Outcomes Associated With Thiotepa-Based Conditioning in Patients With Primary Central Nervous System Lymphoma After Autologous Hematopoietic Cell Transplant

Michael Scordo; Trent P Wang; Kwang W Ahn; Yue Chen; Sairah Ahmed; Farrukh T Awan; Amer Beitinjaneh; Andy Chen; Victor A Chow; Bhagirathbhai Dholaria; Narendranath Epperla; Umar Farooq; Nilanjan Ghosh; Natalie Grover; Nada Hamad; Gerhard C Hildebrandt; Leona Holmberg; Sanghee Hong; David J Inwards; Antonio Jimenez-Jimenez; Reem Karmali; Vaishalee P Kenkre; Farhad Khimani; Evgeny Klyuchnikov; Maxwell M Krem; Pashna N Munshi; Yago Nieto; Tim Prestidge; Praveen Ramakrishnan Geethakumari; Andrew R Rezvani; Peter A Riedell; Sachiko Seo; Nirav N Shah; Melhem Solh; Jean A Yared; Mohamed A Kharfan-Dabaja; Alex Herrera; Mehdi Hamadani; Craig S Sauter

doi:10.1001/jamaoncol.2021.1074

. 2021 May 6;7(7):993–1003. doi: 10.1001/jamaoncol.2021.1074

Outcomes Associated With Thiotepa-Based Conditioning in Patients With Primary Central Nervous System Lymphoma After Autologous Hematopoietic Cell Transplant

Michael Scordo ^1,², Trent P Wang ³, Kwang W Ahn ^4,⁵, Yue Chen ⁴, Sairah Ahmed ⁶, Farrukh T Awan ⁷, Amer Beitinjaneh ³, Andy Chen ⁸, Victor A Chow ⁹, Bhagirathbhai Dholaria ¹⁰, Narendranath Epperla ¹¹, Umar Farooq ¹², Nilanjan Ghosh ¹³, Natalie Grover ¹⁴, Nada Hamad ¹⁵, Gerhard C Hildebrandt ¹⁶, Leona Holmberg ⁹, Sanghee Hong ¹⁷, David J Inwards ¹⁸, Antonio Jimenez-Jimenez ³, Reem Karmali ¹⁹, Vaishalee P Kenkre ²⁰, Farhad Khimani ²¹, Evgeny Klyuchnikov ²², Maxwell M Krem ¹⁶, Pashna N Munshi ²³, Yago Nieto ²⁴, Tim Prestidge ²⁵, Praveen Ramakrishnan Geethakumari ²⁶, Andrew R Rezvani ²⁷, Peter A Riedell ²⁸, Sachiko Seo ²⁹, Nirav N Shah ³⁰, Melhem Solh ³¹, Jean A Yared ³², Mohamed A Kharfan-Dabaja ³³, Alex Herrera ³⁴, Mehdi Hamadani ^4,^✉, Craig S Sauter ^1,²

¹Adult Bone Marrow Transplant Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York

²Department of Medicine, Weill Cornell Medical College, New York, New York

³Division of Transplantation and Cellular Therapy, University of Miami Miller School of Medicine, Miami, Florida

⁴Center for International Blood and Marrow Transplant Research, Department of Medicine, Medical College of Wisconsin, Milwaukee

⁵Institute for Health and Equity, Division of Biostatistics, Medical College of Wisconsin, Milwaukee

⁶Department of Lymphoma and Myeloma, The University of Texas MD Anderson Cancer Center, Houston, Texas

⁷Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas

⁸Department of Medicine, Oregon Health and Science University, Portland

⁹Fred Hutchinson Cancer Research Center, Seattle, Washington

¹⁰Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee

¹¹The James Cancer Hospital and Solove Research Institute, Division of Hematology, Department of Medicine, The Ohio State University, Columbus

¹²Division of Hematology, Oncology and Blood & Marrow Transplantation, University of Iowa Hospitals and Clinics, Iowa City

¹³Levine Cancer Institute, Department of Hematologic Oncology and Blood Disorders, Atrium Health, Charlotte, North Carolina

¹⁴Department of Medicine, University of North Carolina Hospitals, Chapel Hill

¹⁵St Vincent’s Hospital, Darlinghurst, New South Wales, Australia

¹⁶Markey Cancer Center, University of Kentucky, Lexington

¹⁷Blood and Marrow Transplant Program, Taussig Cancer Center, Cleveland Clinic, Cleveland, Ohio

¹⁸Division of Hematology, Mayo Clinic, Rochester, Minnesota

¹⁹Department of Medicine, Northwestern University, Chicago, Illinois

²⁰Department of Medicine, University of Wisconsin–Madison, Madison

²¹H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida

²²Department for Stem Cell Transplantation, University Cancer Center, Hamburg, Germany

²³Department of Medicine, Georgetown University Hospital, Washington, DC

²⁴Department of Stem Cell Transplantation and Cellular Therapy, The University of Texas MD Anderson Cancer Center, Houston

²⁵Blood and Cancer Centre, Starship Children’s Hospital, Auckland, New Zealand

²⁶Lymphoma, BMT and Cellular Therapy Program, University of Texas Southwestern Medical Center, Dallas

²⁷Division of Blood & Marrow Transplantation, Stanford University, Stanford, California

²⁸Department of Medicine, The University of Chicago Medicine, Chicago, Illinois

²⁹Department of Hematology and Oncology, Dokkyo Medical University, Tochigi, Japan

³⁰Department of Medicine, Medical College of Wisconsin, Milwaukee

³¹The Blood and Marrow Transplant Group of Georgia, Northside Hospital, Atlanta

³²Blood & Marrow Transplantation Program, Greenebaum Comprehensive Cancer Center, Division of Hematology/Oncology, Department of Medicine, University of Maryland, Baltimore

³³Division of Hematology-Oncology, Blood and Marrow Transplantation Program, Mayo Clinic, Jacksonville, Florida

³⁴Department of Hematology and Hematopoietic Cell Transplantation, City of Hope National Medical Center, Duarte, California

Accepted for Publication: March 18, 2021.

Published Online: May 6, 2021. doi:10.1001/jamaoncol.2021.1074

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Corresponding Author: Mehdi Hamadani, MD, Center for International Blood and Marrow Transplant Research, Department of Medicine, Medical College of Wisconsin, 9200 W Wisconsin Ave, Ste C5500, Milwaukee, WI 53226 (mhamadani@mcw.edu).

Author Contributions: Dr Hamadani had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Drs Scordo and Wang are co–first authors.

Concept and design: Scordo, Wang, Ahmed, Beitinjaneh, Dholaria, Hamad, Hildebrandt, Holmberg, Hong, Jimenez-Jimenez, Kenkre, Khimani, Klyuchnikov, Nieto, Shah, Solh, Yared, Hamadani, Sauter.

Acquisition, analysis, or interpretation of data: Scordo, Wang, Ahn, Y. Chen, Ahmed, Awan, Beitinjaneh, A. Chen, Chow, Dholaria, Epperla, Farooq, Ghosh, Grover, Hamad, Hildebrandt, Holmberg, Hong, Inwards, Jimenez-Jimenez, Karmali, Kenkre, Khimani, Klyuchnikov, Krem, Munshi, Nieto, Prestidge, Ramakrishnan Geethakumari, Rezvani, Riedell, Seo, Solh, Yared, Kharfan-Dabaja, Herrera, Hamadani.

