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PubMed2022

Significant variation in the performance of DNA methylation predictors across data preprocessing and normalization strategies.

BACKGROUND: DNA methylation (DNAm)-based predictors hold great promise to serve as clinical tools for health interventions and disease management. While these algorithms often have high prediction accuracy, the consistency of their performance remains to be determined. We therefore conduct a systematic evaluation across 101 different DNAm data preprocessing and normalization strategies and assess how each analytical strategy affects the consistency of 41 DNAm-based predictors. RESULTS: Our analyses are conducted in a large EPIC DNAm array dataset from the Jackson Heart Study (N = 2053) that included 146 pairs of technical replicate samples. By estimating the average absolute agreement between replicate pairs, we show that 32 out of 41 predictors (78%) demonstrate excellent consistency when appropriate data processing and normalization steps are implemented. Across all pairs of predictors, we find a moderate correlation in performance across analytical strategies (mean rho = 0.40, SD = 0.27), highlighting significant heterogeneity in performance across algorithms. Successful or unsuccessful removal of technical variation furthermore significantly impacts downstream phenotypic association analysis, such as all-cause mortality risk associations. CONCLUSIONS: We show that DNAm-based algorithms are sensitive to technical variation. The right choice of data processing strategy is important to achieve reproducible estimates and improve prediction accuracy in downstream phenotypic association analyses. For each of the 41 DNAm predictors, we report its degree of consistency and provide the best performing analytical strategy as a guideline for the research community. As DNAm-based predictors become more and more widely used, our work helps improve their performance and standardize their implementation.

DNA Methylation↗

PubMed2025

Gene Specific Pathogenicity Predictor for Chromatin-Remodeling BAF Complex-Associated Neurodevelopmental Disorders.

Advancements in whole genome sequencing have increased the number of variants of uncertain significance (VUS) identified in patient genomes. This has created a diagnostic bottleneck for genetic counselors tasked with sifting through these variants and determining those most likely to be causative for a patient's clinical presentation. Machine learning (ML) tools can aid in identifying pathogenic variants from VUS, but there is a need for gene-specific algorithms that predict pathogenic variants with high accuracy. To address this need, we present a workflow for developing gene-specific, ensemble-learning ML tools, that leverage outputs from other algorithms, locations of variants within the gene, and evolutionary conservation data to make a prediction of pathogenicity. Variants in SMARCA2 and SMARCA4 that are associated with rare neurodevelopmental diseases were used to screen 15 ML algorithms. A random forest learner was tuned to yield a final accuracy of 0.93 on holdout data. Generalizing this predictor to other BAF complex proteins resulted in a sharp decline in performance. We trained a final predictor for all genes in the study to create a predictor that identifies pathogenic variants in these BAF subunits with an accuracy of 0.91 on holdout data. This predictor specific to BAF complex proteins performs with higher accuracy and AUROC than any other predictor. The decline in performance when generalized to other proteins emphasizes the need for the gene-specific calibration of predictors. Our workflow for the development of such models provides a quick, computationally inexpensive route for improving the ML tools available to genetic counselors.

Journal Article↗

PubMed2025

A SuperLearner-based pipeline for the development of DNA methylation-derived predictors of phenotypic traits.

BACKGROUND: DNA methylation (DNAm) provides a window to characterize the impacts of environmental exposures and the biological aging process. Epigenetic clocks are often trained on DNAm using penalized regression of CpG sites, but recent evidence suggests potential benefits of training epigenetic predictors on principal components. METHODOLOGY/FINDINGS: We developed a pipeline to simultaneously train three epigenetic predictors; a traditional CpG Clock, a PCA Clock, and a SuperLearner PCA Clock (SL PCA). We gathered publicly available DNAm datasets to generate i) a novel childhood epigenetic clock, ii) a reconstructed Hannum adult blood clock, and iii) as a proof of concept, a predictor of polybrominated biphenyl exposure using the three developmental methodologies. We used correlation coefficients and median absolute error to assess fit between predicted and observed measures, as well as agreement between duplicates. The SL PCA clocks improved fit with observed phenotypes relative to the PCA clocks or CpG clocks across several datasets. We found evidence for higher agreement between duplicate samples run on alternate DNAm arrays when using SL PCA clocks relative to traditional methods. Analyses examining associations between relevant exposures and epigenetic age acceleration (EAA) produced more precise effect estimates when using predictions derived from SL PCA clocks. CONCLUSIONS: We introduce a novel method for the development of DNAm-based predictors that combines the improved reliability conferred by training on principal components with advanced ensemble-based machine learning. Coupling SuperLearner with PCA in the predictor development process may be especially relevant for studies with longitudinal designs utilizing multiple array types, as well as for the development of predictors of more complex phenotypic traits.

