic medical records from West China Second University Hospital, Sichuan University, supplemented by standardized telephone follow-up. Eligible participants were younger than 18 years, attended the outpatient clinic between October 2021 and October 2023, and met DSM-5 diagnostic criteria for a tic disorder. All included participants underwent telephone follow-up during a prespecified window (April 2025 to August 2025) for outcome ascertainment. Clinical and follow-up information used for outcome adjudication and variable collection was obtained from structured guardian telephone interviews together with outpatient electronic medical records, laboratory records, prescription history, and clinician assessment. We excluded patients with secondary or symptomatic tics or uncertain diagnoses, those with severe neurodevelopmental disorders that precluded reliable assessment, those lost to follow-up or with insufficient outcome information, and pseudo-refractory cases (defined below).\u003c/p\u003e \u003cp\u003e This study was approved by the Ethics Committee of West China Second University Hospital, Sichuan University (No. 2025\u0026thinsp;\u0026minus;\u0026thinsp;241). Written informed consent was waived for the retrospective chart review. Before telephone follow-up, verbal informed consent was obtained from guardians and documented, and all data were de-identified before analysis.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eOutcome and group definitions\u003c/h3\u003e\n\u003cp\u003eThe primary outcome was treatment-refractory outcome at the end of follow-up. Outcome adjudication followed a prespecified pragmatic framework derived from expert consensus on treatment failure in persistent tic disorders, integrating illness duration, adequacy of treatment exposure, persistent clinical burden, and explicit exclusion of pseudo-refractoriness[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Because the Yale Global Tic Severity Scale was not collected systematically in this cohort, endpoint severity and improvement were assessed using the Clinical Global Impressions scales for severity (CGI-S) and improvement relative to baseline (CGI-I), pragmatic instruments for retrospective chart review and telephone follow-up[\u003cspan additionalcitationids=\"CR27\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eParticipants were classified as having a treatment-refractory outcome if all of the following criteria were met: tic duration\u0026thinsp;\u0026gt;\u0026thinsp;12 months; after exclusion of pseudo-refractoriness, failure of at least two adequately delivered anti-tic medications with different mechanisms; treatment trials of adequate dose and duration (generally 8\u0026ndash;12 weeks, including at least 4\u0026ndash;8 weeks within the maximum tolerated dose range)[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]; and persistence at follow-up of at least moderate severity or poor response together with functional impairment, defined as CGI-S\u0026thinsp;\u0026ge;\u0026thinsp;4, or CGI-I\u0026thinsp;\u0026ge;\u0026thinsp;4 plus documentation of academic, social, or family impairment in the medical record or follow-up interview[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan additionalcitationids=\"CR27\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Treatment discontinuation because of documented adverse effects could also count as failure when tolerability precluded an adequate therapeutic course.\u003c/p\u003e \u003cp\u003ePseudo-refractoriness was defined as apparent treatment failure attributable to inadequate treatment exposure or poor adherence, including missed doses, self-discontinuation, clearly insufficient dose or duration, or labeling a regimen ineffective before an adequate trial had been completed. It also included cases in which an uncontrolled comorbidity was judged to be the principal driver of impairment or symptom fluctuation in the absence of sufficient evidence of tic-specific treatment failure. To reduce circularity, baseline comorbidity burden was retained as a candidate predictor but was not itself used to define treatment-refractory outcome or pseudo-refractoriness, and cases were not excluded solely because of a higher baseline comorbidity count[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe non-RTD group included patients who did not meet criteria for treatment-refractory outcome and had a favorable status at follow-up, defined as CGI-I\u0026thinsp;\u0026le;\u0026thinsp;3 or CGI-S\u0026thinsp;\u0026le;\u0026thinsp;3 without the need for further intensification of anti-tic treatment[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eVariable collection and measurement\u003c/h3\u003e\n\u003cp\u003eCandidate predictors were prespecified on the basis of previous literature and clinical interpretability. They included demographic and clinical characteristics, tic phenotype (type, site of onset, age at onset, and age at symptom peak), comorbidity burden, family history, family environment, parenting style, adverse pregnancy and perinatal factors, psychosocial stressors, recurrent respiratory infections, allergy history, screen time, and vitamin D values. Family-reported follow-up information was collected using an investigator-developed structured guardian telephone interview (Additional file 3). Study variables were documented and coded using a study-specific information extraction form (Additional file 4). Baseline clinical, laboratory, and treatment-related data were obtained from outpatient electronic medical records, laboratory records, and prescription records; missing historical information was supplemented by guardian interview where applicable. CGI-S and CGI-I were rated by clinicians on the basis of interview data, chart review, and clinical judgment.