Safety of medications for hereditary angioedema during pregnancy and lactation

INTRODUCTION

Hereditary Angioedema (HAE) attacks show an increased frequency and severity for pregnant and lactating females secondary to the hormonal changes. The diagnosis and management of HAE in pregnant and lactating females pose a challenge for physicians due to the rarity of the disease and the paucity of the data for specific management.

AREAS COVERED

In this manuscript, we discuss the diagnosis and special presentation of HAE types 1 and 2 in pregnant and lactating females, including acute management, short-term prophylaxis, long-term prophylaxis, and drugs that should be avoided. Relevant publications were found through key word search of papers indexed in both Google Scholar and PubMed on 1 July 2022.

EXPERT OPINION

Treatment of HAE in the past has been mainly provided by experts; however, with more medications and an increasing number of patients, knowledge of how to care for HAE patients during pregnancy and lactation is important to review. Despite approval of additional medications in many countries, plasma-derived C1-inhibitor remains the drug of first choice for treatment in this unique population. Additional research is needed to increase safe access to other therapy options. We hope that future clinical studies, registries, and databases will shed additional light on this subject.

Retrospective comparative effectiveness research: will changing the analytical methods change the results?

In medicine, retrospective cohort studies are used to compare treatments to one another. We hypothesize that the outcomes of retrospective comparative effectiveness research studies can be heavily influenced by biostatistical analytic choices, thereby leading to inconsistent conclusions. We selected a clinical scenario currently under investigation: survival in metastatic prostate, breast, or lung cancer after systemic vs systemic + definitive local therapy. We ran >300 000 regression models (each representing a publishable study). Each model had various forms of analytic choices (to account for bias): propensity score matching, left truncation adjustment, landmark analysis, and covariate combinations. There were 72 549 lung, 14 904 prostate, and 13 857 breast cancer patients included. In the most basic analysis, which omitted propensity score matching, left truncation adjustment, and landmark analysis, all of the HRs were < 1 (generally, 0.60-0.95, favoring addition of local therapy), with all P-values < 0.001. Left truncation adjustment landmark analysis produced results with non-significant P-values. The combination of propensity score matching, left truncation adjustment, landmark analysis, and covariate combinations generally produced P-values that were > 0.05 and/or HRs that were > 1 (favoring systemic therapy alone). The use of more statistical methods to reduce the selection bias caused reported HR ranges to approach 1.0. By varying analytic choices in comparative effectiveness research, we generated contrary outcomes. Our results suggest that some retrospective observational studies may find a treatment improves outcomes for patients, while another similar study may find it does not, simply based on analytical choices. This article is protected by copyright. All rights reserved.