Dynamic Graft-versus-Host Disease-Free, Relapse-Free Survival: Multistate Modeling of the Morbidity and Mortality of Allotransplantation

Shernan G. Holtan; Lin Zhang; Todd E. DeFor; Nelli Bejanyan; Mukta Arora; Armin Rashidi; Aleksandr Lazaryan; Florence Kotiso; Bruce R. Blazar; John E. Wagner; Claudio G. Brunstein; Margaret L. MacMillan; Daniel J. Weisdorf

doi:10.1016/j.bbmt.2019.05.015

Dynamic Graft-versus-Host Disease-Free, Relapse-Free Survival: Multistate Modeling of the Morbidity and Mortality of Allotransplantation

Shernan G. Holtan, Lin Zhang, Todd E. DeFor, Nelli Bejanyan, Mukta Arora, Armin Rashidi, Aleksandr Lazaryan, Florence Kotiso, Bruce R. Blazar, John E. Wagner, Claudio G. Brunstein, Margaret L. MacMillan, Daniel J. Weisdorf

Research output: Contribution to journal › Article › peer-review

11 Scopus citations

Abstract

Graft-versus-host disease (GVHD)-free, relapse-free survival (GRFS) represents complete, ideal recovery after allogeneic hematopoietic cell transplantation (HCT). However, as originally proposed, this composite endpoint does not account for the possibility that HCT complications may improve after treatment. To more accurately estimate survival with response to GVHD and relapse after HCT, we developed a dynamic multistate GRFS (dGRFS) model with outcomes data from 949 patients undergoing their first allogeneic HCT for hematologic malignancy at the University of Minnesota. Because some patients were successfully treated for GVHD and relapse, dGRFS was higher than the originally defined time-to-event GRFS at 1 year (37.0 versus 27.6%) through 4 years (37.4% versus 22.2%). Mean survival without failure events was .52 years (95% confidence interval, .45 to .58 year) greater in dGRFS compared with the originally defined GRFS. Patient age (P< .001), disease risk (P < .001), conditioning intensity (P = .007), and donor type (P = .003) all significantly influenced dGRFS. The multistate model of dGRFS closely estimates the continuing and prevalent severe morbidity and mortality of allogeneic HCT. To serve the greater HCT community in more accurately modeling recovery from transplantation, we provide our R code for determination of dGRFS with annotations in Supplementary Materials.

Original language	English (US)
Pages (from-to)	1884-1889
Number of pages	6
Journal	Biology of Blood and Marrow Transplantation
Volume	25
Issue number	9
DOIs	https://doi.org/10.1016/j.bbmt.2019.05.015
State	Published - Sep 2019

Bibliographical note

Funding Information:
Financial disclosure: This project was supported in part by the National Institutes of Health (Grants P30 CA77598 and P01 CA111412), using the Biostatistics and Bioinformatics Shared Resource of the Masonic Cancer Center, University of Minnesota, and by the National Cancer Institute (Grant P01 CA65493, to B.R.B, and C.G.B.).

Publisher Copyright:
© 2019 American Society for Transplantation and Cellular Therapy

Keywords

Allogeneic hematopoietic cell transplantation
GRFS
Graft-versus-host disease
Multistate modeling
Relapse

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.bbmt.2019.05.015

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Holtan, S. G., Zhang, L., DeFor, T. E., Bejanyan, N., Arora, M., Rashidi, A., Lazaryan, A., Kotiso, F., Blazar, B. R., Wagner, J. E., Brunstein, C. G., MacMillan, M. L., & Weisdorf, D. J. (2019). Dynamic Graft-versus-Host Disease-Free, Relapse-Free Survival: Multistate Modeling of the Morbidity and Mortality of Allotransplantation. Biology of Blood and Marrow Transplantation, 25(9), 1884-1889. https://doi.org/10.1016/j.bbmt.2019.05.015

Holtan, SG, Zhang, L, DeFor, TE, Bejanyan, N, Arora, M, Rashidi, A, Lazaryan, A, Kotiso, F, Blazar, BR , Wagner, JE, Brunstein, CG, MacMillan, ML & Weisdorf, DJ 2019, 'Dynamic Graft-versus-Host Disease-Free, Relapse-Free Survival: Multistate Modeling of the Morbidity and Mortality of Allotransplantation', Biology of Blood and Marrow Transplantation, vol. 25, no. 9, pp. 1884-1889. https://doi.org/10.1016/j.bbmt.2019.05.015

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title = "Dynamic Graft-versus-Host Disease-Free, Relapse-Free Survival: Multistate Modeling of the Morbidity and Mortality of Allotransplantation",

abstract = "Graft-versus-host disease (GVHD)-free, relapse-free survival (GRFS) represents complete, ideal recovery after allogeneic hematopoietic cell transplantation (HCT). However, as originally proposed, this composite endpoint does not account for the possibility that HCT complications may improve after treatment. To more accurately estimate survival with response to GVHD and relapse after HCT, we developed a dynamic multistate GRFS (dGRFS) model with outcomes data from 949 patients undergoing their first allogeneic HCT for hematologic malignancy at the University of Minnesota. Because some patients were successfully treated for GVHD and relapse, dGRFS was higher than the originally defined time-to-event GRFS at 1 year (37.0 versus 27.6%) through 4 years (37.4% versus 22.2%). Mean survival without failure events was .52 years (95% confidence interval, .45 to .58 year) greater in dGRFS compared with the originally defined GRFS. Patient age (P< .001), disease risk (P < .001), conditioning intensity (P = .007), and donor type (P = .003) all significantly influenced dGRFS. The multistate model of dGRFS closely estimates the continuing and prevalent severe morbidity and mortality of allogeneic HCT. To serve the greater HCT community in more accurately modeling recovery from transplantation, we provide our R code for determination of dGRFS with annotations in Supplementary Materials.",

