A predictive scoring system for therapy-failure in persons with chronic myeloid leukemia receiving initial imatinib therapy

Cotargeting of thioredoxin 1 and glutamate-cysteine ligase in both imatinib-sensitive and imatinib-resistant CML cells

Chronic myeloid leukemia (CML) is a type of malignancy characterized by harboring the oncogene Bcr-Abl, which encodes the constitutively activated tyrosine kinase BCR-ABL. Although tyrosine kinase inhibitors targeting BCR-ABL have revolutionized CML therapy, native and acquired drug resistance commonly remains a great challenge. Thioredoxin 1 (Trx1) and glutamate-cysteine ligase (GCL), which are two major antioxidants that maintain cellular redox homeostasis, are potential targets for cancer therapy and overcoming drug resistance. However, how their inhibition is implicated in CML is still unclear. Here, our results revealed that Trx1 was overexpressed in patients with CML compared with healthy donors. Trx1 expression was greater in imatinib-resistant CML cells than in imatinib-sensitive cells. Pharmacological inhibitors of Trx1 attenuated cell growth and reduced colony formation in both imatinib-sensitive and imatinib-resistant CML cells. Furthermore, decreased Trx1 expression enhanced the cytotoxicity of the GCL inhibitor buthionine sulfoximine (BSO). We surmise that the combined inhibition of Trx1 and GCL promotes the induction of hydrogen peroxide and depletes GPX4 expression in CML cells, resulting in ferroptosis in cancerous cells. Finally, the combined inhibition of Trx1 and GCL had a synergistic effect on CML cells in murine xenograft models. These findings offer crucial informationregarding the combined roles ofTrx1 and GCL in triggering ferroptosis in CML and suggestefficacioustherapeutic uses for these systems in this disease.

A nomogram for predicting T315I-free survival in chronic phase chronic myeloid leukemia patients: a multicenter retrospective study

The T315I mutation poses a significant threat to patients with chronic phase chronic myeloid leukemia (CP-CML). This study aimed to establish a nomogram to predict the risk of T315I mutation in CP-CML patients. The training cohort included 1,466 patients from 24 hematology centers, and the validation cohort included 820 patients from an additional 20 centers. Peripheral blood blast (PBB), additional chromosomal abnormality (ACA), dasatinib use, non-EMR at 3 months, and BCR::ABLIS > 1% at 6 months were identified as independent risk factors through multivariate Cox regression analysis. The performance of the nomogram was assessed via receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). The area under the ROC curve (AUC) values at 5, 10, and 15 years were 0.874, 0.925, and 0.930 for the training cohort, and 0.864, 0.814, and 0.803 for the validation cohort, respectively. The calibration curves for both cohorts were close to the ideal diagonal, and the decision curves indicated clinical net benefit. In conclusion, we developed a nomogram to predict the 5-year, 10-year, and 15-year T315I-free survival probabilities of CP-CML patients. This tool can aid clinicians in the early prediction and timely management of high-risk CP-CML patients with the T315I mutation.

A predictive model for therapy failure in patients with chronic myeloid leukemia receiving tyrosine kinase inhibitor therapy

ABSTRACT

Although tyrosine kinase inhibitor (TKI) therapy has markedly improved the survival of people with chronic-phase chronic myeloid leukemia (CML), 20% to 30% of people still experienced therapy failure. Data from 1955 consecutive patients with chronic-phase CML diagnosed by the European LeukemiaNet recommendations from 1 center receiving initial imatinib or a second-generation (2G) TKI therapy were interrogated to develop a clinical prediction model for TKI-therapy failure. This model was subsequently validated in 3454 patients from 76 other centers. Using the predictive clinical covariates associated with TKI-therapy failure, we developed a model that stratified patients into low-, intermediate- and high-risk subgroups with significantly different cumulative incidences of therapy failure (P < .001). There was good discrimination and calibration in the external validation data set, and the performance was consistent with that of the training data set. Our model had the better prediction discrimination than the Sokal and European Treatment and Outcome Study long-term survival scores, with the greater time-dependent area under the receiver-operator characteristic curve values and a better ability to redefine the risk of therapy failure. Our model could help physicians estimate the likelihood of initial imatinib or 2G TKI-therapy failure in people with chronic-phase CML.

