Mortality rate in patients with chronic myeloid leukemia in chronic phase treated with frontline second generation tyrosine kinase inhibitors: a retrospective analysis by the monitoring registries of the Italian Medicines Agency (AIFA)

The impact of starting dose on overall survival in myelofibrosis patients treated with ruxolitinib: A prospective real-world study on AIFA monitoring registries

Ruxolitinib is a JAK1/JAK2 inhibitor approved for the treatment of myelofibrosis (MF)-related splenomegaly or symptoms. The recommended starting dose depends on platelet count, regardless of haemoglobin level at baseline. In the recent years, an overall survival (OS) advantage was reported in patients treated with ruxolitinib compared with best available therapy. We analysed a large Italian cohort of 3494 patients identified by Agenzia Italiana del Farmaco (AIFA) monitoring registries. Of them, 2337 (66.9%) started at reduced dose: these patients were older (median age 70 vs. 67), with increased incidence of large splenomegaly (longitudinal diameter 20 vs. 19.1 cm, median volume 1064 cm3 vs. 1016 cm3), with higher IPSS risk (30.9% vs. 26.1%), and worse ECOG score (more than 1 in 14.3% vs. 9.8%). After balancing for baseline characteristics, Kaplan-Meier analysis showed a median OS of 78.2 months (95% CI 65.9-89) for patients who started at full dose and 52.6 (95% CI 49-56.6) months for patients who started with reduced dose (p < 0.001). Group analysis also showed a substantial difference in patients with intermediate-2 and high IPSS risk. The majority of MF patients in real-world analysis started with a reduced dose of ruxolitinib, which is associated with less favourable outcomes.

Blockade of PD-1 and TIM-3 Ameliorates CD8+ T Cell Exhaustion in a Mouse Model of Chronic Myeloid Leukemia

The immune system plays a pivotal role in controlling chronic myeloid leukemia (CML). CD8+ T cell exhaustion results in reduced effectiveness of T cell-mediated immunity, thereby contributing to disease progression. This study intends to figure out whether the combined blockade of inhibitory molecules TIM-3/PD-1 can affect CD8+ T cell exhaustion in CML. A CML mouse model was established via transplantation of bone marrow cells transduced with BCR-ABL-expressing retrovirus vectors. PD-1 and TIM-3 signaling were blocked using corresponding molecular antibodies. Flow cytometry analysis was conducted to detect cell surface molecules and intracellular cytokines. ELISA was employed for measuring cytokine concentrations in the culture medium. The results showed that TIM-3 and PD-1 were coexpressed on exhausted CD8+ T cells from CML mice. Combined blockade of PD-1/TIM3 synergistically delayed CML progression in mice. Moreover, ex vivo experiments showed that their co-blockade promoted the proliferation and cytokine secretion of CD8+ T cells isolated from CML mice. In conclusion, blocking TIM-3 and PD-1 improves exhausted CD8+ T cell function in CML.

Application of artificial intelligence in chronic myeloid leukemia (CML) disease prediction and management: a scoping review

BACKGROUND

Navigating the complexity of chronic myeloid leukemia (CML) diagnosis and management poses significant challenges, including the need for accurate prediction of disease progression and response to treatment. Artificial intelligence (AI) presents a transformative approach that enables the development of sophisticated predictive models and personalized treatment strategies that enhance early detection and improve therapeutic interventions for better patient outcomes.

METHODS

An extensive search was conducted to retrieve relevant articles from PubMed, Scopus, and Web of Science databases up to April 24, 2023. Data were collected using a standardized extraction form, and the results are presented in tables and graphs, showing frequencies and percentages. The authors adhered to the PRISMA-ScR checklist to ensure transparent reporting of the study.

RESULTS

Of the 176 articles initially identified, 12 were selected for our study after removing duplicates and applying the inclusion and exclusion criteria. AI's primary applications of AI in managing CML included tumor diagnosis/classification (n = 9, 75%), prediction/prognosis (n = 2, 17%), and treatment (n = 1, 8%). For tumor diagnosis, AI is categorized into blood smear image-based (n = 5), clinical parameter-based (n = 2), and gene profiling-based (n = 2) approaches. The most commonly employed AI models include Support Vector Machine (SVM) (n = 5), eXtreme Gradient Boosting (XGBoost) (n = 4), and various neural network methods, such as Artificial Neural Network (ANN) (n = 3). Furthermore, Hybrid Convolutional Neural Network with Interactive Autodidactic School (HCNN-IAS) achieved 100% accuracy and sensitivity in organizing leukemia data types, whereas MayGAN attained 99.8% accuracy and high performance in diagnosing CML from blood smear images.

CONCLUSIONS

AI offers groundbreaking insights and tools for enhancing prediction, prognosis, and personalized treatment in chronic myeloid leukemia. Integrated AI systems empower healthcare practitioners with advanced analytics, optimizing patient care and improving clinical outcomes in CML management.