keywords = "Allogeneic hematopoietic cell transplantation, GRFS, Graft-versus-host disease, Multistate modeling, Relapse",

author = "Holtan, {Shernan G.} and Lin Zhang and DeFor, {Todd E.} and Nelli Bejanyan and Mukta Arora and Armin Rashidi and Aleksandr Lazaryan and Florence Kotiso and Blazar, {Bruce R.} and Wagner, {John E.} and Brunstein, {Claudio G.} and MacMillan, {Margaret L.} and Weisdorf, {Daniel J.}",

note = "Funding Information: Financial disclosure: This project was supported in part by the National Institutes of Health (Grants P30 CA77598 and P01 CA111412), using the Biostatistics and Bioinformatics Shared Resource of the Masonic Cancer Center, University of Minnesota, and by the National Cancer Institute (Grant P01 CA65493, to B.R.B, and C.G.B.). Publisher Copyright: {\textcopyright} 2019 American Society for Transplantation and Cellular Therapy",

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AU - Holtan, Shernan G.

AU - Zhang, Lin

AU - DeFor, Todd E.

AU - Bejanyan, Nelli

AU - Arora, Mukta

AU - Rashidi, Armin

AU - Lazaryan, Aleksandr

AU - Kotiso, Florence

AU - Blazar, Bruce R.

AU - Wagner, John E.

AU - Brunstein, Claudio G.

AU - MacMillan, Margaret L.

AU - Weisdorf, Daniel J.

N1 - Funding Information: Financial disclosure: This project was supported in part by the National Institutes of Health (Grants P30 CA77598 and P01 CA111412), using the Biostatistics and Bioinformatics Shared Resource of the Masonic Cancer Center, University of Minnesota, and by the National Cancer Institute (Grant P01 CA65493, to B.R.B, and C.G.B.). Publisher Copyright: © 2019 American Society for Transplantation and Cellular Therapy

PY - 2019/9

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N2 - Graft-versus-host disease (GVHD)-free, relapse-free survival (GRFS) represents complete, ideal recovery after allogeneic hematopoietic cell transplantation (HCT). However, as originally proposed, this composite endpoint does not account for the possibility that HCT complications may improve after treatment. To more accurately estimate survival with response to GVHD and relapse after HCT, we developed a dynamic multistate GRFS (dGRFS) model with outcomes data from 949 patients undergoing their first allogeneic HCT for hematologic malignancy at the University of Minnesota. Because some patients were successfully treated for GVHD and relapse, dGRFS was higher than the originally defined time-to-event GRFS at 1 year (37.0 versus 27.6%) through 4 years (37.4% versus 22.2%). Mean survival without failure events was .52 years (95% confidence interval, .45 to .58 year) greater in dGRFS compared with the originally defined GRFS. Patient age (P< .001), disease risk (P < .001), conditioning intensity (P = .007), and donor type (P = .003) all significantly influenced dGRFS. The multistate model of dGRFS closely estimates the continuing and prevalent severe morbidity and mortality of allogeneic HCT. To serve the greater HCT community in more accurately modeling recovery from transplantation, we provide our R code for determination of dGRFS with annotations in Supplementary Materials.

AB - Graft-versus-host disease (GVHD)-free, relapse-free survival (GRFS) represents complete, ideal recovery after allogeneic hematopoietic cell transplantation (HCT). However, as originally proposed, this composite endpoint does not account for the possibility that HCT complications may improve after treatment. To more accurately estimate survival with response to GVHD and relapse after HCT, we developed a dynamic multistate GRFS (dGRFS) model with outcomes data from 949 patients undergoing their first allogeneic HCT for hematologic malignancy at the University of Minnesota. Because some patients were successfully treated for GVHD and relapse, dGRFS was higher than the originally defined time-to-event GRFS at 1 year (37.0 versus 27.6%) through 4 years (37.4% versus 22.2%). Mean survival without failure events was .52 years (95% confidence interval, .45 to .58 year) greater in dGRFS compared with the originally defined GRFS. Patient age (P< .001), disease risk (P < .001), conditioning intensity (P = .007), and donor type (P = .003) all significantly influenced dGRFS. The multistate model of dGRFS closely estimates the continuing and prevalent severe morbidity and mortality of allogeneic HCT. To serve the greater HCT community in more accurately modeling recovery from transplantation, we provide our R code for determination of dGRFS with annotations in Supplementary Materials.

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KW - Multistate modeling

KW - Relapse

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Dynamic Graft-versus-Host Disease-Free, Relapse-Free Survival: Multistate Modeling of the Morbidity and Mortality of Allotransplantation

Abstract

Bibliographical note

Keywords

UN SDGs

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