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Chen H, Wen Y, Zeng Y, Lin L, Sun B, Zhu H, He H, Wang X, Zou W, Zheng C, Zheng L, Huang J, Pang L, Huang J, Zhang Y, Lin H, Liu Z, Zhu W, Wang Q, Zhou X, Liu X, Qu H, Liu Z, Du X, Xu N. Patient Versus Physician Perspective in the Management of Chronic Myeloid Leukemia During Treatment with Tyrosine Kinase Inhibitors. Oncol Ther 2024; 12:131-145. [PMID: 38104036 PMCID: PMC10881939 DOI: 10.1007/s40487-023-00255-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Accepted: 11/21/2023] [Indexed: 12/19/2023] Open
Abstract
INTRODUCTION Chronic myeloid leukemia (CML) is a chronic disease with treatment-free remission (TFR) increasingly regarded as a feasible goal of treatment. However, various factors may influence adherence to international guidelines for CML management. This study aimed to compare the reporting of care between patients with CML and their treating doctors. METHODS Parallel patient and physician online surveys were conducted between September 22, 2021, and March 15, 2022, which focused on the perceptions of 1882 adult patients with CML and 305 physicians regarding tyrosine kinase inhibitor (TKI) treatment options, monitoring and toxicities, TFR, and challenges faced. RESULTS Among the enrolled patients, 69.9% received first-line imatinib treatment, 18.6% received nilotinib, and 4.7% received dasatinib. Among the patients treated with imatinib, 36.7% switched to other TKIs due to imatinib resistance/intolerance (71.1%), exploration of more potent TKIs to achieve TFR (8.9%), and treating physicians' recommendation (14.0%), with a median duration of initial treatment of 14 months [interquartile range (IQR) 6-36]. Most (91.8%) physicians agreed that the breakpoint cluster region-Abelson 1 (BCR::ABL1) transcript level should be assessed every 3 months, but only 42.7% of individuals committed to 3-monthly testing and only 17.8% strictly followed their treating physicians' recommendation. Half of the patients aimed for TFR; however, just 45.2% of physicians considered TFR as one of the top three goals for their patients. The major concern in obtaining TFR was patients' adherence. Fatigue was often distressing for patients with TKIs, while physicians were more concerned about platelet and neutrophil counts. A total of 12% and 20.8% of patients reported moderate/severe anxiety and depression, respectively, while only 53.7% of physicians had concerns about their patients' mental health. During the coronavirus disease 2019 (COVID-19) pandemic, 69.2% of patients reported a reduction in their income. Among these patients, 61.8% maintained their current treatment, while 7.3% switched to cheaper alternatives or discontinued treatment, with over 80% of these patients belonging to the low-income group. CONCLUSIONS Overcoming challenges in patient-physician communication and treatment access is key to improving disease management and quality of life, especially for patients with low income. TRIAL REGISTRATION ClinicalTrials.gov identifier NCT05092048.
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Affiliation(s)
- Hong Chen
- Department of Hematology, Nanfang Hospital, Southern Medical University, 1838 Guangzhou Da Dao North, Guangzhou, 510515, Guangdong, China
| | - Yan Wen
- Department of Hematology, Yunnan Hematology Hospital, First People' Hospital of Yunnan, Affiliated Hospital of Kunming University of Science and Technology, Kunming, China
| | - Yun Zeng
- Department of Hematology, First Affiliated Hospital of Kunming Medical University, Hematology Research Center of Yunnan Province, Kunming, China
| | - Lie Lin
- Department of Hematology, Hainan General Hospital, Haikou, China
| | - Bihong Sun
- Department of Hematology, People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, China
| | - Hongqian Zhu
- Department of Hematology, Guizhou Provincial People's Hospital, Guiyang, China
| | - Huiqing He
- Department of Hematology, Zhongshan People's Hospital, Zhongshan, China
| | - Xiaotao Wang
- Department of Hematology, Guilin Medical University Affiliated Hospital, Guilin, China
| | - Waiyi Zou
- Department of Hematology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Caifeng Zheng
- Department of Hematology, Shenzhen Bao An People's Hospital, Shenzhen, China
| | - Liling Zheng
- Department of Hematology, The Second People's Hospital of Guangdong Province, Guangzhou, China
| | - Jinxiong Huang
- Department of Hematology, Liuzhou People's Hospital, Liuzhou, China
| | - Liping Pang
- Department of Hematology, Peking University Shenzhen Hospital, Shenzhen, China
| | - Jixian Huang
- Department of Hematology, Yue Bei People's Hospital, Shantou University Medical College, Shaoguan, China
| | - Yuming Zhang
- Department of Hematology, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China
| | - Haiqing Lin
- Department of Hematology, Shenzhen People's Hospital, Second Clinical Medical College of Jinan University, First Affiliated Hospital of Southern University of Science and Technology, Shenzhen, China
| | - Zelin Liu
- Department of Hematology, Huazhong University of Science and Technology Union Shenzhen Hospital, Shenzhen, China
| | - Wanshou Zhu
- Department of Hematology, Gaozhou People's Hospital, Gaozhou, China
| | - Qiang Wang
- Department of Hematology, Nanfang Hospital, Southern Medical University, 1838 Guangzhou Da Dao North, Guangzhou, 510515, Guangdong, China
| | - Xuan Zhou
- Department of Hematology, Nanfang Hospital, Southern Medical University, 1838 Guangzhou Da Dao North, Guangzhou, 510515, Guangdong, China
| | - Xiaoli Liu
- Department of Hematology, Nanfang Hospital, Southern Medical University, 1838 Guangzhou Da Dao North, Guangzhou, 510515, Guangdong, China
| | - Hong Qu
- Department of Hematology, Panyu Central Hospital, Guangzhou, China
| | - Zhenfang Liu
- Department of Hematology, The First Affiliated Hospital of Guangxi Medical University, No. 6, Shuang Yong Road, Nanning, 530021, Guangxi, China.