Drafting of the manuscript: Scordo, Wang, Ahn, Y. Chen, Ahmed, Beitinjaneh, Dholaria, Hamad, Holmberg, Klyuchnikov, Krem, Ramakrishnan Geethakumari, Kharfan-Dabaja, Hamadani.

Critical revision of the manuscript for important intellectual content: Scordo, Wang, Ahn, Ahmed, Awan, Beitinjaneh, A. Chen, Chow, Dholaria, Epperla, Farooq, Ghosh, Grover, Hamad, Hildebrandt, Holmberg, Hong, Inwards, Jimenez-Jimenez, Karmali, Kenkre, Khimani, Klyuchnikov, Krem, Munshi, Nieto, Prestidge, Ramakrishnan Geethakumari, Rezvani, Riedell, Seo, Shah, Solh, Yared, Kharfan-Dabaja, Herrera, Hamadani, Sauter.

Statistical analysis: Scordo, Wang, Ahn, Y. Chen, Hamad, Klyuchnikov, Krem, Prestidge, Riedell, Yared, Kharfan-Dabaja, Hamadani.

Administrative, technical, or material support: Awan, Jimenez-Jimenez, Karmali, Ramakrishnan Geethakumari, Rezvani, Solh, Yared, Hamadani, Sauter.

Supervision: Scordo, Wang, Awan, Beitinjaneh, Jimenez-Jimenez, Rezvani, Herrera, Hamadani, Sauter.

Other - suggestions on statistical analysis: Khimani.

Other: Prestidge.

Other - suggested additional analysis which was done: Ghosh.

Conflict of Interest Disclosures: Dr Scordo reported personal fees from Angiocrine Bioscience, Inc. Consultancy and Research Support, personal fees from Omeros Corporation Consultancy and Research Support, personal fees from McKinsey & Company Consultancy, other from Kite - A Gilead Company Ad hoc advisory board, and personal fees from i3Health CME speaking engagement outside the submitted work. Dr Awan reported personal fees from AstraZeneca, personal fees from Genentech, personal fees from AbbVie, personal fees from Janssen, personal fees from Pharmacyclics, personal fees from Gilead Sciences, personal fees from Kite Pharma, personal fees from Celgene, personal fees from Karyopharm, personal fees from MEI Pharma, personal fees from Verastem, personal fees from Incyte, personal fees from Beigene, personal fees from ADCT Therapeutic, personal fees from Dava Oncology, personal fees from Bristol-Myers Squibb (BMS), personal fees from Merck, and personal fees from Johnson and Johnson Consultant outside the submitted work. Dr A. Chen reported personal fees from Morphosys, personal fees from Genentech, and personal fees from Mesoblast outside the submitted work. Dr Dholaria reported institutional research support from Takeda, Janssen, Angiocrine, Pfizer, and Poseida. Dr Epperla reported speaker’s bureau fees from Verastem, speaker’s bureau fees from Beigene, advisory board fees from Karyopharm, and consultancy fees from Genzyme outside the submitted work. Dr Farooq reported personal fees from Kite Pharma advisory board outside the submitted work. Dr Ghosh reported grants from Genen/Roche Research Funding, other from TG Therapeutics Research funding, consulting, other from Pharmacyclics Research funding, consulting, other from BMS Research funding, consulting, speakers bureau, personal fees from Seattle Genetics Consulting, personal fees from Gilead/Kite Research funding, consulting, speakers bureau, personal fees from AbbVie Consulting, Speakers bureau, personal fees from Astra Zeneca Consulting, Speakers Bureau, personal fees from Janssen Consulting, Speakers Bureau, personal fees from Karyopharm Consulting, personal fees from Genmab Consulting, personal fees from ADC Therapeutics Consulting, personal fees from Beigene Consulting, personal fees from Adaptive Biotech Consulting, and personal fees from Incyte Consulting outside the submitted work. Dr Grover reported grants from Genentech, grants from Tessa Therapeutics, personal fees from Kite, and nonfinancial support from Bellicum outside the submitted work. Dr Hamad reported honoraria from Novartis, AbbVie, Roche, and Janssen outside the submitted work. Dr Holmberg reported study funding from Seattle Genetics, Sanofi, Millennium-Takada, BMS, Merck, and Janssen outside the submitted work; in addition, Dr Holmberg had a patent for UpToDate with royalties paid. Dr Karmali reported personal fees from Janssen, personal fees from Karyopharm, personal fees from Gilead/Kite, personal fees from BMS/Celgene/Juno, personal fees from AstraZeneca, personal fees from BeiGene, personal fees from Morphosys, grants from Takeda, grants from Gilead/Kite, and grants from BMS/Celgene/Juno outside the submitted work. Dr Khimani reported grants from BMS for GVHD prevention trial outside the submitted work. Dr Munshi reported other from Kite Speakers Bureau and other from Incyte Speakers Bureau outside the submitted work. Dr Rezvani reported grants from Pharmacyclics, other from Nohla One-time scientific advisory board, and scientific advisory board fees from Kaleido outside the submitted work. Dr Riedell reported personal fees from Kite/Gilead, grants from MorphoSys, personal fees from BMS, personal fees from Novartis, personal fees from BeiGene, personal fees from Karyopharm Therapeutics, personal fees from Takeda, personal fees from Verastem, grants from Calibr, grants from Celgene, grants from Kite/Gilead, grants from Novartis, grants from BMS, and personal fees from Bayer outside the submitted work. Dr Seo reported personal fees from Janssen Pharmaceutical KK outside the submitted work. Dr Shah reported personal fees from Miltenyi, personal fees from Lilly, personal fees from TG Therapeutics, personal fees from Legend, and personal fees from Epizyme outside the submitted work. Dr Yared reported personal fees from Kite outside the submitted work. Dr Kharfan-Dabaja reported personal fees from Daiichi Sankyo outside the submitted work. Dr Herrera reported personal fees from BMS, personal fees from Merck, personal fees from Karyopharm, personal fees from Seattle Genetics, personal fees from Gilead/Kite Pharma, grants from Gilead Sciences, grants from BMS, grants from Merck, grants from Seattle Genetics, grants from Genentech, and personal fees from Genentech outside the submitted work. Dr Sauter reported grants from Juno Therapeutic, grants from Celgene, grants from BMS, grants from Precision Biosciences, personal fees from Precision Biosciences, grants from Sanofi Genzyme, personal fees from Sanofi Genzyme, personal fees from Juno Therapeutics, personal fees from Spectrum Pharmaceuticals, personal fees from Novartis, personal fees from Genmab, personal fees from Kite, a Gilead Company, personal fees from Celgene, personal fees from Gamida Cell, personal fees from Karyopharm Therapeutics, and personal fees from GlaxoSmithKline outside the submitted work. No other disclosures were reported.