\u003c/p\u003e\n\u003ch3\u003eStatistical analysis and model development\u003c/h3\u003e\n\u003cp\u003eAll analyses were performed in R version 4.5.2. Continuous variables were summarized as medians (IQRs) and categorical variables as counts (%), as appropriate. Baseline comparisons in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e were descriptive and were not used to screen predictors for model development. Group comparisons used the chi-square test or Fisher\u0026rsquo;s exact test for categorical variables and the Mann-Whitney U test for continuous variables, as appropriate. Vitamin D values (vd_value) had missing data (approximately 27%) and were handled using multiple imputation by chained equations (m\u0026thinsp;=\u0026thinsp;5)[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. No other variables had missing values, and the outcome was not imputed. Predictive mean matching was used for continuous variables, logistic regression for binary variables, and polytomous regression for multicategory variables within the imputation model. As a pragmatic workflow, least absolute shrinkage and selection operator regression (glmnet package) with 10-fold cross-validation and preference for the lambda.1se rule was performed in the first completed imputed dataset. Selected variables were then refit across all five imputed datasets using multivariable logistic regression, and adjusted odds ratios (ORs) with 95% confidence intervals (CIs) were pooled using Rubin\u0026rsquo;s rules[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTo assess robustness, we performed two prespecified sensitivity analyses. First, we repeated the multivariable analysis using complete cases only, without multiple imputation. Because complete-case analysis reduced the sample size, this analysis was intended to assess the stability of the main associations rather than to redefine the final model. Second, because some categories were sparse, we refit the model after collapsing comorbidity burden into 0, 1, and \u0026ge;\u0026thinsp;2 and tic type into concurrent mixed versus all other tic types. For comparability, multivariable logistic regression was repeated using the same core predictors as in the primary model; for the sparse-category analysis, pooled estimates were again obtained across imputed datasets. Discrimination in sensitivity analyses was assessed using the area under the receiver operating characteristic curve (AUC). Detailed results are provided in Supplementary Tables S1 and S2.\u003c/p\u003e\n\u003ch3\u003eModel performance, internal validation, calibration, and clinical utility\u003c/h3\u003e\n\u003cp\u003eA nomogram was constructed from the final logistic model. For presentation and potential clinical application, the nomogram, forest plot, receiver operating characteristic (ROC) analyses, calibration plot, decision curve analysis, clinical impact curve, and bootstrap internal validation were generated from the first completed imputed dataset using the final four-variable model. Apparent discrimination was assessed with the area under the ROC curve (AUC), and bootstrap resampling (B\u0026thinsp;=\u0026thinsp;1000) was used to estimate optimism-corrected discrimination and calibration. Calibration was evaluated using a bootstrap calibration plot, the calibration slope, calibration-in-the-large (CITL), the Hosmer-Lemeshow test, and the Brier score. The apparent optimal classification threshold was identified from the ROC curve. Decision curve analysis and the clinical impact curve were used to assess net benefit and the expected number of high-risk classifications across threshold probabilities[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStudy population and baseline characteristics\u003c/h2\u003e \u003cp\u003eA total of 806 children and adolescents with TD were included, comprising 724 non-RTD and 82 RTD cases. Baseline characteristics are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Compared with the non-RTD group, the RTD group differed significantly in tic phenotype (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), comorbidity burden (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), poor family environment (P\u0026thinsp;=\u0026thinsp;0.008), adverse pregnancy and perinatal factors (P\u0026thinsp;=\u0026thinsp;0.002), psychosocial stressors (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), allergy history (P\u0026thinsp;=\u0026thinsp;0.047), and vitamin D level (P\u0026thinsp;=\u0026thinsp;0.004). The RTD group had a substantially higher proportion of concurrent mixed tics (45.1% vs 10.2%), a greater comorbidity burden (\u0026ge;\u0026thinsp;1 comorbidity, 86.6% vs 46.0%), and lower vitamin D levels [22.80 (17.68, 27.08) vs 25.10 (20.58, 30.30)]. Sex, site of onset, age at onset, age at symptom peak, family history, parenting style, recurrent respiratory infection, and screen time did not differ significantly between groups.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of baseline characteristics between the non-RTD and RTD groups\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-RTD (n\u0026thinsp;=\u0026thinsp;724)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRTD (n\u0026thinsp;=\u0026thinsp;82)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender (male)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e536 (74.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e68 (82.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.104\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTic type\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSimple Motor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e326 (45.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22 (26.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSimple Vocal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1 (1.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMixed (non-concurrent)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e304 (42.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22 (26.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMixed (concurrent)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e74 (10.