Basophil differentiation, heterogeneity, and functional implications

Basophils, rare granulocytes, have long been acknowledged for their roles in type 2 immune responses. However, the mechanisms by which basophils adapt their functions to diverse mammalian microenvironments remain unclear. Recent advancements in specific research tools and single-cell-based technologies have greatly enhanced our understanding of basophils. Several studies have shown that basophils play a role in maintaining homeostasis but can also contribute to pathology in various tissues and organs, including skin, lung, and others. Here, we provide an overview of recent basophil research, including cell development, characteristics, and functions. Based on an increasing understanding of basophil biology, we suggest that the precise targeting of basophil features might be beneficial in alleviating certain pathologies such as asthma, atopic dermatitis (AD), and others.

Development and validation of a nomogram to predict poor efficacy of imatinib in the treatment of newly diagnosed chronic phase chronic myeloid leukemia patients

Background

Imatinib is the most widely used tyrosine kinase inhibitor (TKI) in patients with newly diagnosed chronic-phase chronic myeloid leukemia(CML-CP). 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 CML-CP 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 optimal-response 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.

Comparison of the Efficacy Among Nilotinib, Dasatinib, Flumatinib and Imatinib in Newly Diagnosed Chronic-Phase Chronic Myeloid Leukemia Patients: A Real-World Multi-Center Retrospective Study

BACKGROUND

There are limited data comprehensively comparing therapy responses and outcomes among nilotinib, dasatinib, flumatinib and imatinib for newly diagnosed chronic-phase chronic myeloid leukemia in a real-world setting.

PATIENTS AND METHODS

Data from patients with chronic-phase CML receiving initial a second-generation tyrosine-kinase inhibitor (2G-TKI, nilotinib, dasatinib or flumatinib) or imatinib therapy from 77 Chinese centers were retrospectively interrogated. Propensity-score matching (PSM) analyses were performed to to compare therapy responses and outcomes among these 4 TKIs.

RESULTS

2,496 patients receiving initial nilotinib (n = 512), dasatinib (n = 134), flumatinib (n = 411) or imatinib (n = 1,439) therapy were retrospectively interrogated in this study. PSM analyses indicated that patients receiving initial nilotinib, dasatinib or flumatinib therapy had comparable cytogenetic and molecular responses (p = .28-.91) and survival outcomes including failure-free survival (FFS, p = .28-.43), progression-free survival (PFS, p = .19-.93) and overall survival (OS) (p values = .76-.78) but had significantly higher cumulative incidences of cytogenetic and molecular responses (all p values < .001) and higher probabilities of FFS (p < .001-.01) than those receiving imatinib therapy, despite comparable PFS (p = .18-.89) and OS (p = .23-.30).

CONCLUSION

Nilotinib, dasatinib and flumatinib had comparable efficacy, and significantly higher therapy responses and higher FFS rates than imatinib in newly diagnosed CML patients. However, there were no significant differences in PFS and OS among these 4 TKIs. These real-world data may provide additional evidence for routine clinical assessments to identify more appropriate therapies.

Validation of imatinib therapy failure score (IMTF) in chronic phase chronic myeloid leukemia in real life practice

The outcome of chronic myeloid leukemia (CML) patients improved in the last decade. Clinical prognostic scoring systems aim to provide information about survival in the long-term, without determining from baseline the subset of patients who require a strictly monitoring because at increased risk of failure. Imatinib, the first-generation tyrosine kinase inhibitor (TKI), is still widely used as frontline treatment: recently, the imatinib therapy failure (IMTF) score was proposed to identify the failure free survival. Aim of our study was to validate this index in a large cohort of patients treated with imatinib.

An MRI-based scoring system for pretreatment risk stratification in locally advanced rectal cancer

BACKGROUND

Accurately assessing the risk of recurrence in patients with locally advanced rectal cancer (LARC) before treatment is important for the development of treatment strategies. The purpose of this study is to develop an MRI-based scoring system to predict the risk of recurrence in patients with LARC.

METHODS

This was a multicenter observational study that enrolled participants who underwent neoadjuvant chemoradiotherapy. To evaluate the risk of recurrence in these patients, we developed the mrDEC scoring system and assessed inter-reader agreement. Additionally, we plotted Kaplan-Meier curves to compare the 3-year disease-free survival (DFS) and 5-year overall survival (OS) rates among patients with different mrDEC scores.

RESULTS

A total of 1287 patients with LARC were included in this study. We observed substantial inter-reader agreement for mrDEC. Based on the mrDEC scores ranging from 0 to 3, the patients were categorized into four groups. The 3-year DFS rates for the groups were 91.0%, 79.5%, 65.5%, and 44.0% (P < 0.0001), respectively, and the 5-year OS rates were 92.9%, 87.1%, 74.8%, and 44.5%, respectively (P < 0.0001).

CONCLUSIONS

The mrDEC scoring system proved to be an effective tool for predicting the prognosis of patients with LARC and can assist clinicians in clinical decision-making.