Funding/Support: The CIBMTR is supported primarily by Public Health Service U24CA076518 from the National Cancer Institute (NCI), the National Heart, Lung and Blood Institute (NHLBI) and the National Institute of Allergy and Infectious Diseases (NIAID); HHSH250201700006C from the Health Resources and Services Administration (HRSA); and N00014-20-1-2705 and N00014-20-1-2832 from the Office of Naval Research; support is also provided by Be the Match Foundation, the Medical College of Wisconsin, the National Marrow Donor Program, and from the following commercial entities: Actinium Pharmaceuticals Inc; Adienne SA; Allovir Inc; Amgen Inc; Angiocrine Bioscience; Astellas Pharma US; bluebird bio Inc; Bristol-Myers Squibb; Celgene Corp; CSL Behring; CytoSen Therapeutics Inc; Daiichi Sankyo Co, Ltd; ExcellThera; Fate Therapeutics; Gamida-Cell Ltd; Genentech Inc; Incyte Corporation; Janssen/Johnson & Johnson; Jazz Pharmaceuticals Inc; Kiadis Pharma; Kite, a Gilead Company; Kyowa Kirin; Legend Biotech; Magenta Therapeutics; Merck Sharp & Dohme Corp; Millennium, the Takeda Oncology Co; Miltenyi Biotec Inc; Novartis Pharmaceuticals Corporation; Omeros Corporation; Oncoimmune Inc; Orca Biosystems Inc; Pfizer Inc; Pharmacyclics LLC; Sanofi Genzyme; Stemcyte; Takeda Pharma; Vor Biopharma; Xenikos BV.

Role of the Funder/Sponsor: The funding organizations had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Disclaimer: The views expressed in this article do not reflect the official policy or position of the National Institutes of Health, the Department of the Navy, the Department of Defense, Health Resources and Services Administration (HRSA), or any other agency of the US government.

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Corresponding author.

PMCID: PMC8283558 PMID: 33956047

Key Points

Question

What are the outcomes associated with autologous hematopoietic cell transplant based on conditioning regimen used in patients with primary central nervous system lymphoma (PCNSL)?

Findings

In this cohort study of registry data from 603 adult patients with PCNSL undergoing autologous hematopoietic cell transplant, the thiotepa-containing conditioning regimens were associated with higher survival rates compared with carmustine/etoposide/cytarabine/melphalan. Although thiotepa-containing conditioning regimens were associated with a lower relapse risk compared with thiotepa/carmustine, there was comparable survival owing to a higher nonrelapse mortality risk.

Meaning

In this study, thiotepa-based conditioning regimens were associated with favorable outcomes, suggesting that the use of carmustine/etoposide/cytarabine/melphalan should be avoided in patients with PCNSL.

Abstract

Importance

Primary central nervous system lymphoma (PCNSL) requires induction and consolidation to achieve potential cure. High-dose therapy and autologous hematopoietic cell transplant (AHCT) is an accepted and effective consolidation strategy for PCNSL, but no consensus exists on the optimal conditioning regimens.

Objective

To assess the outcomes in patients with PCNSL undergoing AHCT with the 3 most commonly used conditioning regimens: thiotepa/busulfan/cyclophosphamide (TBC), thiotepa/carmustine (TT-BCNU), and carmustine/etoposide/cytarabine/melphalan (BEAM).

Design, Setting, and Participants

This observational cohort study used registry data from the Center for International Blood and Marrow Transplant Research registry. The Center is a working group of more than 380 transplantation centers worldwide that contributed detailed data on HCT to a statistical center at the Medical College of Wisconsin, Milwaukee. The participant data were from 603 adult patients with PCNSL who underwent AHCT as initial, or subsequent, consolidation between January 2010 and December 2018. Patients were excluded if they had a non-Hodgkin lymphoma subtype other than diffuse large B-cell lymphoma, systemic non-Hodgkin lymphoma, or HIV; received an uncommon conditioning regimen; or were not in partial remission or complete remission prior to AHCT. Statistical analysis was performed from July 5, 2020, to March 1, 2021.

Interventions

Patients received 1 of 3 conditioning regimens: TBC (n = 263), TT-BCNU (n = 275), and BEAM (n = 65).

Main Outcomes and Measures

The primary outcome was progression-free survival. Secondary outcomes included hematopoietic recovery, incidence of relapse, nonrelapse mortality, and overall survival.

Results

Of 603 patients, the mean age was 57 (range, 19-77) years and 318 (53%) were male. The 3-year adjusted progression-free survival rates were higher in the TBC cohort (75%) and TT-BCNU cohort (76%) compared with the BEAM cohort (58%) (P = .03) owing to a higher relapse risk in the BEAM cohort (hazard ratio [HR], 4.34; 95% CI, 2.45-7.70; P < .001). In a multivariable regression analysis, compared with the TBC cohort, patients who received TT-BCNU had a higher relapse risk (HR, 1.79; 95% CI, 1.07-2.98; P = .03), lower risk of nonrelapse mortality (NRM) (HR, 0.50; 95% CI, 0.29-0.87; P = .01), and similar risk of all-cause mortality more than 6 months after HCT (HR, 1.54; 95% CI, 0.93-2.55; P = .10). Age of 60 years or older, Karnofsky performance status less than 90, and an HCT-comorbidity index greater than or equal to 3 were associated with lower rates of survival across all 3 cohorts. Subgroup analyses demonstrated that patients aged 60 years and older had considerably higher NRM with TBC.

Conclusions and Relevance

In this cohort study, thiotepa-based conditioning regimen was associated with higher rates of survival compared with BEAM, despite higher rates of early toxic effects and NRM; these findings may assist clinicians in choosing between TBC or TT-BCNU based on patient and disease characteristics.

This cohort study used registry data to assess outcomes in patients with primary central nervous system lymphoma undergoing autologous hematopoietic cell transplant with commonly used conditioning regimens.

Introduction

Primary central nervous system lymphoma (PCNSL) is a rare extranodal subtype of non-Hodgkin lymphoma (NHL) associated with a high relapse risk without high-dose methotrexate-based induction and subsequent consolidation therapy.¹ Commonly used consolidation strategies in patients with PCNSL include whole-brain radiotherapy, nonmyeloablative chemotherapy, and high-dose therapy with autologous hematopoietic cell transplant (AHCT), the latter of which abrogates the risk of chronic neurocognitive toxic effects associated with high-dose whole-brain radiotherapy.^2,3,4,5,6,7 Extrapolating from experience with systemic lymphomas, early AHCT studies for PCNSL used carmustine/etoposide/cytarabine/melphalan (BEAM) conditioning with disappointing disease control and survival results.^8,9,10 More recently, single-arm phase 2 studies demonstrated durable disease control and survival with central nervous system penetrant conditioning regimens, such as thiotepa/busulfan/cyclophosphamide (TBC) and thiotepa/carmustine (TT-BCNU).^{4,11,12,13,14,15,16,17}

To our knowledge, no prospective studies have compared conditioning regimens for AHCT in PCNSL. A 2018 meta-analysis¹⁸ comparing mostly single-center studies suggested that TBC conditioning was associated with superior progression-free survival (PFS) and overall survival (OS) compared with TT-BCNU and other regimens despite the potential for a higher incidence of nonrelapse mortality (NRM) and regimen-related toxicities.^4,19 Two pivotal randomized clinical trials, IELSG32 and PRECIS, investigated TT-BCNU- and TBC-conditioned AHCT, respectively, compared with whole-brain radiotherapy as up-front consolidation.^5,7 Although both trials confirmed the efficacy of AHCT, there are limited data comparing thiotepa-based conditioning regimens with BEAM.

