Early Failure of Induction Impacts Transplant Outcomes in Hodgkin Lymphoma Revealed Through A Longitudinal Nationwide Registry in Taiwan

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Autologous stem cell transplantation (ASCT) is the standard of care in this setting, yet the prognostic impact of early failure of induction (EFI) chemotherapy has not been characterized in Asian populations. This nationwide, multicenter, retrospective longitudinal analysis evaluated the association between EFI and post-ASCT outcomes. Among 238 ASCT-treated patients, 46.6% occurred EFI and was associated with inferior 5-year overall survival (OS) compared to non-EFI (75% vs. 90%, p = 0.013). In multivariable Cox regression, EFI (hazard ratio [HR] 2.21, 95% confidence interval [CI] 1.07–4.58, p = 0.032) and Charlson comorbidity index >2 (HR 3.40, 95% CI 1.63–7.09, p = 0.001)independently predicted poorer OS. Restricted cubic spline modeling demonstrated a dose–response relationship between induction failure duration and mortality risk. These findings were confirmed through propensity score matching and inverse probability of treatment weighting analyses. Among patients who experienced relapse following their first transplantation, EFI remained an adverse prognostic factor (2-year OS, EFI vs. non-EFI: 59% vs. 82%, p = 0.049). This study addresses a crucial gap by providing insights into post-transplantation outcomes and informing future treatment strategies for patients with HL in Asian. Biological sciences/Cancer/Haematological cancer/Lymphoma/Hodgkin lymphoma Biological sciences/Cancer/Cancer therapy/Chemotherapy Figures Figure 1 Figure 2 Figure 3 Introduction Hodgkin lymphoma (HL) is a B cell lymphoproliferative malignancy, demonstrate a favorable overall survival (OS) rate ranging between 80% and 90% for frontline treatment (ref. 1). Nevertheless, in relapsed or refractory HL, autologous stem cell transplantation (ASCT) remains the established standard of care with a cure rate of approximately 50% (ref. 2). Traditionally, early-stage HL has been defined as unfavorable in various prognostic models based on risk factors including “B” symptoms with elevated ESR, large mediastinal mass, nodal sites, bulky disease, and extranodal lesions (ref. 3). The International Prognostic Score (IPS) with seven variables has been developed as a prognostic model for advanced-stage cancer (ref. 4). However, most of these prognostic models were developed in clinical trials during the radiotherapy era, and current therapeutic advancements lead researchers to question their influence on treatment outcomes (ref. 3). Interim positron emission tomography (PET) predicts progression-free survival (PFS) and led to the development of risk-adaptive treatment strategies in some pivotal studies (ref. 5, 6). In various lymphoid malignancies, including follicular lymphoma and MALToma, early progression is associated with poor OS (ref. 7, 8). Early progression of HL has been acknowledged as a predictor of unfavorable prognosis and serves as an inclusion criterion for clinical trials evaluating therapies for high relapse risk after ASCT. However, evidence that early failure of induction (EFI) continues to influence outcomes once patients are successfully bridged to transplantation is still sparse. (ref. 9). Even in the brentuximab vedotin (BV) era, some patients still proceed to ASCT because their frontline response is inadequate; the outcomes of this subgroup after transplantation, however, remain unreported (ref. 1). Accordingly, the present study evaluates real-world outcomes of HL patients undergoing hematopoietic stem-cell transplantation (HSCT) in Taiwan and examines whether EFI is independently associated with inferior post-SCT survival. Patients and methods Patients diagnosed with HL who underwent HSCT between February 2002 and August 2022 were included. Data were retrieved from the Taiwan Society of Blood and Marrow Transplantation (TBMT) Research database, a nationwide registry that collects clinical data from 17 collaborative transplantation centers in Taiwan. Clinical data, including baseline characteristics at diagnosis, chemotherapy regimens, pre-transplantation evaluations, transplantation, and survival, were collected. EFI chemotherapy was defined as an interval of <12 months between the initiation of the first induction therapy and salvage therapy (Figure S1). This study was approved by the Research Ethics Committee of the National Taiwan University Hospital, and data were collected in accordance with the Declaration of Helsinki. (Approval number: 202005129RINC) Our primary objective was to elucidate the survival outcomes among patients who underwent transplantation for HL and to investigate the impact of early disease progression on survival to provide information for future care. OS was defined as the time from induction to death from any cause and event-free survival (EFS) was defined as the time from induction to the occurrence of disease progression following SCT, initiation of salvage therapy post-transplant, or death from any cause after transplantation. In the subgroup of patients who relapsed after SCT, a subsequent analysis was conducted with OS defined as the time from post-transplant relapse to death from any cause. The data of 286 patients with HL who underwent HSCT were retrieved from the TBMT database. Patients with composite lymphoma, nodular lymphocyte-predominant HL, and allogeneic SCT (allo-SCT) at first transplantation were excluded from the primary analysis (Figure S2). All patients with a detailed treatment history were included in the analysis of the prognostic value of EFI, and cases with missing data were excluded from the Cox proportional hazards model. Continuous variables are expressed as medians with interquartile ranges and were compared using the Mann–Whitney U test. Categorical variables were compared using the chi-square test or Fisher’s exact test. Kaplan–Meier estimates were used to describe OS and EFS, and the log-rank test was used to compare groups. The Cox proportional hazard model was used for univariable regression analysis, while variables with a p value <0.2 considered to be clinically significant were included in multivariable Cox regression analysis. The assumptions for proportional hazards were verified. To confirm the results of regression analysis, propensity score matching (PSM) and inverse probability treatment weighting (IPTW) were performed. Propensity scores were derived using logistic regression incorporating clinically relevant variables, including transplantation age, sex, Charlson comorbidity index (CCI) >2, diagnosis after 2016, Ann Arbor stage III/IV, histologic subtype, IPS >2, pre-transplantation brentuximab vedotin (BV) exposure, and pre-transplantation disease status. PSM was conducted using 1:1 optimal matching with a caliper of 0.2 standard deviations. IPTW was applied using stabilized inverse probability weights to estimate the average treatment effect, creating a balanced pseudo-population that simulates randomization. Standardized mean differences (SMD) were used to assess covariate balance between groups before and after PSM or IPTW, with SMD <0.1 indicating sufficient balance. To further evaluate the prognostic impact of the time interval from the initiation of induction therapy to the start of salvage therapy (defined as failure of induction [FI] duration, Figure S1), and FI duration was analyzed as a continuous variable. Given the potential non-linear association between duration of EFI and OS, restricted cubic spline (RCS) method for data modeling was applied. Cox regression models incorporating EFI as a linear term were compared with RCS-based models using three, four, or five knots. Model selection was guided by Akaike information criterion (AIC), Bayesian information criterion (BIC), and concordance index (C-index). The Wald test was used to assess the statistical significance of non-linear relationships identified in the RCS models. A p < 0.05 is considered statistically significant. All statistical analyses were performed using