All content on this site is intended for healthcare professionals only. By acknowledging this message and accessing the information on this website you are confirming that you are a Healthcare Professional. If you are a patient or carer, please visit the International Myeloma Foundation or HealthTree for Multiple Myeloma.

  TRANSLATE

The mm Hub website uses a third-party service provided by Google that dynamically translates web content. Translations are machine generated, so may not be an exact or complete translation, and the mm Hub cannot guarantee the accuracy of translated content. The mm and its employees will not be liable for any direct, indirect, or consequential damages (even if foreseeable) resulting from use of the Google Translate feature. For further support with Google Translate, visit Google Translate Help.

The Multiple Myeloma Hub is an independent medical education platform, sponsored by Bristol Myers Squibb, GSK, Legend Biotech, Pfizer, and Roche. Funders are allowed no direct influence on our content. The levels of sponsorship listed are reflective of the amount of funding given. View funders.

Now you can support HCPs in making informed decisions for their patients

Your contribution helps us continuously deliver expertly curated content to HCPs worldwide. You will also have the opportunity to make a content suggestion for consideration and receive updates on the impact contributions are making to our content.

Find out more

How can we better predict early relapse in multiple myeloma?

By Jennifer Reilly

Share:

Featured:

Meral BeksaçMeral Beksaç

Aug 11, 2023

Learning objective: After reading this article, learners will be able to cite a new clinical development in multiple myeloma.


The Multiple Myeloma Hub was pleased to speak to Meral Beksac, Ankara University, Ankara, TR. We asked, How can we better predict early relapse in multiple myeloma (MM)?

How can we better predict early relapse in multiple myeloma?

In this video, Beksac presents their recent research paper on the predictors of post-transplant early relapse in MM, highlighting the development of a novel risk scoring tool: the EBMT ER score.1

Beksac discusses key prognostic factors including age, sex, disease status, International Staging System score, and Karnofsky score by their impact on relapse. Moving forward, Beksac summarizes how the combination of these factors by individual was used to stratify patients into five subgroups, which may better predict the risk of early relapse after transplantation in MM.1

References

Please indicate your level of agreement with the following statements:

The content was clear and easy to understand

The content addressed the learning objectives

The content was relevant to my practice

I will change my clinical practice as a result of this content

Your opinion matters

On average, how many patients with MGUS/smoldering MM do you see in a month?