A case of allopurinol-induced fixed drug eruption confirmed with a lymphocyte transformation test

Fixed Drug Eruptions With Flavoured Liquid Formulations of Over-the-Counter Analgesics: A Case Report

Type 4 hypersensitivity reactions convey a number of conditions that include fixed drug eruptions (FDEs). They share similar pathophysiologic backgrounds and sometimes presentation but can have very variable prognostications. Drugs are amongst the possible causes with acetaminophen and other NSAIDs being reported very frequently. We present a case of a patient reacting to flavoured oral ibuprofen and acetaminophen formulations, exhibiting FDEs with bullae formation. We describe our successful challenge to non-flavoured acetaminophen and ibuprofen. We briefly discuss FDEs in regard to their incidence, pathophysiology, and management.

A Review of Fixed Drug Eruption with a Special Focus on Generalized Bullous Fixed Drug Eruption

Fixed drug eruption (FDE) is a cutaneous adverse drug reaction characterized by the onset of rash at a fixed location on the body each time a specific medication is ingested. With each recurrence, the eruption can involve additional sites. Lesions can have overlying vesicles and/or bullae, and when they cover a significant percentage of body surface area, the eruption is referred to as generalized bullous fixed drug eruption (GBFDE). Due to the widespread skin denudation that can be seen in this condition, GBFDE may be confused clinically with Stevens-Johnson syndrome/toxic epidermal necrolysis (SJS/TEN). While treatments described for GBFDE include supportive care, topical and/or systemic steroids, and, recently, cyclosporine, the mainstay of management involves identifying and discontinuing the causative drug. This review article will provide an overview of FDE with an emphasis on its generalized bullous variant.

Fixed Drug Eruptions: An Update, Emphasizing the Potentially Lethal Generalized Bullous Fixed Drug Eruption

A fixed drug eruption (FDE) is a relatively common reaction associated with more than 100 medications. It is defined as a same-site recurrence with exposure to a particular medication. The primary approach and treatment for all types of FDEs are to identify and remove the causative agent, often accomplished by a thorough history of medication and other chemical exposures, and possibly prior episodes. The most common category of FDE, localized FDE, whether bullous or non-bullous, is self-limited. Although one can confirm the causative agent using oral challenge testing, it is not recommended due to the risk of severe exacerbation or possible generalization; patch testing is now preferred. Bullous FDE may resemble erythema multiforme. Treatment of localized FDE includes medication removal, patient counseling, and symptomatic relief. Failure to remove the causative agent in localized FDE can lead to recurrence, which is associated with increased inflammation, hyperpigmentation, and risk of a potentially lethal generalized bullous FDE (GBFDE), which may resemble Stevens-Johnson syndrome (SJS) or toxic epidermal necrolysis (TEN). Distinguishing GBFDE from SJS and TEN is salient and will be stressed: GBFDE has more rapid onset in 1-24 h rather than in weeks, less or no mucosal involvement, less or no systemic involvement, and a tendency for a more favorable prognosis; however, recent experience suggests it may be just as life-threatening. This review will provide a comprehensive update and approach to diagnosis and management.

Inverse similarity and reliable negative samples for drug side-effect prediction

BACKGROUND

In silico prediction of potential drug side-effects is of crucial importance for drug development, since wet experimental identification of drug side-effects is expensive and time-consuming. Existing computational methods mainly focus on leveraging validated drug side-effect relations for the prediction. The performance is severely impeded by the lack of reliable negative training data. Thus, a method to select reliable negative samples becomes vital in the performance improvement.

METHODS

Most of the existing computational prediction methods are essentially based on the assumption that similar drugs are inclined to share the same side-effects, which has given rise to remarkable performance. It is also rational to assume an inverse proposition that dissimilar drugs are less likely to share the same side-effects. Based on this inverse similarity hypothesis, we proposed a novel method to select highly-reliable negative samples for side-effect prediction. The first step of our method is to build a drug similarity integration framework to measure the similarity between drugs from different perspectives. This step integrates drug chemical structures, drug target proteins, drug substituents, and drug therapeutic information as features into a unified framework. Then, a similarity score between each candidate negative drug and validated positive drugs is calculated using the similarity integration framework. Those candidate negative drugs with lower similarity scores are preferentially selected as negative samples. Finally, both the validated positive drugs and the selected highly-reliable negative samples are used for predictions.

