Allogeneic stem cell transplantation for myelofibrosis in the modern era: single- center outcomes with DIPSS risk stratification

Allogeneic stem cell transplantation for myelofibrosis in the modern era: single- center outcomes with DIPSS risk stratification | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Allogeneic stem cell transplantation for myelofibrosis in the modern era: single- center outcomes with DIPSS risk stratification Dae-Ho Choi, Jun Ho Jang, Chul Won Jung This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9039701/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Background To describe post-transplant outcomes in patients with myelofibrosis stratified by the Dynamic International Prognostic Scoring System (DIPSS) risk at transplantation, and to identify clinical factors associated with overall survival (OS) after allogeneic hematopoietic stem cell transplantation (allo-HSCT). Methods We retrospectively analyzed 42 patients with myelofibrosis who underwent allo-HSCT at Samsung Medical Center between 2014 and 2023. OS was estimated using the Kaplan-Meier method and compared via the log-rank test. Exploratory Cox proportional hazards regression analyses were performed to assess independent associations with OS. Results At transplantation, 28 patients (66.7%) had Intermediate (Int-1/2) and 14 (33.3%) had High DIPSS risk. OS differed significantly by DIPSS risk group (log-rank p = 0.0034): the median OS was 15.2 months (95% CI, 7.2–NR) in the Intermediate group versus 6.4 months (95% CI, 3.3–35.1) in the High-risk group. All 14 High-risk patients (100%) died during follow-up, compared with 14 of 28 (50.0%) in the Intermediate group. The 1-year OS was 57.1% versus 28.6%, 2-year OS was 50.0% versus 14.3%, and 3-year OS was 50.0% versus 7.1%, respectively. In an exploratory multivariable analysis adjusting for HCT-CI and donor type, DIPSS High risk remained independently associated with inferior OS (adjusted HR, 2.91; 95% CI, 1.27–6.63; p = 0.011). No other clinical variable, including age (≥ 60 vs. <60 years; p = 0.16 by log-rank), achieved statistical significance. Conclusion DIPSS High-risk disease at transplantation was associated with uniformly poor post-transplant survival in this single-center cohort. These hypothesis-generating findings underscore the importance of transplant timing before progression to high-risk disease, and warrant validation in larger, multicenter studies. Myelofibrosis allogeneic stem cell transplantation DIPSS prognosis overall survival transplant outcomes risk stratification Figures Figure 1 Figure 2 Introduction Myelofibrosis (MF) is a rare Philadelphia chromosome–negative myeloproliferative neoplasm with an annual incidence of ~ 0.5 per 100,000 and a median age at diagnosis of ~ 65 years[ 1 , 2 ]. It is characterized by progressive bone marrow fibrosis, extramedullary hematopoiesis with splenomegaly, constitutional symptoms, and a risk of leukemic transformation[ 1 , 3 ]. The prognosis is poor compared with other MPNs, with median survival ranging from > 10 years in low-risk patients to 2–3 years in those at high risk[ 2 , 4 ]. MF pathogenesis involves the clonal proliferation of hematopoietic stem cells, frequently with Janus kinase 2 ( JAK2 ), calreticulin ( CALR ), or myeloproliferative leukemia protein ( MPL ) mutations, and an altered bone marrow microenvironment producing pro-fibrotic cytokines such as transforming growth factor beta 1 (TGF-β1) and bone morphogenetic protein 2 (BMP-2)[ 5 ]. Risk stratification is most commonly performed using the DIPSS, which incorporates age, hemoglobin, leukocyte count, peripheral blasts, and constitutional symptoms, with anemia weighted double[ 4 ]. High molecular risk mutations (e.g., ASXL transcriptional regulator 1 [ ASXL1 ], serine and arginine rich splicing factor 2 [ SRSF2 ], enhancer of zeste 2 polycomb repressive complex 2 subunit [ EZH2 ], and isocitrate dehydrogenase 1 and 2 [ IDH1/2 ]) further worsen prognosis[ 6 ]. Treatment is risk-adapted. Low-risk or asymptomatic patients may be observed, while intermediate-2, high-risk**,** or symptomatic patients typically receive JAK inhibitors such as ruxolitinib[ 7 ], fedratinib[ 8 ], pacritinib[ 9 ], or momelotinib[ 10 ]. These agents improve symptoms and splenomegaly but rarely achieve molecular remission or significantly extend survival. Allogeneic hematopoietic stem cell transplantation (allo-HSCT) remains the only potentially curative therapy[ 11 ] Recent EBMT/ELN consensus recommendations emphasize allo-HSCT as the only potentially curative option and support its consideration in medically fit patients with intermediate-2 or high-risk MF (and selected intermediate-1 patients with additional adverse features), while integrating comorbidity and molecular risk assessment into decision-making[ 12 ]. Transplant-specific prognostic tools such as the Myelofibrosis Transplant Scoring System (MTSS) have been proposed to refine post-transplant risk estimation[ 13 ]. Notably, current consensus suggests that chronological age alone should not constitute an absolute contraindication, and reduced-intensity conditioning may expand HSCT feasibility in selected older patients[ 14 , 15 ]. In this study, we retrospectively described the outcomes of 42 patients with myelofibrosis who underwent allo-HSCT at a single center between 2014 and 2023. We focused on pre-transplant DIPSS risk as the primary stratification variable, and evaluated age and other transplant- and disease-related factors in secondary exploratory analyses. Materials and Methods Patient selection and data collection We performed a retrospective cohort study of patients with myelofibrosis who underwent allo-HSCT at Samsung Medical Center between 2014 and 2023. A total of 42 patients were identified through the institutional transplant database, including those with primary myelofibrosis (PMF), post-polycythemia vera myelofibrosis (post-PV MF), and post-essential thrombocythemia myelofibrosis (post-ET MF). This study was conducted in accordance with the ethical principles of the Declaration of Helsinki (as revised in 2013) and the Korean Good Clinical Practice guidelines. Approval was obtained from the Institutional Review Board at Samsung Medical Center (IRB No. 2025-11-108), and the requirement for individual informed consent was waived. Patients were identified by anonymized patient numbers only, and personally identifiable information was kept confidential according to the IRB protocol. Definitions of variables and outcomes The variables examined included sex, MF subtype, and donor type (matched sibling donor [MSD], matched unrelated donor [MUD], or haploidentical donor). Conditioning intensity (myeloablative conditioning [MAC] vs. reduced-intensity conditioning [RIC]), DIPSS risk at transplantation, and the hematopoietic cell transplantation-specific comorbidity index (HCT-CI; <3 vs. ≥3) were incorporated to address potential confounders. Clinical factors, including pre-transplant spleen size, constitutional symptoms, and JAK inhibitor exposure and response, were also recorded. Driver mutation status ( JAK2 , CALR , MPL ) was included, and next-generation sequencing (NGS) results were incorporated where available. The primary outcome was OS after transplantation, stratified by DIPSS risk. OS was calculated from the date of HSCT to the date of death from any cause or the date of last follow-up, with surviving patients censored at last contact. Secondary analyses evaluated OS by age group (≥ 60 vs. <60 years) and other factors, including donor type, conditioning regimen, HCT-CI, driver mutation status, and spleen size. DIPSS component variables were not tabulated by risk group to avoid circularity. Statistical analysis Survival curves were estimated using the Kaplan-Meier method and compared using the log-rank test. Categorical variables were compared using the chi-square test or Fisher’s exact test, as appropriate. Given the limited sample size and inherent baseline imbalances, all analyses were considered exploratory, and P -values were interpreted with caution. Exploratory Cox proportional hazards regression was performed as a sensitivity analysis and is provided in the Supplementary Appendix (Supplementary Table 1 and Fig. 2 ). Advanced statistical techniques (e.g., propensity score matching and competing-risk models) were not pursued given the limited number of cases and events. Analyses were performed using R version 4.2.2 (R Foundation for Statistical Computing, Vienna, Austria). Results Baseline characteristics From 2014 to 2023, 42 patients with myelofibrosis underwent allo-HSCT. At transplantation, 28 patients (66.7%) had Intermediate (Int-1/2) DIPSS risk, and 14 (33.3%) had High DIPSS risk (Table 1 ). The Intermediate group was predominantly male (71.4%) and comprised mostly patients with PMF (82.1%). Donor types included MSD (32.1%), haploidentical (28.6%), and MUD (39.3%). The High-risk group was also predominantly