DNA Methylation↗

PubMed2026

Predictors of aortic stenosis in homozygous familial hypercholesterolemia: A study from the Canadian HoFH registry.

BACKGROUND: Homozygous familial hypercholesterolemia (HoFH) is a rare genetic disease of low-density lipoprotein cholesterol (LDL-C) metabolism. This disease is associated with a major risk of both atherosclerotic cardiovascular disease and aortic stenosis (AS). The predictors of AS in this population are not well established. OBJECTIVE: To investigate the univariable and multivariable predictors of AS in patients from the Canadian HoFH registry. METHODS: Individuals from the Canadian HoFH registry were included in this retrospective longitudinal study. Clinical data were obtained from the treating physicians using a standardized questionnaire. Cox proportional hazards models were used to investigate the predictors of AS. The observed lifetime risk of AS was calculated using Kaplan-Meier estimates. RESULTS: Among the 67 patients with HoFH, 25 (37%) developed AS. The mean age at baseline was 22 ± 17 years and women represented 57% of the cohort. The independent predictors of AS were the baseline LDL-C (hazard ratio [HR] 1.22 [1.09-1.35], P = .0003) as well as the presence of at least 1 null genetic variant (HR 3.73 [1.41-9.86], P = .008). Having a baseline LDL-C value above 13 mmol/L was associated with an observed lifelong risk of developing AS approaching 100% within this cohort, whereas having a value below this threshold was associated with a risk of 27% (P = .0002). CONCLUSION: This is the first systematic evaluation within a national HoFH registry to report the univariable and multivariable predictors of AS in patients with HoFH. An external validation of our results in an international cohort of HoFH is warranted.

Aortic stenosis↗

PubMedDate not supplied

Predictors of operative mortality for coronary bypass grafting in patients with ischemic heart disease.

Predictors for operative mortality (OM) were studied in 172 consecutive patients (pts) undergoing coronary artery grafts (CAG) for angina pectoris.Seventy eight pts had Class IV angina; of the 147 patients given propranolol, 41 were gradually withdrawn from propranolol and finally discontinued 24 hours before surgery, and 106 were abruptly withdrawn from propranolol 24 hours before CAG; 20 pts had left main coronary disease; 156 pts had cardiopulmonary bypass (CPB) time shorter than 20 minutes, and 16 pts had a CPB longer than 120 minutes.The operative mortality was 5.2% (9/172) for the entire group. Class IV angina (OM 7%), abrupt propranolol withdrawal (OM 6.6%), left main coronary artery disease (OM 25%), and CPB longer than 120 minutes (OM 50%), all significantly increased OM. These variables were interdependent, however, as many pts belonged to several predictor categories, combinations of predictors were examined, in order to more accurately predict the risk of individual pts. The combination of left main coronary artery disease and CPB longer than 120 minutes; and Class IV angina and CPB longer than 120 minutes were significantly associated with higher operative mortality.We conclude that Class IV angina, abrupt propranolol withdrawal, left main coronary artery disease and prolonged CPB are potent, interdependent predictors of OM in pts undergoing CAG. Consideration of these predictors, alone and in combination, allows effective prediction of OM for CAG in patients with stable angina pectoris.