Stata, version 18 (StataCorp, TX, USA) and R software version 4.4.2 (R Foundation for Statistical Computing, Vienna, Austria). Results Baseline patient demographics This study included 286 patients with HL who underwent HSCT. To maintain homogeneity in our study population, we excluded patients with composite lymphoma (n = 10), nodular lymphocyte-predominant HL (n = 21), and those who underwent allo-SCT during the first transplantation (n = 15). The patients’ baseline characteristics are listed in Table 1. The most common histological subtype was nodular sclerosis (75.4%) followed by mixed cellularity (18.5%). Among the 149 patients with an available IPS, 43.9% had a score greater than 2. Patients who received salvage therapy within 12 months of the start of induction therapy were defined as those with EFI, accounting for 46.6% of the 238 patients. EFI was more frequently observed among patients diagnosed after 2016 (34.2% vs. 27.1%, p = 0.03) and those with an IPS score >2 (51.9% vs. 43.6%, p = 0.046), compared to the non-EFI group. Other baseline characteristics did not differ significantly between groups. Treatment The most common first-line induction therapy was adriamycin, bleomycin, vinblastine, and dacarbazine (ABVD; 89.0%), followed by alternating COMP/ABVD (4.7%). As for salvage therapy, the most common regimen was ESHAP (48.9%), followed by ICE (16.9%) and DHAP (4.8%) (Figure S3). A total of 35 patients (14.7%) received brentuximab vedotin (BV) before transplantation, whereas five patients received immune checkpoint inhibitors (mainly pembrolizumab or nivolumab) before HSCT. A total of 38.7% of patients were in complete remission before HSCT. HSCT All patients underwent autologous SCT, with peripheral blood being the dominant stem cell source. Most patients (64.9%) who underwent ASCT received BCNU, etoposide, cytarabine, and melphalan (BEAM)-based conditioning regimens, whereas only 10.5% received gemcitabine, busulfan, and melphalan (GemBuMel)-based regimens. Twenty-seven patients underwent a second transplantation: 33.3% underwent ASCT and 66.7% underwent allo-SCT. The most common reason for a second transplantation was relapse or refractory disease (n = 23, 85.2%). Among the 18 patients who underwent allo-SCT, 50% were from matched sibling donors, 11% were from unrelated donors, and 39% were from haploidentical donors. Survival outcomes At a median follow-up of 4.6 years, the median overall survival (OS) was not reached. The 5-year OS rate was 85% (95% confidence interval [CI], 80%–91%; Figure 1A). The median EFS was 7.2 years, with a 5-year EFS rate of 60% (95% CI, 53%–68%; Figure 1B). Patients with EFI had significantly worse OS compared to those without EFI (5-year OS: 78% vs. 90%; p = 0.013, log-rank test; Figure 1C). Similarly, EFI was associated with inferior EFS (5-year EFS: 50% vs. 68%; p = 0.004, log-rank test; Figure 1D). Post-transplantation BV consolidation was administered to 43 (18.1%) patients and was not associated with a difference in survival ( p = 0.75) or stratification according to EFI status ( p = 0.93; EFI group, p = 0.72 in non-EFI group). Among the 35 patients with detailed cycles of BV consolidation, the median number of cycles received was seven, with a large variation (range 1–24) (Figure S4). The univariable Cox regression revealed that CCI >2 is associated with a significant inferior OS (hazard ratio (HR) for death 3.40 [95% CI, 1.66–6.95], p = 0.001; Table 2), as well as EFI status (HR for death 2.38 (95% CI, 1.18–4.77, p = 0.015). In multivariable Cox regression analysis, adjusting for EFI, advanced Ann Arbor stage, CCI >2, and pretransplantation disease status, EFI remained an independent predictor of poor OS (adjusted HR for death 3.94 [95% CI1.03–15.02], p = 0.044). Pretransplantation refractory disease was not statistically significant, likely due to the small sample size. Among the patients who experienced relapse after the first transplantation, the 2-year OS rate was 74%. The EFI group had a persistent negative prognostic impact on a worse survival (2-year OS EFI vs. non-EFI: 61% vs. 83%, p = 0.049) (Figure S5). To account for potential confounding factors, we performed additional analyses using PSM and IPTW. Fifty-one matched pairs were selected, achieving balance across most covariates, as evidenced by an absolute SMD <0.01 for all variables except sex (Table 3, Figure S6). In the PSM cohort, EFI was consistently associated with significantly worse OS (5-year OS: 71% vs. 98%; p = 0.003; Figure 2A). Similarly, IPTW analysis demonstrated well-balanced covariates between the EFI and non-EFI groups (Table 3, Figure S6) and confirmed EFI as a predictor of inferior survival (5-year OS: 75% vs. 98%; p = 0.0024; Figure 2B). The effect of FI duration We assessed the prognostic significance of FI duration as a continuous variable, applying restricted cubic splines (RCS) in multivariable Cox regression to account for potential non-linear associations and minimizing information loss from dichotomization into EFI status. The analysis adjusted for age, sex, Ann Arbor stage III/IV, IPS >2, and pretransplantation disease status. Model comparisons were performed by incorporating FI duration as a linear term and as an RCS with three, four, or five knots, evaluating goodness of fit using the AIC, BIC, and C-index. The RCS model with three knots demonstrated the highest C-index, the lowest AIC, and a comparable BIC, indicating the best model fit (Figure S7 and Table S1). Longer FI duration was significantly associated with improved OS (adjusted HR 0.87 [95% CI: 0.78–0.98]; p = 0.03). Moreover, the association was non-linear ( p for non-linearity = 0.04). A short FI duration (<10 months) was associated with an increased hazard of mortality, with HR values exceeding 1 (Figure 3). However, the hazard declined progressively with increasing FI duration, reaching a plateau beyond 20 months, suggesting a potential threshold effect. Allo-SCT Fifteen patients who underwent allo-SCT as the first HSCT were excluded from the primary analysis. Of these, 53% underwent myeloablative conditioning. All patients received peripheral blood as the stem cell source: 33% from matched sibling donors, 40% from unrelated donors, and 27% from haploidentical donors. Four patients (57%) died of infection, two patients (29%) died of progressive or relapsed disease, and one patient died of GVHD. Nodular lymphocyte-predominant HL Twenty-one patients with nodular lymphocyte-predominant HL (NLPHL) were excluded from primary analysis. All patients were diagnosed before 2020, and 65% were treated with ABVD. EFI accounted for 45% of the patients and was not associated with worse OS ( p = 0.14). Discussion To the best of our knowledge, this nationwide retrospective cohort analysis is the first large study in Asia to evaluate the association of early progression and outcomes in patients with HL undergoing HSCT, distinguishing this study from previous ones that primarily focused on defining outcomes and prognostic factors for early progression patients with HL receiving HSCT (ref. 10). Our study demonstrated a 5-year OS of 84% in all patients with HL who underwent HSCT, which was comparable to previous studies (ref. 11, 12). The 6-year OS was higher than that observed by Smith et al. (75% vs. 55%), potentially because of a greater proportion of primary refractory patients in their cohort (11% vs. 50%) (ref. 10). We observed that EFI was correlated with diminished OS and relapse after transplantation. This association remained significant in multivariable Cox regression analysis, where EFI remained an independent predictor of poor OS (adjusted HR for death: 3.94 [95% CI, 1.03–15.02], p =0.044). To mitigate potential confounding factors, we applied propensity score matching (PSM) and inverse probability treatment weighting (IPTW), both of which reinforced EFI as a significant determinant of survival. In line with our previous study, which discussed the early progression of the disease in all patients with HL at two medical centers in Taiwan, an IPS score >2 was more likely to be associated