Narrative review explores immune monitoring for relapse prediction after AML stem cell transplantCan better immune monitoring help predict relapse in leukemia patients after stem cell transplants?

Frontiers in Medicine Published April 15, 2026 DOI ↗ Editorial oversight: Dr. Amelia Tan, PhD · Internal Medicine & Chronic Disease

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Key Takeaway

Consider immune monitoring for relapse prediction in AML post-transplant, but evidence is evolving.

This publication is a narrative review focusing on immune monitoring methodologies for predicting relapse in patients with acute myeloid leukemia following allogeneic hematopoietic stem cell transplantation. It covers techniques such as multiparameter flow cytometry, measurable residual disease assessment, immune repertoire analysis, and omics-based approaches, aiming to synthesize their roles in risk stratification and relapse prediction. The review does not report specific study populations, sample sizes, interventions, comparators, or quantitative effect sizes, as it is not a primary trial or meta-analysis.

The authors argue that expanding immune monitoring beyond conventional parameters toward integrated, multidimensional approaches is essential for improving relapse prediction, personalizing post-transplant management, and enhancing long-term outcomes. They emphasize the potential of these methodologies to refine clinical decision-making, but note that the evidence is synthesized from existing literature without new experimental data. No pooled effect sizes, p-values, or confidence intervals are provided, as this is a qualitative synthesis rather than a quantitative analysis.

Limitations are not explicitly detailed in the input, but as a narrative review, it may lack systematic search methods or formal quality assessment of included studies. The practice relevance suggests that clinicians should consider these approaches for better risk stratification, but implementation should be cautious due to the early and evolving nature of the evidence. This review serves as a conceptual framework rather than a definitive guideline, highlighting gaps in current monitoring strategies without providing specific safety data or adverse event reports.

Imagine a patient who has just received a stem cell transplant to treat acute myeloid leukemia. They are hoping for a cure, but the risk of the cancer returning remains. Doctors need to know exactly when that risk is highest so they can act quickly. This review looks at whether new ways of checking the immune system can give that warning earlier than usual tests.

The study examined various immune monitoring techniques, including multiparameter flow cytometry and omics-based approaches. These tools aim to look deeper than standard checks to spot early signs of the disease coming back. The goal is to predict relapse and sort patients into different risk groups so treatment can be tailored to their specific needs.

While the potential to improve long-term outcomes is clear, this evidence comes from reviewing past work, not a single large experiment. The review calls for moving beyond simple checks to more complex, integrated methods. Until more direct evidence is available, these advanced tools remain a promising direction for the future rather than a current standard of care.

What this means for you:

New immune monitoring methods could predict leukemia relapse better, but more direct evidence is needed before they are standard.

Study Details

Study typeSystematic review

EvidenceLevel 1

PublishedApr 2026

View Original Abstract ↓

Relapse remain the leading cause of treatment failure after allogeneic hematopoietic stem cell transplantation (allo-HSCT) in patients with acute myeloid leukemia (AML), despite substantial advances in transplant strategies and supportive care. The dynamics of immune reconstitution (IR) critically determine post-transplant outcomes by shaping the balance between graft-versus-leukemia (GvL) effects, graft-versus-host disease (GvHD), infectious complications, and leukemic immune escape. Importantly, IR is not limited to numerical recovery of immune cells but represents a multidimensional and temporally organized process encompassing quantitative, qualitative, and functional immune restoration. In this review, we provide an integrated clinical laboratory–oriented framework for immune monitoring (IM) after allo-HSCT, with a specific focus on relapse prediction and risk stratification in AML. We discuss the sequential kinetics of innate and adaptive immune recovery, key cellular subsets influencing GvL efficacy, and the impact of transplant-related factors, immunosuppression, and viral reactivations on IR trajectories. Particular emphasis is placed on functional immune states, including T-cell exhaustion, anergy, and senescence, as measurable laboratory correlates of impaired immune surveillance and impending relapse. We further outline current IM methodologies used in routine and advanced clinical laboratories, including multiparameter flow cytometry, measurable residual disease (MRD) assessment, immune repertoire analysis, and emerging omics-based approaches. By integrating immunophenotypic, molecular, and functional data, IM enables earlier detection of relapse-associated immune dysfunction and supports preemptive, risk-adapted therapeutic interventions such as donor lymphocyte infusion or immunomodulatory strategies. Overall, this review highlights the pivotal role of comprehensive, longitudinal immune monitoring in translating complex immunological data into clinically actionable insights. Expanding IM beyond conventional parameters toward integrated, multidimensional approaches is essential for improving relapse prediction, personalizing post-transplant management, and ultimately enhancing long-term outcomes in AML patients undergoing allo-HSCT.

Narrative review explores immune monitoring for relapse prediction after AML stem cell transplantCan better immune monitoring help predict relapse in leukemia patients after stem cell transplants?

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Narrative review explores immune monitoring for relapse prediction after AML stem cell transplantCan better immune monitoring help predict relapse in leukemia patients after stem cell transplants?

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