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37 (45.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSite of onset\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.614\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFace\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e547 (75.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e59 (72.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHead/Neck\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e53 (7.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6 (7.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eShoulder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22 (3.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4 (4.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrunk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22 (3.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2 (2.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLimbs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12 (1.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVocal/throat\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e68 (9.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11 (13.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComorbidity burden\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e391 (54.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11 (13.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e290 (40.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e51 (62.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e37 (5.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16 (19.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6 (0.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4 (4.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily history\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e106 (14.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19 (23.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.063\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor family environment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e81 (11.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18 (22.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.008**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor parenting style\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e164 (22.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18 (22.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.996\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePerinatal factors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e84 (11.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20 (24.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.002**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePsychosocial stress\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12 (1.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9 (11.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRespiratory infection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e422 (58.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e52 (63.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.438\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAllergy history\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e178 (24.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29 (35.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.047*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScreen time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.126\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;30 min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e327 (45.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40 (48.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;60 min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e197 (27.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17 (20.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u0026ndash;2 h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e108 (14.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14 (17.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u0026ndash;4 h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e77 (10.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6 (7.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;4 h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15 (2.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5 (6.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge at onset\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.00 [4.75, 8.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.00 [5.00, 7.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.502\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge at symptom peak\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.42 [5.00, 8.25]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.50 [5.33, 8.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.992\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVitamin D level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25.1 [20.6, 30.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22.8 [17.7, 27.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.004**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eNote: *p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; **p\u0026thinsp;\u0026lt;\u0026thinsp;0.01.