Monocyte engraftment dynamics and flow cytometric analysis in allogeneic and autologous peripheral blood stem cell transplantation: a prospective study.

Introduction

Hematopoietic stem cell transplantation (HSCT) represents the cornerstone of curative therapy for various hematologic malignancies and non-malignant disorders. The success of HSCT fundamentally depends on the timely engraftment of donor-derived hematopoietic cells, which reconstitute the recipient’s immune and hematopoietic systems [ 1 ]. While neutrophil and platelet engraftment have been extensively studied and serve as standard markers of transplant success, the dynamics of monocyte engraftment and its relationship with other hematopoietic lineages remain less well characterized [ 2 ].

Recent advances in flow cytometry and cellular immunophenotyping have provided new insights into the complex process of hematopoietic reconstitution following HSCT [ 3 , 4 ]. Monocytes, as key effector cells of the innate immune system, play crucial roles in tissue homeostasis, inflammation, and immune surveillance [ 5 ]. The reconstitution of monocyte populations following HSCT is particularly important given their role in preventing opportunistic infections and facilitating tissue repair [ 6 ].

Studies have demonstrated that monocyte subsets, characterized by differential expression of CD14 and CD16 surface markers, exhibit distinct functional properties and kinetics during hematopoietic recovery [ 7 ]. Human monocytes are subdivided into classical (CD14 + + CD16−), intermediate (CD14 + + CD16+), and non-classical (CD14 + CD16++) subsets, which exhibit distinct functional roles in immune responses and contribute differentially to immune reconstitution and clinical outcomes, particularly in the context of transplantation [ 2 , 7 ]. Recent research has shown that the metabolic profile of reconstituting monocytes, particularly CD14 + + CD16 + intermediate monocytes, may correlate with clinical outcomes following autologous stem cell transplantation [ 8 ].

The relationship between CD34 + cell dose and engraftment outcomes has been well-established, with higher CD34 + cell doses generally associated with faster neutrophil and platelet recovery [ 9 ]. Although CD34⁺ cell dose is a well-established determinant of hematopoietic engraftment kinetics, its specific impact on monocyte engraftment dynamics and the subsequent development of distinct monocyte subsets remains poorly defined. Furthermore, while early monocyte recovery has been associated with clinical outcomes following transplantation, its potential as a predictive biomarker of successful engraftment has not been fully elucidated [ 2 , 10 – 11 ].

Several factors influence engraftment kinetics, including the type of transplant (allogeneic versus autologous), conditioning regimen intensity, donor characteristics, and recipient factors such as age and comorbidities [ 12 ]. Allogeneic transplants typically exhibit delayed engraftment compared to autologous procedures due to immunologic barriers and the need for more intensive immunosuppression [ 6 ]. Recent studies have also highlighted the importance of mobilization regimens in determining the quality and quantity of harvested stem cells, with implications for subsequent engraftment [ 13 ].

The development of graft-versus-host disease (GVHD) and infectious complications can significantly impact the trajectory of immune reconstitution following allogeneic HSCT [ 14 ]. Understanding the patterns of monocyte recovery in the context of these complications may provide valuable insights for risk stratification and therapeutic intervention [ 2 ].

Contemporary approaches to HSCT increasingly emphasize the importance of precision medicine and personalized risk assessment [ 15 ]. The identification of early biomarkers that can predict transplant success and guide clinical decision-making represents an active area of research [ 16 , 17 ]. Given their early appearance and functional importance, monocytes represent attractive candidates for such biomarker development.

This prospective study aims to characterize the dynamics of monocyte engraftment and associated immunophenotypic changes during the early post-transplant period in patients undergoing both allogeneic and autologous peripheral blood stem cell transplantation. By employing comprehensive flow cytometric analysis, we seek to elucidate the relationship between monocyte recovery patterns and traditional engraftment markers, while exploring potential clinical correlates that may inform transplant management strategies.

