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1478 Novel Prediction Models of Nonrelapse Mortality in Patients Specific to Each Myeloablative Conditioning before Allogeneic Hematopoietic Stem Cell Transplantation: A Multicenter Analysis from the Kanto Study Group for Cell Therapy (KSGCT)

Program: Oral and Poster Abstracts
Session: 721. Clinical Allogeneic Transplantation: Conditioning Regimens, Engraftment, and Acute Transplant Toxicities: Poster I
Hematology Disease Topics & Pathways:
AML, Diseases, Myeloid Malignancies, Clinically relevant
Saturday, December 5, 2020, 7:00 AM-3:30 PM

Arata Ishii1*, Akira Yokota, MD, PhD2*, Emiko Sakaida, MD, PhD1, Shokichi Tsukamoto, MD, PhD1, Katsuhiro Shono, MD, PhD2*, Takashi Toya, MD, PhD3, Yuho Najima, MD, PhD3, Takeshi Kobayashi, MD3, Noriko Doki, MD, PhD3*, Hideki Nakasone, MD, PhD4, Shinichi Kako, MD4, Takayoshi Tachibana, MD5*, Masatsugu Tanaka, MD5*, Nobuyuki Aotsuka, MD, PhD6*, Toru Sakura, PhD, MD7*, Shingo Yano, MD, PhD8, Shin Fujisawa, MD9*, Yuki Shiko10*, Yohei Kawasaki10*, Chiaki Nakaseko, MD, PhD11 and Yoshinobu Kanda, MD, PhD12,13

1Department of Hematology, Chiba University Hospital, Chiba, Japan
2Department of Hematology, Chiba Aoba Municipal Hospital, Chiba, Japan
3Hematology Division, Tokyo Metropolitan Cancer and Infectious Diseases Center, Komagome Hospital, Tokyo, Japan
4Division of Hematology, Jichi Medical University Saitama Medical Center, Saitama, Japan
5Department of Hematology, Kanagawa Cancer Center, Yokohama, Japan
6Department of Hematology and Oncology, Japanese Red Cross Narita Hospital, Narita, Japan
7Leukemia Research Center, Saiseikai Maebashi Hospital, Maebashi, Japan
8Division of Clinical Oncology and Hematology, Jikei University School of Medicine, Tokyo, Japan
9Department of Hematology, Yokohama City University Medical Center, Yokohama, Japan
10Biostatistics Section, Clinical Research Center, Chiba University Hospital, Chiba, Japan
11Department of Hematology, International University of Health and Welfare, Narita, Japan
12Jichi Medical University, Shimotsuke, Japan
13Kanto Study Group for Cell Therapy, Tokyo, Japan


Despite recent developments on various transplantation procedures and supportive therapy, nonrelapse mortality (NRM) after allogeneic stem cell transplantation (allo-SCT) remains an essential issue. In choosing the appropriate regimen for allo-SCT, decision-making information that considers the complexity of different risk factors is vital. The Hematopoietic Cell Transplantation-Comorbidity Index (HCT-CI), which was initially derived and validated by investigators at the Fred Hutchinson Cancer Research Center to predict NRM, has become a widely validated tool for predicting outcomes in many transplant settings (Sorror et al. Blood. 2005). It can also stratify patients for the risk of other outcomes, including overall survival and graft versus host disease. Patients with a high HCT-CI score tend to prefer allo-SCT with reduced-intensity conditioning. Conversely, for those who prefer allo-SCT with myeloablative conditioning (MAC) and has a low HCT-CI score, a prognostic indicator is unnecessary. Furthermore, the risk factors for NRM may differ among various conditioning regimens. Therefore, the current study aimed to establish a new prognostic model for patients specific to each MAC regimen before allo-SCT.


We performed a retrospective cohort study to develop prognostic models of NRM in patients conditioned with cyclophosphamide/total body irradiation (Cy/TBI) or busulfan/cyclophosphamide (Bu/Cy). We selected patients who had leukemia and lymphoma in remission or had untreated or stable myelodysplastic syndrome and experienced initial allo-SCT relapse between 2007 and 2017 in the Kanto Study of Group for Cell Therapy (KSGCT). The primary outcome measure was 2-year NRM. Furthermore, we evaluated variables such as patient age, albumin, liver function, renal function, respiratory function, ejection fraction (EF), C-reactive protein (CRP), stem cell source, donor type, antithymocyte globulin use, performance status, recipient/donor sexes, time interval from diagnosis to transplant, and HCT-CI score. To identify a set of variables for Cox proportional hazards, we used an Akaike Information Criterion (AIC)-based variable selection procedure. We assigned weights to individual parameters according to their prognostic significance in Cox proportional hazard models. The identified model’s discriminative ability was assessed by Harrell’s C-statistic calculated using the bootstrap method.