with early progression (ref. 13). Both IPS scores >2 and CCI scores >2 were associated with EFI status. However, neither of these factors was associated with poor OS, indicating that they were not confounding factors when evaluating the role of EFI on OS. Patients with EFIs in our study were similar to those with primary refractory disease or early relapse in other studies. In our study, patients with EFI status comprised 49% of the entire cohort, whereas 65% of patients in the Stanford Hospital cohort exhibited primary refractory or early relapse (ref. 14). Their study demonstrated a 4-year OS rate of 89%, as opposed to 78% in our cohort, possibly attributable to a higher proportion of patients achieving CR or PR (chi-square test, p <0.05) and more widespread utilization of PD-1 inhibitor-based salvage therapy before transplantation. In addition to EFI status, we examined the impact of FI duration as a continuous variable. Using RCS in multivariable Cox regression, we observed a non-linear association between FI duration and OS ( p for non-linearity = 0.04). A shorter FI duration (<10 months) was associated with an increased hazard of mortality, with HR values exceeding 1, whereas the hazard declined progressively with increasing FI duration, stabilizing beyond 20 months. These findings suggest that the timing of disease progression plays a critical role in determining long-term outcomes, and patients with rapid progression may require more aggressive interventions. BV was first reimbursed by Taiwan’s National Health Insurance in 2016 as a frontline therapy in combination with AVD in stage IV CD30+ HL with an IPS >4 or as consolidation therapy after ASCT in patients fulfilling the inclusion criteria of the AETHERA trial. In our cohort, 26.5% of the patients had received BV at any time point, and 18.1% of the patients had post-transplantation BV consolidation. Our study had a higher prevalence of primary refractory disease than the AETHERA trial (60% vs. 11% in our study) (ref. 9). Despite its use, post-transplantation BV consolidation was not associated with improved post-transplantation survival, likely due to the limited sample size in this study. NLPHL accounts for 7% of all patients with HL who undergo transplantation. The ABVD regimen is the most used, with a low prevalence of rituximab use. Compared with that in the EBMT cohort, the 5-year OS rate was lower in our cohort (73% compared to 87% in the EBMT cohort), which was probably attributed to the lower rituximab use in our cohort (5% vs. 63%) (ref. 15). EFI was not associated with worse OS; however, this interpretation should be made cautiously because of the small sample size in the NLPHL cohort. Our study has several limitations. First, the retrospective nature of the study made this susceptible to unmeasured confounding factors, as is common in real-world evidence. Moreover, we used EFS rather than PFS, which requires a retrospective review of PET scans to define disease progression and is not available in the TBMT database. However, most patients with relapse receive subsequent therapy, and EFS is considered to be an acceptable surrogate marker of PFS. Furthermore, the start time of the survival analysis was set at the date of induction therapy, which may have been prone to immortal time bias. However, all patients in this study developed refractoriness to anti-lymphoma treatment or progressive disease and proceeded to ASCT. Our focus is to study the impact of EFI (a pre-HSCT condition) on long-term outcome. As such, both EFI and non-EFI groups were subject to a comparable at-risk period between induction and HSCT, thereby minimizing the risk of asymmetrically granted immortal time and mitigating its potential bias in the survival analysis. Conclusion This study depicted the outcomes of transplantation for HL in an Asian population while emphasizing the important prognostic role of EFI chemotherapy in OS. While acknowledging the confirmatory nature of this study, this holds distinctive significance as Asian-based evidence of a relatively uncommon lymphoma subtype in Asians. Moreover, the poor survival of patients who experience EFI therapy warrants the evaluation of more effective therapeutic regimens, such as immune checkpoint inhibitors, to improve patient outcomes. Declarations Competing Interests statement: The authors declare that they have no competing interests. Author contributions Conceptualization: B.S. Ko, M. Yao, C.C. Li; Study Design: T.C. Huang; Data Curation: H.M. Chang, L.T. Hsiao, C.Y. Hsieh, M.C. Ma, T.L. Lin, Y.T. Hsu, T.D. Tan, Y.Y. Wu, Y.C. Liu, P.Y. Chuang, Y.C. Hong, Y.Y. Chen; Formal Analysis: Y.S. Chang, W.C. Hsieh; Writing – Original; Draft: Y.S. Chang, W.C. Hsieh; Writing – Review & Editing: All authors; Supervision: B.S. Ko, M. Yao, C.C. Li; Project Administration: T.C. Huang, C.C. Li; Approval of Final Manuscript: All authors Acknowledgments The authors express their gratitude to Po-Wei Liao (Division of Hematology-Medical Oncology, Department of Medicine, Taichung Veterans General Hospital), Wei-Han Huang (Department of Hematology & Oncology, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation), Chuan-Cheng Wang (Division of Hematology & Oncology, Department of Internal Medicine, Changhua Christian Hospital), Pei-Ying Hsieh (Division of Oncology-Hematology, Far Eastern Memorial Hospital), Yu-Ting Lee (Division of Hematology and Oncology, Department of Medicine, Ditmanson Medical Foundation Chiayi Christian Hospital) and the staff of the Taiwan Society of Blood and Marrow Transplantation and the Transplant Registry Task Force for providing clinical data. Conflict of Interest Statement The authors report no conflicts of interest. Data availability statement The datasets generated during and analysed during the current study are available from the corresponding author upon reasonable request. References Ansell SM, Radford J, Connors JM, Długosz-Danecka M, Kim WS, Gallamini A, et al. Overall Survival with Brentuximab Vedotin in Stage III or IV Hodgkin's Lymphoma. N Engl J Med. 2022;387(4):310-20. Samara Y, Mei M. Autologous Stem Cell Transplantation in Hodgkin Lymphoma-Latest Advances in the Era of Novel Therapies. Cancers (Basel). 2022;14(7):1738. Klimm B, Goergen H, Fuchs M, von Tresckow B, Böll B, Meissner J, et al. Impact of risk factors on outcomes in early-stage Hodgkin's lymphoma: an analysis of international staging definitions. Ann Oncol. 2013;24(12):3070-6. Hasenclever D, Diehl V. A prognostic score for advanced Hodgkin's disease. International Prognostic Factors Project on Advanced Hodgkin's Disease. N Engl J Med. 1998;339(21):1506-14. Casasnovas RO, Bouabdallah R, Brice P, Lazarovici J, Ghesquieres H, Stamatoullas A, et al. PET-adapted treatment for newly diagnosed advanced Hodgkin lymphoma (AHL2011): a randomised, multicentre, non-inferiority, phase 3 study. Lancet Oncol. 2019;20(2):202-15. Borchmann P, Ferdinandus J, Schneider G, Moccia A, Greil R, Hertzberg M, et al. Assessing the efficacy and tolerability of PET-guided BrECADD versus eBEACOPP in advanced-stage, classical Hodgkin lymphoma (HD21): a randomised, multicentre, parallel, open-label, phase 3 trial. Lancet. 2024;404(10450):341-52. Lipof JJ, Barr PM. Early Progression of Follicular Lymphoma: Biology and Treatment. Hematol Oncol Clin North Am. 2020;34(4):757-69. Conconi A, Thieblemont C, Cascione L, Torri V, Kiesewetter B, Margiotta Casaluci G, et al. Early progression of disease predicts shorter survival in MALT lymphoma patients receiving systemic treatment. Haematologica. 2020;105(11):2592-7. Moskowitz CH, Nademanee A, Masszi T, Agura E, Holowiecki J, Abidi MH, et al. Brentuximab vedotin as consolidation therapy after autologous stem-cell transplantation in patients with Hodgkin's lymphoma at risk of relapse or progression (AETHERA): a randomised, double-blind, placebo-controlled, phase 3 trial. Lancet. 2015;385(9980):1853-62. Smith SD, Moskowitz CH, Dean R, Pohlman B, Sobecks R, Copelan E, et al. Autologous stem cell transplant for early relapsed/refractory Hodgkin lymphoma: results from two transplant centres. Br J Haematol. 