Materials and methods

This prospective observational study was conducted at the Hematology Bone Marrow Transplantation Center of Mersin University Medical Faculty Hospital between July 1, 2022, and May 31, 2023. The study protocol received approval from the Clinical Research Ethics Committee of Mersin University Medical Faculty (Decision No: 2022/396, dated June 8, 2022), and all participants provided written informed consent prior to enrollment. The study was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki. Eligible participants were adults aged 18–72 years with benign or malignant hematologic/oncologic conditions who had undergone successful stem cell collection followed by allogeneic or autologous peripheral blood stem cell transplantation and provided signed informed consent. Exclusion criteria included age outside the 18–72 year range, stem cell collection without subsequent transplantation, pregnancy or postpartum status, and refusal to provide informed consent.

Conditioning regimens were administered according to transplant type and underlying diagnosis. In autologous transplantation, patients with multiple myeloma received high-dose melphalan (200 mg/m²), whereas patients with lymphoma received combination of melphalan (180 mg/m²) and mitoxantrone (60 mg/m²). In allogeneic transplantation, conditioning consisted of either busulfan-based (total dose 12.8 mg/kg) or treosulfan-based regimens (42 g/m²), both combined with fludarabine (150 mg/m²). GVHD prophylaxis included anti-thymocyte globulin (ATG), cyclosporine, and methotrexate, or alternatively post-transplant cyclophosphamide in combination with cyclosporine and mycophenolate mofetil, according to institutional protocols. Mobilization regimens for autologous transplants predominantly involved cyclophosphamide plus G-CSF (71.9%), with other regimens including plerixafor plus G-CSF (18.8%) and etoposide plus G-CSF (9.3%). Engraftment was defined according to established criteria: neutrophil engraftment was marked by the first of three consecutive days with an absolute neutrophil count (ANC) ≥ 500/µL post-nadir (EBMT and CIBMTR criteria); platelet engraftment was the first day of a platelet count > 20,000/µL for three consecutive days without platelet transfusion (EBMT criteria); and pre-engraftment monocyte peak day (monocyte engraftment) was defined as the day on which the highest peripheral blood monocyte percentage was recorded prior to neutrophil engraftment, based on serial daily complete blood count (CBC) measurements.

Early post-transplant complications were defined as events occurring during the neutropenic phase prior to engraftment, including febrile neutropenia, documented bacteraemia, mucositis, organ toxicity, and veno-occlusive disease.

Flow cytometric analysis was performed on peripheral blood samples (2–3 mL collected in EDTA tubes) using a Navios EX flow cytometer (Beckman Coulter, Ireland). The gating strategy included sequential selection of leukocytes based on forward scatter (FSC) and side scatter (SSC), followed by doublet exclusion and viability gating. Monocytes were identified based on CD14 and CD16 expression using a bivariate gating approach, allowing classification into classical (CD14 + + CD16−), intermediate (CD14 + + CD16+), and non-classical (CD14 + CD16++) subsets. Lymphocyte subsets (CD3+, CD4+, CD8+, CD19+, CD27+, CD34+) were analysed within the lymphocyte gate. A representative gating strategy is provided in Supplementary Fig. 1. Standard laboratory reference ranges were: LDH: 135–225 IU/L; CRP: <5 mg/L; monocytes: 1.7–9.3%; lymphocytes: 20.5–51.1%; platelets: 150 − 400 × 103/µL; leukocytes: 4.5 − 11 × 10 3 /µL and neutrophils: 1.5 − 6.7 × 10 3 /µL.