Severe Gastrointestinal Toxicity Following the Use of Gilteritinib: A Case Series and Analysis of Postmarketing Surveillance Data

Gilteritinib has been approved as monotherapy in adults with acute myeloid leukemia (AML) FLT3 mutated with relapsed or refractory disease, in light of its advantages in terms of survival and the favorable safety profile. Hepatobiliary disorders and musculoskeletal and connective tissue disorders represent the most frequent adverse reactions associated with gilteritinib, whereas the most frequent serious adverse reaction is acute kidney injury. In the summary of product characteristics, gastrointestinal (GI) events are indicated as very common, in particular diarrhea, nausea and stypsis. Furthermore, serious GI disorders have been observed with gilteritinib in clinical trials, including GI hemorrhage, GI perforation and GI obstruction. However, the association with the FLT3 inhibitor has not been confirmed. Nevertheless, serious GI AEs have been recognized as an important potential risk to be monitored in postmarketing surveillance. We present three cases of serious self-limiting GI events observed in patients on gilteritinib treatment for AML, and an analysis of relevant available postmarketing surveillance data.

Comparing machine learning algorithms to predict 5-year survival in patients with chronic myeloid leukemia

INTRODUCTION

Chronic myeloid leukemia (CML) is a myeloproliferative disorder resulting from the translocation of chromosomes 19 and 22. CML includes 15-20% of all cases of leukemia. Although bone marrow transplant and, more recently, tyrosine kinase inhibitors (TKIs) as a first-line treatment have significantly prolonged survival in CML patients, accurate prediction using available patient-level factors can be challenging. We intended to predict 5-year survival among CML patients via eight machine learning (ML) algorithms and compare their performance.

METHODS

The data of 837 CML patients were retrospectively extracted and randomly split into training and test segments (70:30 ratio). The outcome variable was 5-year survival with potential values of alive or deceased. The dataset for the full features and important features selected by minimal redundancy maximal relevance (mRMR) feature selection were fed into eight ML techniques, including eXtreme gradient boosting (XGBoost), multilayer perceptron (MLP), pattern recognition network, k-nearest neighborhood (KNN), probabilistic neural network, support vector machine (SVM) (kernel = linear), SVM (kernel = RBF), and J-48. The scikit-learn library in Python was used to implement the models. Finally, the performance of the developed models was measured using some evaluation criteria with 95% confidence intervals (CI).

RESULTS

Spleen palpable, age, and unexplained hemorrhage were identified as the top three effective features affecting CML 5-year survival. The performance of ML models using the selected-features was superior to that of the full-features dataset. Among the eight ML algorithms, SVM (kernel = RBF) had the best performance in tenfold cross-validation with an accuracy of 85.7%, specificity of 85%, sensitivity of 86%, F-measure of 87%, kappa statistic of 86.1%, and area under the curve (AUC) of 85% for the selected-features. Using the full-features dataset yielded an accuracy of 69.7%, specificity of 69.1%, sensitivity of 71.3%, F-measure of 72%, kappa statistic of 75.2%, and AUC of 70.1%.

CONCLUSIONS

Accurate prediction of the survival likelihood of CML patients can inform caregivers to promote patient prognostication and choose the best possible treatment path. While external validation is required, our developed models will offer customized treatment and may guide the prescription of personalized medicine for CML patients.

Cost-effectiveness analysis of olaparib as maintenance therapy in patients with platinum-sensitive relapsed ovarian cancer and a BRCA1/2 mutation in china

Objective: The aim of this study was to investigate the cost-effectiveness of olaparib as the maintenance therapy in patients with platinum-sensitive relapsed ovarian cancer and a BRCA1/2 mutation in China.

Methods: A Markov model was developed to simulate the clinical course of typical patients with ovarian cancer in the SOLO2 trial. The Weibull survival model was employed to fit the Kaplan–Meier progression-free survival and overall survival probabilities of the olaparib and placebo strategies, respectively. The clinical and direct costs data were derived from randomized clinical trials and published reports. Quality-adjusted life-years (QALYs) and incremental cost-effectiveness ratios (ICERs) were estimated over a 10-year lifetime horizon. Meanwhile, one-way and probabilistic sensitivity analyses were used to explore the impact of uncertainty on the model’s outcomes.

Results: Overall, the incremental effectiveness and cost of olaparib versus placebo were 0.56 QALYs and $43,292.92, respectively, resulting in an ICER of $77,620.56/QALY, higher than the willingness-to-pay (WTP) threshold of China ($31,498.70/QALY). The results were sensitive to the cost of olaparib and utility of PFS. Scenario analyses suggested that when the cost of olaparib was reduced by 60%, ICER decreased to $30,611.52/QALY, lower than the WTP threshold of China.

Conclusion: The findings from the present analysis suggest that olaparib with a 60% discount as maintenance therapy might be cost effective in patients with platinum-sensitive relapsed ovarian cancer and a BRCA1/2 mutation in China.

