Acute Pancreatitis in a Patient Treated with Micafungin

Drug-Induced Acute Pancreatitis: An Evidence-Based Classification (Revised)

INTRODUCTION

Drug induced acute pancreatitis is a difficult diagnosis for clinicians. We previously published an "Evidence-Based Classification System" on Drug-Induced Acute Pancreatitis widely used by clinicians to assist in the identification of drugs. Unfortunately, this prior analysis based only on published case reports has been misunderstood. The prior review did not include studies with higher evidentiary value, such as randomized trials, case-control studies, and/or pharmacoepidemiologic studies. The use of the prior classification system has led to many patients being inappropriately labeled as having drug-induced acute pancreatitis. We now propose a "Revised" Evidence- Based Classification System for the purpose of determining which drugs cause acute pancreatitis based on the Grading of Recommendations, Development, and Evaluation criteria.

METHODS

A search of the English Language literature was performed to identify all case reports with medication and/or drug induced acute pancreatitis. We divided the drugs implicated as causing acute pancreatitis into four groups based on the quality of evidence as defined by GRADE quality parameters.

RESULTS

Although 141 drugs were identified in the literature as causing acute pancreatitis, only 106 drugs published in the literature as causing acute pancreatitis were high quality case reports. Only 3 drugs had evidence as causing acute pancreatitis from randomized controlled clinical trials, including 6-mercaptopurine and azathioprine.

DISCUSSION

The vast majority of drugs implicated as causing acute pancreatitis in the literature have low or very low quality of evidence supporting those claims.

Drug induced pancreatitis: A systematic review of case reports to determine potential drug associations

OBJECTIVE

A current assessment of case reports of possible drug-induced pancreatitis is needed. We systematically reviewed the case report literature to identify drugs with potential associations with acute pancreatitis and the burden of evidence supporting these associations.

METHODS

A protocol was developed a priori (PROSPERO CRD42017060473). We searched MEDLINE, Embase, the Cochrane Library, and additional sources to identify cases of drug-induced pancreatitis that met accepted diagnostic criteria of acute pancreatitis. Cases caused by multiple drugs or combination therapy were excluded. Established systematic review methods were used for screening and data extraction. A classification system for associated drugs was developed a priori based upon the number of cases, re-challenge, exclusion of non-drug causes of acute pancreatitis, and consistency of latency.

RESULTS

Seven-hundred and thirteen cases of potential drug-induced pancreatitis were identified, implicating 213 unique drugs. The evidence base was poor: exclusion of non-drug causes of acute pancreatitis was incomplete or poorly reported in all cases, 47% had at least one underlying condition predisposing to acute pancreatitis, and causality assessment was not conducted in 81%. Forty-five drugs (21%) were classified as having the highest level of evidence regarding their association with acute pancreatitis; causality was deemed to be probable or definite for 19 of these drugs (42%). Fifty-seven drugs (27%) had the lowest level of evidence regarding an association with acute pancreatitis, being implicated in single case reports, without exclusion of other causes of acute pancreatitis.

DISCUSSION

Much of the case report evidence upon which drug-induced pancreatitis associations are based is tenuous. A greater emphasis on exclusion of all non-drug causes of acute pancreatitis and on quality reporting would improve the evidence base. It should be recognized that reviews of case reports, are valuable scoping tools but have limited strength to establish drug-induced pancreatitis associations.

REGISTRATION

CRD42017060473.

Enhancing adverse drug event detection in electronic health records using molecular structure similarity: application to pancreatitis

Background

Adverse drug events (ADEs) detection and assessment is at the center of pharmacovigilance. Data mining of systems, such as FDA’s Adverse Event Reporting System (AERS) and more recently, Electronic Health Records (EHRs), can aid in the automatic detection and analysis of ADEs. Although different data mining approaches have been shown to be valuable, it is still crucial to improve the quality of the generated signals.

Objective

To leverage structural similarity by developing molecular fingerprint-based models (MFBMs) to strengthen ADE signals generated from EHR data.

Methods

A reference standard of drugs known to be causally associated with the adverse event pancreatitis was used to create a MFBM. Electronic Health Records (EHRs) from the New York Presbyterian Hospital were mined to generate structured data. Disproportionality Analysis (DPA) was applied to the data, and 278 possible signals related to the ADE pancreatitis were detected. Candidate drugs associated with these signals were then assessed using the MFBM to find the most promising candidates based on structural similarity.

Results

The use of MFBM as a means to strengthen or prioritize signals generated from the EHR significantly improved the detection accuracy of ADEs related to pancreatitis. MFBM also highlights the etiology of the ADE by identifying structurally similar drugs, which could follow a similar mechanism of action.

Conclusion

The method proposed in this paper provides evidence of being a promising adjunct to existing automated ADE detection and analysis approaches.

Endocrine and metabolic manifestations of invasive fungal infections and systemic antifungal treatment

Systemic fungal infections are increasingly reported in immunocompromised patients with hematological malignancies, recipients of bone marrow and solid organ allografts, and patients with AIDS. Mycoses may infiltrate endocrine organs and adversely affect their function or produce metabolic complications, such as hypopituitarism, hyperthyroidism or hypothyroidism, pancreatitis, hypoadrenalism, hypogonadism, hypernatremia or hyponatremia, and hypercalcemia. Antifungal agents used for prophylaxis and/or treatment of mycoses also have adverse endocrine and metabolic effects, including hypoadrenalism, hypogonadism, hypoglycemia, dyslipidemia, hypernatremia, hypocalcemia, hyperphosphatemia, hyperkalemia or hypokalemia, and hypomagnesemia. Herein, we review how mycoses and conventional systemic antifungal treatment can affect the endocrine system and cause metabolic abnormalities. If clinicians are equipped with better knowledge of the endocrine and metabolic complications of fungal infections and antifungal therapy, they can more readily recognize them and favorably affect outcome.