No margin for non-adherence: Probabilistic kaplan-meier modeling of imatinib non-adherence and treatment response in CML (ADAGIO study)

Obeng-Kusi, Mavis; MacDonald, Karen; Lierde, Marie-Anne van; Lee, Christopher S.; Geest, Sabina De; Abraham, Ivo

doi:10.1016/j.leukres.2021.106734

Cited by 7 publications

(6 citation statements)

References 15 publications

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“…A natural consequence of the overall success of CML therapy, with a growing number of patients having a near-normal life expectancy, has been a necessary increasing attention to the long-term outcomes other than the quality of life of these CML “survivors”. Consequently, a tailored approach to the CML patient requires the consideration of the adverse events associated with the TKIs as well, including the side-effects, since non-adherence to therapy is a key treatment-failure risk factor and a real challenging clinical issue [ 209 , 210 , 211 , 212 ].…”

Section: Discussionmentioning

confidence: 99%

Prognosis in Chronic Myeloid Leukemia: Baseline Factors, Dynamic Risk Assessment and Novel Insights

Iezza

Cortesi

Ottaviani

et al. 2023

Cells

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The introduction of tyrosine kinase inhibitors (TKIs) has changed the treatment paradigm of chronic myeloid leukemia (CML), leading to a dramatic improvement of the outcome of CML patients, who now have a nearly normal life expectancy and, in some selected cases, the possibility of aiming for the more ambitious goal of treatment-free remission (TFR). However, the minority of patients who fail treatment and progress from chronic phase (CP) to accelerated phase (AP) and blast phase (BP) still have a relatively poor prognosis. The identification of predictive elements enabling a prompt recognition of patients at higher risk of progression still remains among the priorities in the field of CML management. Currently, the baseline risk is assessed using simple clinical and hematologic parameters, other than evaluating the presence of additional chromosomal abnormalities (ACAs), especially those at “high-risk”. Beyond the onset, a re-evaluation of the risk status is mandatory, monitoring the response to TKI treatment. Moreover, novel critical insights are emerging into the role of genomic factors, present at diagnosis or evolving on therapy. This review presents the current knowledge regarding prognostic factors in CML and their potential role for an improved risk classification and a subsequent enhancement of therapeutic decisions and disease management.

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Section: Discussionmentioning

confidence: 99%

Prognosis in Chronic Myeloid Leukemia: Baseline Factors, Dynamic Risk Assessment and Novel Insights

Iezza

Cortesi

Ottaviani

et al. 2023

Cells

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Section: Risks Of Non-adherencementioning

confidence: 99%

“…Non-adherence to therapy is a key treatment-failure risk and a challenge for treating clinicians [61][62][63][64][65][66]. Anything less than complete adherence in patients treated with imatinib is associated with increased risk of a poor response [65]. Although TKIs have been lifesaving, chronic illness and lifelong therapy are financial and quality of life burdens affecting many aspects of patients' lives.…”

Section: Risks Of Non-adherencementioning

confidence: 99%

Defining Higher-Risk Chronic Myeloid Leukemia: Risk Scores, Genomic Landscape, and Prognostication

Shahrin

Wadham

Branford

2022

Curr Hematol Malig Rep

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Purpose of Review The chronic myeloid leukemia (CML) treatment success story is incomplete as some patients still fail therapy, leading to end-stage disease and death. Here we discuss recent research into CML incidence, the role of comorbidities on survival and detecting patients at risk of failing therapy. Recent Findings The incidence of CML has fallen markedly in high social-demographic index (SDI) regions of the world but there is disturbing evidence that this is not the case in low and low-middle SDI countries. Now that CML patients more frequently die from their co-morbid conditions than from CML the Adult Comorbidity Evaluation-27 score can assist in risk assessment at diagnosis. Non-adherence to therapy contributes greatly to treatment failure. A good doctor-patient relationship and social support promote good adherence, but patient age, gender, and financial burden have negative effects, suggesting avenues for intervention. Mutations in cancer-associated genes adversely affect outcome and their detection at diagnosis may guide therapeutic choice and offer non-BCR::ABL1 targeted therapies. A differential gene expression signature to assist risk detection is a highly sought-after diagnostic tool being actively researched on several fronts. Summary Detecting patients at risk of failing therapy is being assisted by recent technological advances enabling highly sensitive genomic and expression analysis of insensitive cells. However, patient lifestyle, adherence to therapy, and comorbidities are critical risk factors that need to be addressed by interventions such as social and financial support.

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“…There is convincing evidence that full adherence to therapy is critical to attain and maintain an optimal response. 4,5 Regardless of the type of front-line TKI used, patients who achieve optimal responses during the early phases of therapy are more likely to obtain better long-term survival outcomes. 6 However, patients with CML are frequently nonadherent to therapy, 7,8 with adverse events (AEs) likely to be the most frequent reason for intentional nonadherence to TKIs.…”

Section: Introductionmentioning

confidence: 99%

“…Therapy with TKIs is generally lifelong for most patients, and a key challenge is that of ensuring that they adhere to the prescribed treatment schedule. There is convincing evidence that full adherence to therapy is critical to attain and maintain an optimal response 4,5 . Regardless of the type of front‐line TKI used, patients who achieve optimal responses during the early phases of therapy are more likely to obtain better long‐term survival outcomes 6 …”

Section: Introductionmentioning

confidence: 99%

Patient‐reported symptom monitoring and adherence to therapy in patients with newly diagnosed chronic myeloid leukemia

Efficace,

Cottone,

Yanez

et al. 2023

Cancer

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BackgroundThe authors assessed the clinical utility of patient‐reported symptom monitoring in the setting of newly diagnosed chronic myeloid leukemia (CML). The primary objective was to evaluate adherence to therapy.MethodsThe authors conducted an international prospective study that included patients with newly diagnosed, chronic‐phase CML. Before clinical consultation, patients were provided a tablet computer to self‐rate their symptoms, and the results were available in real time to each physician during the patient’s visit. Adherence was assessed by pill count and with a validated self‐reported questionnaire. The proportions of optimal responders at 3 and 6 months were assessed according to the European LeukemiaNet criteria.ResultsBetween July 2020 and August 2021, 94 patients with a median age of 57 years were enrolled. Pill count adherence analysis indicated that 86 of 93 evaluable patients (92.5%) took at least 90% of prescribed tyrosine kinase inhibitor therapy during the 6‐month observation period. The online platform was well accepted by patients and physicians. An optimal response was achieved by 69 of 79 patients (87.3%) at 3 months and by 61 of 81 patients (75.3%) at 6 months.ConclusionsPatient‐reported symptom monitoring from the beginning of therapy in patients with CML may be critical to improve adherence to therapy and early molecular response rates (ClinicalTrials.gov identifier NCT04384848).

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No margin for non-adherence: Probabilistic kaplan-meier modeling of imatinib non-adherence and treatment response in CML (ADAGIO study)

Cited by 7 publications

References 15 publications

Prognosis in Chronic Myeloid Leukemia: Baseline Factors, Dynamic Risk Assessment and Novel Insights

Prognosis in Chronic Myeloid Leukemia: Baseline Factors, Dynamic Risk Assessment and Novel Insights

Defining Higher-Risk Chronic Myeloid Leukemia: Risk Scores, Genomic Landscape, and Prognostication

Patient‐reported symptom monitoring and adherence to therapy in patients with newly diagnosed chronic myeloid leukemia

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