male (92.9%), with a higher proportion of haploidentical donors (57.1%). All patients received busulfan plus fludarabine-based conditioning; BuFlu2 was used in all High-risk patients, whereas BuFlu4 was used in 50.0% of Intermediate-risk patients. An HCT-CI ≥ 3 was observed in 42.9% and 57.1% of Intermediate- and High-risk patients, respectively. Spleen size categories and prior ruxolitinib exposure were broadly similar between the groups (Table 1 ). Table 1 Baseline characteristics of 42 myelofibrosis patients undergoing allogeneic HSCT, stratified by DIPSS risk group at transplantation (Intermediate [Int-1/2] vs High) Characteristic Intermediate (n = 28) High (n = 14) P-value Sex Male 20 (71.4%) 13 (92.9%) 0.23 Female 8 (28.6%) 1 (7.1%) Types of myelofibrosis PMF 23 (82.1%) 9 (64.3%) 0.337 Post ET MF 3 (10.7%) 4 (28.6%) Post PV MF 2 (7.1%) 1 (7.1%) Driver mutation TN 7 (25.0%) 2 (14.3%) 0.36 JAK2 13 (46.4%) 9 (64.3%) CALR 4 (14.3%) 0 (0.0%) MPL 3 (10.7%) 1 (7.1%) Unknown 1 (3.6%) 2 (14.3%) Donor type Matched sibling donor 9 (32.1%) 1 (7.1%) 0.106 Haploidentical 8 (28.6%) 8 (57.1%) Matched unrelated donor 11 (39.3%) 5 (35.7%) Conditioning regimen BuFlu4 14 (50.0%) 0 (0.0%) 0.001 BuFlu2 14 (50.0%) 14 (100.0%) HCT-CI score <3 16 (57.1%) 6 (42.9%) 0.515 ≥3 12 (42.9%) 8 (57.1%) NGS available Yes 9 (32.1%) 4 (28.6%) 1.0 No 19 (67.9%) 10 (71.4%) Spleen size before HSCT Longest diameter < 22 cm 19 (67.9%) 9 (64.3%) 0.715 Longest diameter ≥ 22 cm 8 (28.6%) 5 (35.7%) Splenectomy 1 (3.6%) 0 (0.0%) Previous ruxolitinib exposure Yes 18 (64.3%) 11 (78.6%) 0.485 No 10 (35.7%) 3 (21.4%) Response to JAK inhibitor among exposed (descriptive) Any response 16 (88.9%) 8 (72.7%) 0.339 Disease progression 2 (11.1%) 3 (27.3%) All patients received busulfan plus fludarabine-based conditioning regimens. Comparisons between groups are exploratory; p-values should be interpreted with caution. DIPSS component variables (age, hemoglobin, leukocyte count, peripheral blasts, and constitutional symptoms) were not tabulated by risk group to avoid circularity. Abbreviations: ET, Essential thrombocythemia; MF, Myelofibrosis; PV, Polycythemia vera; JAK2, Janus kinase 2; CALR, Calreticulin; MPL, Myeloproliferative leukemia protein; Bu, Busulfan; Flu, Fludarabine; HCT-CI, Hematopoietic Cell Transplantation–Comorbidity Index; NGS, Next-generation sequencing; HSCT, Hematopoietic stem cell transplantation Overall survival according to DIPSS risk and age OS was significantly inferior in the High-risk group (log-rank P = 0.0034) (Fig. 1 ). The median OS was 15.2 months (95% CI, 7.2–NR) in the Intermediate group and 6.4 months (95% CI, 3.3–35.1) in the High-risk group. All 14 High-risk patients (100%) died during follow-up, compared with 14 of 28 (50.0%) in the Intermediate group. The 1-year OS was 57.1% versus 28.6%, the 2-year OS was 50.0% versus 14.3%, and the 3-year OS was 50.0% versus 7.1% for the Intermediate and High-risk groups, respectively. A swimmer plot illustrating patient-level follow-up by DIPSS risk is shown in Supplementary Fig. 4. In the age-based comparison (≥ 60 vs. <60 years), the median OS was 8.0 months (95% CI, 5.4–36.3) in the ≥ 60-year group and 15.2 months (95% CI, 6.3–NR) in the < 60-year group ( P = 0.16) (Supplementary Fig. 1). Exploratory subgroup and multivariable analyses Univariable subgroup analyses are shown in Fig. 2 . DIPSS High risk showed the strongest association with inferior OS (HR, 2.93; 95% CI, 1.38–6.21) ; all other subgroup estimates were not statistically significant. In the exploratory multivariable Cox regression analysis (Supplementary Table 1), DIPSS High risk remained independently associated with inferior OS after adjustment for HCT-CI and donor type (adjusted HR, 2.91; 95% CI, 1.27–6.63; P = 0.011), whereas age ≥ 60 years was not significant (adjusted HR, 1.65; 95% CI, 0.66–4.15; P = 0.30). These models are presented as hypothesis-generating and should not be interpreted as confirmatory. Driver mutation and spleen size No significant differences in OS were observed according to driver mutation status (log-rank P = 0.10) (Supplementary Fig. 2) or spleen size category before transplantation (log-rank P = 0.85) (Supplementary Fig. 3). Spleen size was categorized by the longest diameter (< 22 cm vs. ≥22 cm) ; one patient with a prior splenectomy was excluded from this analysis. Cause of death Overall, 28 deaths occurred during follow-up. Infection was the most frequent cause of death in both groups (Intermediate: 9/28 [32.1%]; High: 6/14 [42.9%]), followed by disease progression and graft-versus-host disease (GVHD) (Table 2 ). Among the 13 patients who died within the first 6 months after HSCT, 9 (69.2%) died of infection, compared with 6 of 15 (40.0%) among those who died at ≥ 6 months. Because the post-transplant disease status near the time of death was not uniformly available, deaths were not formally attributed to relapse-related versus non-relapse mortality. Table 2 Causes of death stratified by DIPSS risk group at transplantation Causes of death Intermediate (N = 28) High (N = 14) Number of deaths 14 (50.0%) 14 (100.0%) Infection 9 (32.1%) 6 (42.9%) Disease progression 2 (7.1%) 3 (21.4%) GVHD 1 (3.6%) 3 (21.4%) Bleeding (Engraftment failure) 1 (3.6%) 0 (0.0%) Unknown 1 (3.6%) 2 (14.3%) Discussion In this single-center retrospective cohort study, DIPSS risk at transplantation was the only clinical variable significantly associated with post-transplant OS. All 14 patients transplanted with DIPSS High-risk disease died during follow-up, with a median OS of only 6.4 months, compared with 15.2 months in the Intermediate group. In exploratory multivariable models, DIPSS High risk retained an independent association with inferior OS (adjusted HR, 2.91; P = 0.011), whereas no other variable—including age, HCT-CI, and donor type—reached statistical significance. Notably, all DIPSS High-risk patients in this cohort were aged ≥ 60 years, precluding the reliable separation of age and disease risk effects ; the observed trend toward inferior OS in older recipients ( P = 0.16) is likely driven by this overlap rather than by an independent effect of age These findings suggest that the disease burden captured by the DIPSS at transplantation is a critical determinant of post-transplant outcomes, and that allo-HSCT should ideally be pursued before progression to DIPSS High-risk disease [ 16 , 17 ]. Our findings suggest that progression to DIPSS High-risk disease before transplantation may substantially limit the benefit of allo-HSCT. Whether this reflects an inherently aggressive disease biology that is resistant to the graft-versus-myelofibrosis effect, increased transplant-related toxicity in patients with a greater disease burden, or both, cannot be determined from our data. These observations support the concept of a therapeutic window for allo-HSCT in MF, in which transplantation is most likely to be beneficial when performed before progression to high-risk disease. Consistent with the updated EBMT/ELN recommendations, risk stratification is central to transplant decision-making in MF [ 12 ]. In our cohort, DIPSS High risk was associated with inferior OS in both unadjusted and exploratory adjusted analyses. Transplant-specific scoring systems, such as the MTSS, may further refine post-transplant risk estimation [ 13 ]. However, comprehensive molecular annotation was limited because NGS data were available for only a subset of patients, precluding the evaluation of high-molecular-risk features. In particular, integrated clinical-molecular scoring systems such as MIPSS70 + v2.0 [ 27 ] incorporate high-molecular-risk mutations and cytogenetic findings that were not systematically available in our cohort. Future studies with comprehensive molecular annotation will be essential to determine whether molecular risk features refine the prognostic impact of the DIPSS category in the transplant setting. Although not statistically significant, we observed a trend toward poorer outcomes in patients who were triple-negative or harbored JAK2 mutations. Given the limited sample size and incomplete molecular data, these findings should be interpreted cautiously [ 18 , 19 ]. Spleen size before transplantation was not associated with survival in our cohort. Data from large registry analyses have shown that although splenectomy itself does not have a major impact on overall survival, smaller spleen size has been associated with better outcomes [ 20 , 21 ]. Our findings may reflect limited statistical power. Taken together, rather than performing splenectomy or splenic irradiation solely to reduce spleen size, it may be reasonable in transplant-eligible patients with advanced-risk MF to use JAK inhibitors primarily as pretransplant optimization or bridging therapy, with spleen reduction as a secondary benefit when achieved [ 22 ]. In patients who do not respond to JAK inhibitors, prognosis can remain poor even with transplantation, and