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eVariable selection and independent predictors of RTD\u003c/h3\u003e\n\u003cp\u003eLASSO regression was used for variable reduction and predictor selection. In the first completed imputed dataset, 10-fold cross-validation favored the lambda.1se criterion as the more parsimonious solution, and four variables retained non-zero coefficients: tic type, comorbidity burden, adverse pregnancy and perinatal factors, and psychosocial stressors (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe four LASSO-selected variables were then entered into multivariable logistic regression across the five imputed datasets, and pooled estimates are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Using simple motor tics as the reference, concurrent mixed tics were independently associated with a higher risk of RTD (OR\u0026thinsp;=\u0026thinsp;4.28, 95% CI 2.27\u0026ndash;8.20, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), whereas simple vocal tics (OR\u0026thinsp;=\u0026thinsp;0.75, P\u0026thinsp;=\u0026thinsp;0.792) and sequential mixed tics (OR\u0026thinsp;=\u0026thinsp;0.88, P\u0026thinsp;=\u0026thinsp;0.701) were not. Comorbidity burden showed a clear dose-response association: compared with no comorbidity, one comorbidity (OR\u0026thinsp;=\u0026thinsp;4.79, 95% CI 2.44\u0026ndash;10.20, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), two comorbidities (OR\u0026thinsp;=\u0026thinsp;11.06, 95% CI 4.52\u0026ndash;27.77, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and three or more comorbidities (OR\u0026thinsp;=\u0026thinsp;24.62, 95% CI 5.20\u0026ndash;106.32, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were associated with progressively higher risk. Adverse pregnancy and perinatal factors (OR\u0026thinsp;=\u0026thinsp;2.10, 95% CI 1.09\u0026ndash;3.91, P\u0026thinsp;=\u0026thinsp;0.028) and psychosocial stressors (OR\u0026thinsp;=\u0026thinsp;5.30, 95% CI 1.77\u0026ndash;15.57, P\u0026thinsp;=\u0026thinsp;0.004) were also independent predictors.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eNomogram construction\u003c/h2\u003e \u003cp\u003eA nomogram based on the final four-variable model was constructed and visualized in the first completed imputed dataset (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). In practice, points are assigned for tic type, comorbidity burden, adverse pregnancy and perinatal factors, and psychosocial stressors, and the total score corresponds to an individualized predicted probability of RTD.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eModel discrimination, calibration, internal validation, and clinical utility\u003c/h2\u003e \u003cp\u003eThe nomogram was evaluated for discrimination, calibration, internal validation, and potential clinical utility in the first completed imputed dataset (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Apparent discrimination was good, with an AUC of 0.820 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Bootstrap internal validation suggested limited optimism, with an optimism-corrected AUC of 0.802 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). At the apparent optimal threshold of 0.114, sensitivity was 0.659 and specificity was 0.826. Calibration was acceptable, with a calibration slope of 0.876 and a CITL of -0.214; the bias-corrected curve remained close to the ideal line (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC). The Hosmer-Lemeshow test was non-significant (P\u0026thinsp;=\u0026thinsp;0.916), and the Brier score was 0.0752. Decision curve analysis showed net benefit across an approximate threshold range of 5%\u0026ndash;75% compared with treat-all and treat-none strategies (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD). The clinical impact curve suggested acceptable classification efficiency across clinically relevant thresholds; around the apparent optimal threshold (~\u0026thinsp;0.11), about 223 per 1000 patients would be classified as high risk, including about 67 true RTD events per 1000 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eSensitivity analyses\u003c/h2\u003e \u003cp\u003eSensitivity analyses supported the robustness of the primary findings. In the complete-case analysis (n\u0026thinsp;=\u0026thinsp;574; 60 events), the direction of association for the four main predictors remained unchanged. Concurrent mixed tics, greater comorbidity burden, adverse pregnancy and perinatal factors, and psychosocial stressors all remained associated with higher odds of treatment-refractory outcome, and model discrimination remained similar to that of the primary model (AUC 0.815). Similar findings were observed after collapsing sparse categories. In the sparse-category merged analysis, concurrent mixed tic type versus all other tic types (OR 4.61, 95% CI 2.67\u0026ndash;7.94, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and higher comorbidity burden (OR 4.37, 95% CI 2.09\u0026ndash;9.12, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001 for one comorbidity; OR 11.50, 95% CI 4.71\u0026ndash;28.05, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001 for \u0026ge;\u0026thinsp;2 comorbidities) remained strongly associated with treatment-refractory outcome; adverse pregnancy and perinatal factors (OR 2.09, 95% CI 1.12\u0026ndash;3.93, P\u0026thinsp;=\u0026thinsp;0.021) and psychosocial stressors (OR 4.91, 95% CI 1.67\u0026ndash;14.41, P\u0026thinsp;=\u0026thinsp;0.004) also remained significant. Discrimination in the sparse-category merged model was similar to that of the primary model (AUC 0.817). Overall, these analyses indicate that the primary findings were not materially driven by the imputation strategy or sparse category structure.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003ePrincipal findings\u003c/h2\u003e \u003cp\u003eIn this single-center retrospective pediatric outpatient cohort, we developed and internally validated a pragmatic clinic-based nomogram that estimates the probability of treatment-refractory outcome by the end of a prespecified follow-up window using four routinely available baseline variables: tic type, comorbidity burden, adverse pregnancy and perinatal factors, and psychosocial stressors. The model showed good apparent discrimination with limited optimism after bootstrap correction, acceptable calibration, favorable net benefit across clinically plausible thresholds, and stable results in prespecified sensitivity analyses. Together, these findings suggest that routinely collected baseline clinical information can be translated into an interpretable early risk estimate for children and adolescents with tic disorders.