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Related Concept Videos

Gene Therapy00:59

Gene Therapy

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Gene therapy is a technique where a gene is inserted into a person’s cells to prevent or treat a serious disease. The added gene may be a healthy version of the gene that is mutated in the patient, or it could be a different gene that inactivates or compensates for the patient’s disease-causing gene. For example, in patients with severe combined immunodeficiency (SCID) due to a mutation in the gene for the enzyme adenosine deaminase, a functioning version of the gene can be...
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Selecting β-thalassemia Patients for Gene Therapy: A Decision-making Algorithm.

Donatella Baronciani1, Maddalena Casale2, Lucia De Franceschi3

  • 1UOC Immunoematologia e Trasfusionale, AORMN, Pesaro-Fano, Italy.

Hemasphere
|May 10, 2021
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Summary

This expert opinion provides a decision-making algorithm to identify transfusion-dependent beta-thalassemia (TDT) patients who may benefit from gene therapy (GT). It prioritizes GT for suitable candidates, considering factors like prior treatment and clinical condition for optimal outcomes.

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Area of Science:

  • Hematology
  • Medical Genetics
  • Clinical Decision-Making

Background:

  • Gene therapy (GT) presents a new treatment paradigm for transfusion-dependent beta-thalassemia (TDT).
  • Allogeneic hematopoietic stem-cell transplantation (HSCT) is an established curative option for TDT.
  • Establishing priority indications for GT is crucial due to its current limitations in availability, cost, and resources.

Purpose of the Study:

  • To develop a priority decision-making algorithm for identifying TDT patients suitable for gene therapy (GT).
  • To guide the rational and progressive adoption of innovative GT treatments in clinical practice.
  • To leverage experience from allogeneic HSCT as a predictive model for GT indications.

Main Methods:

  • Expert opinion developed by the Italian Society of Thalassemias and Hemoglobinopathies (SITE).
  • Reviewed and adopted by the European Hematology Association (EHA) Scientific Working Group on Red Cells and Iron.
  • Algorithm development based on evidence, consensus, and predictive modeling using HSCT outcomes.

Main Results:

  • The algorithm considers various clinical scenarios and their impact on treatment outcomes.
  • Optimal pre-transplant transfusion and chelation therapy are key predictors of successful HSCT outcomes.
  • The algorithm aims to prioritize GT for TDT patients based on evidence and clinical condition.

Conclusions:

  • This expert opinion provides dynamic, updatable, priority-based indications for physicians managing TDT patients.
  • The algorithm serves as a guide for the rational and progressive use of gene therapy in TDT.
  • Physicians should consider patient clinical condition and prior therapies when evaluating GT suitability.