alternative approaches or supportive care should be considered [ 23 , 24 ] Infection was the most frequently recorded cause of death. Infection-related deaths were more frequent within the first 6 months after HSCT. These observations should be interpreted cautiously because we did not perform competing-risk or time-dependent analyses. Reduced-intensity conditioning was commonly used in this selected population and was deliverable, although the small sample size precludes firm conclusions regarding comparative effectiveness [ 25 ]. Our study has several limitations. The small sample size and retrospective, single-center design limit statistical power and generalizability. Age-stratified comparisons should be interpreted cautiously because the conditioning regimen, JAK inhibitor use, and DIPSS risk were not uniformly distributed between the age groups. The only statistically significant association observed was OS according to the DIPSS risk category ; all other comparisons should be regarded as hypothesis-generating. When transplantation is considered in patients with DIPSS High-risk disease, pretransplant risk optimization—including JAK inhibitor bridging therapy—may be reasonable. If meaningful disease-risk reduction cannot be achieved, non-transplant approaches and supportive care should be discussed, regardless of patient age. Conclusion In this single-center retrospective analysis, DIPSS High-risk disease at transplantation was associated with uniformly poor post-transplant survival, with 100% mortality despite allo-HSCT. These findings highlight the importance of transplant timing and suggest that allo-HSCT should be considered before progression to DIPSS High-risk disease. Given the limitations of this small, retrospective cohort, these hypothesis-generating observations warrant validation in multicenter studies incorporating integrated clinical-molecular transplant risk models. Declarations Ethics Approval and Consent to Participate: This study was conducted in accordance with the ethical principles of the Declaration of Helsinki (as revised in 2013). Approval was obtained from the Institutional Review Board of Samsung Medical Center (IRB No. 2025-11-108). The requirement for individual informed consent was waived by the IRB given the retrospective design. Consent for Publication: Not applicable. Competing Interests: The authors declare no competing interests. Funding: This research received no external funding. Author Contribution DHC was responsible for study design, data collection, statistical analysis, data interpretation, and manuscript writing. JHJ contributed to data collection, data interpretation, and critical review. CWJ was responsible for study conception and design, data interpretation, critical revision, and supervision. All authors reviewed and approved the final manuscript. Data Availability The data underlying this article are available from the corresponding author on reasonable request, subject to institutional and ethical regulations. References Mora B, Bucelli C, Cattaneo D, Bellani V, Versino F, Barbullushi K, et al. Prognostic and predictive models in myelofibrosis. Curr Hematol Malig Rep. 2024;19:223–235. Martino M, Pitea M, Sgarlata A, Delfino IM, Cogliandro F, Scopelliti A, et al. Treatment strategies used in treating myelofibrosis: state of the art. Hematol Rep. 2024;16:698–713. Leiva O, Ng SK, Chitalia S, Balduini A, Matsuura S, Ravid K. The role of the extracellular matrix in primary myelofibrosis. Blood Cancer J. 2017;7:e525. Passamonti F, Cervantes F, Vannucchi AM, Morra E, Rumi E, Cazzola M, et al. Dynamic International Prognostic Scoring System (DIPSS) predicts progression to acute myeloid leukemia in primary myelofibrosis. Blood. 2010;116:2857–2858. Martinaud C, Desterke C, Konopacki J, Pieri L, Torossian F, Golub R, et al. Osteogenic potential of mesenchymal stromal cells contributes to primary myelofibrosis. Cancer Res. 2015;75:4753–4765. Tefferi A, Nicolosi M, Mudireddy M, Lasho TL, Gangat N, Begna KH, et al. Revised cytogenetic risk stratification in primary myelofibrosis: analysis based on 1002 informative patients. Leukemia. 2018;32:1189–1199. Verstovsek S, Mesa RA, Gotlib J, Levy RS, Gupta V, DiPersio JF, et al. A double-blind, placebo-controlled trial of ruxolitinib for myelofibrosis. N Engl J Med. 2012;366:799–807. Pardanani A, Harrison C, Cortes JE, Cervantes F, Mesa RA, Milligan D, et al. Safety and efficacy of fedratinib in patients with primary or secondary myelofibrosis: a randomized clinical trial. JAMA Oncol. 2015;1:643–651. Mascarenhas J, Hoffman R, Talpaz M, Gerds AT, Stein B, Gupta V, et al. Pacritinib vs best available therapy, including ruxolitinib, in patients with myelofibrosis: a randomized clinical trial. JAMA Oncol. 2018;4:652–659. Mesa RA, Kiladjian JJ, Catalano JV, Devos T, Egyed M, Hellmann A, et al. SIMPLIFY-1: a phase III randomized trial of momelotinib versus ruxolitinib in Janus kinase inhibitor-naive patients with myelofibrosis. J Clin Oncol. 2017;35:3844–3850. Ranalli P, Natale A, Guardalupi F, Santarone S, Canto C, La Barba G, et al. Myelofibrosis and allogeneic transplantation: critical points and challenges. Front Oncol. 2024;14:1396435. Kroger N, Bacigalupo A, Barbui T, Ditschkowski M, Gagelmann N, Griesshammer M, et al. Indication and management of allogeneic haematopoietic stem-cell transplantation in myelofibrosis: updated recommendations by the EBMT/ELN international working group. Lancet Haematol. 2024;11:e62–e74. Gagelmann N, Ditschkowski M, Bogdanov R, Bredin S, Robin M, Cassinat B, et al. Comprehensive clinical-molecular transplant scoring system for myelofibrosis undergoing stem cell transplantation. Blood. 2019;133:2233–2242. Fauble V, Leis J, Mesa RA. Allogeneic stem cell transplant for myelofibrosis patients over age 60: likely impact of the JAK2 inhibitors. Leuk Suppl. 2012;1:S2–7. Daghia G, Zabelina T, Zeck G, von Pein UM, Christopeit M, Wolschke C, et al. Allogeneic stem cell transplantation for myelofibrosis patients aged **≥**65 years. Eur J Haematol. 2019;103:370–378. Ditschkowski M, Elmaagacli AH, Trenschel R, Gromke T, Steckel NK, Koldehoff M, et al. Dynamic International Prognostic Scoring System scores, pre-transplant therapy and chronic graft-versus-host disease determine outcome after allogeneic hematopoietic stem cell transplantation for myelofibrosis. Haematologica. 2012;97:1574–1581. Cooper JP, Scott BL. Allogeneic transplantation for myelofibrosis with adverse risk karyotype: attack on the clones? Am J Hematol. 2018;93:603–604. Tefferi A, Lasho TL, Finke CM, Knudson RA, Ketterling R, Hanson CH, et al. CALR vs JAK2 vs MPL -mutated or triple-negative myelofibrosis: clinical, cytogenetic and molecular comparisons. Leukemia. 2014;28:1472–1477. Schulze S, Stengel R, Jaekel N, Wang SY, Franke GN, Roskos M, et al. Concomitant and noncanonical JAK2 and MPL mutations in JAK2 V617F- and MPL W515L-positive myelofibrosis. Genes Chromosomes Cancer. 2019;58:747–755. Polverelli N, Mauff K, Kroger N, Robin M, Beelen D, Beauvais D, et al. Impact of spleen size and splenectomy on outcomes of allogeneic hematopoietic cell transplantation for myelofibrosis: a retrospective analysis by the chronic malignancies working party on behalf of European Society for Blood and Marrow Transplantation (EBMT). Am J Hematol. 2021;96:69–79. Kroger N, Sbianchi G, Sirait T, Wolschke C, Beelen D, Passweg J, et al. Impact of prior JAK-inhibitor therapy with ruxolitinib on outcome after allogeneic hematopoietic stem cell transplantation for myelofibrosis: a study of the CMWP of EBMT. Leukemia. 2021;35:3551–3560. Polverelli N, Hernandez-Boluda JC, Czerw T, Barbui T, D’Adda M, Deeg HJ, et al. Splenomegaly in patients with primary or secondary myelofibrosis who are candidates for allogeneic hematopoietic cell transplantation: a position paper on behalf of the chronic malignancies working party of the EBMT. Lancet Haematol. 2023;10:e59–e70. Harrison CN, Kiladjian JJ, Koschmieder S, Passamonti F. Myelofibrosis: current unmet needs, emerging treatments, and future perspectives. Cancer. 2024;130:2091–2097. Reynolds SB, Pettit K. New approaches to tackle cytopenic myelofibrosis. Hematology Am Soc Hematol Educ Program. 2022;2022:235–244. Murthy GSG, Kim S, Estrada-Merly N, Abid MB, Aljurf M, Assal A, et al. Association between the choice of the conditioning regimen and outcomes of allogeneic hematopoietic cell transplantation for myelofibrosis. Haematologica. 2023;108:1900–1908. Luque Paz D, Gagelmann N, Benajiba L, Riou J, Salit R, Orvain C, et al. Role of molecular alterations in transplantation decisions for patients with primary myelofibrosis. Blood Adv. 2025;9:797–807. Ali H, Aldoss I, Yang D, Mokhtari S, Khaled S, Aribi A, et al. MIPSS70 + v2.0 predicts long-term survival in myelofibrosis after allogeneic HCT with the flu/mel conditioning regimen. Blood Adv. 2019;3:83–95. Machherndl-Spandl S, Hannouf S, Nikoloudis A, Zach O, Strassl I, Kaynak E, et al. Improved outcomes in myelofibrosis after allogeneic stem-cell transplantation in the era of ruxolitinib pretreatment and intensified conditioning regimen: single-center analysis. Cancers (Basel). 