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Background: Imatinib is the most widely used tyrosine kinase inhibitor (TKI) in patients with newly diagnosed chronic-phase chronic myeloid leukemia(CMLCP). However, failure to achieve optimal response after imatinib administration, and subsequent switch to second-generation TKI therapy results in poor efficacy and induces drug resistance. In the present study, we developed and validated a nomogram to predict the efficacy of imatinib in the treatment of patients newly diagnosed with CML-CP in order to help clinicians truly select patients who need 2nd generation TKI during initial therapy and to supplement the risk score system. Methods: We retrospectively analyzed 156 patients newly diagnosed with CMLCP who met the inclusion criteria and were treated with imatinib at the Second Affiliated Hospital of Xi'an Jiao Tong University from January 2012 to June 2022. The patients were divided into a poor-response cohort (N = 60)and an optimalresponse cohort (N = 43) based on whether they achieved major molecular remission (MMR) after 12 months of imatinib treatment. Using univariate and multivariate logistic regression analyses, we developed a chronic myeloid leukemia imatinib-poor treatment (CML-IMP) prognostic model using a nomogram considering characteristics like age, sex, HBG, splenic size, and ALP. The CML-IMP model was internally validated and compared with Sokal, Euro, EUTOS, and ELTS scores. Results: The area under the curve of the receiver operator characteristic curve (AUC)of 0.851 (95% CI 0.778-0.925) indicated satisfactory discriminatory ability of the nomogram. The calibration plot shows good consistency between the predicted and actual observations. The net reclassification index (NRI), continuous NRI value, and the integrated discrimination improvement (IDI) showed that the nomogram exhibited superior predictive performance compared to the Sokal, EUTOS, Euro, and ELTS scores (P < 0.05). In addition, the clinical decision curve analysis (DCA) showed that the nomogram was useful for clinical decision-making. In predicting treatment response, only Sokal and CML-IMP risk stratification can effectively predict the cumulative acquisition rates of CCyR, MMR, and DMR (P<0.05). Conclusion: We constructed a nomogram that can be effectively used to predict the efficacy of imatinib in patients with newly diagnosed CML-CP based on a single center, 10-year retrospective cohort study. [ABSTRACT FROM AUTHOR]

This study investigated changes in treatment modalities and outcomes of chronic myeloid leukemia in the chronic phase (CP-CML) after the approval of second-generation tyrosine kinase inhibitors (2G-TKIs) for first-line therapy. Patients were grouped into those who underwent TKI therapy up to December 2010 (imatinib era group, n = 185) and after January 2011 (2G-TKI era group, n = 425). All patients in the imatinib era group were initially treated with imatinib, whereas patients in the 2G-TKI era group were mostly treated with dasatinib (55%) or nilotinib (36%). However, outcomes including progression-free survival, overall survival, and CML-related death (CRD) did not differ significantly between groups. When stratified by risk scores, the prognostic performance of the ELTS score was superior to that of the Sokal score. Even though both scoring systems predicted CRD in the imatinib era, only the ELTS score predicted CRD in the 2G-TKI era. Notably, the outcome of patients classified as high-risk by ELTS score was more favorable in the 2G-TKI era group than in the imatinib era group. Thus, expanding treatment options may have improved patient outcomes in CP-CML, particularly in patients classified as high-risk by ELTS score. [ABSTRACT FROM AUTHOR]