RESULTS

The performance of the proposed method was evaluated on simulative side-effect prediction of 917 DrugBank drugs, comparing with four machine-learning algorithms. Extensive experiments show that the drug similarity integration framework has superior capability in capturing drug features, achieving much better performance than those based on a single type of drug property. Besides, the four machine-learning algorithms achieved significant improvement in macro-averaging F1-score (e.g., SVM from 0.655 to 0.898), macro-averaging precision (e.g., RBF from 0.592 to 0.828) and macro-averaging recall (e.g., KNN from 0.651 to 0.772) complimentarily attributed to the highly-reliable negative samples selected by the proposed method.

CONCLUSIONS

The results suggest that the inverse similarity hypothesis and the integration of different drug properties are valuable for side-effect prediction. The selection of highly-reliable negative samples can also make significant contributions to the performance improvement.

Allopurinol-induced severe cutaneous adverse reactions: A report of three cases with the HLA-B*58:01 allele who underwent lymphocyte activation test

Allopurinol-induced severe cutaneous adverse reactions (SCARs) such as Stevens-Johnson syndrome (SJS), toxic epidermal necrolysis (TEN), and drug reaction with eosinophilia and systemic symptoms (DRESS) syndrome are reportedly associated with the HLA-B^*58:01 genotype. Three patients who developed SCARs after allopurinol administration were subjected to HLA-B genotyping and lymphocyte activation test (LAT) to evaluate genetic risk and to detect the causative agent, respectively. All three patients given allopurinol to treat gout were diagnosed with DRESS syndrome. Symptom onset commenced 7-24 days after drug exposure; the patients took allopurinol (100-200 mg/d) for 2-30 days. HLA-B genotyping was performed using a polymerase chain reaction (PCR)-sequence-based typing (SBT) method. All patients had a single HLA-B^*58:01 allele: HLA-B^*13:02/^*58:01 (a 63-year-old male), HLA-B^*48:01/^*58:01 (a 71-year-old female), and HLA-B^*44:03/^*58:01 (a 22-year-old male). Only the last patient yielded a positive LAT result, confirming that allopurinol was the causative agent. These findings suggest that patients with HLA-B^*58:01 may develop SCARs upon allopurinol administration. Therefore, HLA-B genotyping could be helpful in preventing serious problems attributable to allopurinol treatment, although PCR-SBT HLA-B genotyping is time consuming. A simple genotyping test is required in practice. LAT may help to identify a causative agent.

A Case of Dasatinib-Induced Hemorrhagic Colitis Diagnosed by the Lymphocyte Transformation Test in a Chronic Myeloid Leukemia Patient

Dasatinib is an effective treatment option for patients diagnosed with Philadelphia chromosome positive chronic myeloid leukemia and who are non-responsive or intolerant to imatinib treatment. Dasatinib, however, is associated with various adverse effects and on rare occasions, may cause hemorrhagic colitis. We report the case of a 68-year-old male patient with dasatinib-induced hemorrhagic colitis, the first such case in Korea. Endoscopic biopsy of the transverse colon demonstrated non-specific inflammatory changes only. Cessation of dasatinib led to the resolution of symptoms, while reintroduction of the therapy led to the recurrence of his bloody diarrhea. To clarify the association between dasatinib and hemorrhagic colitis, the lymphocyte transformation test (LTT) was performed. The LTT result sustained a relatively high proliferation activity in the affected patient compared with almost no proliferation activity in normal control.

A case of fixed drug eruption due to doxycycline and erythromycin present in food

A fixed drug eruption (FDE) is not difficult to diagnose, given its clinical characteristics. However, the causative agent can be difficult to identify, particularly when the patient denies ingestion of any drugs. To the best of our knowledge, we present herein the first reported case of an FDE caused by antibiotics taken in food; doxycycline and erythromycin contained in pork and fish. A 57-year-old female experienced repeated episodes of well-demarcated erythematous patches covering her entire body. She denied taking any medications, but she thought that the lesions appeared after consuming pork and/or fish. An oral provocation test showed positive results for doxycycline and erythromycin, commonly used antibiotics in live-stock farming and in the fishing industry. Because of the antibiotics' thermostability, cooking does not guarantee the elimination of residual drugs. From the patient's history, we concluded that doxycycline and erythromycin contained in the pork and fish that she ate were the cause of the FDE.