2011;153(3):358-63. Akay OM, Ozbalak M, Pehlivan M, Yildiz B, Uzay A, Yigenoglu TN, et al. Brentuximab vedotin consolidation therapy after autologous stem-cell transplantation in patients with high-risk Hodgkin lymphoma: Multicenter retrospective study. Hematol Oncol. 2021;39(4):498-505. Nieto Y, Gruschkus S, Valdez BC, Jones RB, Anderlini P, Hosing C, et al. Improved outcomes of high-risk relapsed Hodgkin lymphoma patients after high-dose chemotherapy: a 15-year analysis. Haematologica. 2022;107(4):899-908. Yu TC, Yu SC, Wang RC, Lai SF, Teng CJ, Lin JW, et al. Investigating early progression of Hodgkin lymphoma in a two-center analysis. J Formos Med Assoc. 2022;121(7):1215-22. Spinner MA, Sica RA, Tamaresis JS, Lu Y, Chang C, Lowsky R, et al. Improved outcomes for relapsed/refractory Hodgkin lymphoma after autologous transplantation in the era of novel agents. Blood. 2023;141(22):2727-37. Akhtar S, Montoto S, Boumendil A, Finel H, Masszi T, Jindra P, et al. High dose chemotherapy and autologous stem cell transplantation in nodular lymphocyte-predominant Hodgkin lymphoma: A retrospective study by the European society for blood and marrow transplantation-lymphoma working party. Am J Hematol. 2018;93(1):40-6. Tables Tables 1 to 3 are available in the Supplementary Files section Additional Declarations The authors have declared there is NO conflict of interest to disclose. Supplementary Files Tables20250528.docx Table 1, Table 2, Table 3 Supplementarymaterials20250528.docx Figure S1, Figure S2, Figure S3, Figure S4, Figure S5, Figure S6, Figure S7, Table S1, Cite Share Download PDF Status: Published Journal Publication published 18 Dec, 2025 Read the published version in Bone Marrow Transplantation → Version 1 posted Editorial decision: revise 17 Jul, 2025 Review # 2 received at journal 13 Jul, 2025 Review # 1 received at journal 07 Jul, 2025 Reviewer # 2 agreed at journal 26 Jun, 2025 Reviewer # 1 agreed at journal 24 Jun, 2025 Reviewers invited by journal 11 Jun, 2025 Submission checks completed at journal 11 Jun, 2025 Editor assigned by journal 11 Jun, 2025 First submitted to journal 11 Jun, 2025 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. 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hospital","correspondingAuthor":false,"prefix":"","firstName":"Ching-Yun","middleName":"","lastName":"Hsieh","suffix":""},{"id":469951398,"identity":"af3829b1-494f-471f-a625-02cda0ac6588","order_by":8,"name":"Ming-Chun Ma","email":"","orcid":"","institution":"Kaohsiung Chang Gung Memorial Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ming-Chun","middleName":"","lastName":"Ma","suffix":""},{"id":469951399,"identity":"af3117c5-00b3-493f-a8fc-39e32c281cbb","order_by":9,"name":"Tung-Liang Lin","email":"","orcid":"","institution":"Chang Gung Memorial Hospital at Linkou","correspondingAuthor":false,"prefix":"","firstName":"Tung-Liang","middleName":"","lastName":"Lin","suffix":""},{"id":469951400,"identity":"2967b6bf-ece6-48fb-bdf9-54350709092b","order_by":10,"name":"Ya-Ting Hsu","email":"","orcid":"","institution":"National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University","correspondingAuthor":false,"prefix":"","firstName":"Ya-Ting","middleName":"","lastName":"Hsu","suffix":""},{"id":469951401,"identity":"227afdc8-dee4-4fec-8c07-a7888d2d3f87","order_by":11,"name":"Tran-Der Tan","email":"","orcid":"","institution":"Koo Foundation Sun Yat-Sen Cancer Center","correspondingAuthor":false,"prefix":"","firstName":"Tran-Der","middleName":"","lastName":"Tan","suffix":""},{"id":469951402,"identity":"f7400dac-66ae-48eb-976f-b60594dbe124","order_by":12,"name":"Yi-Ying Wu","email":"","orcid":"","institution":"Tri-Service General Hospital, National Defense Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Yi-Ying","middleName":"","lastName":"Wu","suffix":""},{"id":469951403,"identity":"52d738c5-4ca5-4ea3-a980-e468dcd3b8a3","order_by":13,"name":"Yi-Chang Liu","email":"","orcid":"","institution":"Kaohsiung Medical University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yi-Chang","middleName":"","lastName":"Liu","suffix":""},{"id":469951404,"identity":"1bce32de-d892-4135-977c-e5958c5dd5b3","order_by":14,"name":"Po-Ya Chuang","email":"","orcid":"","institution":"Taipei Medical University-Shuang Ho Hospital","correspondingAuthor":false,"prefix":"","firstName":"Po-Ya","middleName":"","lastName":"Chuang","suffix":""},{"id":469951405,"identity":"8bc07a43-9f77-4aa3-b88e-af4b92937399","order_by":15,"name":"Ying-Chung Hong","email":"","orcid":"","institution":"Kaohsiung Veterans General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ying-Chung","middleName":"","lastName":"Hong","suffix":""},{"id":469951406,"identity":"48ef9631-48b4-4320-85ff-687edbf29c83","order_by":16,"name":"Yi-Yang Chen","email":"","orcid":"","institution":"Chang Gung Memorial Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yi-Yang","middleName":"","lastName":"Chen","suffix":""},{"id":469951407,"identity":"909cc27f-88e9-4b01-99ba-40bdd2d88970","order_by":17,"name":"Chi-Cheng Li","email":"","orcid":"","institution":"National Taiwan University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Chi-Cheng","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2025-06-11 08:20:24","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6869381/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6869381/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41409-025-02773-1","type":"published","date":"2025-12-18T05:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":84776156,"identity":"216fad0e-bf08-4df9-9e64-1c8dbd0831c6","added_by":"auto","created_at":"2025-06-17 08:58:23","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":154059,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKaplan–Meier Estimates of Survival Outcomes by Early Failure of Induction (EFI) Status.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Overall survival (OS) in the full cohort.\u003c/p\u003e\n\u003cp\u003e(B) Event-free survival (EFS) in the full cohort.\u003c/p\u003e\n\u003cp\u003e(C) OS stratified by EFI status.\u003c/p\u003e\n\u003cp\u003e(D) EFS stratified by EFI status.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6869381/v1/e8c2f8c4a0baa593734a96f3.png"},{"id":84776154,"identity":"c1f9a3d3-37b0-496e-a44e-939543b3e05b","added_by":"auto","created_at":"2025-06-17 08:58:23","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":68833,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSurvival Outcomes Stratified by EFI Status After Propensity Score Adjustment.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) OS stratified by EFI status after propensity score matching (PSM).\u003c/p\u003e\n\u003cp\u003e(B) OS stratified by EFI status after inverse probability of treatment weighting (IPTW).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6869381/v1/528005e14804e241c5ee1f62.png"},{"id":84776155,"identity":"c6a71d55-c29c-4cd8-9442-f4846fb81b57","added_by":"auto","created_at":"2025-06-17 08:58:23","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":33192,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eNon-Linear Association Between Failure of Induction (FI) Duration and Overall Survival.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRestricted cubic spline (RCS) modeling was used to assess the association between failure of induction (FI) duration (months) and OS in a multivariable Cox regression framework. RCS with three knots were selected based on optimal Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) values.