Statistical analysis was conducted using IBM SPSS version 21 and MedCalc software. Continuous variables were described as mean ± standard deviation and median (minimum-maximum), while categorical variables were presented as frequencies and percentages. Continuous variables were assessed for normality using the Shapiro–Wilk test. Normally distributed variables were analysed using Student’s t-test or ANOVA, while non-normally distributed variables were analysed using Mann–Whitney U or Kruskal–Wallis tests. Correlations were evaluated using Pearson or Spearman coefficients as appropriate. To account for multiple testing, the Benjamini–Hochberg false discovery rate correction was applied. Multivariate linear regression analyses were performed to assess independent associations between pre-engraftment monocyte peak day and neutrophil and platelet engraftment, adjusting for age, transplant type, CD34 + cell dose, and diagnosis. Statistical significance was set at p < 0.05. No a priori sample size calculation was performed, as this was a prospective observational study including all consecutive eligible patients during the study period. A post-hoc power analysis was conducted based on the primary outcome (correlation between pre-engraftment monocyte peak day and neutrophil engraftment). Given the observed correlation (ρ = 0.83), the achieved statistical power exceeded 99% at a significance level of α = 0.05. Primary analyses were defined a priori, while secondary analyses were considered exploratory.

Results

A total of 56 patients who underwent peripheral blood stem cell transplantation were included in the study. The patient demographic and transplant characteristics are summarized in Tables 1 and 2 . The average age of the patient cohort was 53.3 ± 11.1 years. The gender distribution consisted of 32 males (57.1%) and 24 females (42.9%). Of the procedures, 32 were autologous transplants (57.1%) and 24 were allogeneic (42.9%). The most common diagnosis was Multiple Myeloma, accounting for 50.0% of cases ( n = 28). This was followed by Acute Myeloid Leukemia at 30.4% ( n = 17), Myelodysplastic Syndrome at 5.4% ( n = 3), Mantle Cell Lymphoma at 3.6% ( n = 2), and B-cell Acute Lymphoblastic Leukemia at 3.6% ( n = 2). Other diagnoses included Hodgkin Lymphoma (1.8%, n = 1), Burkitt Lymphoma (1.8%, n = 1), B-cell Non-Hodgkin Lymphoma (1.8%, n = 1), and T-cell Acute Lymphoblastic Leukemia (1.8%, n = 1). All patients with multiple myeloma underwent autologous transplantation, and no myeloma patient received allogeneic HSCT. The mean CD34 + cell dose administered was 5.19 ± 1.66 × 10⁶/kg. Early post-transplant complications were observed in 32 patients (57.1%), and 20 patients (35.7%) required parenteral antibiotic use. Graft versus host disease (GVHD) was observed in 6 of 24 patients (25%) undergoing allogeneic transplantation and was graded based on MAGIC and NIH Consensus Criteria. Among these, 4 cases were acute, whereas 2 patients exhibited features of both acute and chronic GVHD. All cases of acute GVHD observed in the cohort were limited to cutaneous involvement and were classified as grade I. These cases resolved completely with short-term immunosuppressive therapy. Chronic GVHD developed in two patients, both presenting with isolated skin involvement and classified as grade I. One patient was treated with mycophenolate mofetil and the other with ruxolitinib, with complete resolution achieved in both cases. No cases of primary graft failure or severely delayed engraftment were observed. Regarding pre-transplant substance use, 49 patients (87.5%) reported none, while 6 (10.7%) were smokers and 1 (1.8%) used alcohol (Table 1 ).

Flow cytometric analysis at the time of monocyte engraftment revealed distinct patterns of cellular reconstitution. Laboratory values measured during this period showed a median LDH level of 119 IU/L (range 70–454) and a median CRP level of 42.26 mg/L (range 4.09–232). The median monocyte percentage was 26 (range 9–53), and the median neutrophil count was 0.08 × 10³/µL (range 0.01–0.47). Analysis of flow cytometry markers indicated a mean CD3 + percentage of 87.52 ± 18.26%, a mean CD4 + percentage of 56.55 ± 20.81%, and a mean CD8 + percentage of 34.19 ± 15.66%. The CD19 + cell percentage was 7.75 ± 5.17%, and the CD34 + cell percentage was 3.15 ± 1.96%. Among monocyte subsets, the CD14 + percentage was 87.74 ± 8.94%, and the CD16 + percentage was 17.15 ± 9.06%. As an additional marker CD27 + percentage was 7.08 ± 4.01% (Table 3 ).