| | - Xin Du
- Department of Hematology and Shenzhen Bone Marrow Transplantation Public Service Platform, The First Affiliated Hospital of Shenzhen University, Shenzhen Second People's Hospital, Shenzhen University School of Medicine, 3002 Sungang West Road, Futian District, Shenzhen, 518035, China.
| | - Na Xu
- Department of Hematology, Nanfang Hospital, Southern Medical University, 1838 Guangzhou Da Dao North, Guangzhou, 510515, Guangdong, China.
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Liu YT, Zhang XS, Hou Y, Jiang Q. [Survey and analysis of the concerns of patients with chronic myeloid leukemia in China in 2021]. ZHONGHUA XUE YE XUE ZA ZHI = ZHONGHUA XUEYEXUE ZAZHI 2022; 43:760-765. [PMID: 36709170 PMCID: PMC9613486 DOI: 10.3760/cma.j.issn.0253-2727.2022.09.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/16/2022] [Indexed: 11/29/2022]
Abstract
Objective: To investigate the concerns of adult patients with chronic myeloid leukemia (CML) in the chronic phase receiving tyrosine kinase inhibitor (TKI) therapy in China. Methods: A cross-sectional questionnaire including 23 issues of concern was filled by patients with CML nationwide from August to September 2021. The results were compared with those from 2015 to 2016. Results: Data from 952 questionnaires were analyzed. The five most concerned issues were "TKI-related adverse effects and management" (66%) , "stopping TKI therapy" (46%) , "CML risk assessment" (46%) , "TKI dose reduction" (42%) , and "restrictions in daily life activities" (41%) . Compared with the results from 2015 to 2016, patients paid more attention to "TKI-related adverse effects and management" , "monitoring" , and "interpretation of laboratory reports" (all P<0.01) . Concerns of "TKI reimbursement policies" , "price reduction of TKIs" , and issues related to generic TKIs decreased significantly (all P<0.01) . Multivariate analysis showed that female patients (OR=1.8, 95% CI 1.4-2.5, P<0.001) , elderly patients (OR=1.0, 95% CI 1.0-1.0, P<0.001) , or patients with bachelor's degree or higher (OR=1.8, 95% CI 1.3-2.4, P<0.001) were more concerned with "TKI dose reduction" than others. Patients with a bachelor's degree or higher (OR=1.6, 95% CI 1.2-2.2, P=0.002) paid more attention to "CML risk assessment" , whereas those currently receiving a second- or third-generation TKI therapy (OR=1.9, 95% CI 1.3-2.6, P<0.001) were more concerned about "TKI resistance" . Conclusion: Patients with CML paid the most attention to "TKI-related adverse effects and management" , "stopping TKI therapy" , "CML risk assessment" , "TKI dose reduction" , and "restrictions in daily life activities" . Patients' sociodemographic covariates and treatment status were associated with their concerns.
