DOI: 10.1200/jco.2026.44.19_suppl.256 ISSN: 0732-183X

Predictive scoring systems for molecular response assessment in pediatric chronic-phase chronic myeloid leukemia.

Xingchen Wang, Wenbin An, Fenying Zhao, Xue Li, Lingzhen Wang, Ningling Wang, Fu Li, Futian Ma, Xiangling He, Wenpeng Hao, Xue Han, Yan Gu, Jianping Liu, Xiaofan Zhu, Wenyu Yang

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Background: For pediatric patients with chronic myeloid leukemia (CML), accurately predicting at the start of imatinib therapy the likelihood of achieving a deep molecular response (DMR; at least MR4) is clinically important and may inform treatment goals and strategies. Methods: We analyzed 98 consecutive children with chronic-phase CML treated with frontline imatinib as a training cohort. Cumulative incidence functions were estimated and Fine–Gray subdistribution hazard models were used for univariable and multivariable analyses to identify covariates associated with MR4. A predictive scoring system was derived from the final multivariable Fine–Gray model. Results: In univariable analyses, older age, higher WBC, lower hemoglobin, lower platelet count, higher peripheral blood basophils, larger spleen size, and a lower 0–3-month BCR::ABL1 log-reduction were significantly associated with a lower cumulative incidence of DMR (all P < 0.05). In the multivariable Fine–Gray model, a lower 0–3-month BCR::ABL1 log-reduction (P < 0.001) and higher baseline WBC (P = 0.002) remained independently associated with a lower likelihood of achieving DMR. We developed a DMR predictive score using the final model coefficients: DMRscore = 0.6903 × (0–3-month BCR::ABL1 log-reduction) –0.3019 ×(WBC/100). Patients were stratified into low-, intermediate-, and high-score groups according to score tertiles: low (DMRscore ≤ −0.1389, n = 32, 33.3%), intermediate (−0.1389 < DMRscore < 0.9594, n = 32, 33.3%), and high (DMRscore ≥0.9594, n = 32, 33.3%). The cumulative incidence of DMR differed significantly across groups (Gray test P < 0.001); at 24 months, the DMR cumulative incidence was 22.6%, 69.3%, and 82.9% in the low-, intermediate-, and high-score groups, respectively. The model showed good discrimination with time-dependent AUROC values of 0.90, 0.84, and 0.80 at 12, 24, and 36 months, respectively, and favorable predictive accuracy (Brier score: 0.1555/0.1983/0.2114 at 12/24/36 months). Conclusions: We developed a MR4 risk score using routine clinical and early molecular kinetics in pediatric chronic-phase CML receiving frontline imatinib, enabling early risk stratification to guide individualized treatment planning.

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