Adult↗

PubMed2026

Psychiatric and neurological predictors of early ADHD medication discontinuation across the lifespan: a multinational study.

BACKGROUND: Early discontinuation of attention-deficit/hyperactivity disorder (ADHD) medication is common and linked to worse outcomes. Identifying clinical predictors could aid personalised treatment yet evidence is inconsistent across ages and countries/regions. OBJECTIVE: Investigate psychiatric and neurological comorbidity as predictors of early ADHD medication discontinuation in new ADHD medication users across age groups, sex and countries/regions. METHODS: Using health records from eight countries/regions, we identified 1 000 411 (44% female) new ADHD medication users (2011-2020). Discontinuation was defined as a ≥180 day gap between dispensations. We examined 23 indicators of psychiatric or neurological comorbidity, severity and psychotropic medication use. Associations were estimated using Cox regression, pooled with random-effects meta-analyses and stratified by age-at-initiation and sex. FINDINGS: Discontinuation rates varied widely (children 19%-61%, adolescents 37%-68%, young adults 52-67%, adults 38%-68%). In pooled analyses, earlier discontinuation in children was predicted by intellectual disability, autism and use of psychotropic medications (HR range 1.32-1.51), while conduct/oppositional defiant disorder (CD/ODD) was protective (HR 0.83, 95% CI 0.73 to 0.94). In adolescents, no indicators remained statistically significant after multiple-testing control. In young adults, CD/ODD (HR 1.42, 95% CI 1.30 to 1.55), and in adults, schizophrenia (HR 1.25, 95% CI 1.09 to 1.44) and tic disorders (HR 1.27, 95% CI 1.11 to 1.46) predicted earlier discontinuation. Statistical heterogeneity was substantial, largely driven by US estimates. In meta-analyses excluding the USA, additional associations emerged. For example, in children, OCD and anxiety disorders predicted earlier discontinuation, while eating disorders and antidepressants/anxiolytics were protective in adults. Associations with schizophrenia, tic disorders and CD/ODD were no longer significant. Country-specific analyses showed similar association patterns, except in the USA, Hong Kong and the UK. Sex differences were limited. CONCLUSIONS: Children with neuropsychiatric comorbidity and related comedication are more likely to discontinue ADHD medication early, whereas few consistent predictors were seen from adolescence onwards. Marked cross-country variation, particularly in the USA, points to system-level influences on treatment patterns. CLINICAL IMPLICATIONS: Improving ADHD medication persistence will require consideration of healthcare context and age-specific strategies, including close monitoring for children with complex neuropsychiatric profiles, and consideration of broader factors in adolescents and adults, where clinical predictors were limited.

Humans↗

PubMed2026

Preoperative Proximal Migration of the Radial Head as an Independent Predictor of Suboptimal Outcomes After Osteochondral Autograft Transplantation for Capitellar Osteochondritis Dissecans: A Retrospective Cohort Study.