We used the Center for International Blood and Marrow Transplant Research (CIBMTR) registry to compare the outcomes of patients with PCNSL undergoing AHCT with the 3 most commonly used conditioning regimens: TBC, TT-BCNU, and BEAM. We hypothesized that patients who received TBC or TT-BCNU, owing to central nervous system bioavailability of thiotepa, would have superior outcomes compared with those who received BEAM.

Methods

This study used data from the CIBMTR registry, a working group of more than 380 transplantation centers worldwide that contributed detailed HCT data to a statistical center at the Medical College of Wisconsin, Milwaukee. Participating centers are required to report all HCTs consecutively, and compliance is monitored by on-site audits. Computerized checks for discrepancies, physicians’ review of submitted data, and on-site audits of participating centers ensured data integrity. Observational studies conducted by the CIBMTR are performed in compliance with all applicable federal regulations pertaining to the protection of human research participants. Patients provided written informed consent for research. The institutional review boards of the Medical College of Wisconsin and the National Marrow Donor Program approved this study. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline for cohort studies.

The CIBMTR collects data at 2 levels: Transplant Essential Data and Comprehensive Report Form data. Transplant Essential Data include disease type, age, sex, pre-HCT disease stage and chemotherapy responsiveness, date of diagnosis, graft type, conditioning regimen, post-HCT disease progression and survival, development of a new malignant neoplasm, and cause of death. All CIBMTR centers contribute Transplant Essential Data. The CIBMTR uses a weighted randomization scheme to select a subset of patients for Comprehensive Report Form reporting with more details about disease and pre-HCT and post-HCT clinical information. Both Transplant Essential Data and Comprehensive Report Form–level data are collected before HCT, at 100 days and 6 months after HCT, and annually thereafter or until death. Data for the current analysis were retrieved from CIBMTR Transplant (Transplant Essential Data and Comprehensive Report Form) report forms.

Patients

This retrospective analysis included adults aged 18 years or older who underwent their first AHCT with peripheral-blood mobilized autografts for chemotherapy-sensitive PCNSL as initial, or subsequent, consolidation between January 2010 and December 2018. Patients were excluded if they had an NHL subtype other than diffuse large B-cell lymphoma, systemic NHL, or HIV; received an uncommon conditioning regimen; or were not in partial remission or complete remission prior to AHCT. The study population was divided into 3 conditioning regimen cohorts: TBC, TT-BCNU, and BEAM (eTable 4 in the Supplement).

Study End Points and Definitions

Disease response prior to AHCT was assessed using standard criteria.²⁰ The primary outcome was PFS, with treatment failure considered at lymphoma relapse, progression, or death from any cause. Secondary outcomes included hematopoietic recovery, relapse or progression, NRM, and OS. Nonrelapse mortality was defined as death without evidence of relapse or progression, with relapse considered a competing risk. Relapse or progression was defined as progressive lymphoma after AHCT, or recurrence after a complete remission, with NRM considered a competing risk. Patients who survived were censored at the date of last follow-up.

Neutrophil recovery was defined as the first of 3 consecutive days with an absolute neutrophil count of greater than or equal to 500/μL (to convert neutrophils to ×10⁹/L, multiply by 0.001) after AHCT nadir. Platelet recovery was defined as the first of 3 consecutive days with a platelet count of greater than or equal to 20 000/μL (to convert platelet count to ×10⁹/L, multiply by 1.0) without platelet transfusion for 7 consecutive days. For neutrophil and platelet recovery, death without the event was considered a competing risk. The PFS and OS probabilities were calculated using the Kaplan-Meier estimates.

Statistical Analyses

Baseline patient and HCT characteristics were compared using the Pearson χ² test for discrete variables and the Kruskal-Wallis test for continuous variables. Cumulative incidences of hematopoietic recovery, relapse, and NRM were calculated to accommodate for competing risks. Cox proportional hazards regression analysis for PFS and OS and the proportional cause-specific hazards model for relapse and NRM were used to identify prognostic factors via forward stepwise selection. The proportional hazard assumption for each variable was examined by testing whether its coefficient was constant over time. Time-varying effects were considered via piecewise proportional hazards models for the variables that violated the proportional hazards assumption.²¹ The interaction between the conditioning regimen and significant covariates was examined. Center effect was tested using the score test of homogeneity.²² Adjusted PFS and OS were calculated based on the final Cox model. Using the variables in the final cause-specific hazards model, cumulative incidences were calculated based on the Fine-Gray model.^23,24 Covariates with a 2-sided P < .05 were considered statistically significant. The variables considered in the multivariable regression analysis are shown in eTable 1 of the Supplement. We also conducted sensitivity analyses to confirm the regression analysis and results using the inverse probability weighting method based on propensity score and the censoring distribution. The bootstrap method was used to evaluate the uncertainty of parameter estimates for the sensitivity analyses. Statistical analysis was performed from July 5, 2020, to March 1, 2021. All statistical analyses were performed using SAS, version 9.4 (SAS Institute) and R, version 4.0.3 (R Foundation for Statistical Computing).

Results

Baseline Characteristics

The study included 603 patients (mean age, 57 [range, 19-77] years; 318 [53%] were male and 285 [47%] were female. Patients received TBC (n = 263), TT-BCNU (n = 275), or BEAM (n = 65) conditioning (Table 1). The cohorts were comparable with respect to age, sex, race, HCT-comorbidity index (HCT-CI), and remission status at HCT. More patients with a Karnofsky performance status (KPS) of 90 to 100 received TBC (n = 147; 56%) compared with TT-BCNU (n = 121; 44%) and BEAM (n = 27; 42%) (P = .02). Median time from diagnosis to HCT in months was longer in the BEAM cohort (11 months; range, 3-122 months) compared with the TBC cohort (8, range 2-192 months) and TT-BCNU cohort (7, range 3-139 months) (P < .001). The conditioning regimen included rituximab more frequently in the BEAM cohort (22%) compared with the TBC cohort (12%) and the TT-BCNU cohort (8%) (P = .004). The median total dose of thiotepa was 18 mg/kg (range, 16-19 mg/kg) in the TBC cohort and 20 mg/kg (range, 10-20 mg/kg) in the TT-BCNU cohort. A higher percentage of patients in the BEAM cohort (55%) underwent AHCT between 2010 and 2014 compared with 2015 and 2018, whereas a higher percentage of patients in the TBC (65%) and TT-BCNU (77%) cohorts underwent AHCT between 2015 and 2018 (P < .001). Median follow-up time of survivors for TBC was 36 months (range, 1-120 months), for TT-BCNU was 24 months (range, 5-98 months), and for BEAM was 48 months (range, 6-97 months).

Table 1. Patient and HCT Characteristics.

