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Response to: Correspondence on 'Cardiovascular toxicities associated with bispecific T-cell engager therapy' by Noguchi et al
  1. Ahmed Sayed1,
  2. Malak Munir1,
  3. Michael Poliner2,
  4. Sana Sughra2,
  5. Narendranath Epperla3 and
  6. Daniel Addison4,5
  1. 1Ain Shams University Faculty of Medicine, Cairo, Egypt
  2. 2The Ohio State University Medical Center, Columbus, Ohio, USA
  3. 3The Ohio State University, Columbus, Ohio, USA
  4. 4Cardio-Oncology Program, Division of Cardiology, The Ohio State University Wexner Medical Center, Columbus, Ohio, USA
  5. 5Division of Cancer Control and Prevention, The Ohio State University James Cancer Hospital, Columbus, Ohio, USA
  1. Correspondence to Dr Daniel Addison; daniel.addison{at}

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We would like to thank Dr Noguchi and his colleagues for their comments regarding our paper Cardiovascular toxicities associated with bispecific T-cell engager therapy. We agree that our analysis using the Food and Drug Administration Adverse Event Reporting System (FAERS) database is subject to several limitations, some of which are inherent to pharmacovigilance analyses in general and some of which are unique to FAERS. However, we believe some of the stated concerns may not majorly impact our analysis. The concerns raised by Noguchi and his colleagues can be organized into four main categories: (1) representativeness (or lack thereof), (2) factors affecting reporting rates (ripple effect, Weber effect, and notoriety bias), (3) the consideration of an overall bispecific T-cell engager (BTE) category (which may overlook intraclass differences), and (4) timing of onset in relation to approval date.

With respect to representativeness, we agree that more geographically diverse analyses would help shed further light on the cardiovascular adverse events (CVAEs) associated with BTEs. For example, some previously-approved drugs have adverse events that are more likely to affect certain populations due to genetic variants affecting drug metabolism.1 In this regard, if such variation also affects BTE-related CVAEs, then some of the adverse events examined in our analysis may be underestimated or overestimated.

However, it is important to note that there are structural barriers that impede the uniform reporting of adverse events across the world. Many resource-poor settings may not have access to the drug of interest (BTEs) at all because of their expense. Furthermore, they may not have routine access to advanced imaging that may be diagnostically helpful or necessary for certain CVAEs (eg, MRI for myocarditis).2 3 Lastly, even if both BTEs and the appropriate diagnostic apparatus to detect their CVAEs are present, some places may not have well-established reporting mechanisms. These factors result in non-uniform reporting of CVAEs that over-represents high-resource settings and under-represents low-resource settings. Going forward, improving access to newer therapies and reporting standards across the globe will be necessary to ensure that analyses can detect geographic differences in susceptibility to CVAEs.

The second limitation pertains to factors which affect reporting rates, including the ripple effect, the Weber effect, and notoriety bias. The ripple effect refers to an adverse events signal found with one member of a class that subsequently results in an over-reporting of the same adverse event with all other members of that class. However, in our analysis, we did not find adverse event signals that were shared uniformly across all BTEs. As such, the ripple effect was not a relevant bias to consider in the present study.

The Weber effect refers to a pattern of reporting wherein adverse event reports peak during the second year of drug approval and decline thereafter. However, a study of 62 Food and Drug Administration (FDA)-approved drugs did not find that such a pattern was evident across most drugs.4 Further, an analysis of oncology drugs specifically did not find clear evidence of the Weber effect for most examined drugs.5 In addition, it is not clear that such a pattern would necessarily induce bias, as pharmacovigilance analyses consider the proportion of specific adverse events rather than their sheer number.

Notoriety bias refers to an over-reporting of a specific adverse event with a particular drug due to an external stimulus (such as media attention or a warning from a regulatory agency). However, to our knowledge, none of the CVAEs examined herein were subject to such a stimulus for BTEs. Further, a report of 100 drugs approved by the FDA did not show that alerts had a significant impact on reporting rates, casting doubt on this effect.6

The third limitation raised refers to our consideration of a ‘class-effect’ (by including an overall BTE category) despite the possibility that important differences may exist between different BTEs. However, it is important to note two points. First, it is only possible to say this in hindsight (ie, after it has been shown that different BTEs have distinct side effects rather than shared class side effects). Because little data preceded our report, we did not have adequate grounds to disregard class-effects a priori. As such, it was reasonable in our opinion to conduct an analysis considering BTEs as an overall category (though we understand this will primarily be driven by blinatumomab as it is the BTE with the most reports). Second, it is important to note that we present analyses restricted to individual BTEs precisely for this possibility. Indeed, an important finding of our analysis was a possible signal of myocarditis with teclistamab specifically.

The fourth presented critique refers to the latter approval dates for certain BTEs rendering long-term follow-up impossible (because not enough time has passed since approval) for these BTE products. Thus, adverse events occurring at longer follow-up periods will most likely be those that are reported with BTEs that have been approved for longer (namely blinatumomab). We agree that this is an important limitation that requires longer follow-up data across different BTEs to remedy.

In summary, we thank the authors for their insightful comments on our work. Noguchi and colleagues present several important methodological points related to pharmacovigilance analyses, which future researchers would do well to consider. Some points constitute important limitations that will require more long-term data to remedy (such as long-term follow-up data with a more diverse array of BTE products) and more diverse sources of data (such as the lack of geographic representativeness of our analyses). However, others (such as the Weber effect, the ripple effect, and notoriety bias) are not very likely to significantly change our findings. As with all pharmacovigilance studies, our findings should be interpreted as a signal for possible adverse events and serve to encourage further validation and clinical vigilance.

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The manuscript’s content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.



  • X @ahmed_sayed_98, @NEpperla

  • Contributors AS and MM wrote the original draft of this response letter. DA, NE, MP, and SS provided substantive reviews, comments, and edits to the original draft.

  • Funding This work was supported in part by an NIH P50-CA140158 grant. DA is supported by NIH grant numbers K23-HL155890, R01HL168045 and R01HL170038, and an American Heart Association‐Robert Wood Johnson Foundation (Harold Amos) grant. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.

  • Provenance and peer review Not commissioned; internally peer reviewed.

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