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Affiliation(s)
- Y T Liu
- Peking University People's Hospital, Peking University Institute of Hematology, National Clinical Research Center for Hematologic Disease, Beijing 100044, China
| | - X S Zhang
- Peking University People's Hospital, Peking University Institute of Hematology, National Clinical Research Center for Hematologic Disease, Beijing 100044, China
| | - Y Hou
- Peking University People's Hospital, Peking University Institute of Hematology, National Clinical Research Center for Hematologic Disease, Beijing 100044, China
| | - Q Jiang
- Peking University People's Hospital, Peking University Institute of Hematology, National Clinical Research Center for Hematologic Disease, Beijing 100044, China
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A predictive scoring system for therapy-failure in persons with chronic myeloid leukemia receiving initial imatinib therapy. Leukemia 2022; 36:1336-1342. [PMID: 35194158 DOI: 10.1038/s41375-022-01527-y] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Revised: 01/25/2022] [Accepted: 02/07/2022] [Indexed: 01/06/2023]
Abstract
Data from 1,364 consecutive subjects with chronic-phase chronic myeloid leukemia (CML) receiving initial imatinib-therapy were interrogated to identify co-variates predicting therapy failure. Subjects were randomly divided into training (n = 908) and validation datasets (n = 456). In the training dataset, WBC count ≥120 × 10E + 9/L, haemoglobin concentration <115 g/L, blood basophils ≥12% and European Treatment and Outcome Study for CML Long-Term Survival (ELTS) risk score were significantly-associated with failure-free survival (FFS). Each co-variate was assigned 1 point to develop the imatinib-therapy failure (IMTF) model except ELTS high-risk category which was assigned 2 points based on multi-variable regression coefficients. Area under receiver-operator characteristic curve values in the IMTF model for 1-, 3- and 5-year FFS were 0.79-0.84 in the training dataset and 0.78-0.85 in the validation dataset. Calibration plots showed high agreement between predicted and observed outcomes. Decision curve analyses indicated subjects benefited from clinical use of this model. Cumulative incidences of imatinib-therapy failure and probabilities of FFS among the 5 risk cohorts (very low-, low-, intermediate-, high- and very high-risk) using the IMTF model were significantly different (all p values < 0.001). The IMTF model also correlated with probabilities of progression-free survival and survival (all p values < 0.001). These data should help physicians optimize TKI-therapy strategy at diagnosis in persons with chronic phase CML.
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[Combination of socio-demographic and clinical co-variates for predicting treatment responses and outcomes in patients with chronic myeloid leukemia in the chronic phase]. ZHONGHUA XUE YE XUE ZA ZHI = ZHONGHUA XUEYEXUE ZAZHI 2022; 43:54-62. [PMID: 35231994 PMCID: PMC8980668 DOI: 10.3760/cma.j.issn.0253-2727.2022.01.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Objective: To explore the impacts of socio-demographic and clinical co-variates on treatment responses and outcomes in patients with chronic myeloid leukemia in the chronic phase (CML-CP) receiving tyrosine kinase inhibitor (TKI) and identified the predictive models for them. Methods: Data of newly diagnosed adult patients with CML-CP receiving first-line TKI and having complete socio-demographic data and clinical information were reviewed. Cox model was used to identify the independent variables associated with complete cytogenetic response (CCyR) , major molecular response (MMR) , molecular response 4 (MR(4)) and molecular response 4.5 (MR(4.5)) , as well as failure-free survival (FFS) , progression-free survival (PFS) , overall survival (OS) and CML-related OS. Results: A total of 1414 CML-CP patients treated with first-line imatinib (n=1176) , nilotinib (n=170) or dasatinib (n=68) were reviewed. Median age was 40 (18-83) years and 873 patients (61.7% ) were males. Result of the multivariate analysis showed that lower educational level (P<0.001-0.070) and EUTOS long-term survival intermediate or high-risk (P<0.001-0.009) were significantly associated with lower cumulative incidences of CCyR, MMR, MR(4) and MR(4.5), as well as the inferior FFS, PFS, OS and CML-related OS. In addition, those who were males, from rural households, had white blood cells (WBC) ≥120×10(9)/L, hemoglobin (HGB) <115 g/L and treated with first-line imatinib had significantly lower cumulative incidences of cytogenetic and/or molecular responses. Being single, divorced or widowed, having, rural household registration, WBC≥120×10(9)/L, HGB<15 g/L, and comorbidity (ies) was significantly associated with inferior FFS, PFS, OS, and/or CML-related OS. Thereafter, the patients were classified into several subgroups using the socio-demographic characteristics and clinical variables by cytogenetic and molecular responses, treatment failure and disease progression, as well as overall survival and CML-related OS, respectively. There were significant differences in treatment responses and outcomes among the subgroups (P<0.001) . Conclusion: Except for clinical co-variates, socio-demographic co-variates significantly correlated with TKI treatment responses and outcomes in CML-CP patients. Models established by the combination of independent socio-demographic and clinical co-variates could effectively predict the responses and outcome.
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