Characteristic	No. (%)			P value
Characteristic	TBC (n = 263)	TT-BCNU (n = 275)	BEAM (n = 65)	P value
Age, y
Median (range)	59 (23-76)	60 (20-78)	62 (23-74)	.16
50-59	93 (35)	74 (27)	22 (34)
60-69	104 (40)	115 (42)	28 (43)
≥70	12 (4)	29 (10)	6 (9)
Female sex	129 (49)	125 (46)	31 (48)	.70
Race
White	219 (84)	231 (84)	54 (83)	.10
African American	4 (1)	12 (4)	3 (5)
Asian	25 (9)	15 (6)	4 (6)
Other^a	2 (1)	5 (2)	3 (5)
Missing	13 (5)	12 (4)	1 (1)
KPS
90-100	147 (56)	121 (44)	27 (42)	.02
<90	111 (42)	148 (53)	38 (58)
Missing	7 (3)	9 (3)	0
HCT-CI
0	76 (29)	59 (21)	18 (28)	.26
1-2	79 (30)	91 (33)	16 (25)
≥3	108 (41)	125 (46)	31 (48)
Remission status at HCT
CR1	143 (54)	166 (60)	32 (49)	.18
CR2+	58 (22)	41 (15)	15 (23)
Any PR	62 (24)	68 (25)	18 (28)
Time from diagnosis to HCT, mo
Median (range)	8 (2-192)	7 (3-139)	11 (3-122)	<.001
<6	84 (32)	106 (39)	14 (22)	.03
≥6	175 (67)	169 (61)	51 (78)
Missing	4 (1)	0	0
Remission status and time from diagnosis to HCT
CR1 and ≤6 mo	69 (26)	83 (30)	9 (14)	.09
CR1 and ≥6 mo	71 (27)	83 (30)	23 (35)
CR2+ and >6 mo	58 (22)	41 (15)	15 (23)
PR and ≤6 mo	16 (6)	23 (8)	5 (8)
PR and ≥6 mo	46 (17)	45 (17)	13 (20)
Missing	3 (1)	0	0
Rituximab used in conditioning
Yes	32 (12)	21 (8)	14 (22)	.004
No	231 (88)	254 (92)	51 (78)	.004
Year of HCT
2010-2014	93 (35)	62 (23)	35 (54)	<.001
2015-2018	170 (65)	213 (77)	30 (46)	<.001
Follow-up of survivors, median (range), mo	36 (1-120)	24 (5-98)	48 (6-97)

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Abbreviations: BEAM, carmustine, etoposide, cytarabine, melphalan; CR1, first complete remission; CR2+, second or later complete remission; HCT, hematopoietic cell transplant; HCT-CI, hematopoietic cell transplant–comorbidity index; KPS, Karnofsky performance status; PR, partial remission; TBC, thiotepa, busulfan, cyclophosphamide; TT-BCNU, thiotepa, carmustine.

^{^a}

Other includes other race, for TBC (n = 2): Native Hawaiian/Pacific Islander (n = 1); American Indian/Alaska Native (n = 1); for TT-BCNU (n = 5): Native Hawaiian/Pacific Islander (n = 2); more than one race (n = 3); and for BEAM (n = 3): American Indian/Alaska Native (n = 1); more than one race (n = 2).

Hematopoietic Recovery

The 1-month cumulative incidence of neutrophil recovery for the TBC cohort was 96% (95% CI, 94%-98%), for the TT-BCNU cohort was 100% (95% CI, 98%-100%), and for the BEAM cohort was 100% (95% CI, 0%-100%) (P = .03). The day 100 cumulative incidence of platelet recovery for the TBC cohort was 92% (95% CI, 88%-95%), for the TT-BCNU cohort was 98% (95% CI, 96%-100%), and for the BEAM cohort was 100% (95% CI, 0%-100%) (P = .002) (Table 2). The median number of days to neutrophil engraftment for the TBC cohort was 9 (range, 7-91 days), for the TT-BCNU cohort was 10 (range, 8-24 days), and for the BEAM cohort was 10 (range, 8-24 days) (P < .001). The median number of days to platelet engraftment for the TBC cohort was 17 (range, 10-180 days), for the TT-BCNU cohort was 16 (range, 10-64 days), and for the BEAM cohort was 16 (range, 10-50 days) (P = .61).

Table 2. Unadjusted and Adjusted Probability of Outcomes in Patients Undergoing AHCT for PCNSL.

Outcome	TBC (n = 263)		TT-BCNU (n = 275)		BEAM (n = 65)		P value
Outcome	No. evaluated	Probability, % (95% CI)	No. evaluated	Probability, % (95% CI)	No. evaluated	Probability, % (95% CI)	P value
Neutrophil recovery	261		271		63		<.001
At 30 d		96 (94-98)		100 (98-100)		100 (0-100)	.03
Platelet recovery	253		266		63		.02
At 100 d		92 (88-95)		98 (96-100)		100 (0-100)	.002
Relapse	263		273		63		<.001
At 1 y		6 (3-9)		10 (7-14)		22 (13-34)	.01
At 3 y		11 (7-16)		15 (10-20)		36 (24-49)	.001
Adjusted NRM	263		273		63
At 100 d		7 (4-10)		2 (0.2-3)		0^a	<.001
At 1 y		11 (7-15)		4 (2-6)		4 (0-9)	.01
At 3 y		14 (9-19)		9 (5-14)		6 (0.5-12)	.14
Adjusted PFS	263		273		63
1 y		83 (79-88)		86 (82-90)		72 (62-83)	.05
3 y		75 (69-81)		76 (70-82)		58 (46-70)	.03
Adjusted OS	263		275		65
1 y		87 (83-91)		92 (88-95)		90 (83-97)	.28
3 y		81 (75-86)		78 (72-85)		69 (58-80)	.17

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Abbreviations: AHCT, autologous hematopoietic cell transplant; BEAM, carmustine, etoposide, cytarabine, melphalan; NRM, nonrelapse mortality; OS, overall survival; PCNSL, primary central nervous system lymphoma; PFS, progression-free survival; TBC, thiotepa, busulfan, cyclophosphamide; TT-BCNU, thiotepa, carmustine.

^{^a}

No patients with BEAM experienced either relapse or death by day 100. Thus, its estimate is 0.

Nonrelapse Mortality and Relapse

The adjusted cumulative incidence of NRM at day 100 for the TBC cohort was 7% (95% CI, 4%-10%), for the TT-BCNU cohort was 2% (95% CI, 0.2%-3%), and for the BEAM cohort was 0% (P < .001). The adjusted cumulative incidence of NRM at 1 year for the TBC cohort was 11% (95% CI, 7%-15%), for the TT-BCNU cohort was 4% (95% CI, 2%-6%), and for the BEAM cohort was 4% (95% CI, 0%-9%) (P = .01) (Table 2). In a multivariable regression analysis after adjusting for age and HCT-CI, the use of TT-BCNU (hazard ratio [HR], 0.5; 95% CI, 0.29-0.87; P = .01), but not BEAM (HR, 0.5; 95% CI, 0.2-1.28, P = .15) was associated with a reduced risk of NRM, compared with use of TBC (P = .03) (Table 3, Figure, A).

Table 3. Main Outcomes of Multivariable Regression Analysis.