Platelet engraftment time did not differ significantly between autologous and allogeneic transplant recipients. The median platelet engraftment time was 13 days (range 10–15) in the autologous group and 13.5 days (range 10–38) in the allogeneic group ( p = 0.18). In contrast, neutrophil engraftment occurred significantly later in the allogeneic group compared to the autologous group. The median neutrophil engraftment time was 11 days (range 10–12) in autologous recipients and 13 days (range 9–16) in allogeneic recipients ( p = 0.003). Similarly, the pre-engraftment monocyte peak day was significantly delayed in the allogeneic group. The median pre-engraftment monocyte peak day was 9 days (range 8–11) in the autologous group and 11 days (range 8–14) in the allogeneic group ( p = 0.001).

No significant association was observed between the development of GVHD and engraftment kinetics. Median platelet engraftment time was 12.5 days (range 10–19) in patients with GVHD and 14 days (range 10–38) in those without GVHD. Median neutrophil engraftment time was 13 days (range 9–14) in the GVHD group and 11.5 days (range 10–16) in the non-GVHD group. Similarly, the median pre-engraftment monocyte peak day was 12 days (range 8–13) in patients with GVHD and 11 days (range 9–14) in those without GVHD. These differences were not statistically significant (all p > 0.05) (Table 4 ).

Spearman analyses confirmed a strong association between pre-engraftment monocyte peak day and neutrophil recovery (ρ = 0.83, adjusted p < 0.001) and a moderate association with platelet recovery (ρ = 0.46, adjusted p = 0.001). Other candidate correlations lost significance after false-discovery correction (Table 5 ) (Figs. 1 and 2 ) No significant association was observed between infused CD34 + cell dose and pre-engraftment monocyte peak timing (ρ = 0.10, p = 0.462).

In exploratory multivariable models, pre-engraftment monocyte peak day remained independently associated with neutrophil recovery (B = 0.87, 95% CI 0.76 to 0.98, p < 0.001; model R²=0.88) and platelet recovery (B = 1.53, 95% CI 0.29 to 2.76, p = 0.015; model R²=0.37). Transplant group, infused CD34 + dose, and age were not independently significant in either model (Table 6 ).

Discussion

This prospective study provides novel insights into the dynamics of pre-engraftment monocyte peak and associated immunophenotypic changes during hematopoietic recovery following peripheral blood stem cell transplantation. Our findings demonstrate that pre-engraftment monocyte peak patterns are strongly predictive of subsequent neutrophil and platelet recovery, supporting their potential utility as early biomarkers of transplant success.

The main finding of this study is that the prospectively recorded pre-engraftment monocyte peak day remained associated with both neutrophil and platelet recovery after adjustment for transplant group, age, and infused CD34 + cell dose. Interestingly, CD34 + cell dose was not independently associated with monocyte engraftment timing, suggesting that early monocyte dynamics may be regulated by additional biological mechanisms beyond stem cell dose. This supports the idea that early monocyte dynamics may track broader hematopoietic recovery; however, the result should be interpreted cautiously because the variable analyzed here is an operational timing marker rather than a standardized consensus endpoint.

In the present study, neutrophil engraftment was significantly delayed in allogeneic transplant recipients compared to autologous recipients, consistent with prior literature demonstrating slower hematopoietic recovery in the allogeneic setting due to immunologic barriers and the effects of immunosuppressive therapy [ 12 ]. In contrast, platelet engraftment time did not differ significantly between the two groups, despite a wider range observed in the allogeneic cohort. Although previous studies have frequently reported delayed platelet recovery following allogeneic transplantation [ 12 ], our findings did not confirm this association. This discrepancy may be attributable to the relatively limited sample size, heterogeneity in underlying diagnoses and conditioning regimens, or variability in post-transplant clinical factors influencing platelet recovery. Notably, the pre-engraftment monocyte peak day was also significantly delayed in the allogeneic group, paralleling the pattern observed for neutrophil engraftment. This supports the concept that early monocyte dynamics reflect broader hematopoietic recovery kinetics and may be sensitive to the immunological complexity inherent to allogeneic transplantation.