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eRelation to previous work and interpretation\u003c/h2\u003e \u003cp\u003eThis study extends previous work by moving from descriptive identification of higher-risk features to individualized risk prediction. The existing literature on refractory TS/TD has focused largely on conceptual definitions[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], treatment strategies[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], or comparisons between refractory and non-refractory groups[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Some longitudinal studies have identified predictors of later tic severity[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] or response to behavioral therapy[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], but directly usable clinic-based prediction models for treatment-refractory outcomes in pediatric TD remain scarce. By restricting the model to a small set of routinely available variables, we sought to balance parsimony, interpretability, and clinical usefulness in real-world outpatient practice.\u003c/p\u003e \u003cp\u003eThe retained predictors appear to capture complementary dimensions of vulnerability: symptom complexity, psychiatric burden, developmental vulnerability, and psychosocial context. Concurrent mixed tics may mark more complex disease expression[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], whereas the clear gradient across comorbidity categories suggests that adverse outcome in TD is shaped not only by tic manifestations themselves but also by accumulated neuropsychiatric burden[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Adverse pregnancy and perinatal factors are best interpreted as markers of neurodevelopmental vulnerability rather than as a single direct cause[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e], and psychosocial stressors may represent potentially modifiable contextual factors that intensify symptom fluctuation[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], strain coping capacity, and complicate longer-term management[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The model therefore appears to capture a multidimensional clinical phenotype rather than a single severity axis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eImplications for child and adolescent mental health services\u003c/h2\u003e \u003cp\u003eImportantly, the value of this model lies not only in predicting a more adverse clinical course, but also in supporting service delivery in child and adolescent mental health settings[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. In routine outpatient practice, the model may help clinicians identify children who are more likely to require earlier comorbidity-focused assessment[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], psychosocial intervention[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], family-school coordination[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], and intensified follow-up[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], rather than relying solely on symptom-focused management. In this sense, the model should be viewed as a pragmatic decision-support and risk-stratification tool that may help prioritize multidisciplinary care for higher-risk patients, rather than as a substitute for clinical judgment.\u003c/p\u003e \u003cp\u003eThe practical value of the model lies less in the exact numerical probability than in its potential to support stratified outpatient management. Threshold probabilities around the observed optimal threshold (~\u0026thinsp;0.11) may be most useful for identifying children who warrant enhanced follow-up, earlier screening for co-occurring psychiatric problems[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], more timely psychosocial review[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], and closer coordination across family, school, and specialist services[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. The model may therefore help move care beyond a narrow focus on tic symptoms alone toward a broader child and adolescent mental health service framework that addresses comorbidity, psychosocial adversity, and functional impairment in an integrated way. Low-risk patients may continue routine follow-up and standard education, whereas children at moderate or high predicted risk may benefit from earlier multidisciplinary review, including screening for attention-deficit/hyperactivity disorder, obsessive-compulsive symptoms, anxiety, depression, sleep problems, and school maladaptation[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], together with strengthened family guidance and psychosocial support[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Whether this form of risk-stratified care improves real-world outcomes should be tested prospectively.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eStrengths, limitations, and next steps\u003c/h2\u003e \u003cp\u003eThis study has several strengths. It addresses a clinically under-recognized yet important outcome, uses a relatively large pediatric outpatient cohort, and derives a parsimonious model from variables usually available in routine care, which supports feasibility. The model also integrates symptom phenotype, comorbidity burden, developmental vulnerability, and psychosocial context, reflecting the multidimensional nature of tic disorder management. The main findings were further supported by prespecified sensitivity analyses, which showed similar directions and magnitudes of association after complete-case analysis and simplification of sparse categories.