Variable	No.	HR (95% CI)	P value	Overall P value
Relapse
Conditioning regimen
TBC	263	1 [Reference]		<.001
TT-BCNU	275	1.79 (1.07-2.98)	.03
BEAM	65	4.34 (2.45-7.70)	<.001
NRM^a
Conditioning regimen
TBC	263	1 [Reference]		.03
TT-BCNU	275	0.50 (0.29-0.87)	.01
BEAM	65	0.50 (0.20-1.28)	.15
PFS^b
Conditioning regimen
TBC	263	1 [Reference]		.04
TT-BCNU	275	1.04 (0.72-1.50)	.86
BEAM	65	1.74 (1.10-2.75)	.02
OS^c
Conditioning regimen (≤6 mo after HCT)^a
TBC	263	1 [Reference]		.008
TT-BCNU	275	0.35 (0.17-0.73)	.01
BEAM	65	0.26 (0.06-1.12)	.07
Conditioning regimen (>6 mo after HCT)^d
TBC	232	1 [Reference]		.002
TT-BCNU	257	1.54 (0.93-2.55)	.10
BEAM	62	2.73 (1.56-4.76)	<.001
Missing	3	4.08 (0.53-31.55)	.18

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Abbreviations: BEAM, carmustine, etoposide, cytarabine, melphalan; HCT, hematopoietic cell transplant; HCT-CI, hematopoietic cell transplant comorbidity index; HR, hazard ratio; KPS, Karnofsky performance status; NRM, nonrelapse mortality; OS, overall survival; PFS, progression-free survival; TBC, thiotepa, busulfan, cyclophosphamide; TT-BCNU, thiotepa, carmustine.

^{^a}

NRM adjusted for significant covariates: age, HCT-CI.

^{^b}

PFS adjusted for significant covariates: age, KPS, disease status/time from diagnosis to HCT.

^{^c}

OS adjusted for significant covariates: age, HCT-CI, disease status/time from diagnosis to HCT.

^{^d}

The 6-month time frame was chosen as the cutoff OS based on the maximum likelihood value in the Cox model.

Figure. — BEAM indicates carmustine, etoposide, cytarabine, melphalan; TBC, thiotepa, busulfan, cyclophosphamide; TT-BCNU, thiotepa, carmustine.

The cumulative incidence of relapse or progression at 3 years for the TBC cohort was 11% (95% CI, 7%-16%), for the TT-BCNU cohort was 15% (95% CI, 10%-20%), and for the BEAM cohort was 36% (95% CI, 24%-49%) (P = .001) (Table 2). In a multivariable regression analysis, use of TT-BCNU (HR, 1.79; 95% CI, 1.07-2.98; P = .03) and BEAM (HR, 4.34; 95% CI, 2.45-7.70; P < .001) were associated with an increased risk of relapse or progression, compared with use of TBC (P < .001) (Table 3, Figure, B). Compared with BEAM, use of TT-BCNU was associated with a lower risk of relapse or progression (HR, 0.41; 95% CI, 0.25-0.69; P < .001).

Progression-Free Survival

The adjusted PFS rate at 1 year for the TBC cohort was 83% (95% CI, 79%-88%), for the TT-BCNU cohort was 86% (95% CI, 82%-90%), and for the BEAM cohort was 72% (95% CI, 62%-83%) (P = .05). At 3 years the adjusted PFS rate for the TBC cohort was 75% (95% CI, 69%-81%), for the TT-BCNU cohort was 76% (95% CI, 70%-82%), and for the BEAM cohort was 58% (95% CI, 46%-70%) (P = .03) (Table 2). On multivariable regression analysis after adjusting for age, KPS, and disease status/time from diagnosis to HCT, use of TT-BCNU was associated with similar PFS (HR, 1.04; 95% CI, 0.72-1.5; P = .86), whereas BEAM was associated with inferior PFS (HR, 1.74; 95% CI, 1.1-2.75; P = .02), compared with use of TBC (P = .04) (Table 3, Figure, C).

Overall Survival

The adjusted OS rate at 1 year for the TBC cohort was 87% (95% CI, 83%-91%), for the TT-BCNU cohort was 92% (95% CI, 88%-95%), and for the BEAM cohort was 90% (95% CI, 83%-97%) (P = .28). The adjusted OS rate at 3 years for the TBC cohort was 81% (95% CI, 75%-86%), for the TT-BCNU cohort was 78% (95% CI, 72%-85%), and for the BEAM cohort was 69% (95% CI, 58%-80%) (P = .17) (Table 2). On multivariable regression analysis, the proportional hazards assumption for Cox regression model for OS was violated. Thus, a piecewise proportional hazards model was built, wherein the best cutoff of 6 months after HCT was selected based on the maximum likelihood method. After adjusting for age, HCT-CI, and disease status or time from diagnosis to HCT, in 6 months or less after HCT, the use of TT-BCNU (HR, 0.35; 95% CI, 0.17-0.73; P = .01) was associated with a lower risk of all-cause mortality, compared with use of TBC, but after 6 months, use of TT-BCNU was not associated with a different mortality risk (HR, 1.54; 95% CI, 0.93-2.55; P = .10) compared with TBC. The use of BEAM (HR, 2.73; 95% CI, 1.56-4.76; P < .001) was associated with a higher risk of all-cause mortality compared with use of TBC after 6 months post-HCT (overall P = .002) (Figure, D).

Additional significant covariates in the multivariable analysis for NRM, relapse, PFS, and OS are detailed in eTable 2 in the Supplement. To address potential treatment selection biases, we performed an inverse probability weighting analysis using propensity score. To minimize biases associated with censoring mechanisms or time-dependent selection, we performed an inverse probability censoring weighted regression. The HRs in these analyses were directionally consistent with the regression analysis in Table 3 and are detailed in eTable 5 in the Supplement.

Subgroup Analyses

Among patients aged 59 years or younger who received TBC, the cumulative incidence of NRM was 6% (95% CI, 2%-10%), for those who received TT-BCNU, the cumulative incidence of NRM was 6% (95% CI, 2%-13%), and for those who received BEAM, the cumulative incidence of NRM was 3% (95% CI, 0%-12%) (P = .004). The cumulative incidence of relapse among the same group who received TBC was 8% (95% CI, 4%-14%), for those who received TT-BCNU was 15% (95% CI, 8%-22%), and for those who received BEAM was 43% (95% CI, 24%-62%) (P = .002). The PFS rate for those who received TBC was 86% (95% CI, 79%-92%), for those who received TT-BCNU was 79% (95% CI, 70%-87%), and for those who received BEAM was 54% (95% CI, 35%-72%) (P = .01). The OS rate for those who received TBC was 90% (95% CI, 84%-95%), for those who received TT-BCNU was 81% (95% CI, 71%-89%), and for those who received BEAM was 73% (95% CI, 55%-58%) (P = .05).

Among patients aged 60 years or older who received TBC, the cumulative incidence of NRM at 3 years was 21% (95% CI, 14%-29%), for those who received TT-BCNU, the cumulative incidence of NRM at 3 years was 13% (95% CI, 7%-22%), and for those who received BEAM, the cumulative incidence of NRM at 3 years was 10% (95% CI, 2%-24%) (P = .22). The cumulative incidence of relapse for those who received TBC was 14% (95% CI, 8%-23%), for those who received TT-BCNU was 15% (95% CI, 8%-22%), and for those who received BEAM was 30% (95% CI, 15%-47%) (P = .25). The PFS rate for those who received TBC was 65% (95% CI, 55%-74%), for those who received TT-BCNU was 72% (95% CI, 62%-81%), and for those who received BEAM was 60% (95% CI, 43%-77%) (P = .43). The OS rate for those who received TBC was 69% (95% CI, 59%-78%), for those who received TT-BCNU was 76% (95% CI, 66%-85%), and for those who received BEAM was 57% (95% CI, 39%-74%) (P = .15) (eTable 3 in the Supplement).

