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Dynamic trajectory of platelet counts after the first cycle of induction chemotherapy in AML patients
BACKGROUND: Platelet counts varied over time after induction chemotherapy. We aimed to investigate the different trajectories of platelet counts after the first cycle of induction chemotherapy in patients newly diagnosed with acute myeloid leukemia. METHODS AND RESULTS: In total, 149 individuals wer...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9059911/ https://www.ncbi.nlm.nih.gov/pubmed/35501722 http://dx.doi.org/10.1186/s12885-022-09601-5 |
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author | Bi, Yazhen Wang, Zhaohui Feng, Saran Wang, Yan Zhao, Yang Li, Hong Yu, Jingyi Liu, Qian Zhu, Chuansheng Li, Mingzhuo |
author_facet | Bi, Yazhen Wang, Zhaohui Feng, Saran Wang, Yan Zhao, Yang Li, Hong Yu, Jingyi Liu, Qian Zhu, Chuansheng Li, Mingzhuo |
author_sort | Bi, Yazhen |
collection | PubMed |
description | BACKGROUND: Platelet counts varied over time after induction chemotherapy. We aimed to investigate the different trajectories of platelet counts after the first cycle of induction chemotherapy in patients newly diagnosed with acute myeloid leukemia. METHODS AND RESULTS: In total, 149 individuals were included in this study. We identified four distinct trajectories using a group-based trajectory model: low- stability group (n = 27, 18.12%), low-level decrease–medium elevation group (n = 42, 28.19%), low-level decrease–high elevation group (n = 60, 40.27%), and high-level decrease–medium elevation group (n = 20, 13.42%). The baseline characteristics of the high-level decrease–medium elevation group included higher platelet count, lower white blood cell count, lower percentage of bone marrow blasts, and lower rates of complete remission after the first cycle of induction chemotherapy. Compared with the low-stability group, the hazard ratios were 0.32 (95% confidence interval, 0.15–0.68) for the low-level decrease–medium elevation group, 0.31 (95% confidence interval, 0.15–0.63) for the low-level decrease–high elevation group, and 0.35 (95% confidence interval, 0.13–0.89) for the high-level decrease–medium elevation group after adjustment for age and gender by Cox proportional hazard regression. Compared with the low-stability group, the hazard ratios were 0.33 (95% confidence interval, 0.14–0.77) for the low-level decrease–medium elevation group and 0.31 (95% confidence interval, 0.14–0.67) for the low-level decrease–high elevation group after adjustment for age, gender, white blood cell count, and bone marrow blasts. These associations persisted after adjusting for age, gender, white blood cell count, bone marrow blasts, and platelet count. CONCLUSION: The dynamic trajectory of platelet counts after the first cycle of induction chemotherapy is a significant predictor of all-cause mortality in patients with acute myeloid leukemia. Timely intervention should be considered for the low-stability group. The low-level decrease–medium elevation and low-level decrease-high elevation groups were independent protective factors for all-cause mortality. |
format | Online Article Text |
id | pubmed-9059911 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-90599112022-05-03 Dynamic trajectory of platelet counts after the first cycle of induction chemotherapy in AML patients Bi, Yazhen Wang, Zhaohui Feng, Saran Wang, Yan Zhao, Yang Li, Hong Yu, Jingyi Liu, Qian Zhu, Chuansheng Li, Mingzhuo BMC Cancer Research BACKGROUND: Platelet counts varied over time after induction chemotherapy. We aimed to investigate the different trajectories of platelet counts after the first cycle of induction chemotherapy in patients newly diagnosed with acute myeloid leukemia. METHODS AND RESULTS: In total, 149 individuals were included in this study. We identified four distinct trajectories using a group-based trajectory model: low- stability group (n = 27, 18.12%), low-level decrease–medium elevation group (n = 42, 28.19%), low-level decrease–high elevation group (n = 60, 40.27%), and high-level decrease–medium elevation group (n = 20, 13.42%). The baseline characteristics of the high-level decrease–medium elevation group included higher platelet count, lower white blood cell count, lower percentage of bone marrow blasts, and lower rates of complete remission after the first cycle of induction chemotherapy. Compared with the low-stability group, the hazard ratios were 0.32 (95% confidence interval, 0.15–0.68) for the low-level decrease–medium elevation group, 0.31 (95% confidence interval, 0.15–0.63) for the low-level decrease–high elevation group, and 0.35 (95% confidence interval, 0.13–0.89) for the high-level decrease–medium elevation group after adjustment for age and gender by Cox proportional hazard regression. Compared with the low-stability group, the hazard ratios were 0.33 (95% confidence interval, 0.14–0.77) for the low-level decrease–medium elevation group and 0.31 (95% confidence interval, 0.14–0.67) for the low-level decrease–high elevation group after adjustment for age, gender, white blood cell count, and bone marrow blasts. These associations persisted after adjusting for age, gender, white blood cell count, bone marrow blasts, and platelet count. CONCLUSION: The dynamic trajectory of platelet counts after the first cycle of induction chemotherapy is a significant predictor of all-cause mortality in patients with acute myeloid leukemia. Timely intervention should be considered for the low-stability group. The low-level decrease–medium elevation and low-level decrease-high elevation groups were independent protective factors for all-cause mortality. BioMed Central 2022-05-01 /pmc/articles/PMC9059911/ /pubmed/35501722 http://dx.doi.org/10.1186/s12885-022-09601-5 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Bi, Yazhen Wang, Zhaohui Feng, Saran Wang, Yan Zhao, Yang Li, Hong Yu, Jingyi Liu, Qian Zhu, Chuansheng Li, Mingzhuo Dynamic trajectory of platelet counts after the first cycle of induction chemotherapy in AML patients |
title | Dynamic trajectory of platelet counts after the first cycle of induction chemotherapy in AML patients |
title_full | Dynamic trajectory of platelet counts after the first cycle of induction chemotherapy in AML patients |
title_fullStr | Dynamic trajectory of platelet counts after the first cycle of induction chemotherapy in AML patients |
title_full_unstemmed | Dynamic trajectory of platelet counts after the first cycle of induction chemotherapy in AML patients |
title_short | Dynamic trajectory of platelet counts after the first cycle of induction chemotherapy in AML patients |
title_sort | dynamic trajectory of platelet counts after the first cycle of induction chemotherapy in aml patients |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9059911/ https://www.ncbi.nlm.nih.gov/pubmed/35501722 http://dx.doi.org/10.1186/s12885-022-09601-5 |
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