BACKGROUND: Osteochondral autograft transplantation (OAT) is widely performed for capitellar osteochondritis dissecans (OCD). However, preoperative predictors of suboptimal postoperative outcomes remain unclear. PURPOSE/HYPOTHESIS: The authors aimed to evaluate clinical outcomes after OAT for capitellar OCD and identify preoperative risk factors associated with suboptimal outcomes. They hypothesized that radiographic indicators of disease severity, including preoperative proximal migration of the radial head, lesion size, and lateral wall disruption, would be associated with suboptimal postoperative clinical outcomes. STUDY DESIGN: Cohort study; Level of evidence, 3. METHODS: The records of adolescent athletes who underwent OAT for capitellar OCD with a minimum 2-year follow-up were retrospectively reviewed. Clinical outcomes included elbow range of motion (ROM) and Timmerman-Andrews (T-A) score. A suboptimal outcome was defined as a postoperative T-A score <160. Preoperative radiographs were used to measure proximal migration of the radial head relative to the coronoid process, hypertrophy of the radial head, OCD lesion area, and a 5-grade lateral wall disruption classification; measurement reliability was assessed. Multivariate logistic regression analysis was performed to identify independent predictors of a suboptimal outcome, and receiver operating characteristic (ROC) curve analysis was used to determine the optimal cutoff value for proximal migration. RESULTS: A total of 69 elbows (mean age, 13.6 years; mean follow-up, 48 months) were included. ROM and T-A scores improved significantly after OAT, and all athletes returned to any sports. Of these, 50 elbows (72%) achieved good outcomes, whereas 19 (28%) had suboptimal outcomes. Preoperative proximal migration was significantly greater in the suboptimal outcome group compared with the good outcome group (mean, 2.1 ± 2.3 vs 0.5 ± 1.7 mm; P = .002), as were lesion area (mean, 70 ± 16 vs 58 ± 20 mm2; P = .02) and lateral wall disruption grade (median, 5 vs 3; P = .01). On multivariate analysis, proximal migration of the radial head was the only independent predictor of a suboptimal outcome (adjusted OR, 1.47 per 1-mm increase; 95% CI, 1.03-2.09; P = .033). ROC analysis showed an area under the curve of 0.72 with an optimal cutoff of 2.2 mm (sensitivity, 56%; specificity, 84%). CONCLUSION: OAT resulted in significant clinical improvement in adolescents with capitellar OCD; however, 28% of patients were classified as having suboptimal outcomes. Preoperative proximal migration of the radial head is an independent predictor of a suboptimal postoperative outcome. A value >2.2 mm may indicate advanced radiocapitellar incongruity, a condition in which OAT may be less effective.

Humans↗

PubMed1976

An analysis of potential physiological predictors of respiratory adequacy following cardiac surgery.

More than 50 potential physiological and clinical predictors of postoperative respiratory adequacy were examined in an attempt to identify those few variables which, singly or in combination, best predicted the outcome of the first trial of spontaneous respiration following cardiac surgery. This trial was initiated when patients seemed hemodynamically stable and relatively alert following surgery. Analysis of data from 124 patients identified the following useful predictors: forced vital capacity, total lung capacity, and maximal mid-expiratory flow rate from preoperative pulmonary function tests; resting cardiac index from preoperative cardiac catheterization; postoperative compliance and resistance measured by a computer-based monitoring system; postoperative vital capacity per kilogram, and maximum inspiratory force, measured at the bedside prior to the weaning trial. Stepwise linear discriminant analysis indicated that vital capacity per kilogram and maximum inspiratory force were the most useful predictors, the dividing line between successes and failures being represented by a vital capacity per kilogram of 15 ml. and a maximum inspiratory force of 28 cm. H2O. Mean values of successes were 18.3 +/- 7 ml. per kilogram and 30.7 +/- 9 cm. H2O and, for failures, 11.9 +/- 4 ml. per kilogram and 24.3 +/- 8.4 cm H2O. These physiological variables assess patient effort acting upon an abnormal pulmonary system. Measurements of passive pulmonary mechanics, cardiac function, and the measurement of arterial blood gases were suprisingly poor predictors.

Airway Resistance↗

PubMed1977

Prediction of outcome in schizophrenia. III. Five-year outcome and its predictors.

Recent studies of schizophrenia have begun to demonstrate the complex nature of its outcome characteristics and their predictors. However, generalization of findings has been limited by methodological problems such as relatively short-term follow-up the use of retrospective data, or employment of evaluation techniques without demonstrated reliability. This report describes a prospective, five-year follow-up using reliable evaluation techniques to determine whether specific relations between predictors and outcome variables represent behavior patterns persisting over an extended period. Results demonstrate the prognostic importance and specificity of certain predictors over five years. These results support the view that outcome function is comprised of persisting open-linked systems of behavior.

Employment↗

PubMed1978

Demographic and clinical characteristics as predictors of readmission: a one-year follow-up.