Causes of Death

The primary cause of death was relapsed or progressive PCNSL in 38% (20 of 53) of patients for TBC, 72% (33 of 46) of patients for TT-BCNU, and 76% (19 of 25) of patients for BEAM (Table 4). Organ failure in 21% (11 of 53) and infection in 15% (8 of 53) of patients were common causes of death in the TBC cohort. The 11 organ failure–related deaths were pulmonary (6 of 11 [55%]), hepatic (2 of 11 [18%]), cardiac (1 of 11 [9%]), neurologic (1 of 11 [9%]), and multiorgan (1 of 11 [9%]).

Table 4. Causes of Death.

Characteristic	No. (%)
Characteristic	TBC (n = 263)	TT-BCNU (n = 275)	BEAM (n = 65)
Overall survival
Alive	210 (80)	229 (83)	40 (62)
Dead	53 (20)	46 (17)	25 (38)
Cause of death
Primary disease	20 (38)	33 (72)	19 (76)
Infection	8 (15)	3 (7)	2 (8)
IPS	0	1 (2)	0
ARDS	0	1 (2)	0
Organ failure	11 (21)	2 (4)	1 (4)
Secondary malignant neoplasm	2 (4)	1 (2)	1 (4)
Hemorrhage	1 (2)	0	1 (4)
Vascular	0	1 (2)	0
Other	6 (11)	2 (4)	0
Unknown	5 (9)	2 (4)	1 (4)

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Abbreviations: ARDS, acute respiratory distress syndrome; BEAM, carmustine, etoposide, cytarabine, melphalan; IPS, idiopathic pneumonia syndrome; TBC, thiotepa, busulfan, cyclophosphamide; TT-BCNU, thiotepa, carmustine.

Discussion

To address the lack of comparative data regarding the conditioning regimen of choice in patients with PCNSL undergoing AHCT, we performed a registry analysis comparing outcomes of patients across 3 cohorts of the most commonly used conditioning regimens. Despite finding more toxic effects, lower early engraftment rates, and higher early NRM, we also found that use of the thiotepa-containing conditioning regimens, TBC and TT-BCNU, was associated with higher rates of survival compared with use of BEAM owing to protection from relapse and found that BEAM was associated with lower rates of survival and is likely not suitable in patients with PCNSL. We speculate that one potential explanation is the inadequate central nervous system penetration of BEAM.^3,8,9,17,25 Patients who received TBC had a lower risk of relapse than those who received TT-BCNU, but at the cost of a higher risk of NRM, that ultimately was associated with similar long-term OS. The adjusted 3-year NRM rate of 14% for the TBC cohort is high but comparable to the variable rates seen in previous studies.^3,18 However, patients aged 59 years or younger who received TBC conditioning had highly favorable outcomes with 3-year PFS and OS rates of 86% and 90%, respectively.

Although this study cannot definitively determine the optimal thiotepa-containing regimen, it may inform a clinician’s choice based on key patient and disease characteristics. Across all 3 cohorts, age (≥60 years), lower KPS (<90), and high HCT-CI (≥3) were associated with worse survival. More chemotherapy-resistant disease (eg, second or later complete remission, partial remission) and greater time from PCNSL diagnosis to HCT were associated with higher risks of relapse and mortality. Although the TBC cohort had a higher proportion of patients with KPS greater than 90, early NRM was higher than that of the TT-BCNU cohort, leading to similar PFS and OS owing to an increased risk of relapse in patients who received TT-BCNU. In subgroup analyses, patients aged 59 years or younger who received TBC vs TT-BCNU, respectively, had a lower risk of relapse (8% vs 15%), better PFS (86% vs 79%) and OS (90% vs 81%), and comparable NRM (6% vs 6%) at 3 years. For patients aged 60 years or older who received TBC vs TT-BCNU, respectively, despite similar incidences of relapse (14% vs 15%), there was worse 3-year PFS (65% vs 72%) and OS (69% vs 76%), likely reflecting higher NRM (21% vs 13%). This finding suggests that TBC may be more suited to patients who are younger and fitter, particularly those with more advanced disease beyond complete remission 1 given the better protection from relapse, and that TT-BCNU may be more suited to patients who are older with more comorbid conditions.^7,19,26

Limitations

This study has limitations. Limitations include potential patient-selection and center-specific practice biases in choosing the conditioning regimens. This point may be evidenced by greater use of TBC and TT-BCNU in recent years compared with BEAM. Notably, the TT-BCNU cohort had a shorter median follow-up time compared with the TBC cohort (the BEAM cohort had the longest follow-up), although it is uncertain whether relapse and survival rates would be similar with equivalent follow-up. Important data elements were unavailable, including the types of methotrexate-based induction used, whether or when patients received whole-brain radiotherapy, whether pharmacokinetically targeted busulfan was used, if additional consolidation was used after HCT, and which therapies were used after relapse, such as immunotherapies and Bruton tyrosine kinase inhibitors.^27,28 There were insufficient data to evaluate the number of lines of prior therapy and to estimate a PCNSL-specific disease-risk score, thereby limiting a thorough understanding of each cohort’s inherent disease course.²⁹ We attempted to account for this limitation by evaluating best response prior to HCT and time from diagnosis to HCT as surrogates and noted worse OS in patients whose time from diagnosis to HCT was greater than 6 months despite achieving complete remission or partial remission prior to AHCT, suggesting that patients who have longer time from diagnosis to AHCT may have more chemotherapy-resistant disease. Other conditioning regimens that have been studied in PCNSL, such as TT-busulfan and thiotepa-free regimens, are not yet well represented in the registry for adequate comparison.^30,31,32 Our results do not apply to patients with secondary CNSL who were excluded from this study. However, given that thiotepa-containing regimens have been successfully used for secondary CNSL, a separate analysis would be of interest.^{19,33,34,35,36}

Conclusions

To our knowledge, this is the largest retrospective analysis comparing outcomes of patients with PCNSL undergoing consolidative AHCT. Our findings suggest that thiotepa-containing regimens should be considered the standard in patients with PCNSL wherein AHCT is determined to be the consolidation of choice.¹⁸ Given the similar OS seen with TBC and TT-BCNU, a prospective randomized clinical trial would be required to determine the preferred alkylating agent partners with thiotepa that balance the goals of maximal disease control with minimal risk of NRM, although this type of study may be difficult to power. Randomized clinical trials should include comparative toxic effect evaluations and health care resource use data that may better define regimen tolerability and allow for more personalized decision-making for patients. Moreover, we strongly support ongoing efforts to refine the TBC and TT-BCNU conditioning regimens, define optimal chemotherapy dosing, and develop novel approaches for reducing early toxicities to help extend this potentially curative therapy to patients who are older with more comorbid conditions with PCNSL.³⁷

Supplement.