\u003c/p\u003e \u003cp\u003eSeveral limitations should be acknowledged. First, this was a single-center retrospective study and is therefore vulnerable to selection bias; external validation is still lacking. Second, some historical exposure information was supplemented retrospectively from guardians during telephone follow-up and may therefore be subject to recall bias. Third, outcome classification relied mainly on CGI together with integrated assessment of illness duration, treatment exposure, and functional impairment, rather than on a uniformly collected quantitative scale such as the Yale Global Tic Severity Scale. Fourth, because the outcome was defined at the end of a prespecified follow-up window rather than at a single uniform time horizon, some heterogeneity in follow-up duration may remain. Fifth, in retrospective clinical data, true refractoriness and pseudo-refractoriness may not be fully separable, particularly in the presence of severe comorbidity. Sixth, variable selection and graphical or internal-validation procedures were performed in the first completed imputed dataset, whereas coefficient estimates for inference were pooled across all five imputed datasets; this pragmatic workflow may underestimate selection uncertainty. Seventh, bootstrap validation was applied to the fixed final model rather than the full variable-selection process, so some residual optimism may remain. Finally, although optimism was modest, generalizability remains to be established.\u003c/p\u003e \u003cp\u003eFuture work should focus on external validation, recalibration when baseline risk differs across settings, and prospective implementation studies to determine whether risk-stratified care can improve outcomes and service efficiency. It will also be important to assess whether more standardized severity measures, adherence indicators, or longitudinal treatment variables can improve performance without sacrificing the simplicity that makes the current model potentially usable in routine outpatient care.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eWe developed an internally validated, pragmatic clinic-based nomogram for early estimation of treatment-refractory outcome risk in pediatric tic disorders. By integrating tic type, comorbidity burden, adverse pregnancy and perinatal factors, and psychosocial stressors, the model may support earlier comorbidity-focused assessment, psychosocial intervention, family-school coordination, and intensified follow-up in child and adolescent mental health outpatient services. External validation, recalibration, and implementation-focused prospective studies are needed before routine use.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAUC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eArea under the receiver operating characteristic curve\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCGI-I\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eClinical Global Impression\u0026ndash;Improvement\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCGI-S\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eClinical Global Impression\u0026ndash;Severity\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eConfidence interval\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCITL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCalibration-in-the-large\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDSM-5\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDiagnostic and Statistical Manual of Mental Disorders, Fifth Edition\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIQR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInterquartile range\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLASSO\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLeast absolute shrinkage and selection operator\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eOR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eOdds ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eROC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eReceiver operating characteristic\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRTD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTreatment-refractory tic disorder\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTic disorder\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTourette syndrome\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":" \u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003e This study was approved by the Ethics Committee of West China Second University Hospital, Sichuan University (approval no. 2025\u0026thinsp;\u0026minus;\u0026thinsp;241). Written informed consent was waived for the retrospective chart review because this study used existing clinical records. Before telephone follow-up, verbal informed consent was obtained from guardians and documented. All data were de-identified before analysis. All procedures were performed in accordance with the Declaration of Helsinki and relevant institutional requirements.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis study was supported by the Tibet Autonomous Region Scientific and Technological Program (grant number XZ202501YD0006).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eZL contributed to conceptualization, data curation, formal analysis, visualization, drafting of the manuscript, and revision of the manuscript. HH contributed to data collection and data verification. DY and CY contributed to study design, supervision, interpretation of the findings, and critical revision of the manuscript for important intellectual content. DY and CY jointly supervised the study and served as co-corresponding authors. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eWe thank the children and their guardians for their participation in the follow-up process. We also thank the clinicians and staff of West China Second University Hospital, Sichuan University, for their support in clinical data collection and follow-up coordination.