Our flow cytometric analysis revealed that during pre-engraftment monocyte peak, the majority of monocytes expressed CD14, while a smaller subset expressed CD16. This pattern is consistent with the predominance of classical and intermediate monocytes during early immune reconstitution [ 2 , 7 ]. Recent studies have highlighted the importance of CD14 + + CD16 + intermediate monocytes in transplant outcomes, and our findings suggest these cells are present during early engraftment [ 2 ].

The elevated CRP levels observed in patients receiving parenteral antibiotics and those with early post-transplant complications highlight the relationship between inflammation and immune reconstitution. Despite these inflammatory changes, engraftment kinetics remained similar, suggesting that the inflammatory response does not necessarily impair the fundamental process of hematopoietic recovery [ 18 , 19 ].

Our findings have several important clinical implications. First, the strong predictive value of pre-engraftment monocyte peak timing could allow clinicians to anticipate neutrophil and platelet recovery earlier than current standard practices permit. This could facilitate more precise timing of supportive care measures and discharge planning. Second, the distinct patterns observed between allogeneic and autologous transplants support the need for transplant type-specific monitoring and management protocols. Delayed engraftment in allogeneic recipients highlights the need for continued vigilance, as patients remain at risk for infectious and transplant-related complications throughout the prolonged recovery period [ 19 ]. The lack of a significant association between GVHD and engraftment kinetics in our cohort is likely attributable to the uniformly mild nature of GVHD observed, as all cases were limited to grade I cutaneous involvement and resolved with short-term therapy. More severe forms of GVHD, which are known to impact hematopoietic recovery, were not present in this cohort. Accordingly, the absence of a detectable effect should be interpreted in the context of limited GVHD severity rather than absence of biological relevance.

Several limitations must be acknowledged. In particular, the relatively small sample size for some subgroup analyses limits the generalisability of certain findings. The single-centre design may introduce institutional bias. Although GVHD data were included and analysed, the number of GVHD cases was limited and all acute GVHD events were uniformly mild (grade I), with only two cases of chronic GVHD observed. Therefore, the study was not powered to fully evaluate the impact of GVHD severity on engraftment kinetics or long-term outcomes such as chronic GVHD, recurrence, or survival. Additionally, the lack of long-term follow-up precludes comprehensive assessment of the relationship between early monocyte dynamics and these outcomes. Our study did not include functional assays of monocyte activity, which could provide additional insights into the quality of immune reconstitution. Future studies incorporating both phenotypic and functional analyses would be valuable. Additionally, the absence of an a priori sample size calculation represents a limitation, although post-hoc analysis demonstrated adequate statistical power for the primary endpoint. The post-hoc power analysis, derived from the observed effect size in the study cohort, should be interpreted with caution, as such calculations are methodologically circular and may overestimate the true statistical power.

Several areas warrant further investigation. Larger multi-center studies are needed to validate our findings and establish whether pre-engraftment monocyte peak patterns can be incorporated into clinical decision-making algorithms. Functional studies examining the phagocytic activity, cytokine production, and antigen presentation capacity of engrafting monocytes would provide important mechanistic insights.

Long-term follow-up studies are needed to determine whether early pre-engraftment monocyte peak patterns predict important clinical outcomes such as infection risk, GVHD development, relapse rates, and overall survival. Additionally, investigation of monocyte dynamics in other transplant settings, such as haploidentical or cord blood transplantation, would broaden the applicability of these findings.

The potential for using monocyte dynamics to guide clinical interventions, such as timing of antimicrobial prophylaxis changes or immunosuppression modifications, represents an exciting area for future clinical trials.