2024;16. Gagelmann N, Hobbs GS, Campodonico E, Helbig G, Novak P, Schroeder T, et al. Splenic irradiation for myelofibrosis prior to hematopoietic cell transplantation: a global collaborative analysis. Am J Hematol. 2024;99:844–853. Helbig G, Wieczorkiewicz-Kabut A, Markiewicz M, Krzemien H, Wojciak M, Bialas K, et al. Splenic irradiation before allogeneic stem cell transplantation for myelofibrosis. Med Oncol. 2019;36:16. Additional Declarations No competing interests reported. Supplementary Files SupplementaryMaterials.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 09 Apr, 2026 Reviews received at journal 08 Apr, 2026 Reviewers agreed at journal 18 Mar, 2026 Reviewers invited by journal 17 Mar, 2026 Editor assigned by journal 13 Mar, 2026 Submission checks completed at journal 12 Mar, 2026 First submitted to journal 05 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9039701","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":607329684,"identity":"e5bcdfcc-62b6-447f-8df3-ba4e691effee","order_by":0,"name":"Dae-Ho Choi","email":"","orcid":"","institution":"Samsung Medical Center, Sungkyunkwan University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Dae-Ho","middleName":"","lastName":"Choi","suffix":""},{"id":607329685,"identity":"362bdd85-98ed-40f5-827c-8d1579ded6ec","order_by":1,"name":"Jun Ho Jang","email":"","orcid":"","institution":"Samsung Medical Center, Sungkyunkwan University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Jun","middleName":"Ho","lastName":"Jang","suffix":""},{"id":607329688,"identity":"b0c2ed2e-fb99-4c6d-b84e-ec2fb4c97440","order_by":2,"name":"Chul Won Jung","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3UlEQVRIiWNgGAWjYBACPgYGZiAlwcDP3gCkDSwIa2GDaZHsOQDSIkG0FqDiGwkMYL2EtbD3GBt8zLGQZ7j5/OqGHwVAF7Z3J+DXwnPGOHHmNgnDxtk5ZTd7gA6TOHN2A34tEjnGh3m3STA2S+ek3eABajGQyCWgRf6N8eG/2yTs2yTPpN38Q5QWCR7jZMZtEok9EuzHbhNnC09asWHvNonkGTw5bLdlDCR4CPqFn/3wZomf2+ps9x8//uzmmz82cvztvfi1IAEeAzBJrHIQYH9AiupRMApGwSgYQQAAoy1BO3/KEEQAAAAASUVORK5CYII=","orcid":"","institution":"Samsung Medical Center, Sungkyunkwan University School of Medicine","correspondingAuthor":true,"prefix":"","firstName":"Chul","middleName":"Won","lastName":"Jung","suffix":""}],"badges":[],"createdAt":"2026-03-05 11:54:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9039701/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9039701/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104997325,"identity":"b68b08f9-f885-48eb-bdcc-c2c1666778a4","added_by":"auto","created_at":"2026-03-19 16:23:10","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":318154,"visible":true,"origin":"","legend":"\u003cp\u003eOverall survival after allogeneic HSCT by DIPSS risk at transplantation. Kaplan-Meier curves for the Intermediate (Intermediate-1/2 combined; n=28) and High (n=14) DIPSS risk groups. The median OS was 15.2 months (95% CI, 7.2–NR) in the Intermediate group and 6.4 months in the High-risk group (log-rank \u003cem\u003eP\u003c/em\u003e=0.0034). Numbers at risk are shown below the x-axis.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-9039701/v1/94a770fa8c5f8495e5b7f574.png"},{"id":104997326,"identity":"a78918b0-f973-4106-8823-db556c3eb38d","added_by":"auto","created_at":"2026-03-19 16:23:10","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":206068,"visible":true,"origin":"","legend":"\u003cp\u003eUnivariable subgroup analysis of overall survival after allogeneic HSCT. Hazard ratios (HR) with 95% confidence intervals are shown for pre-specified clinical variables (DIPSS risk, sex, age, donor type, conditioning intensity, and HCT-CI). All analyses are exploratory; confidence intervals are wide due to the limited sample size, and results should be interpreted as hypothesis-generating only.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-9039701/v1/5aa9332bc7233e5b8420f96d.png"},{"id":105035768,"identity":"025ed7ae-bd78-47cc-9e8b-237d888f1d38","added_by":"auto","created_at":"2026-03-20 07:26:36","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1153071,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9039701/v1/4059e3d4-2aed-4734-b7e9-76c556ef6b68.pdf"},{"id":104997327,"identity":"d9d59ae7-20fd-4434-af0c-6c30e75df5a2","added_by":"auto","created_at":"2026-03-19 16:23:10","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":1310556,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterials.docx","url":"https://assets-eu.researchsquare.com/files/rs-9039701/v1/1c179b2f9a8c23d7423a8b82.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Allogeneic stem cell transplantation for myelofibrosis in the modern era: single- center outcomes with DIPSS risk stratification","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMyelofibrosis (MF) is a rare Philadelphia chromosome\u0026ndash;negative myeloproliferative neoplasm with an annual incidence of ~\u0026thinsp;0.5 per 100,000 and a median age at diagnosis of ~\u0026thinsp;65 years[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. It is characterized by progressive bone marrow fibrosis, extramedullary hematopoiesis with splenomegaly, constitutional symptoms, and a risk of leukemic transformation[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The prognosis is poor compared with other MPNs, with median survival ranging from \u0026gt;\u0026thinsp;10 years in low-risk patients to 2\u0026ndash;3 years in those at high risk[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. MF pathogenesis involves the clonal proliferation of hematopoietic stem cells, frequently with Janus kinase 2 (\u003cem\u003eJAK2\u003c/em\u003e), calreticulin (\u003cem\u003eCALR\u003c/em\u003e), or myeloproliferative leukemia protein (\u003cem\u003eMPL\u003c/em\u003e) mutations, and an altered bone marrow microenvironment producing pro-fibrotic cytokines such as transforming growth factor beta 1 (TGF-β1) and bone morphogenetic protein 2 (BMP-2)[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eRisk stratification is most commonly performed using the DIPSS, which incorporates age, hemoglobin, leukocyte count, peripheral blasts, and constitutional symptoms, with anemia weighted double[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. High molecular risk mutations (e.g., ASXL transcriptional regulator 1 [\u003cem\u003eASXL1\u003c/em\u003e], serine and arginine rich splicing factor 2 [\u003cem\u003eSRSF2\u003c/em\u003e], enhancer of zeste 2 polycomb repressive complex 2 subunit [\u003cem\u003eEZH2\u003c/em\u003e], and isocitrate dehydrogenase 1 and 2 [\u003cem\u003eIDH1/2\u003c/em\u003e]) further worsen prognosis[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Treatment is risk-adapted. Low-risk or asymptomatic patients may be observed, while intermediate-2, high-risk**,** or symptomatic patients typically receive JAK inhibitors such as ruxolitinib[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], fedratinib[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], pacritinib[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], or momelotinib[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. These agents improve symptoms and splenomegaly but rarely achieve molecular remission or significantly extend survival. Allogeneic hematopoietic stem cell transplantation (allo-HSCT) remains the only potentially curative therapy[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eRecent EBMT/ELN consensus recommendations emphasize allo-HSCT as the only potentially curative option and support its consideration in medically fit patients with intermediate-2 or high-risk MF (and selected intermediate-1 patients with additional adverse features), while integrating comorbidity and molecular risk assessment into decision-making[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Transplant-specific prognostic tools such as the Myelofibrosis Transplant Scoring System (MTSS) have been proposed to refine post-transplant risk estimation[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Notably, current consensus suggests that chronological age alone should not constitute an absolute contraindication, and reduced-intensity conditioning may expand HSCT feasibility in selected older patients[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. In this study, we retrospectively described the outcomes of 42 patients with myelofibrosis who underwent allo-HSCT at a single center between 2014 and 2023. We focused on pre-transplant DIPSS risk as the primary stratification variable, and evaluated age and other transplant- and disease-related factors in secondary exploratory analyses.