Acute pancreatitis in children with acute lymphoblastic leukemia correlates with L-asparaginase dose intensity

Risk factors for drug-related acute pancreatitis: an analysis of the FDA adverse event reporting system (FAERS)

Objective: While several drugs have been linked to acute pancreatitis (AP), the AP-related risk of most drugs remains unclear. This study investigated the risk factors for drug-induced AP by analyzing a large dataset from the FDA Adverse Event Reporting System (FAERS). Methods: The reporting odds ratios (ROR) were used to assess the reports of drug-induced AP from the first quarter of 2004 to the second quarter of 2022. Single-factor, LASSO, and multi-factor regression analysis were performed to explore drug-related AP-related risk factors. Bonferroni correction was applied for the multiple comparisons performed. Results: A total of 264 drugs associated with AP, including antineoplastic drugs (35/264), antidiabetic drugs (28/264), antibacterial drugs (24/264), immunomodulatory drugs (11/264), antipsychotic drugs (6/264), and other drugs (160/264) were retrieved. Multi-factor analysis showed that males, age 41-54 years old, and 36 drugs, including Tigecycline, were risk factors for drug-related AP. The median time to drug-related AP onset was 31 days (interquartile range [IQR] 7-102 days) and about 75% of adverse events occurred within 100 days. Conclusion: These findings may help clinicians to identify drug-related AP at the early stage and can be used to inform future studies of drug-related AP pathogenesis.

Severe complications in the induction phase of therapy in a pediatric patient with T-cell acute lymphoblastic leukemia: A case report

RATIONALE

Acute lymphoblastic leukemia (ALL) represents approximately 1-quarter of all new cases of childhood cancer. Although overall survival following diagnosis has improved in recent years, the toxicity of chemotherapy remains a concern.

PATIENT CONCERNS

We describe an 11-year-old male patient diagnosed with T-cell precursor ALL who developed compounded complications during the induction phase of chemotherapy. Patient was hospitalized in the Department of Pediatric Hematology, Oncology, and Transplantology of the Medical University of Lublin, Poland. The patient's induction therapy was started according to the AIEOP-BFM ALL 2017 protocol IAp (International Collaborative Treatment Protocol for Children and Adolescents with Acute Lymphoblastic Leukemia).

DIAGNOSES

Patient developed compounded complications such as cholecystitis, hepatotoxicity, pancreatitis and myelosuppression.

INTERVENTIONS

The patient was treated with leukapheresis, received a broad-spectrum antibiotic, potassium supplementation and hepatoprotective treatment and laparotomy cholecystectomy.

OUTCOMES

In the available literature, there is a limited amount of similar clinical cases with multiple complications in pediatric patients with ALL. Toxicities cause delays in the treatment of the underlying disease.

LESSONS

In children with acute lymphoblastic leukemia, there are side effects during the treatment such as cholecystitis and pancreatitis. Complications during treatment require a quick response and modification of disease management. Abdominal ultrasound performed before treatment makes it possible to observe the dynamics of lesions. Genetic mutation analysis could allow us to more precisely respond to the possible susceptibility to and appearance of complications after the use of a given chemotherapeutic agent.

Prediction of chemotherapy-related complications in pediatric oncology patients: artificial intelligence and machine learning implementations

Although the overall incidence of pediatric oncological diseases tends to increase over the years, it is among the rare diseases of the pediatric population. The diagnosis, treatment, and healthcare management of this group of diseases are important. Prevention of treatment-related complications is vital for patients, particularly in the pediatric population. Nowadays, the use of artificial intelligence and machine learning technologies in the management of oncological diseases is becoming increasingly important. With the advancement of software technologies, improvements have been made in the early diagnosis of risk groups in oncological diseases, in radiology, pathology, and imaging technologies, in cancer staging and management. In addition, these technologies can be used to predict the outcome in chemotherapy treatment of oncological diseases. In this context, this study identifies artificial intelligence and machine learning methods used in the prediction of complications due to chemotherapeutic agents used in childhood cancer treatment. For this purpose, the concepts of artificial intelligence and machine learning are explained in this review. A general framework for the use of machine learning in healthcare and pediatric oncology has been drawn and examples of studies conducted on this topic in pediatric oncology have been given. IMPACT: Artificial intelligence and machine learning are advanced tools that can be used to predict chemotherapy-related complications. Algorithms can assist clinicians' decision-making processes in the management of complications. Although studies are using these methods, there is a need to increase the number of studies on artificial intelligence applications in pediatric clinics.

The Effect of Chemotherapy Induction Therapy on the Pancreas in Patients with Acute Lymphoblastic Leukemia

Background

The effect of chemotherapy induction on the pancreatic in patients with acute lymphoblastic leukemia is not described in Ethiopia. The study determined the chemotherapy drug-induced pancreatitis in patients with acute lymphoblastic leukemia.

Method

A preexperimental study (pretest and posttests) was conducted in forty patients with acute lymphoblastic leukemia. For some skewed data, a log transformation was computed. The back transformation was then calculated. Descriptive statistics and a mixed-model ANOVA were used to analyze the data. A post hoc Bonferroni test was used. A p value < 0.05 was declared statistically significant.

Results

In this study, no clinically significant acute pancreatitis occurred. Elevated amylase and lipase levels, indicating grade 2 acute pancreatitis, were observed in 25% and 17.5% of patients, respectively. Amylase enzyme levels in children differed significantly from preinduction to the second week of induction (p = 0.001) and fourth week of induction (p = 0.001), as well as between the second and fourth weeks of induction (p = 0.033), but adults' amylase enzyme levels did not differ significantly (p = 0.2). Lipase levels in adults are nearly identical in all three measures, implying that there is no statistically significant difference (p = 0.775). However, the level of lipase enzyme in children was significantly higher from baseline to two and four weeks of induction (p = 0.007) but not between two and four weeks of induction (p = 0.129).

Conclusion

Clinically significant acute pancreatitis did not occur, but patients experienced mild (grade 2) acute pancreatitis. Amylase and lipase enzymes responded significantly to chemotherapy induction in children. Chemotherapy drugs should be given without altering pancreatic enzymes, specifically in children.

Case Report: Genetic Analysis of PEG-Asparaginase Induced Severe Hypertriglyceridemia in an Adult With Acute Lymphoblastic Leukaemia

PEG-Asparaginase (also known as Pegaspargase), along with glucocorticoids (predominantly prednisolone or dexamethasone) and other chemotherapeutic agents (such as cyclophosphamide, idarubicin, vincristine, cytarabine, methotrexate and 6-mercaptopurine) is the current standard treatment for acute lymphoblastic leukaemia in both children and adults. High doses of PEG-asparaginase are associated with side effects such as hepatotoxicity, pancreatitis, venous thrombosis, hypersensitivity reactions against the drug and severe hypertriglyceridemia. We report a case of a 28-year-old male who was normolipidemic at baseline and developed severe hypertriglyceridemia (triglycerides of 1793 mg/dl) following treatment with PEG-asparaginase for acute lymphoblastic leukaemia. Thorough genetic analysis was conducted to assess whether genetic variants could suggest a predisposition to this drug-induced metabolic condition. This genetic analysis showed the presence of a rare heterozygous missense variant c.11G > A-p.(Arg4Gln) in the APOC3 gene, classified as a variant of uncertain significance, as well as its association with four common single nucleotide polymorphisms (SNPs; c.*40C > G in APOC3 and c.*158T > C; c.162-43G > A; c.-3A > G in APOA5) related to increased plasma triglyceride levels. To our knowledge this is the first case that a rare genetic variant associated to SNPs has been related to the onset of severe drug-induced hypertriglyceridemia.