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6869381/v1/79d84d4888bc06b05a9493c8.png"},{"id":98579725,"identity":"086ce842-c696-4629-b520-37f78371304e","added_by":"auto","created_at":"2025-12-19 08:10:19","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":851047,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6869381/v1/891c4900-b186-41ec-9a59-c1205426b736.pdf"},{"id":84776153,"identity":"27b36915-6c7c-438d-bdcb-cbbf10988199","added_by":"auto","created_at":"2025-06-17 08:58:23","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":36843,"visible":true,"origin":"","legend":"Table 1, Table 2, Table 3","description":"","filename":"Tables20250528.docx","url":"https://assets-eu.researchsquare.com/files/rs-6869381/v1/3d198edc243b47ed3e647f68.docx"},{"id":84776157,"identity":"86a7fe8b-fd51-4471-bd6a-6b02b958fef9","added_by":"auto","created_at":"2025-06-17 08:58:23","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":513619,"visible":true,"origin":"","legend":"Figure S1, Figure S2, Figure S3, Figure S4, Figure S5, Figure S6, Figure S7, Table S1,","description":"","filename":"Supplementarymaterials20250528.docx","url":"https://assets-eu.researchsquare.com/files/rs-6869381/v1/cf20c06e4c39168a5ac64e13.docx"}],"financialInterests":"The authors have declared there is \u003cb\u003eNO\u003c/b\u003e conflict of interest to disclose.","formattedTitle":"Early Failure of Induction Impacts Transplant Outcomes in Hodgkin Lymphoma Revealed Through A Longitudinal Nationwide Registry in Taiwan","fulltext":[{"header":"Introduction","content":"\u003cp\u003eHodgkin lymphoma (HL) is a B cell lymphoproliferative malignancy, demonstrate a favorable overall survival (OS) rate ranging between 80% and 90% for frontline treatment (ref. 1). Nevertheless, in relapsed or refractory HL, autologous stem cell transplantation (ASCT) remains the established standard of care with a cure rate of approximately 50% (ref. 2). Traditionally, early-stage HL has been defined as unfavorable in various prognostic models based on risk factors including \u0026ldquo;B\u0026rdquo; symptoms with elevated ESR, large mediastinal mass, nodal sites, bulky disease, and extranodal lesions (ref. 3). The International Prognostic Score (IPS) with seven variables has been developed as a prognostic model for advanced-stage cancer (ref. 4). However, most of these prognostic models were developed in clinical trials during the radiotherapy era, and current therapeutic advancements lead researchers to question their influence on treatment outcomes (ref. 3). Interim positron emission tomography (PET) predicts progression-free survival (PFS) and led to the development of risk-adaptive treatment strategies in some pivotal studies (ref. 5, 6). In various lymphoid malignancies, including follicular lymphoma and MALToma, early progression is associated with poor OS (ref. 7, 8). Early progression of HL has been acknowledged as a predictor of unfavorable prognosis and serves as an inclusion criterion for clinical trials evaluating therapies for high relapse risk after ASCT. However, evidence that early failure of induction (EFI) continues to influence outcomes once patients are successfully bridged to transplantation is still sparse. (ref. 9). Even in the brentuximab vedotin (BV) era, some patients still proceed to ASCT because their frontline response is inadequate; the outcomes of this subgroup after transplantation, however, remain unreported (ref. 1). Accordingly, the present study evaluates real-world outcomes of HL patients undergoing hematopoietic stem-cell transplantation (HSCT) in Taiwan and examines whether EFI is independently associated with inferior post-SCT survival.\u003c/p\u003e"},{"header":"Patients and methods","content":"\u003cp\u003ePatients diagnosed with HL who underwent HSCT between February 2002 and August 2022 were included. Data were retrieved from the Taiwan Society of Blood and Marrow Transplantation (TBMT) Research database, a nationwide registry that collects clinical data from 17 collaborative transplantation centers in Taiwan. Clinical data, including baseline characteristics at diagnosis, chemotherapy regimens, pre-transplantation evaluations, transplantation, and survival, were collected. EFI chemotherapy was defined as an interval of \u0026lt;12 months between the initiation of the first induction therapy and salvage therapy (Figure S1). This study was approved by the Research Ethics Committee of the National Taiwan University Hospital, and data were collected in accordance with the Declaration of Helsinki. (Approval number: 202005129RINC)\u003c/p\u003e\n\u003cp\u003eOur primary objective was to elucidate the survival outcomes among patients who underwent transplantation for HL and to investigate the impact of early disease progression on survival to provide information for future care. OS was defined as the time from induction to death from any cause and event-free survival (EFS) was defined as the time from induction to the occurrence of disease progression following SCT, initiation of salvage therapy post-transplant, or death from any cause after transplantation. In the subgroup of patients who relapsed after SCT, a subsequent analysis was conducted with OS defined as the time from post-transplant relapse to death from any cause.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe data of 286 patients with HL who underwent HSCT were retrieved from the TBMT database. Patients with composite lymphoma, nodular lymphocyte-predominant HL, and allogeneic SCT (allo-SCT) at first transplantation were excluded from the primary analysis (Figure S2). All patients with a detailed treatment history were included in the analysis of the prognostic value of EFI, and cases with missing data were excluded from the Cox proportional hazards model. Continuous variables are expressed as medians with interquartile ranges and were compared using the Mann–Whitney U test. Categorical variables were compared using the chi-square test or Fisher’s exact test. Kaplan–Meier estimates were used to describe OS and EFS, and the log-rank test was used to compare groups. The Cox proportional hazard model was used for univariable regression analysis, while variables with a \u003cem\u003ep\u003c/em\u003e value \u0026lt;0.2 considered to be clinically significant were included in multivariable Cox regression analysis. The assumptions for proportional hazards were verified. To confirm the results of regression analysis, propensity score matching (PSM) and inverse probability treatment weighting (IPTW) were performed. Propensity scores were derived using logistic regression incorporating clinically relevant variables, including transplantation age, sex, Charlson comorbidity index (CCI) \u0026gt;2, diagnosis after 2016, Ann Arbor stage III/IV, histologic subtype, IPS \u0026gt;2, pre-transplantation brentuximab vedotin (BV) exposure, and pre-transplantation disease status. PSM was conducted using 1:1 optimal matching with a caliper of 0.2 standard deviations. IPTW was applied using stabilized inverse probability weights to estimate the average treatment effect, creating a balanced pseudo-population that simulates randomization. Standardized mean differences (SMD) were used to assess covariate balance between groups before and after PSM or IPTW, with SMD \u0026lt;0.1 indicating sufficient balance. To further evaluate the prognostic impact of the time interval from the initiation of induction therapy to the start of salvage therapy (defined as failure of induction [FI] duration, Figure S1), and FI duration was analyzed as a continuous variable. Given the potential non-linear association between duration of EFI and OS, restricted cubic spline (RCS) method for data modeling was applied. Cox regression models incorporating EFI as a linear term were compared with RCS-based models using three, four, or five knots. Model selection was guided by Akaike information criterion (AIC), Bayesian information criterion (BIC), and concordance index (C-index). The Wald test was used to assess the statistical significance of non-linear relationships identified in the RCS models. A \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05 is considered statistically significant. All statistical analyses were performed using Stata, version 18 (StataCorp, TX, USA) and R software version 4.4.2 (R Foundation for Statistical Computing, Vienna, Austria).