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatient selection and data collection\u003c/h2\u003e \u003cp\u003eWe performed a retrospective cohort study of patients with myelofibrosis who underwent allo-HSCT at Samsung Medical Center between 2014 and 2023. A total of 42 patients were identified through the institutional transplant database, including those with primary myelofibrosis (PMF), post-polycythemia vera myelofibrosis (post-PV MF), and post-essential thrombocythemia myelofibrosis (post-ET MF). This study was conducted in accordance with the ethical principles of the Declaration of Helsinki (as revised in 2013) and the Korean Good Clinical Practice guidelines. Approval was obtained from the Institutional Review Board at Samsung Medical Center (IRB No. 2025-11-108), and the requirement for individual informed consent was waived. Patients were identified by anonymized patient numbers only, and personally identifiable information was kept confidential according to the IRB protocol.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eDefinitions of variables and outcomes\u003c/h3\u003e\n\u003cp\u003eThe variables examined included sex, MF subtype, and donor type (matched sibling donor [MSD], matched unrelated donor [MUD], or haploidentical donor). Conditioning intensity (myeloablative conditioning [MAC] vs. reduced-intensity conditioning [RIC]), DIPSS risk at transplantation, and the hematopoietic cell transplantation-specific comorbidity index (HCT-CI; \u0026lt;3 vs. \u0026ge;3) were incorporated to address potential confounders. Clinical factors, including pre-transplant spleen size, constitutional symptoms, and JAK inhibitor exposure and response, were also recorded. Driver mutation status (\u003cem\u003eJAK2\u003c/em\u003e, \u003cem\u003eCALR\u003c/em\u003e, \u003cem\u003eMPL\u003c/em\u003e) was included, and next-generation sequencing (NGS) results were incorporated where available.\u003c/p\u003e \u003cp\u003eThe primary outcome was OS after transplantation, stratified by DIPSS risk. OS was calculated from the date of HSCT to the date of death from any cause or the date of last follow-up, with surviving patients censored at last contact. Secondary analyses evaluated OS by age group (\u0026ge;\u0026thinsp;60 vs. \u0026lt;60 years) and other factors, including donor type, conditioning regimen, HCT-CI, driver mutation status, and spleen size. DIPSS component variables were not tabulated by risk group to avoid circularity.\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eSurvival curves were estimated using the Kaplan-Meier method and compared using the log-rank test. Categorical variables were compared using the chi-square test or Fisher\u0026rsquo;s exact test, as appropriate. Given the limited sample size and inherent baseline imbalances, all analyses were considered exploratory, and \u003cem\u003eP\u003c/em\u003e-values were interpreted with caution. Exploratory Cox proportional hazards regression was performed as a sensitivity analysis and is provided in the Supplementary Appendix (Supplementary Table\u0026nbsp;1 and Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Advanced statistical techniques (e.g., propensity score matching and competing-risk models) were not pursued given the limited number of cases and events. Analyses were performed using R version 4.2.2 (R Foundation for Statistical Computing, Vienna, Austria).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eBaseline characteristics\u003c/h2\u003e \u003cp\u003eFrom 2014 to 2023, 42 patients with myelofibrosis underwent allo-HSCT. At transplantation, 28 patients (66.7%) had Intermediate (Int-1/2) DIPSS risk, and 14 (33.3%) had High DIPSS risk (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The Intermediate group was predominantly male (71.4%) and comprised mostly patients with PMF (82.1%). Donor types included MSD (32.1%), haploidentical (28.6%), and MUD (39.3%). The High-risk group was also predominantly male (92.9%), with a higher proportion of haploidentical donors (57.1%). All patients received busulfan plus fludarabine-based conditioning; BuFlu2 was used in all High-risk patients, whereas BuFlu4 was used in 50.0% of Intermediate-risk patients. An HCT-CI\u0026thinsp;\u0026ge;\u0026thinsp;3 was observed in 42.9% and 57.1% of Intermediate- and High-risk patients, respectively. Spleen size categories and prior ruxolitinib exposure were broadly similar between the groups (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics of 42 myelofibrosis patients undergoing allogeneic HSCT, stratified by DIPSS risk group at transplantation (Intermediate [Int-1/2] vs High)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIntermediate (n\u0026thinsp;=\u0026thinsp;28)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHigh (n\u0026thinsp;=\u0026thinsp;14)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20 (71.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13 (92.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8 (28.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1 (7.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTypes\u003c/b\u003e of myelofibrosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePMF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23 (82.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9 (64.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.337\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePost ET MF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3 (10.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4 (28.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePost PV MF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2 (7.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1 (7.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDriver mutation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7 (25.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2 (14.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJAK2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13 (46.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9 (64.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCALR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4 (14.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMPL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3 (10.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1 (7.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1 (3.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2 (14.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDonor type\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMatched sibling donor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9 (32.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1 (7.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.106\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHaploidentical\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8 (28.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8 (57.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMatched unrelated donor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11 (39.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5 (35.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eConditioning regimen\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBuFlu4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14 (50.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBuFlu2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14 (50.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHCT-CI score\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16 (57.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6 (42.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.515\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12 (42.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8 (57.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNGS available\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9 (32.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4 (28.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19 (67.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10 (71.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSpleen size before HSCT\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLongest diameter\u0026thinsp;\u0026lt;\u0026thinsp;22 cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19 (67.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9 (64.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.715\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLongest diameter\u0026thinsp;\u0026ge;\u0026thinsp;22 cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8 (28.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5 (35.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSplenectomy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1 (3.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePrevious ruxolitinib exposure\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18 (64.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11 (78.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.485\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10 (35.