Conclusions

This prospective study demonstrates that pre-engraftment monocyte peak provides valuable early insights into hematopoietic recovery following peripheral blood stem cell transplantation. The strong correlation between monocyte recovery timing and subsequent neutrophil and platelet engraftment suggests potential clinical utility as an early exploratory marker of hematopoietic recovery.

Significant discoveries from the study highlight that the timing of the monocyte peak occurring before engraftment strongly forecasts neutrophil engraftment. Furthermore, it was noted that allogeneic transplants exhibit a longer engraftment period across all cell lineages compared to autologous procedures. Analyses using flow cytometry identified a prevalence of CD14 + monocyte populations during the early stages of engraftment. Although inflammatory markers show a connection with clinical complications, they do not negatively impact the kinetics of engraftment. These findings support the incorporation of monocyte monitoring into routine post-transplant care and suggest that monocyte dynamics could serve as valuable biomarkers for transplant outcomes. Further research is needed to validate these findings in larger cohorts and explore their implications for clinical decision-making and patient management strategies.

Authors’ contributions

All authors contributed to the study conception and design. P.A. performed the transplantations. P.A. and D.M. followed the patients. C.M. and M.B.Y.C. performed the laboratory studies. Material preparation, data collection and analysis were performed by D.M., P.A., and M.B.Y.C. The first draft of the manuscript was written by D.M. and P.A. and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Funding

None.

Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

The study protocol received approval from the Clinical Research Ethics Committee of Mersin University Medical Faculty (Decision No: 2022/396, dated June 8, 2022). All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. Informed consent was obtained from all individual participants included in the study.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

References

1. Bordenave J, Gajda D, Michonneau D et al. Deciphering bone marrow engraftment after allogeneic stem cell transplantation in humans using single-cell analyses. J Clin Investig. 2024;134(20). 10.1172/JCI180331.

2. Turcotte LM, Cao Q, Cooley SA, Curtsinger J, Holtan SG, Luo X, Yingst A, Weisdorf DJ, Blazar BR, Miller JS, Wagner JE, Verneris MR. Monocyte Subpopulation Recovery as Predictors of Hematopoietic Cell Transplantation Outcomes. Biol Blood Marrow Transpl. 2019;25(5):883–90. 10.1016/j.bbmt.2019.01.003.

3. Dai W, Dong F, Cheng T, Hao S. T Cell immune reconstitution after allo-HSCT: key factors and implications. Blood Sci. 2025;7(4):e00261. 10.1097/BS9.0000000000000261. PMID: 41347010; PMCID: PMC12672197.

4. Li CM, Wang QY, Chen ZG, Wang CC, Xie YT, Gao L. Immune reconstruction after allogeneic hematopoietic stem cell transplantation: rules, mechanisms, and applications. Ann Hematol. 2026;105(4):162. 10.1007/s00277-026-06922-4.

5. Dash SP, Gupta S, Sarangi PP. Monocytes and macrophages: Origin, homing, differentiation, and functionality during inflammation. Heliyon. 2024;10(8):e29686. 10.1016/j.heliyon.2024.e29686.

6. Storek J, Geddes M, Khan F, Huard B, Helg C, Chalandon Y, Passweg J, Roosnek E. Reconstitution of the immune system after hematopoietic stem cell transplantation in humans. Semin Immunopathol. 2008;30(4):425–37. 10.1007/s00281-008-0132-5.

7. Wong KL, Yeap WH, Tai JJ, Ong SM, Dang TM, Wong SC. The three human monocyte subsets: implications for health and disease. Immunol Res. 2012;53(1–3):41–57. 10.1007/s12026-012-8297-3.

8. Richter S, Böttcher M, Völkl S, et al. The metabolic profile of reconstituting T-cells, NK-cells, and monocytes following autologous stem cell transplantation and its impact on outcome. Sci Rep. 2022;12(1):11406.