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cem\u003eBaseline patient demographics\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis study included 286 patients with HL who underwent HSCT. To maintain homogeneity in our study population, we excluded patients with composite lymphoma (n = 10), nodular lymphocyte-predominant HL (n = 21), and those who underwent allo-SCT during the first transplantation (n = 15). The patients’ baseline characteristics are listed in Table 1. The most common histological subtype was nodular sclerosis (75.4%) followed by mixed cellularity (18.5%). Among the 149 patients with an available IPS, 43.9% had a score greater than 2. Patients who received salvage therapy within 12 months of the start of induction therapy were defined as those with EFI, accounting for 46.6% of the 238 patients. EFI was more frequently observed among patients diagnosed after 2016 (34.2% vs. 27.1%, \u003cem\u003ep\u003c/em\u003e = 0.03) and those with an IPS score \u0026gt;2 (51.9% vs. 43.6%, \u003cem\u003ep\u003c/em\u003e = 0.046), compared to the non-EFI group. Other baseline characteristics did not differ significantly between groups.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eTreatment\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe most common first-line induction therapy was adriamycin, bleomycin, vinblastine, and dacarbazine (ABVD; 89.0%), followed by alternating COMP/ABVD (4.7%). As for salvage therapy, the most common regimen was ESHAP (48.9%), followed by ICE (16.9%) and DHAP (4.8%) (Figure S3). A total of 35 patients (14.7%) received brentuximab vedotin (BV) before transplantation, whereas five patients received immune checkpoint inhibitors (mainly pembrolizumab or nivolumab) before HSCT. A total of 38.7% of patients were in complete remission before HSCT.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eHSCT\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAll patients underwent autologous SCT, with peripheral blood being the dominant stem cell source. Most patients (64.9%) who underwent ASCT received BCNU, etoposide, cytarabine, and melphalan (BEAM)-based conditioning regimens, whereas only 10.5% received gemcitabine, busulfan, and melphalan (GemBuMel)-based regimens. Twenty-seven patients underwent a second transplantation: 33.3% underwent ASCT and 66.7% underwent allo-SCT. The most common reason for a second transplantation was relapse or refractory disease (n = 23, 85.2%). Among the 18 patients who underwent allo-SCT, 50% were from matched sibling donors, 11% were from unrelated donors, and 39% were from haploidentical donors.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSurvival outcomes\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAt a median follow-up of 4.6 years, the median overall survival (OS) was not reached. The 5-year OS rate was 85% (95% confidence interval [CI], 80%–91%; Figure 1A). The median EFS was 7.2 years, with a 5-year EFS rate of 60% (95% CI, 53%–68%; Figure 1B). Patients with EFI had significantly worse OS compared to those without EFI (5-year OS: 78% vs. 90%; \u003cem\u003ep\u003c/em\u003e = 0.013, log-rank test; Figure 1C). Similarly, EFI was associated with inferior EFS (5-year EFS: 50% vs. 68%; \u003cem\u003ep\u003c/em\u003e = 0.004, log-rank test; Figure 1D). Post-transplantation BV consolidation was administered to 43 (18.1%) patients and was not associated with a difference in survival (\u003cem\u003ep\u0026nbsp;\u003c/em\u003e= 0.75) or stratification according to EFI status (\u003cem\u003ep\u0026nbsp;\u003c/em\u003e= 0.93; EFI group, \u003cem\u003ep\u0026nbsp;\u003c/em\u003e= 0.72 in non-EFI group). Among the 35 patients with detailed cycles of BV consolidation, the median number of cycles received was seven, with a large variation (range 1–24) (Figure S4). The univariable Cox regression revealed that CCI \u0026gt;2 is associated with a significant inferior OS (hazard ratio (HR) for death 3.40 [95% CI, 1.66–6.95], \u003cem\u003ep\u0026nbsp;\u003c/em\u003e= 0.001; Table 2), as well as EFI status (HR for death 2.38 (95% CI, 1.18–4.77, \u003cem\u003ep\u0026nbsp;\u003c/em\u003e= 0.015). In multivariable Cox regression analysis, adjusting for EFI, advanced Ann Arbor stage, CCI \u0026gt;2, and pretransplantation disease status, EFI remained an independent predictor of poor OS (adjusted HR for death 3.94 [95% CI1.03–15.02], \u003cem\u003ep\u0026nbsp;\u003c/em\u003e= 0.044). Pretransplantation refractory disease was not statistically significant, likely due to the small sample size. Among the patients who experienced relapse after the first transplantation, the 2-year OS rate was 74%. The EFI group had a persistent negative prognostic impact on a worse survival (2-year OS EFI vs. non-EFI: 61% vs. 83%, \u003cem\u003ep\u0026nbsp;\u003c/em\u003e= 0.049) (Figure S5).\u003c/p\u003e\n\u003cp\u003eTo account for potential confounding factors, we performed additional analyses using PSM and IPTW. Fifty-one matched pairs were selected, achieving balance across most covariates, as evidenced by an absolute SMD \u0026lt;0.01 for all variables except sex (Table 3, Figure S6). In the PSM cohort, EFI was consistently associated with significantly worse OS (5-year OS: 71% vs. 98%; \u003cem\u003ep\u003c/em\u003e = 0.003; Figure 2A). Similarly, IPTW analysis demonstrated well-balanced covariates between the EFI and non-EFI groups (Table 3, Figure S6) and confirmed EFI as a predictor of inferior survival (5-year OS: 75% vs. 98%; \u003cem\u003ep\u003c/em\u003e = 0.0024; Figure 2B).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThe effect of FI duration\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;We assessed the prognostic significance of FI duration as a continuous variable, applying restricted cubic splines (RCS) in multivariable Cox regression to account for potential non-linear associations and minimizing information loss from dichotomization into EFI status. The analysis adjusted for age, sex, Ann Arbor stage III/IV, IPS \u0026gt;2, and pretransplantation disease status. Model comparisons were performed by incorporating FI duration as a linear term and as an RCS with three, four, or five knots, evaluating goodness of fit using the AIC, BIC, and C-index. The RCS model with three knots demonstrated the highest C-index, the lowest AIC, and a comparable BIC, indicating the best model fit (Figure S7 and Table S1). Longer FI duration was significantly associated with improved OS (adjusted HR 0.87 [95% CI: 0.78–0.98]; \u003cem\u003ep\u003c/em\u003e = 0.03). Moreover, the association was non-linear (\u003cem\u003ep\u003c/em\u003e for non-linearity = 0.04). A short FI duration (\u0026lt;10 months) was associated with an increased hazard of mortality, with HR values exceeding 1 (Figure 3). However, the hazard declined progressively with increasing FI duration, reaching a plateau beyond 20 months, suggesting a potential threshold effect.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAllo-SCT\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eFifteen patients who underwent allo-SCT as the first HSCT were excluded from the primary analysis. Of these, 53% underwent myeloablative conditioning. All patients received peripheral blood as the stem cell source: 33% from matched sibling donors, 40% from unrelated donors, and 27% from haploidentical donors. Four patients (57%) died of infection, two patients (29%) died of progressive or relapsed disease, and one patient died of GVHD.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNodular lymphocyte-predominant HL\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTwenty-one patients with nodular lymphocyte-predominant HL (NLPHL) were excluded from primary analysis. All patients were diagnosed before 2020, and 65% were treated with ABVD. EFI accounted for 45% of the patients and was not associated with worse OS (\u003cem\u003ep\u0026nbsp;\u003c/em\u003e= 0.14).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eTo the best of our knowledge, this nationwide retrospective cohort analysis is the first large study in Asia to evaluate the association of early progression and outcomes in patients with HL undergoing HSCT, distinguishing this study from previous ones that primarily focused on defining outcomes and prognostic factors for early progression patients with HL receiving HSCT (ref. 10). Our study demonstrated a 5-year OS of 84% in all patients with HL who underwent HSCT, which was comparable to previous studies\u0026nbsp;(ref. 11, 12). The 6-year OS was higher than that observed by Smith et al. (75% vs. 55%), potentially because of a greater proportion of primary refractory patients in their cohort (11% vs. 50%) (ref. 10).