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3 (21.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eResponse to JAK inhibitor among exposed (descriptive)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAny response\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16 (88.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8 (72.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.339\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisease progression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2 (11.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3 (27.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eAll patients received busulfan plus fludarabine-based conditioning regimens.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eComparisons between groups are exploratory; p-values should be interpreted with caution.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eDIPSS component variables (age, hemoglobin, leukocyte count, peripheral blasts, and constitutional symptoms) were not tabulated by risk group to avoid circularity. Abbreviations: ET, Essential thrombocythemia; MF, Myelofibrosis; PV, Polycythemia vera; JAK2, Janus kinase 2; CALR, Calreticulin; MPL, Myeloproliferative leukemia protein; Bu, Busulfan; Flu, Fludarabine; HCT-CI, Hematopoietic Cell Transplantation\u0026ndash;Comorbidity Index; NGS, Next-generation sequencing; HSCT, Hematopoietic stem cell transplantation\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eOverall survival according to DIPSS risk and age\u003c/h2\u003e \u003cp\u003eOS was significantly inferior in the High-risk group (log-rank \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0034) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The median OS was 15.2 months (95% CI, 7.2\u0026ndash;NR) in the Intermediate group and 6.4 months (95% CI, 3.3\u0026ndash;35.1) in the High-risk group. All 14 High-risk patients (100%) died during follow-up, compared with 14 of 28 (50.0%) in the Intermediate group. The 1-year OS was 57.1% versus 28.6%, the 2-year OS was 50.0% versus 14.3%, and the 3-year OS was 50.0% versus 7.1% for the Intermediate and High-risk groups, respectively. A swimmer plot illustrating patient-level follow-up by DIPSS risk is shown in Supplementary Fig.\u0026nbsp;4. In the age-based comparison (\u0026ge;\u0026thinsp;60 vs. \u0026lt;60 years), the median OS was 8.0 months (95% CI, 5.4\u0026ndash;36.3) in the \u0026ge;\u0026thinsp;60-year group and 15.2 months (95% CI, 6.3\u0026ndash;NR) in the \u0026lt;\u0026thinsp;60-year group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.16) (Supplementary Fig.\u0026nbsp;1).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eExploratory subgroup and multivariable analyses\u003c/h3\u003e\n\u003cp\u003eUnivariable subgroup analyses are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003e. DIPSS High risk showed the strongest association with inferior OS (HR, 2.93; 95% CI, 1.38\u0026ndash;6.21) ; all other subgroup estimates were not statistically significant. In the exploratory multivariable Cox regression analysis (Supplementary Table\u0026nbsp;1), DIPSS High risk remained independently associated with inferior OS after adjustment for HCT-CI and donor type (adjusted HR, 2.91; 95% CI, 1.27\u0026ndash;6.63; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.011), whereas age\u0026thinsp;\u0026ge;\u0026thinsp;60 years was not significant (adjusted HR, 1.65; 95% CI, 0.66\u0026ndash;4.15; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.30). These models are presented as hypothesis-generating and should not be interpreted as confirmatory.\u003c/p\u003e\n\u003ch3\u003eDriver mutation and spleen size\u003c/h3\u003e\n\u003cp\u003eNo significant differences in OS were observed according to driver mutation status (log-rank \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.10) (Supplementary Fig.\u0026nbsp;2) or spleen size category before transplantation (log-rank \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.85) (Supplementary Fig.\u0026nbsp;3). Spleen size was categorized by the longest diameter (\u0026lt;\u0026thinsp;22 cm vs. \u0026ge;22 cm) ; one patient with a prior splenectomy was excluded from this analysis.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eCause of death\u003c/h2\u003e \u003cp\u003eOverall, 28 deaths occurred during follow-up. Infection was the most frequent cause of death in both groups (Intermediate: 9/28 [32.1%]; High: 6/14 [42.9%]), followed by disease progression and graft-versus-host disease (GVHD) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Among the 13 patients who died within the first 6 months after HSCT, 9 (69.2%) died of infection, compared with 6 of 15 (40.0%) among those who died at \u0026ge;\u0026thinsp;6 months. Because the post-transplant disease status near the time of death was not uniformly available, deaths were not formally attributed to relapse-related versus non-relapse mortality.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCauses of death stratified by DIPSS risk group at transplantation\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCauses of death\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIntermediate (N\u0026thinsp;=\u0026thinsp;28)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHigh (N\u0026thinsp;=\u0026thinsp;14)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of deaths\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14 (50.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInfection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9 (32.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6 (42.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisease progression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2 (7.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3 (21.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGVHD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1 (3.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3 (21.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBleeding (Engraftment failure)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1 (3.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1 (3.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2 (14.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this single-center retrospective cohort study, DIPSS risk at transplantation was the only clinical variable significantly associated with post-transplant OS. All 14 patients transplanted with DIPSS High-risk disease died during follow-up, with a median OS of only 6.4 months, compared with 15.2 months in the Intermediate group. In exploratory multivariable models, DIPSS High risk retained an independent association with inferior OS (adjusted HR, 2.91; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.011), whereas no other variable\u0026mdash;including age, HCT-CI, and donor type\u0026mdash;reached statistical significance. Notably, all DIPSS High-risk patients in this cohort were aged\u0026thinsp;\u0026ge;\u0026thinsp;60 years, precluding the reliable separation of age and disease risk effects ; the observed trend toward inferior OS in older recipients (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.16) is likely driven by this overlap rather than by an independent effect of age\u003c/p\u003e \u003cp\u003eThese findings suggest that the disease burden captured by the DIPSS at transplantation is a critical determinant of post-transplant outcomes, and that allo-HSCT should ideally be pursued before progression to DIPSS High-risk disease [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Our findings suggest that progression to DIPSS High-risk disease before transplantation may substantially limit the benefit of allo-HSCT. Whether this reflects an inherently aggressive disease biology that is resistant to the graft-versus-myelofibrosis effect, increased transplant-related toxicity in patients with a greater disease burden, or both, cannot be determined from our data. These observations support the concept of a therapeutic window for allo-HSCT in MF, in which transplantation is most likely to be beneficial when performed before progression to high-risk disease.\u003c/p\u003e \u003cp\u003eConsistent with the updated EBMT/ELN recommendations, risk stratification is central to transplant decision-making in MF [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. In our cohort, DIPSS High risk was associated with inferior OS in both unadjusted and exploratory adjusted analyses. Transplant-specific scoring systems, such as the MTSS, may further refine post-transplant risk estimation [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. However, comprehensive molecular annotation was limited because NGS data were available for only a subset of patients, precluding the evaluation of high-molecular-risk features. In particular, integrated clinical-molecular scoring systems such as MIPSS70\u0026thinsp;+\u0026thinsp;v2.0 [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] incorporate high-molecular-risk mutations and cytogenetic findings that were not systematically available in our cohort. Future studies with comprehensive molecular annotation will be essential to determine whether molecular risk features refine the prognostic impact of the DIPSS category in the transplant setting.