Follows up an earlier investigation in which demographic and clinical characteristics of psychiatric patients were used to predict readmission within 3 months of discharge. In the initial study, stepwise multiple regression analysis identified six variables as the optimal set of predictors for readmission within 3 months of discharge: type of discharge, number of prior psychiatric hospitalizations, race, suicide attempt within 1 month of admission, subjective report of depression upon admission, and occupational level (R = .452). In the present study the same sample was followed up at 1 year after discharge, and demographic and clinical variables were used to predict readmission within 1 year of discharge. Stepwise multiple regression analysis identified three variables as the optimal set of predictors for readmission within 1 year of discharge: past history of suicidal behavior, subjective report of depression upon admission, and number of prior psychiatric hospitalizations. Changes in predictors as a function of length of follow-up period are considered, and implications of the findings for identifying high-risk readmission candidates are discussed.

Adult↗

PubMed2025

Prevalence and predictors of low bone mineral density in pediatric inflammatory bowel disease.

OBJECTIVES: Bone health is at risk in children with inflammatory bowel disease (IBD). This study examined the prevalence and predictors of low bone mineral density (BMD) in a cohort of children and young adults with IBD. METHODS: This single-center retrospective study included patients with IBD, ages 3.5-22 years, with completed dual x-ray absorptiometry (DXA) scans from 2006 to 2019. Demographic, clinical, and laboratory data were collected. Logistic regression analysis identified predictors associated with low BMD (Z-scores ≤ -2 standard deviations [SDs]) for three outcomes. In an overlapping IBD cohort with available genetic data between 2002 and 2019 (n = 378), genetic risk for diminished bone health was calculated using published polygenic risk scores generated from genome-wide association studies based on DXA or heel ultrasound speed of sound (SOS). Linear regression analysis examined associations of low BMD and genetic risk. RESULTS: Low BMD prevalence was 7% in our cohort (n = 600) based on spine bone mineral apparent density (BMAD), which best accounts for growth delays. Median (interquartile range [IQR]) spine BMAD Z-score was -0.37 SD (-1.11 to 0.35). Predictors of low BMAD included lower BMI Z-score (odds ratio [OR]: 0.67, p value: 0.02) and decreased height Z-score (OR: 0.6, p value: 0.005). Of those with longitudinal data (n = 118), low BMI (OR: 0.44, p value: <0.001) and steroid use (OR: 3.42, p value: 0.01) were associated with suboptimal bone health (Z-scores ≤ -1SD). In the cohort with genetic data, heel genomic SOS (β [standard error] = 0.17 [0.35], p ≤ 0.01) was associated with BMD. CONCLUSIONS: Lower BMI should prompt DXA monitoring in pediatric IBD. Genetic predisposition may identify an at-risk subpopulation.

Humans↗

PubMed1977

Noninvasive predictors of sudden cardiac death in men with coronary heart disease. Predictive value of maximal stress testing.

In a follow-up study of 1,852 men with coronary heart disease, 195 deaths occurred within the first 3 years (33 +/- 13 months [mean +/- standard deviation]). Analysis of these cases indicated that the risk of sudden cardiac death in ambulatory men with clinical manifestations of coronary heart disease may be readily estimated from noninvasive clinical and exercise criteria. The important predictors are indexes of the severity of coronary heart disease and impairment of peak left ventricular function demonstrated with symptom-limited maximal exercise. The advantages of these predictors are that they may be elicited on the initial study as well as on follow-up noninvasive examinations of ambulatory patients. The appearance of nonelectrocardiographic predictors in serial examinations may provide an indication for invasive studies and be a more important finding than the ischemic S-T reponse to exertion.

Adult↗

PubMed1978

Sturdy childhood predictors of adult antisocial behaviour: replications from longitudinal studies.