eTable 1. Variables Considered in the Multivariable Analysis

eTable 2. Multivariable Regression Analysis of Outcomes

eTable 3. Univariable Subgroup Analysis of Outcomes by Age Group

eTable 4. Conditioning Chemotherapy Regimen Details

eTable 5. Multivariate Regression – Inverse Probability Weighted Estimator (IPWE-PS) Based on Propensity Score and Inverse Probability Censoring Weighted Estimator (IPCW)

Click here for additional data file.^{(288.5KB, pdf)}

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28.Ferreri AJM, Holdhoff M, Nayak L, Rubenstein JL. Evolving treatments for primary central nervous system lymphoma. Am Soc Clin Oncol Educ Book. 2019;39:454-466. doi: 10.1200/EDBK_242547 [DOI] [PubMed] [Google Scholar]
29.Ferreri AJM, Blay JY, Reni M, et al. Prognostic scoring system for primary CNS lymphomas: the International Extranodal Lymphoma Study Group experience. J Clin Oncol. 2003;21(2):266-272. doi: 10.1200/JCO.2003.09.139 [DOI] [PubMed] [Google Scholar]
30.Yoon DH, Lee DH, Choi DR, et al. Feasibility of BU, CY and etoposide (BUCYE), and auto-SCT in patients with newly diagnosed primary CNS lymphoma: a single-center experience. Bone Marrow Transplant. 2011;46(1):105-109. doi: 10.1038/bmt.2010.71 [DOI] [PubMed] [Google Scholar]
31.Miyao K, Sakemura R, Imai K, et al. Upfront autologous stem-cell transplantation with melphalan, cyclophosphamide, etoposide, and dexamethasone (LEED) in patients with newly diagnosed primary central nervous system lymphoma. Int J Hematol. 2014;100(2):152-158. doi: 10.1007/s12185-014-1608-9 [DOI] [PubMed] [Google Scholar]
32.Sanders S, Chua N, Larouche JF, Owen C, Shafey M, Stewart DA. Outcomes of consecutively diagnosed primary central nervous system lymphoma patients using the Alberta Lymphoma Clinical Practice Guideline incorporating thiotepa-busulfan conditioning for transplantation-eligible patients. Biol Blood Marrow Transplant. 2019;25(8):1505-1510. doi: 10.1016/j.bbmt.2019.04.004 [DOI] [PubMed] [Google Scholar]
33.Welch MR, Sauter CS, Matasar MJ, et al. Autologous stem cell transplant in recurrent or refractory primary or secondary central nervous system lymphoma using thiotepa, busulfan and cyclophosphamide. Leuk Lymphoma. 2015;56(2):361-367. doi: 10.3109/10428194.2014.916800 [DOI] [PubMed] [Google Scholar]
34.DeFilipp Z, Li S, El-Jawahri A, et al. High-dose chemotherapy with thiotepa, busulfan, and cyclophosphamide and autologous stem cell transplantation for patients with primary central nervous system lymphoma in first complete remission. Cancer. 2017;123(16):3073-3079. doi: 10.1002/cncr.30695 [DOI] [PubMed] [Google Scholar]
35.Qualls D, Sullivan A, Li S, et al. High-dose thiotepa, busulfan, cyclophosphamide, and autologous stem cell transplantation as upfront consolidation for systemic non-Hodgkin lymphoma with synchronous central nervous system involvement. Clin Lymphoma Myeloma Leuk. 2017;17(12):884-888. doi: 10.1016/j.clml.2017.08.100 [DOI] [PubMed] [Google Scholar]
36.Korfel A, Elter T, Thiel E, et al. Phase II study of central nervous system (CNS)-directed chemotherapy including high-dose chemotherapy with autologous stem cell transplantation for CNS relapse of aggressive lymphomas. Haematologica. 2013;98(3):364-370. doi: 10.3324/haematol.2012.077917 [DOI] [PMC free article] [PubMed] [Google Scholar]
37.Schorb E, Kasenda B, Ihorst G, et al. High-dose chemotherapy and autologous stem cell transplant in elderly patients with primary CNS lymphoma: a pilot study. Blood Adv. 2020;4(14):3378-3381. doi: 10.1182/bloodadvances.2020002064 [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplement.

eTable 1. Variables Considered in the Multivariable Analysis

eTable 2. Multivariable Regression Analysis of Outcomes

eTable 3. Univariable Subgroup Analysis of Outcomes by Age Group

eTable 4. Conditioning Chemotherapy Regimen Details

eTable 5. Multivariate Regression – Inverse Probability Weighted Estimator (IPWE-PS) Based on Propensity Score and Inverse Probability Censoring Weighted Estimator (IPCW)

Click here for additional data file.^{(288.5KB, pdf)}

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PERMALINK

Outcomes Associated With Thiotepa-Based Conditioning in Patients With Primary Central Nervous System Lymphoma After Autologous Hematopoietic Cell Transplant

Michael Scordo, MD

Trent P Wang, DO, MPH

Kwang W Ahn, PhD

Yue Chen

Sairah Ahmed, MD

Farrukh T Awan, MBBS, MD

Amer Beitinjaneh, MD, MPH

Andy Chen, MD, PhD

Victor A Chow, MD

Bhagirathbhai Dholaria, MBBS

Narendranath Epperla, MD

Umar Farooq, MD

Nilanjan Ghosh, MD, PhD

Natalie Grover, MD

Nada Hamad, MBBS

Gerhard C Hildebrandt, MD

Leona Holmberg, MD, PhD

Sanghee Hong, MD

David J Inwards, MD

Antonio Jimenez-Jimenez, MD, MSc

Reem Karmali, MD, MS

Vaishalee P Kenkre, MD

Farhad Khimani, MD

Evgeny Klyuchnikov, MD

Maxwell M Krem, MD

Pashna N Munshi, MD

Yago Nieto, MD, PhD

Tim Prestidge, BHB, MBChB

Praveen Ramakrishnan Geethakumari, MD

Andrew R Rezvani, MD

Peter A Riedell, MD

Sachiko Seo, MD, PhD

Nirav N Shah, MD

Melhem Solh, MD

Jean A Yared, MD

Mohamed A Kharfan-Dabaja, MD, MBA

Alex Herrera, MD

Mehdi Hamadani, MD

Craig S Sauter, MD

Key Points

Question

Findings

Meaning

Abstract

Importance

Objective

Design, Setting, and Participants

Interventions

Main Outcomes and Measures

Results

Conclusions and Relevance

Introduction

Methods

Patients

Study End Points and Definitions

Statistical Analyses

Results

Baseline Characteristics

Table 1. Patient and HCT Characteristics.

Hematopoietic Recovery

Table 2. Unadjusted and Adjusted Probability of Outcomes in Patients Undergoing AHCT for PCNSL.

Nonrelapse Mortality and Relapse

Table 3. Main Outcomes of Multivariable Regression Analysis.

Figure. Autologous Hematopoietic Cell Transplant Outcomes for Patients With Primary Central Nervous System Lymphoma.

Progression-Free Survival

Overall Survival

Subgroup Analyses

Causes of Death

Table 4. Causes of Death.

Discussion

Limitations

Conclusions

References

Associated Data

Supplementary Materials

ACTIONS

PERMALINK

RESOURCES