\u003c/p\u003e \u003cp\u003eAlthough not statistically significant, we observed a trend toward poorer outcomes in patients who were triple-negative or harbored \u003cem\u003eJAK2\u003c/em\u003e mutations. Given the limited sample size and incomplete molecular data, these findings should be interpreted cautiously [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Spleen size before transplantation was not associated with survival in our cohort. Data from large registry analyses have shown that although splenectomy itself does not have a major impact on overall survival, smaller spleen size has been associated with better outcomes [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Our findings may reflect limited statistical power. Taken together, rather than performing splenectomy or splenic irradiation solely to reduce spleen size, it may be reasonable in transplant-eligible patients with advanced-risk MF to use JAK inhibitors primarily as pretransplant optimization or bridging therapy, with spleen reduction as a secondary benefit when achieved [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. In patients who do not respond to JAK inhibitors, prognosis can remain poor even with transplantation, and alternative approaches or supportive care should be considered [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eInfection was the most frequently recorded cause of death. Infection-related deaths were more frequent within the first 6 months after HSCT. These observations should be interpreted cautiously because we did not perform competing-risk or time-dependent analyses. Reduced-intensity conditioning was commonly used in this selected population and was deliverable, although the small sample size precludes firm conclusions regarding comparative effectiveness [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOur study has several limitations. The small sample size and retrospective, single-center design limit statistical power and generalizability. Age-stratified comparisons should be interpreted cautiously because the conditioning regimen, JAK inhibitor use, and DIPSS risk were not uniformly distributed between the age groups. The only statistically significant association observed was OS according to the DIPSS risk category ; all other comparisons should be regarded as hypothesis-generating. When transplantation is considered in patients with DIPSS High-risk disease, pretransplant risk optimization\u0026mdash;including JAK inhibitor bridging therapy\u0026mdash;may be reasonable. If meaningful disease-risk reduction cannot be achieved, non-transplant approaches and supportive care should be discussed, regardless of patient age.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn this single-center retrospective analysis, DIPSS High-risk disease at transplantation was associated with uniformly poor post-transplant survival, with 100% mortality despite allo-HSCT. These findings highlight the importance of transplant timing and suggest that allo-HSCT should be considered before progression to DIPSS High-risk disease. Given the limitations of this small, retrospective cohort, these hypothesis-generating observations warrant validation in multicenter studies incorporating integrated clinical-molecular transplant risk models.\u003c/p\u003e"},{"header":"Declarations","content":" \u003cp\u003e \u003cstrong\u003eEthics Approval and Consent to Participate:\u003c/strong\u003e \u003cp\u003eThis study was conducted in accordance with the ethical principles of the Declaration of Helsinki (as revised in 2013). Approval was obtained from the Institutional Review Board of Samsung Medical Center (IRB No. 2025-11-108). The requirement for individual informed consent was waived by the IRB given the retrospective design.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for Publication:\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCompeting Interests:\u003c/strong\u003e \u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding:\u003c/h2\u003e \u003cp\u003eThis research received no external funding.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eDHC was responsible for study design, data collection, statistical analysis, data interpretation, and manuscript writing. JHJ contributed to data collection, data interpretation, and critical review. CWJ was responsible for study conception and design, data interpretation, critical revision, and supervision. All authors reviewed and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data underlying this article are available from the corresponding author on reasonable request, subject to institutional and ethical regulations.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMora B, Bucelli C, Cattaneo D, Bellani V, Versino F, Barbullushi K, et al. Prognostic and predictive models in myelofibrosis. Curr Hematol Malig Rep. 2024;19:223\u0026ndash;235.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMartino M, Pitea M, Sgarlata A, Delfino IM, Cogliandro F, Scopelliti A, et al. Treatment strategies used in treating myelofibrosis: state of the art. Hematol Rep. 2024;16:698\u0026ndash;713.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLeiva O, Ng SK, Chitalia S, Balduini A, Matsuura S, Ravid K. The role of the extracellular matrix in primary myelofibrosis. Blood Cancer J. 2017;7:e525.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePassamonti F, Cervantes F, Vannucchi AM, Morra E, Rumi E, Cazzola M, et al. Dynamic International Prognostic Scoring System (DIPSS) predicts progression to acute myeloid leukemia in primary myelofibrosis. Blood. 2010;116:2857\u0026ndash;2858.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMartinaud C, Desterke C, Konopacki J, Pieri L, Torossian F, Golub R, et al. Osteogenic potential of mesenchymal stromal cells contributes to primary myelofibrosis. Cancer Res. 2015;75:4753\u0026ndash;4765.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTefferi A, Nicolosi M, Mudireddy M, Lasho TL, Gangat N, Begna KH, et al. Revised cytogenetic risk stratification in primary myelofibrosis: analysis based on 1002 informative patients. Leukemia. 2018;32:1189\u0026ndash;1199.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVerstovsek S, Mesa RA, Gotlib J, Levy RS, Gupta V, DiPersio JF, et al. A double-blind, placebo-controlled trial of ruxolitinib for myelofibrosis. N Engl J Med. 2012;366:799\u0026ndash;807.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePardanani A, Harrison C, Cortes JE, Cervantes F, Mesa RA, Milligan D, et al. Safety and efficacy of fedratinib in patients with primary or secondary myelofibrosis: a randomized clinical trial. JAMA Oncol. 2015;1:643\u0026ndash;651.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMascarenhas J, Hoffman R, Talpaz M, Gerds AT, Stein B, Gupta V, et al. Pacritinib vs best available therapy, including ruxolitinib, in patients with myelofibrosis: a randomized clinical trial. JAMA Oncol. 2018;4:652\u0026ndash;659.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMesa RA, Kiladjian JJ, Catalano JV, Devos T, Egyed M, Hellmann A, et al. SIMPLIFY-1: a phase III randomized trial of momelotinib versus ruxolitinib in Janus kinase inhibitor-naive patients with myelofibrosis. J Clin Oncol. 2017;35:3844\u0026ndash;3850.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRanalli P, Natale A, Guardalupi F, Santarone S, Canto C, La Barba G, et al. Myelofibrosis and allogeneic transplantation: critical points and challenges. Front Oncol. 2024;14:1396435.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKroger N, Bacigalupo A, Barbui T, Ditschkowski M, Gagelmann N, Griesshammer M, et al. Indication and management of allogeneic haematopoietic stem-cell transplantation in myelofibrosis: updated recommendations by the EBMT/ELN international working group. Lancet Haematol. 2024;11:e62\u0026ndash;e74.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGagelmann N, Ditschkowski M, Bogdanov R, Bredin S, Robin M, Cassinat B, et al. Comprehensive clinical-molecular transplant scoring system for myelofibrosis undergoing stem cell transplantation. Blood. 2019;133:2233\u0026ndash;2242.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFauble V, Leis J, Mesa RA. Allogeneic stem cell transplant for myelofibrosis patients over age 60: likely impact of the \u003cem\u003eJAK2\u003c/em\u003e inhibitors. Leuk Suppl. 2012;1:S2\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDaghia G, Zabelina T, Zeck G, von Pein UM, Christopeit M, Wolschke C, et al. Allogeneic stem cell transplantation for myelofibrosis patients aged **\u0026ge;**65 years. Eur J Haematol. 