Among the 555 patients analyzed, 338 received Cy/TBI, and 217 received Bu/Cy. In Cy/TBI and Bu/Cy, the median age was 39 (11–60) and 44 (18–62) years, the HCT-CI score ≤ 2 was observed in 82.1% and 87.6%, and 2-year NRM was found in 13.5% and 16.0% of the patients, respectively. Before transplantation, the most dominant parameters in Cy/TBI were abnormal liver function (AST/ALT or bilirubin >upper limit of normal) and albumin value < 4.5g/dL, whereas those in Bu/Cy were age >40 years, EF < 65 %, and CRP ≥ 0.2 mg/dL. Internal validation with bootstrap resampling showed good discrimination, with C-statistic values of 0.70 (95% CI: 0.69–0.71) in Cy/TBI and 0.68 (95% CI: 0.67–0.69) in Bu/Cy. Each of the abovementioned parameters, including age >40 years, was scored as 1 point. To evaluate the 2-year NRM, we divided the total scores into three risk groups. In the Cy/TBI group, the NRM was 6.9% in low (score 0–1, n = 186), 19.5% in intermediate (score 2, n = 127), and 35.3% in high (score 3, n = 25) scores. In the Bu/Cy group, the NRM was 8.3% in low (score 0–1, n = 93), 21.7% in intermediate (score 2, n = 98), and 29.8% in high (score 3, n = 26) scores (Figure). Higher scores were strongly associated with worse NRM and survival.


Our prognostic models for NRM estimation can distinguish patients with a high NRM risk. To our knowledge, these models are the first prognostic models used to estimate NRM for standard-risk patients specific to each MAC regimen. This new simple index may help predict NRM and choose an appropriate conditioning regimen before allo-SCT.

Disclosures: Nakasone: Takeda Pharmaceutical: Honoraria; Otsuka Pharmaceutical: Honoraria; Bristol-Myers Squibb: Honoraria; Celgene: Honoraria; Pfizer: Honoraria; Novartis: Honoraria; Janssen Pharmaceutical: Honoraria; Eisai: Honoraria; Chugai Pharmaceutical: Honoraria; Nippon Shinyaku: Honoraria. Fujisawa: Takeda Pharmaceutical Company Limited.: Speakers Bureau; Astellas Pharma Inc.: Research Funding, Speakers Bureau; Otsuka Pharmaceutical: Speakers Bureau; Pfizer Japan Inc.: Research Funding, Speakers Bureau; Bristol-Myers Squibb Company: Speakers Bureau; Novartis Pharma KK: Research Funding, Speakers Bureau; Celgene: Speakers Bureau; Janssen Pharmaceutical K.K: Speakers Bureau; NIPPON SHINYAKU CO.,LTD.: Research Funding. Nakaseko: Novartis Pharma KK: Speakers Bureau; Pfizer Japan Inc.: Speakers Bureau. Kanda: Novartis: Honoraria; Kyowa Kirin: Honoraria, Research Funding; Bristol-Myers Squibb: Honoraria; Takeda Pharmaceuticals: Honoraria; Alexion Pharmaceuticals: Honoraria; Shire: Honoraria; Daiichi Sankyo: Honoraria; Ono Pharmaceutical: Honoraria; Nippon Shinyaku: Honoraria, Research Funding; Mochida Pharmaceutical: Honoraria; Mundipharma: Honoraria; Sanofi: Honoraria, Research Funding; Meiji Seika Kaisha: Honoraria; Shionogi: Research Funding; Otsuka: Honoraria, Research Funding; Celgene: Honoraria; Chugai Pharma: Honoraria, Research Funding; Eisai: Honoraria, Research Funding; Janssen: Honoraria; Astellas Pharma: Honoraria, Research Funding; Sumitomo Dainippon Pharma: Honoraria; Pfizer: Honoraria, Research Funding; Merck Sharp & Dohme: Honoraria.

*signifies non-member of ASH