Patients with chronic myeloid leukemia and coronavirus disease 2019 in the Omicron era

To explore the prevalence and severity of COVID-19 and the mental health during the Omicron pandemic in patients with chronic myeloid leukemia (CML), a cross-sectional survey from 2609 respondents with CML was performed. A total of 1725 (66%) reported that they had COVID-19 during this period. Among them, 1621 (94%) were mild; 97 (6%), moderate; 7 (0.4%), severe; and 0, critical or death. Four hundred three (15%), 199 (8%), and 532 (20%) had moderate to severe depression, anxiety, and distress, respectively. Eight hundred ninety (34%), 667 (26%), and 573 (22%), avoidance, intrusion, and hyper-arousal, respectively. In multivariate analyses, longer TKI-therapy duration was significantly associated with a lower prevalence of COVID-19 (odds ratio [OR] = 0.98; 95% confidence interval [CI], 0.95, 0.99; p = 0.043); however, living in urban areas (OR = 1.6 [1.3, 2.0]; p < 0.001) and having family members with COVID-19 (OR = 18.6 [15.1, 22.8]; p < 0.001), a higher prevalence of COVID-19. Increasing age (OR = 1.2 [1.1, 1.4]; p = 0.009), comorbidity(ies) (OR = 1.7 [1.1, 2.7]; p = 0.010), and multi-TKI-resistant patients receiving 3rd-generation TKIs or investigational agents (OR = 2.2 [1.2, 4.2]; p = 0.010) were significantly associated with moderate or severe COVID-19. Female, comorbidity(ies), unvaccinated, and moderate or severe COVID-19 were significantly associated with almost all adverse mental health consequences; increasing age or forced TKI dose reduction because of various restriction during the pandemic, moderate to severe distress, avoidance, or intrusion; however, mild COVID-19, none or mild anxiety, distress, avoidance, or intrusion. In conclusion, shorter TKI-therapy duration, increasing age, comorbidity(ies), or multi-TKI-resistant patients receiving 3rd-generation TKIs or investigational agents had a higher prevalence of COVID-19 or higher risk of moderate or severe disease in patients with CML; increasing age, female, comorbidity(ies), forced TKI dose reduction due to the pandemic, moderate or severe COVID-19, unvaccinated, a higher likelihood of worse mental health.

Real-world experience with ponatinib therapy in chronic phase chronic myeloid leukemia: impact of depth of response on survival and prior exposure to nilotinib on arterial occlusive events

We surveyed the performance of ponatinib, as salvage therapy, in a real-world setting of chronic phase chronic myeloid leukemia (CML-CP). Among 55 consecutive patients (median age 49 years) with relapsed/refractory CML-CP, 35 (64%) had failed ≥3 tyrosine kinase inhibitors (TKIs), 35 (64%) were pre-treated with nilotinib, and 14 (28%) harbored ABL1T315I. At start of ponatinib (median dose 30 mg/day), 40 patients were already in complete hematologic (CHR), 4 in complete cytogenetic (CCyR), 3 in major molecular (MMR) remission, while 8 had not achieved CHR (NR). Ponatinib improved the depth of response in 13 (33%), 3 (75%), 2 (66%), and 4 (50%) patients with CHR, CCyR, MMR, and NR, respectively (p = 0.02). At a median follow-up of 42 months, 13 (23%) deaths, 5 (9%) blast transformations, and 25 (45%) allogeneic transplants were recorded. Five/10-year post-ponatinib survival was 77%/58% with no significant difference when patients were stratified by allogeneic transplant (p = 0.94), ponatinib-induced deeper response (p = 0.28), or a post-ponatinib ≥CCyR vs CHR remission state (p = 0.25). ABL1T315I was detrimental to survival (p = 0.04) but did not appear to affect response. Prior exposure to nilotinib was associated with higher risk of arterial occlusive events (AOEs; 11% vs 0%; age-adjusted p = 0.04). Ponatinib starting/maintenance dose (45 vs 15 mg/day) did not influence either treatment response or AOEs. Our observations support the use of a lower starting/maintenance dose for ponatinib in relapsed/refractory CML-CP but a survival advantage for deeper responses was not apparent and treatment might not overcome the detrimental impact of ABL1T315I on survival. The association between prior exposure to nilotinib and a higher risk of post-ponatinib AOEs requires further validation.