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets generated and/or analysed during the current study are not publicly available because they contain potentially identifiable clinical information from minors and are subject to institutional and ethical restrictions, but they are available from the corresponding author on reasonable request and with permission from the Ethics Committee of West China Second University Hospital, Sichuan University.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eRobertson MM, Eapen V, Singer HS, Martino D, Scharf JM, Paschou P, et al. Gilles de la tourette syndrome. 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Eur Child Adolesc Psychiatry. 2022;31:403\u0026ndash;23. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00787-021-01845-z\u003c/span\u003e\u003cspan address=\"10.1007/s00787-021-01845-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":false,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-psychiatry","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bpsy","sideBox":"Learn more about [BMC Psychiatry](http://bmcpsychiatry.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bpsy/default.aspx","title":"BMC Psychiatry","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"tic disorders, treatment-refractory outcomes, prediction model, nomogram, comorbidity burden, psychosocial stress, perinatal adversity","lastPublishedDoi":"10.21203/rs.3.rs-9327833/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9327833/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eA clinically important subgroup of children and adolescents with tic disorders develops persistent symptoms and functional impairment despite treatment, yet practical tools for early risk stratification in outpatient care are lacking. We aimed to develop and internally validate a pragmatic nomogram to predict treatment-refractory outcomes in pediatric tic disorders.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eIn this single-center retrospective cohort study, we included patients younger than 18 years with DSM-5 tic disorders who attended West China Second University Hospital between October 2021 and October 2023 and completed follow-up between April and August 2025. Treatment-refractory outcome at the end of follow-up was adjudicated using a prespecified framework that explicitly excluded pseudo-refractoriness. Vitamin D, the only substantially incomplete variable, was handled with multiple imputation. Predictors were selected using LASSO with 10-fold cross-validation and preference for the lambda.1se rule, followed by multivariable logistic regression with pooled estimates across imputed datasets. We assessed discrimination, calibration, internal validation, clinical utility, and prespecified sensitivity analyses.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAmong 806 participants, 82 (10.2%) met criteria for treatment-refractory outcome. Four predictors were retained in the final model: tic type, comorbidity burden, adverse pregnancy and perinatal factors, and psychosocial stressors. Concurrent mixed tics, greater comorbidity burden, adverse pregnancy and perinatal factors, and psychosocial stressors were independently associated with higher risk. The model showed good apparent discrimination (AUC 0.820), limited optimism after bootstrap correction (optimism-corrected AUC 0.802), acceptable calibration, and net benefit across clinically relevant threshold probabilities. Sensitivity analyses supported the robustness of the main findings.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThis internally validated nomogram may help identify children and adolescents with tic disorders who are at increased risk of a treatment-refractory course. Beyond risk prediction, it may help child and adolescent mental health outpatient services identify patients who need earlier comorbidity-focused assessment, psychosocial intervention, family-school coordination, and intensified follow-up. External validation, recalibration, and prospective implementation studies are needed before routine use.\u003c/p\u003e","manuscriptTitle":"Development and internal validation of a pragmatic nomogram for predicting treatment-refractory outcomes in pediatric tic disorders: a single-center retrospective cohort study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-15 17:49:37","doi":"10.21203/rs.3.rs-9327833/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"5530425652619288175260760894685598013","date":"2026-05-15T01:06:48+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"115371978476693734985708077055564654949","date":"2026-05-06T15:46:41+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-05-06T12:16:46+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-05-04T12:13:16+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-04-14T18:32:50+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-14T15:45:48+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Psychiatry","date":"2026-04-14T14:40:08+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-psychiatry","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bpsy","sideBox":"Learn more about [BMC Psychiatry](http://bmcpsychiatry.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bpsy/default.aspx","title":"BMC Psychiatry","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9c5b755d-0bd0-4d58-b98e-6c29fed5cce4","owner":[],"postedDate":"May 15th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"5530425652619288175260760894685598013","date":"2026-05-15T01:06:48+00:00","index":64,"fulltext":""},{"type":"reviewerAgreed","content":"115371978476693734985708077055564654949","date":"2026-05-06T15:46:41+00:00","index":41,"fulltext":""},{"type":"reviewersInvited","content":"30","date":"2026-05-06T12:16:46+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-05-04T12:13:16+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-15T17:49:37+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-15 17:49:37","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9327833","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9327833","identity":"rs-9327833","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}