2019;103:370\u0026ndash;378.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDitschkowski M, Elmaagacli AH, Trenschel R, Gromke T, Steckel NK, Koldehoff M, et al. Dynamic International Prognostic Scoring System scores, pre-transplant therapy and chronic graft-versus-host disease determine outcome after allogeneic hematopoietic stem cell transplantation for myelofibrosis. Haematologica. 2012;97:1574\u0026ndash;1581.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCooper JP, Scott BL. Allogeneic transplantation for myelofibrosis with adverse risk karyotype: attack on the clones? Am J Hematol. 2018;93:603\u0026ndash;604.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTefferi A, Lasho TL, Finke CM, Knudson RA, Ketterling R, Hanson CH, et al. \u003cem\u003eCALR\u003c/em\u003e vs \u003cem\u003eJAK2\u003c/em\u003e vs \u003cem\u003eMPL\u003c/em\u003e-mutated or triple-negative myelofibrosis: clinical, cytogenetic and molecular comparisons. Leukemia. 2014;28:1472\u0026ndash;1477.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchulze S, Stengel R, Jaekel N, Wang SY, Franke GN, Roskos M, et al. Concomitant and noncanonical \u003cem\u003eJAK2\u003c/em\u003e and \u003cem\u003eMPL\u003c/em\u003e mutations in \u003cem\u003eJAK2\u003c/em\u003eV617F- and \u003cem\u003eMPL\u003c/em\u003eW515L-positive myelofibrosis. Genes Chromosomes Cancer. 2019;58:747\u0026ndash;755.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePolverelli N, Mauff K, Kroger N, Robin M, Beelen D, Beauvais D, et al. Impact of spleen size and splenectomy on outcomes of allogeneic hematopoietic cell transplantation for myelofibrosis: a retrospective analysis by the chronic malignancies working party on behalf of European Society for Blood and Marrow Transplantation (EBMT). Am J Hematol. 2021;96:69\u0026ndash;79.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKroger N, Sbianchi G, Sirait T, Wolschke C, Beelen D, Passweg J, et al. Impact of prior JAK-inhibitor therapy with ruxolitinib on outcome after allogeneic hematopoietic stem cell transplantation for myelofibrosis: a study of the CMWP of EBMT. Leukemia. 2021;35:3551\u0026ndash;3560.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePolverelli N, Hernandez-Boluda JC, Czerw T, Barbui T, D\u0026rsquo;Adda M, Deeg HJ, et al. Splenomegaly in patients with primary or secondary myelofibrosis who are candidates for allogeneic hematopoietic cell transplantation: a position paper on behalf of the chronic malignancies working party of the EBMT. Lancet Haematol. 2023;10:e59\u0026ndash;e70.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHarrison CN, Kiladjian JJ, Koschmieder S, Passamonti F. Myelofibrosis: current unmet needs, emerging treatments, and future perspectives. Cancer. 2024;130:2091\u0026ndash;2097.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eReynolds SB, Pettit K. New approaches to tackle cytopenic myelofibrosis. Hematology Am Soc Hematol Educ Program. 2022;2022:235\u0026ndash;244.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMurthy GSG, Kim S, Estrada-Merly N, Abid MB, Aljurf M, Assal A, et al. Association between the choice of the conditioning regimen and outcomes of allogeneic hematopoietic cell transplantation for myelofibrosis. Haematologica. 2023;108:1900\u0026ndash;1908.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLuque Paz D, Gagelmann N, Benajiba L, Riou J, Salit R, Orvain C, et al. Role of molecular alterations in transplantation decisions for patients with primary myelofibrosis. Blood Adv. 2025;9:797\u0026ndash;807.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAli H, Aldoss I, Yang D, Mokhtari S, Khaled S, Aribi A, et al. MIPSS70\u0026thinsp;+\u0026thinsp;v2.0 predicts long-term survival in myelofibrosis after allogeneic HCT with the flu/mel conditioning regimen. Blood Adv. 2019;3:83\u0026ndash;95.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMachherndl-Spandl S, Hannouf S, Nikoloudis A, Zach O, Strassl I, Kaynak E, et al. Improved outcomes in myelofibrosis after allogeneic stem-cell transplantation in the era of ruxolitinib pretreatment and intensified conditioning regimen: single-center analysis. Cancers (Basel). 2024;16.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGagelmann N, Hobbs GS, Campodonico E, Helbig G, Novak P, Schroeder T, et al. Splenic irradiation for myelofibrosis prior to hematopoietic cell transplantation: a global collaborative analysis. Am J Hematol. 2024;99:844\u0026ndash;853.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHelbig G, Wieczorkiewicz-Kabut A, Markiewicz M, Krzemien H, Wojciak M, Bialas K, et al. Splenic irradiation before allogeneic stem cell transplantation for myelofibrosis. Med Oncol. 2019;36:16.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":false,"email":"","identity":"blood-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"BLOOD RESEARCH","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"VoR Journals","inReviewEnabled":false,"inReviewRevisionsEnabled":false},"keywords":"Myelofibrosis, allogeneic stem cell transplantation, DIPSS, prognosis, overall survival, transplant outcomes, risk stratification","lastPublishedDoi":"10.21203/rs.3.rs-9039701/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9039701/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eTo describe post-transplant outcomes in patients with myelofibrosis stratified by the Dynamic International Prognostic Scoring System (DIPSS) risk at transplantation, and to identify clinical factors associated with overall survival (OS) after allogeneic hematopoietic stem cell transplantation (allo-HSCT).\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe retrospectively analyzed 42 patients with myelofibrosis who underwent allo-HSCT at Samsung Medical Center between 2014 and 2023. OS was estimated using the Kaplan-Meier method and compared via the log-rank test. Exploratory Cox proportional hazards regression analyses were performed to assess independent associations with OS.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAt transplantation, 28 patients (66.7%) had Intermediate (Int-1/2) and 14 (33.3%) had High DIPSS risk. OS differed significantly by DIPSS risk group (log-rank p\u0026thinsp;=\u0026thinsp;0.0034): the median OS was 15.2 months (95% CI, 7.2\u0026ndash;NR) in the Intermediate group versus 6.4 months (95% CI, 3.3\u0026ndash;35.1) in the High-risk group. All 14 High-risk patients (100%) died during follow-up, compared with 14 of 28 (50.0%) in the Intermediate group. The 1-year OS was 57.1% versus 28.6%, 2-year OS was 50.0% versus 14.3%, and 3-year OS was 50.0% versus 7.1%, respectively. In an exploratory multivariable analysis adjusting for HCT-CI and donor type, DIPSS High risk remained independently associated with inferior OS (adjusted HR, 2.91; 95% CI, 1.27\u0026ndash;6.63; p\u0026thinsp;=\u0026thinsp;0.011). No other clinical variable, including age (\u0026ge;\u0026thinsp;60 vs. \u0026lt;60 years; p\u0026thinsp;=\u0026thinsp;0.16 by log-rank), achieved statistical significance.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eDIPSS High-risk disease at transplantation was associated with uniformly poor post-transplant survival in this single-center cohort. These hypothesis-generating findings underscore the importance of transplant timing before progression to high-risk disease, and warrant validation in larger, multicenter studies.\u003c/p\u003e","manuscriptTitle":"Allogeneic stem cell transplantation for myelofibrosis in the modern era: single- center outcomes with DIPSS risk stratification","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-19 16:23:02","doi":"10.21203/rs.3.rs-9039701/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-10T01:25:37+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-08T14:01:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"235375951318503946295276559139426024188","date":"2026-03-18T08:45:43+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-17T05:28:26+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-13T06:36:31+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-12T05:27:56+00:00","index":"","fulltext":""},{"type":"submitted","content":"BLOOD RESEARCH","date":"2026-03-05T11:43:20+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":false,"email":"","identity":"blood-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"BLOOD RESEARCH","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"VoR Journals","inReviewEnabled":false,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"95f9c8a9-2d32-40b7-b21f-7642a1e07122","owner":[],"postedDate":"March 19th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-04T06:55:56+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-19 16:23:02","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9039701","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9039701","identity":"rs-9039701","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}