Bioequivalence, Drugs with Narrow Therapeutic Index and the Phenomenon of Biocreep: A Critical Analysis of the System for Generic Substitution

The prescription of generic drugs represents one of the main cost-containment strategies of health systems, aimed at reducing pharmaceutical expenditure. In this context, most regulatory authorities encourage or obligate dispensing generic drugs because they are far less expensive than their brand-name alternatives. However, drug substitution can be critical in particular situations, such as the use of drugs with a narrow therapeutic index (NTI). Moreover, generics cannot automatically be considered bioequivalent with each other due to the biocreep phenomenon. In Italy, the regulatory authority has established the Transparency Lists which include the medications that will be automatically substituted for brand-name drugs, except in exceptional cases. This is a useful tool to guide prescribers and guarantee pharmaceutical sustainability, but it does not consider the biocreep phenomenon.

Access to Innovative Neurological Drugs in Europe: Alignment of Health Technology Assessments Among Three European Countries

Even for products centrally approved, each European country is responsible for national market access after European Medicines Agency (EMA) approval. This step can result in inequalities in terms of access, due to different opinions about the therapeutic value assessed by Health Technology Assessment (HTA) bodies. This study aims to provide a comparative analysis of HTA recommendations issued by EU countries (France, Germany, and Italy) for new neurological drugs following EMA approval. In the reference period, we identified 11 innovative medicines authorized in Europe for five neurological diseases (cerebral adrenoleukodystrophy, spinal muscular atrophy, metachromatic leukodystrophy, migraine, and polyneuropathy in patients with hereditary transthyretin amyloidosis), including eight drugs for genetic rare diseases. We found no agreement on the therapeutic value (in particular the “added value” compared to the standard of care) of the selected drugs. Despite the differences in terms of assessment, the access has been usually guaranteed even if with various types of limitations. The heterogeneity of the HTA assessment of clinical data among countries is probably related to the uncertainties about clinical value at the time of EMA approval and the lack of long-term data and of direct comparison with available alternatives. Given the importance of new medicines especially for rare diseases, it is crucial to understand and act on the causes of inconsistency among the HTA assessments, in order to ensure rapid and uniform access to innovation for patients who can benefit.

Emerging concepts for assessing and predicting treatment-free remission in chronic myeloid leukemia patients

INTRODUCTION

In chronic myeloid leukemia (CML) patients who have reached a deep and sustained reduction of residual disease can attempt a discontinuation. The 'treatment-free remission' (TFR) has become a real long-term endpoint for 30-40% of chronic phase patients.

AREAS COVERED

In this review, we focus our attention on possible prognostic features who can predict the success of tyrosine kinase inhibitors discontinuation and how we can assess the minimal residual disease (MRD) during the TFR phase. Broad research was made on Medline, Embase and archives from EHA and ASH congresses.

EXPERT OPINION

Median duration of TKI therapy and of deep molecular response are the main prognostic factors identified in most trials and real-life experiences on discontinuation. Immunological pathways have been proposed as possible control on successful TFR as also early molecular response dynamics. Appropriate molecular monitoring by RQ-PCR in the TFR phase has been proposed by several international recommendations and digital droplet PCR (ddPCR) seems to have a possible role in the future for a better identification of candidate to this possible therapeutic strategy.

A nationwide prospective registry of bortezomib-based therapy in light chain (AL) amyloidosis

Until recently, no drug was labeled for AL amyloidosis. In 2011, the Italian Medicines Agency started a program to grant access to upfront bortezomib to patients with AL amyloidosis. All subjects were enrolled in a prospective online registry. Response was evaluated after two cycles to assess the possibility of continuing treatment. A total of 764 patients were included until 2019, and 615 were evaluable. Sixteen percent of patents had advanced (stage-IIIb) heart involvement, and 27% had severe or end-stage renal failure. Bortezomib delivery was possible in stage-IIIb patients at a reduced dose. Bortezomib discontinuation was associated with increasing age, advanced heart involvement and bi-weekly administration. Fifty-nine percent of subjects attained a hematologic response and 14% a cardiac response. Bortezomib-based therapy tends to be discontinued early in elderly patients and in advanced disease. Nevertheless, early response to therapy is possible in this challenging population.

Measuring prognosis in chronic myeloid leukemia: what's new?

Introduction: The outcome of chronic myeloid leukemia (CML) patients in chronic phase has changed after the introduction of tyrosine kinase inhibitors (TKIs). The life expectancy is actually similar to that of the general population. Prognostic stratification at baseline is part of a patient-centered approach to decide the best therapeutic approach.Areas covered: In this review, the current prognostic factors examined at baseline are detailed and the meaning is explained. A broad research on Medline, Embase and archives from EHA and ASH congresses, was performed. Prognostic factors have been divided into patient-related (age, gender, comorbidities, etc.) and disease-related (additional cytogenetic abnormalities, type of transcript, etc). New information about genomic data and the potential role of patient-reported outcomes is also discussed.Expert Opinion: Prognostic factors at baseline should be considered to evaluate the long-term probability of disease-related death, the possible toxicity, and the projected long-term overall survival. The genomic assessment would provide the basis for a genomic-based risk and help in oriented decision-making process.