Results are compared in studies of 4 male cohorts - 1 all white, 1 all black, and 2 racially representative of the population - growing up in different eras, followed past varying portions of their adult lives, living in different parts of the US. Despite sample differences and differences in sources of information and in the variables used to measure both childhood predictors and adult outcomes, some striking replications appear with respect to childhood predictors of adult antisocial behaviour. All types of antisocial behaviour in childhood predict a high level of antisocial behaviour in adulthood and each kind of adult antisocial behaviour is predicted by the number of childhood antisocial behaviours, indicating that adult and childhood antisocial behaviour both form syndromes and that these syndromes are closely interconnected. Also confirmed across studies are: (1) adult antisocial behaviour virtually requires childhood antisocial behaviour; (2) most antisocial children do not become antisocial adults; (3) the variety of antisocial behaviour in childhood is a better predictor of adult antisocial behaviour than is any particular behaviour; (4) adult antisocial behaviour is better predicted by childhood behaviour than by family background or social class of rearing; (5) social class makes little contribution to the prediction of serious adult antisocial behaviour.

Adolescent↗

PubMed1979

Open-heart surgery: somatic predictors of postoperative psychopathology.

This study reports on some relationships between somatic conditions and postoperative psychopathological disturbances in 102 subjects from 20 to 65 years of age, undergoing open heart surgery. The overall incidence of postoperative psychiatric complications was 40%. Only two variables showed a significant correlation with the psychiatric criteria we used, independent of the different diagnoses: body weight and preoperative urea-N levels in serum. Some of the somatic predictors reported in the literature could be found to be specific for mitral or aortic valve disease. Predictors for psychiatric complications in patients with aortic valve replacement were: age, preoperative protein and urea-N levels in serum, and daytime sedation. The predictor in mitral valve replacement was the decrease in venous oxygenation (pulmonary artery) under physical strain.

Adult↗

PubMed1978

[Some psychological predictors for psychosis after open heart surgery (author's transl)].

In a study of postoperative psychosis after open heart surgery three psychopathological syndromes were identified which had different psychological predictors. Predictors of postoperative emotional disturbances are family problems and the lack of plans for the future, whereas patients with postoperative disorientations seem to have difficulties in their jobs and therefore feel distressed preoperatively. Predictors of the paranoid syndrome after the operation are: a high degree of fear in awaiting the operation and little confidence in the doctors. The social surroundings of these patients are often unstable and although they have no precise plans for the future they object to start working again after operation.

Adaptation, Psychological↗

PubMed2025

Negative dataset selection impacts machine learning-based predictors for multiple bacterial species promoters.

MOTIVATION: Advances in bacterial promoter predictors based on machine learning have greatly improved identification metrics. However, existing models overlooked the impact of negative datasets, previously identified in GC-content discrepancies between positive and negative datasets in single-species models. This study aims to investigate whether multiple-species models for promoter classification are inherently biased due to the selection criteria of negative datasets. We further explore whether the generation of synthetic random sequences (SRS) that mimic GC-content distribution of promoters can partly reduce this bias. RESULTS: Multiple-species predictors exhibited GC-content bias when using CDS as a negative dataset, suggested by specificity and sensibility metrics in a species-specific manner, and investigated by dimensionality reduction. We demonstrated a reduction in this bias by using the SRS dataset, with less detection of background noise in real genomic data. In both scenarios DNABERT showed the best metrics. These findings suggest that GC-balanced datasets can enhance the generalizability of promoter predictors across Bacteria. AVAILABILITY AND IMPLEMENTATION: The source code of the experiments is freely available at https://github.com/maigonzalezh/MultispeciesPromoterClassifier.

Machine Learning↗

PubMed2026

Extent of resection as an independent predictor of survival for patients with glioblastoma as defined by the new WHO 2021 classification.