9. Bittencourt H, Rocha V, Chevret S, Socié G, Espérou H, Devergie A, Dal Cortivo L, Marolleau JP, Garnier F, Ribaud P, Gluckman E. Association of CD34 cell dose with hematopoietic recovery, infections, and other outcomes after HLA-identical sibling bone marrow transplantation. Blood. 2002;99(8):2726–33. 10.1182/blood.v99.8.2726.

10. Pérez-Simón JA, et al. Impact of CD34⁺ cell dose on the outcome of patients receiving allogeneic peripheral blood stem cell transplants. Blood. 2003;102:1108–13.

11. Zubair AC, et al. CD34⁺ cell dose and subsets and their association with hematopoietic recovery after transplantation. Cytotherapy. 2006;8(3):237–45.

12. Copelan EA. Hematopoietic stem-cell transplantation. N Engl J Med. 2006;354(17):1813–26. 10.1056/NEJMra052638.

13. Jeker B, Thalmann L, Bacher U, et al. Comparing stem cell mobilization with chemotherapy and cytokine (G-CSF) versus cytokine alone in myeloma patients (MOCCCA): a randomized phase II, open-label, non-inferiority trial. Bone Marrow Transplant. 2025;60(3):270–6.

14. Kolloch L, Berning P, Albring JC, Ronnacker J, Reicherts C, Call S, Marx J, Floeth M, Esseling E, Eich HT, Schliemann C, Mikesch JH, Lenz G, Stelljes M. Immune reconstitution in AML and MDS patients undergoing allogeneic hematopoietic cell transplantation (allo-HCT) with treosulfan- or TBI-based conditioning. Bone Marrow Transpl. 2025;60(11):1533–6. 10.1038/s41409-025-02702-2.

15. Duarte RF, Labopin M, Bader P, Basak GW, Bonini C, Chabannon C, Corbacioglu S, Dreger P, Dufour C, Gennery AR, Kuball J, Lankester AC, Lanza F, Montoto S, Nagler A, de Peffault R, Snowden JA, Styczynski J, Yakoub-Agha I, Kröger N, Mohty M. European Society for Blood and Marrow Transplantation (EBMT). Indications for haematopoietic stem cell transplantation for haematological diseases, solid tumours and immune disorders: current practice in Europe, 2019. Bone Marrow Transpl. 2019;54(10):1525–52. 10.1038/s41409-019-0516-2.

16. Zhao XS, Huang XJ. Seeking biomarkers for acute graft-versus-host disease: where we are and where we are heading? Biomark Res. 2019;7:17. 10.1186/s40364-019-0167-x.

17. Hartwell MJ, Özbek U, Holler E, Renteria AS, Major-Monfried H, Reddy P, Aziz M, Hogan WJ, Ayuk F, Efebera YA, Hexner EO, Bunworasate U, Qayed M, Ordemann R, Wölfl M, Mielke S, Pawarode A, Chen YB, Devine S, Harris AC, Jagasia M, Kitko CL, Litzow MR, Kröger N, Locatelli F, Morales G, Nakamura R, Reshef R, Rösler W, Weber D, Wudhikarn K, Yanik GA, Levine JE, Ferrara JL. An early-biomarker algorithm predicts lethal graft-versus-host disease and survival. JCI Insight. 2017;2(3):e89798. 10.1172/jci.insight.89798. Erratum in: JCI Insight. 2018;3(16):124015. doi: 10.1172/jci.insight.124015.

18. Melenhorst JJ, Tian X, Xu D, Sandler NG, Scheinberg P, Biancotto A, et al. Cytopenia and leukocyte recovery shape cytokine profiles during hematopoietic reconstitution after allogeneic stem cell transplantation. Haematologica. 2012;97(6):867–73. 10.3324/haematol.2011.056028.

19. Pereira MR, Pouch SM, Saiman L. Infections in allogeneic stem cell transplantation. Clin Microbiol Rev. 2018;31(2):e00029–17.29142078

Associated Data

Data Availability Statement

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.