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe observed that EFI was correlated with diminished OS and relapse after transplantation. This association remained significant in multivariable Cox regression analysis, where EFI remained an independent predictor of poor OS (adjusted HR for death: 3.94 [95% CI, 1.03–15.02], \u003cem\u003ep\u003c/em\u003e=0.044). To mitigate potential confounding factors, we applied propensity score matching (PSM) and inverse probability treatment weighting (IPTW), both of which reinforced EFI as a significant determinant of survival. In line with our previous study, which discussed the early progression of the disease in all patients with HL at two medical centers in Taiwan, an IPS score \u0026gt;2 was more likely to be associated with early progression (ref. 13). Both IPS scores \u0026gt;2 and CCI scores \u0026gt;2 were associated with EFI status. However, neither of these factors was associated with poor OS, indicating that they were not confounding factors when evaluating the role of EFI on OS. Patients with EFIs in our study were similar to those with primary refractory disease or early relapse in other studies. In our study, patients with EFI status comprised 49% of the entire cohort, whereas 65% of patients in the Stanford Hospital cohort exhibited primary refractory or early relapse\u0026nbsp;(ref. 14). Their study demonstrated a 4-year OS rate of 89%, as opposed to 78% in our cohort, possibly attributable to a higher proportion of patients achieving CR or PR (chi-square test, \u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt;0.05) and more widespread utilization of PD-1 inhibitor-based salvage therapy before transplantation. In addition to EFI status, we examined the impact of FI duration as a continuous variable. Using RCS in multivariable Cox regression, we observed a non-linear association between FI duration and OS (\u003cem\u003ep\u003c/em\u003e for non-linearity = 0.04). A shorter FI duration (\u0026lt;10 months) was associated with an increased hazard of mortality, with HR values exceeding 1, whereas the hazard declined progressively with increasing FI duration, stabilizing beyond 20 months. These findings suggest that the timing of disease progression plays a critical role in determining long-term outcomes, and patients with rapid progression may require more aggressive interventions.\u003c/p\u003e\n\u003cp\u003eBV was first reimbursed by Taiwan’s National Health Insurance in 2016 as a frontline therapy in combination with AVD in stage IV CD30+ HL with an IPS \u0026gt;4 or as consolidation therapy after ASCT in patients fulfilling the inclusion criteria of the AETHERA trial. In our cohort, 26.5% of the patients had received BV at any time point, and 18.1% of the patients had post-transplantation BV consolidation. Our study had a higher prevalence of primary refractory disease than the AETHERA trial (60% vs. 11% in our study)\u0026nbsp;(ref. 9). Despite its use, post-transplantation BV consolidation was not associated with improved post-transplantation survival, likely due to the limited sample size in this study.\u003c/p\u003e\n\u003cp\u003eNLPHL accounts for 7% of all patients with HL who undergo transplantation. The ABVD regimen is the most used, with a low prevalence of rituximab use. Compared with that in the EBMT cohort, the 5-year OS rate was lower in our cohort (73% compared to 87% in the EBMT cohort), which was probably attributed to the lower rituximab use in our cohort (5% vs. 63%)\u0026nbsp;(ref. 15). EFI was not associated with worse OS; however, this interpretation should be made cautiously because of the small sample size in the NLPHL cohort.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur study has several limitations. First, the retrospective nature of the study made this susceptible to unmeasured confounding factors, as is common in real-world evidence. Moreover, we used EFS rather than PFS, which requires a retrospective review of PET scans to define disease progression and is not available in the TBMT database. However, most patients with relapse receive subsequent therapy, and EFS is considered to be an acceptable surrogate marker of PFS. Furthermore, the start time of the survival analysis was set at the date of induction therapy, which may have been prone to immortal time bias. However, all patients in this study developed refractoriness to anti-lymphoma treatment or progressive disease and proceeded to ASCT. Our focus is to study the impact of EFI (a pre-HSCT condition) on long-term outcome. As such, both EFI and non-EFI groups were subject to a comparable at-risk period between induction and HSCT, thereby minimizing the risk of asymmetrically granted immortal time and mitigating its potential bias in the survival analysis.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study depicted the outcomes of transplantation for HL in an Asian population while emphasizing the important prognostic role of EFI chemotherapy in OS. While acknowledging the confirmatory nature of this study, this holds distinctive significance as Asian-based evidence of a relatively uncommon lymphoma subtype in Asians. Moreover, the poor survival of patients who experience EFI therapy warrants the evaluation of more effective therapeutic regimens, such as immune checkpoint inhibitors, to improve patient outcomes.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCompeting Interests statement:\u003c/strong\u003e The authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConceptualization:\u003c/strong\u003e B.S. Ko, M. Yao, C.C. Li; \u003cstrong\u003eStudy Design:\u003c/strong\u003e T.C. Huang; \u003cstrong\u003eData Curation:\u003c/strong\u003e H.M. Chang, L.T. Hsiao, C.Y. Hsieh, M.C. Ma, T.L. Lin, Y.T. Hsu, T.D. Tan, Y.Y. Wu, Y.C. Liu, P.Y. Chuang, Y.C. Hong, Y.Y. Chen; \u003cstrong\u003eFormal Analysis:\u003c/strong\u003e Y.S. Chang, W.C. Hsieh; \u003cstrong\u003eWriting – Original; Draft:\u003c/strong\u003e Y.S. Chang, W.C. Hsieh; \u003cstrong\u003eWriting – Review \u0026amp; Editing:\u003c/strong\u003e All authors; \u003cstrong\u003eSupervision:\u003c/strong\u003e B.S. Ko, M. Yao, C.C. Li; \u003cstrong\u003eProject Administration:\u003c/strong\u003e T.C. Huang, C.C. Li; \u003cstrong\u003eApproval of Final Manuscript:\u003c/strong\u003e All authors\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors express their gratitude to Po-Wei Liao (Division of Hematology-Medical Oncology, Department of Medicine, Taichung Veterans General Hospital), Wei-Han Huang (Department of Hematology \u0026amp; Oncology, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation),\u0026nbsp;Chuan-Cheng Wang (Division of Hematology \u0026amp; Oncology, Department of Internal Medicine, Changhua Christian Hospital), Pei-Ying Hsieh (Division of Oncology-Hematology, Far Eastern Memorial Hospital), Yu-Ting Lee (Division of Hematology and Oncology, Department of Medicine, Ditmanson Medical Foundation Chiayi Christian Hospital) and the staff of the Taiwan Society of Blood and Marrow Transplantation and the Transplant Registry Task Force for providing clinical data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors report no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during and analysed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAnsell SM, Radford J, Connors JM, Długosz-Danecka M, Kim WS, Gallamini A, et al. Overall Survival with Brentuximab Vedotin in Stage III or IV Hodgkin\u0026apos;s Lymphoma. N Engl J Med. 2022;387(4):310-20.\u003c/li\u003e\n\u003cli\u003eSamara Y, Mei M. Autologous Stem Cell Transplantation in Hodgkin Lymphoma-Latest Advances in the Era of Novel Therapies. Cancers (Basel). 2022;14(7):1738.