OBJECTIVE: Extent of resection (EOR) has previously been demonstrated to have an impact on survival in patients with glioblastoma (GBM). However, with the World Health Organization (WHO) 2021 reclassification of GBMs based on IDH-mutation status, patients with "IDH-mutant GBMs," who typically survive long term, were reclassified as WHO grade 4 IDH-mutant astrocytomas and removed from the GBM taxonomy. Therefore, it is unknown whether the previously reported impact of resection on survival was a false-positive result due to the inclusion of the less aggressive IDH-mutant tumors in previous datasets. This study aimed to determine the extent to which EOR remains an independent predictor of survival in patients with WHO 2021 GBM after the reclassification of IDH-mutant grade 4 astrocytomas. METHODS: All cases of GBM tumors (based on the pre-2021 GBM classification) that were newly diagnosed between 2005 and 2021 were identified in our institutional database and subsequently reclassified based on the updated WHO 2021 criteria using IDH status. Multivariable statistical analyses of demographic information, survival time, and EOR based on volumetric MRI were performed to determine the independent predictors of survival for the whole group of patients and for IDH-wildtype GBM patients exclusively. Additional analyses were performed to identify an EOR threshold for improvement in survival. RESULTS: Of the 523 tumors classified as GBM based on the pre-2021 taxonomy, 52 (9.9%) cases were reclassified as WHO grade 4 IDH-mutant astrocytomas, and the median survival of patients in this group was 7.9 years, whereas median survival of the IDH-wildtype GBM patients was 1.4 years. Multivariate analyses of the whole group demonstrated that IDH-mutant astrocytomas were associated with reduced hazard of death. In both the whole group (n = 523) and in IDH-wildtype GBMs (n = 471), higher EOR of the contrast-enhancing (CE) tumor was associated with reduced hazard of death, whereas older age or male sex was associated with increased hazard of death. Because most patients (90%) had high EOR values (> 81%), a statistically meaningful EOR threshold could not be established. CONCLUSIONS: These analyses demonstrated that EOR of the CE tumor is an independent predictor of survival and that greater EOR is associated with improved survival in WHO 2021 IDH-wildtype GBMs even after excluding grade 4 IDH-mutant astrocytomas. However, an absolute EOR threshold below which resection did not improve survival could not be established, raising concerns about prior cutoff assessments.

Humans↗

PubMed2026

Predictors of Treatment Failure in Children With HIV Starting First-line Antiretroviral Therapy in the ODYSSEY Trial.

BACKGROUND: Data on predictors of treatment failure in children starting antiretroviral therapy (ART) are limited, particularly on dolutegravir-based regimens (DTG). METHODS: ODYSSEY demonstrated superior efficacy of DTG versus standard-of-care (SOC). We assessed predictors at ART initiation of treatment failure by 96 weeks. RESULTS: Three hundred and eighty-one children started first-line ART (82% African). At ART-initiation, median age was 10.5 years (IQR: 6.5, 14.0, 67 < 3 years), CD4% 20% (IQR: 12, 28), BMI-for-age Z-score -.58 (IQR:-1.48, +.25). One hundred and eighty-nine children started DTG, 192 started SOC (91% ≥3 years started efavirenz; 79% <3 years started lopinavir). Seventy-five children experienced treatment failure (24 DTG, 51 SOC). Failure risk was lower on DTG than SOC (hazard ratio [HR] = 0.47, 95% CI: 0.29-0.77, P = .002). Lower BMI-for-age Z-score (HR = 0.82 for each unit gain, 95% CI: 0.70-0.96, P = .01) and being at an African site (HR = 2.09, 95% CI: 0.82-5.31, P = .09) were associated with higher failure risk. Risk was also higher at younger ages with the steepest increase in the youngest children and increased at lower CD4%, with a stronger CD4% effect at younger ages. At CD4% = 20, HRs relative to age 10 years were 2.40 (95% CI: 1.58-3.65) at age 1 year, 1.30 (95% CI: 1.15-1.48) at age 5 years, and 0.80 (95% CI: 0.72-0.89) at age 18 years. At age 1 year, HRs relative to CD4% = 20 were 1.39 (95% CI: 1.16-1.66) at CD4% = 15, and 0.52 (95% CI: 0.36-0.75) at CD4% = 30; at age 10, corresponding estimates were 1.07 (95% CI: 0.94-1.20) at CD4% = 15, and 0.88 (95% CI: 0.69-1.13) at CD4% = 30. CONCLUSIONS: Young age, low BMI-for-age, and low CD4% at ART initiation predicted higher risk of treatment failure and can guide targeted support.

Humans↗