Introduction: The advent of tyrosine kinase inhibitors (TKIs) has revolutionized the treatment of chronic phase chronic myeloid leukemia (CP-CML). However, the T315I mutation, accounting for 15-20% of BCR::ABL1 kinase domain (KD) mutations, poses a significant threat to patients. Currently, no clinical predictive model for the T315I mutation in CML patients has been developed. This retrospective study aimed to establish a nomogram model to predict the T315I-free survival probability in CP-CML patients, aiding clinicians in early assessment, proactive measures, and improving patient outcomes.

Methods: The training cohort included 1,466 patients from 24 hematology centers between January 2010, and May 2023, and the validation cohort included 820 patients from an additional 20 centers during the same period. The inclusion criteria were as follows: (1) met the diagnostic criteria for CML; (2) were aged older than 18 years; and (3) had a follow-up duration exceeding 12 months. The exclusion criteria were (1) experienced AP or BP, (2) missing critical clinical records, and (3) having other BCR::ABL1 KD mutations excluding T315I. Independent risk factors were identified by multivariate Cox regression analysis, and a nomogram for predicting T315I-free survival was constructed. The performance was assessed using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA).

Results:In the training cohort, a total of 898 (61.3%) patients were male, and the median age was 50 years (IQR 37-60 years). With a median follow-up time of 3.6 years (range 1-24.9 years), 30 patients (2.0%) developed the T315I mutation. The validation cohort included 820 patients. A total of 23 patients (2.8%) developed the T315I mutation and the median follow-up time was 3.7 years (range 1-29.5 years). According to the multivariable Cox regression analysis, peripheral blood blast (PBB) (P=0.042, hazard ratio (HR) = 1.171, 95% confidence interval (CI) 1.006-1.364), chromosomal abnormality (ACA) (P=0.020, HR=3.712, 95% CI 1.224-11.255), TKI choice of dasatinib (P=0.011, HR=7.769, 95% CI 1.594-37.868), non-early molecular response (EMR) at 3 months (P=0.033, HR=5.692, 95% CI 1.146-28.262), and BCR::ABLIS > 1% at 6 months (P=0.005, HR=22.794, 95% CI 2.529-205.450) were found to be independent risk factors for the occurrence of the T315I mutation in CP-CML patients. By integrating the above five factors, a nomogram model was constructed to predict the T315I-free survival probability at 5, 10 and 15 years for CP-CML patients. The C-indices of the training and validation cohorts were 0.894 and 0.857, respectively. The AUC values at 5, 10, and 15 years were 0.874 (95% CI 0.798-0.950), 0.925 (95% CI 0.857-0.989), and 0.930 (95% CI 0.864-0.995) for the training cohort and 0.864 (95% CI 0.731-0.998), 0.814 (95% CI 0.668-0.959), and 0.803 (95% CI 0.624-0.981) for the validation cohort. The calibration curves for both cohorts were close to the ideal diagonal, reflecting good accuracy. The DCA curve demonstrated clinical net benefit within a certain range. Furthermore, we defined patients with scores >128 as the high-risk group, while those with scores ≤128 were defined as the low-risk group. The Kaplan‒Meier curve showed that patients in the high-risk group had a lower T315I-free survival probability than patients in the low-risk group (P<0.0001, P<0.0001). The 5-year and 10-year T315I-free survival probabilities for the low-risk group were 99.6% (95% CI 99.3%-100.0%), 98.8% (95% CI 97.6%-100.0%), respectively, while for the high-risk group, the 5-year, 10-year, and 15-year T315I-free survival probabilities were 92.9% (95% CI 90.1%-95.7%), 83.3% (95% CI 77.6%-89.5%), and 60.6% (95% CI 47.4%-77.4%), respectively.

Conclusions: We developed a nomogram to predict the 5-year, 10-year, and 15-year T315I-free survival probability in CP-CML patients. This tool aids clinicians in the early prediction and timely management of high-risk CP-CML patients with the T315I mutation.

Acknowledgement: This research was funded by the Key R&D Program of Zhejiang (No. 2022C03137) and the Zhejiang Medical Association Clinical Medical Research Special Fund Project (No. 2022ZYC-D09).

*Correspondence to: Jian Huang, M.D., Ph.D., Department of Hematology, The First Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310003, Zhejiang, China. E-mail: househuang@zju.edu.cn

Disclosures

No relevant conflicts of interest to declare.

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2024
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