\u003c/li\u003e\n\u003cli\u003eKlimm B, Goergen H, Fuchs M, von Tresckow B, B\u0026ouml;ll B, Meissner J, et al. Impact of risk factors on outcomes in early-stage Hodgkin\u0026apos;s lymphoma: an analysis of international staging definitions. Ann Oncol. 2013;24(12):3070-6.\u003c/li\u003e\n\u003cli\u003eHasenclever D, Diehl V. A prognostic score for advanced Hodgkin\u0026apos;s disease. International Prognostic Factors Project on Advanced Hodgkin\u0026apos;s Disease. N Engl J Med. 1998;339(21):1506-14.\u003c/li\u003e\n\u003cli\u003eCasasnovas RO, Bouabdallah R, Brice P, Lazarovici J, Ghesquieres H, Stamatoullas A, et al. PET-adapted treatment for newly diagnosed advanced Hodgkin lymphoma (AHL2011): a randomised, multicentre, non-inferiority, phase 3 study. Lancet Oncol. 2019;20(2):202-15.\u003c/li\u003e\n\u003cli\u003eBorchmann P, Ferdinandus J, Schneider G, Moccia A, Greil R, Hertzberg M, et al. Assessing the efficacy and tolerability of PET-guided BrECADD versus eBEACOPP in advanced-stage, classical Hodgkin lymphoma (HD21): a randomised, multicentre, parallel, open-label, phase 3 trial. Lancet. 2024;404(10450):341-52.\u003c/li\u003e\n\u003cli\u003eLipof JJ, Barr PM. Early Progression of Follicular Lymphoma: Biology and Treatment. Hematol Oncol Clin North Am. 2020;34(4):757-69.\u003c/li\u003e\n\u003cli\u003eConconi A, Thieblemont C, Cascione L, Torri V, Kiesewetter B, Margiotta Casaluci G, et al. Early progression of disease predicts shorter survival in MALT lymphoma patients receiving systemic treatment. Haematologica. 2020;105(11):2592-7.\u003c/li\u003e\n\u003cli\u003eMoskowitz CH, Nademanee A, Masszi T, Agura E, Holowiecki J, Abidi MH, et al. Brentuximab vedotin as consolidation therapy after autologous stem-cell transplantation in patients with Hodgkin\u0026apos;s lymphoma at risk of relapse or progression (AETHERA): a randomised, double-blind, placebo-controlled, phase 3 trial. Lancet. 2015;385(9980):1853-62.\u003c/li\u003e\n\u003cli\u003eSmith SD, Moskowitz CH, Dean R, Pohlman B, Sobecks R, Copelan E, et al. Autologous stem cell transplant for early relapsed/refractory Hodgkin lymphoma: results from two transplant centres. Br J Haematol. 2011;153(3):358-63.\u003c/li\u003e\n\u003cli\u003eAkay OM, Ozbalak M, Pehlivan M, Yildiz B, Uzay A, Yigenoglu TN, et al. Brentuximab vedotin consolidation therapy after autologous stem-cell transplantation in patients with high-risk Hodgkin lymphoma: Multicenter retrospective study. Hematol Oncol. 2021;39(4):498-505.\u003c/li\u003e\n\u003cli\u003eNieto Y, Gruschkus S, Valdez BC, Jones RB, Anderlini P, Hosing C, et al. Improved outcomes of high-risk relapsed Hodgkin lymphoma patients after high-dose chemotherapy: a 15-year analysis. Haematologica. 2022;107(4):899-908.\u003c/li\u003e\n\u003cli\u003eYu TC, Yu SC, Wang RC, Lai SF, Teng CJ, Lin JW, et al. Investigating early progression of Hodgkin lymphoma in a two-center analysis. J Formos Med Assoc. 2022;121(7):1215-22.\u003c/li\u003e\n\u003cli\u003eSpinner MA, Sica RA, Tamaresis JS, Lu Y, Chang C, Lowsky R, et al. Improved outcomes for relapsed/refractory Hodgkin lymphoma after autologous transplantation in the era of novel agents. Blood. 2023;141(22):2727-37.\u003c/li\u003e\n\u003cli\u003eAkhtar S, Montoto S, Boumendil A, Finel H, Masszi T, Jindra P, et al. High dose chemotherapy and autologous stem cell transplantation in nodular lymphocyte-predominant Hodgkin lymphoma: A retrospective study by the European society for blood and marrow transplantation-lymphoma working party. Am J Hematol. 2018;93(1):40-6.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 3 are available in the Supplementary Files section\u003c/p\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":true,"email":"[email protected]","identity":"bone-marrow-transplantation","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"bmt","sideBox":"Learn more about [Bone Marrow Transplantation](http://www.nature.com/bmt/)","snPcode":"41409","submissionUrl":"https://mts-bmt.nature.com/cgi-bin/main.plex","title":"Bone Marrow Transplantation","twitterHandle":"@bmtjournal","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6869381/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6869381/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eHodgkin lymphoma (HL) has favorable outcomes with frontline therapy; however, prognosis remains suboptimal in relapsed or refractory cases. Autologous stem cell transplantation (ASCT) is the standard of care in this setting, yet the prognostic impact of early failure of induction (EFI) chemotherapy has not been characterized in Asian populations. This nationwide, multicenter, retrospective longitudinal analysis evaluated the association between EFI and post-ASCT outcomes. Among 238 ASCT-treated patients, 46.6% occurred EFI and was associated with inferior 5-year overall survival (OS) compared to non-EFI (75% vs. 90%, p = 0.013). In multivariable Cox regression, EFI (hazard ratio [HR] 2.21, 95% confidence interval [CI] 1.07–4.58, p = 0.032) and Charlson comorbidity index \u0026gt;2 (HR 3.40, 95% CI 1.63–7.09, \u003cem\u003ep \u003c/em\u003e= 0.001)independently predicted poorer OS. Restricted cubic spline modeling demonstrated a dose–response relationship between induction failure duration and mortality risk. These findings were confirmed through propensity score matching and inverse probability of treatment weighting analyses. Among patients who experienced relapse following their first transplantation, EFI remained an adverse prognostic factor (2-year OS, EFI vs. non-EFI: 59% vs. 82%, \u003cem\u003ep \u003c/em\u003e= 0.049). This study addresses a crucial gap by providing insights into post-transplantation outcomes and informing future treatment strategies for patients with HL in Asian.\u003c/p\u003e","manuscriptTitle":"Early Failure of Induction Impacts Transplant Outcomes in Hodgkin Lymphoma Revealed Through A Longitudinal Nationwide Registry in Taiwan","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-17 08:58:18","doi":"10.21203/rs.3.rs-6869381/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"revise","date":"2025-07-17T12:42:55+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-07-14T01:31:13+00:00","index":2,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-07-07T12:35:42+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-06-26T18:12:25+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-06-24T10:56:52+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2025-06-11T16:56:40+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-06-11T10:51:59+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-06-11T08:16:03+00:00","index":"","fulltext":""},{"type":"submitted","content":"Bone Marrow Transplantation","date":"2025-06-11T08:16:02+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bone-marrow-transplantation","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"bmt","sideBox":"Learn more about [Bone Marrow Transplantation](http://www.nature.com/bmt/)","snPcode":"41409","submissionUrl":"https://mts-bmt.nature.com/cgi-bin/main.plex","title":"Bone Marrow Transplantation","twitterHandle":"@bmtjournal","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"5d2fd7e0-226e-4ec8-a537-2498722a3bb3","owner":[],"postedDate":"June 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":49903489,"name":"Biological sciences/Cancer/Haematological cancer/Lymphoma/Hodgkin lymphoma"},{"id":49903490,"name":"Biological sciences/Cancer/Cancer therapy/Chemotherapy"}],"tags":[],"updatedAt":"2025-12-19T08:10:14+00:00","versionOfRecord":{"articleIdentity":"rs-6869381","link":"https://doi.org/10.1038/s41409-025-02773-1","journal":{"identity":"bone-marrow-transplantation","isVorOnly":false,"title":"Bone Marrow Transplantation"},"publishedOn":"2025-12-18 05:00:00","publishedOnDateReadable":"December 18th, 2025"},"versionCreatedAt":"2025-06-17 08:58:18","video":"","vorDoi":"10.1038/s41409-025-02773-1","vorDoiUrl":"https://doi.org/10.1038/s41409-025-02773-1","workflowStages":[]},"version":"v1","identity":"rs-6869381","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6869381","identity":"rs-6869381","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}