Prognostic factors and survival prediction for patients with metastatic lung adenocarcinoma: A population-based study

The prognosis of metastatic lung adenocarcinoma (MLUAD) varies greatly. At present, no studies have constructed a satisfactory prognostic model for MLUAD. We identified 44,878 patients with MLUAD. The patients were randomized into the training and validation cohorts. Cox regression models were performed to identify independent prognostic factors. Then, R software was employed to construct a new nomogram for predicting overall survival (OS) of patients with MLUAD. Accuracy was assessed by the concordance index (C-index), receiver operating characteristic curves and calibration plots. Finally, clinical practicability was examined via decision curve analysis. The OS time range for the included populations was 0 to 107 months, and the median OS was 7.00 months. Nineteen variables were significantly associated with the prognosis, and the top 5 prognostic factors were chemotherapy, grade, age, race and surgery. The nomogram has excellent predictive accuracy and clinical applicability compared to the TNM system (C-index: 0.723 vs 0.534). The C-index values were 0.723 (95% confidence interval: 0.719-0.726) and 0.723 (95% confidence interval: 0.718-0.729) in the training and validation cohorts, respectively. The area under the curve for 6-, 12-, and 18-month OS was 0.799, 0.764, and 0.750, respectively, in the training cohort and 0.799, 0.762, and 0.746, respectively, in the validation cohort. The calibration plots show good accuracy, and the decision curve analysis values indicate good clinical applicability and effectiveness. The nomogram model constructed with the above 19 prognostic factors is suitable for predicting the OS of MLUAD and has good predictive accuracy and clinical applicability.

Targeted Next-Generation Sequencing Identifies Additional Mutations Other than BCR∷ABL in Chronic Myeloid Leukemia Patients: A Chinese Monocentric Retrospective Study

A proportion of patients with somatic variants show resistance or intolerance to TKI therapy, indicating additional mutations other than BCR∷ABL1 may lead to TKI treatment failure or disease progression. We retrospectively evaluated 151 CML patients receiving TKI therapy and performed next-generation sequencing (NGS) analysis of 22 CML patients at diagnosis to explore the mutation spectrum other than BCR∷ABL1 affecting the achievement of molecular responses. The most frequently mutated gene was ASXL1 (40.9%). NOTCH3 and RELN mutations were only carried by subjects failing to achieve a major molecular response (MMR) at 12 months. The distribution frequency of ASXL1 mutations was higher in the group that did not achieve MR4.0 at 36 months (p = 0.023). The achievement of MR4.5 at 12 months was adversely impacted by the presence of >2 gene mutations (p = 0.024). In the analysis of clinical characteristics, hemoglobin concentration (HB) and MMR were independent factors for deep molecular response (DMR), and initial 2GTKI therapy was better than 1GTKI in the achievement of molecular response. For the scoring system, we found the ELTS score was the best for predicting the efficacy of TKI therapy and the Socal score was the best for predicting mutations other than BCR∷ABL.

Model Embraced Electromechanical Coupling Time for Estimation of Heart Failure in Patients With Hypertrophic Cardiomyopathy

Objective

This study aimed to establish a model embraced electromechanical coupling time (EMC-T) and assess the value of the model for the prediction of heart failure (HF) in patients with hypertrophic cardiomyopathy (HCM).

Materials and Methods

Data on 82 patients with HCM at Shaanxi Provincial People’s Hospital between February 2019 and November 2021 were collected and then formed the training dataset (n = 82). Data were used to screen predictors of HF using univariate and multivariate analyses. Predictors were implemented to discover the optimal cut-off value, were incorporated into a model, and shown as a nomogram. The cumulative HF curve was calculated using the Kaplan–Meier method. Additionally, patients with HCM at other hospitals collected from March 2019 to March 2021 formed the validation dataset. The model’s performance was confirmed both in training and validation sets.

Results

During a median of 22.91 months, 19 (13.38%) patients experienced HF. Cox analysis showed that EMC-T courses in the lateral wall, myoglobin, PR interval, and left atrial volume index were independent predictors of HF in patients with HCM. Five factors were incorporated into the model and shown as a nomogram. Stratification of patients into two risk subgroups by applying risk score (<230.65, ≥230.65) allowed significant distinction between Kaplan–Meier curves for cumulative incidence of HF events. In training dataset, the model had an AUC of 0.948 (95% CI: 0.885–1.000, p < 0.001) and achieved a good C-index of 0.918 (95% CI: 0.867–0.969). In validation dataset, the model had an AUC of 0.991 (95% CI: 0.848–1.000, p < 0.001) and achieved a strong C-index of 0.941 (95% CI: 0.923–1.000). Calibration plots showed high agreement between predicted and observed outcomes in both two datasets.

Conclusion

We established and validated a novel model incorporating electromechanical coupling time courses for predicting HF in patients with HCM.