Literature DB >> 28823055

Effectivity of a modified Sanz risk model for early death prediction in patients with newly diagnosed acute promyelocytic leukemia.

Yinjun Lou1, Yafang Ma1, Jianai Sun1, Sansan Suo1, Hongyan Tong1, Wenbin Qian1, Wenyuan Mai1, Haitao Meng1, Jie Jin2,3.   

Abstract

Early death is the main obstacle for the cure of patients with acute promyelocytic leukemia (APL). We have analyzed risk factors of early death from 526 consecutive newly diagnosed APL patients between 2004 and 2016. The overall incidence of early death was 7.2% (38/526). The peak hazard of early death occurred in the first 0-3 days. Multivariate logistic analysis demonstrated white blood cell (WBC) counts [odds ratio (OR) = 1.039; 95% confidence interval (CI): 1.024-1.055; P < 0.001], age (OR = 1.061; 95% CI: 1.025-1.099; P = 0.001) and platelet counts (OR = 0.971; 95% CI: 0.944-0.999; P = 0.038) were independent risk factors for early death. Furthermore, receiver-operator characteristic (ROC) curve analyses revealed a simple WBC/platelet ratio was significantly more accurate in predicting early death [areas under the ROC curve (AUC) = 0.842, 95% CI: 0.807-0.872) than WBC counts (AUC = 0.793; 95% CI: 0.756-0.827) or Sanz score (AUC = 0.746; 95% CI: 0.706-0.783). We stratified APL patients into four risk subgroups: low risk (WBC ≤ 10 × 109/L, platelet >40 × 109/L), intermediate risk (WBC/platelet <0.2 and age ≤ 60, not in low risk), high risk (WBC/platelet ≥0.2 or age > 60, not in low and ultra-high risk) and ultra-high risk (WBC > 50 × 109/L), the early death rates were 0, 0.6, 12.8, and 41.2%, respectively. In conclusion, we proposed a modified Sanz risk model as a useful predictor of early death risk in patients with APL.

Entities:  

Keywords:  Acute promyelocytic leukemia; Early death; Prediction; Prognostic factors; White blood cell

Mesh:

Year:  2017        PMID: 28823055     DOI: 10.1007/s00277-017-3096-5

Source DB:  PubMed          Journal:  Ann Hematol        ISSN: 0939-5555            Impact factor:   3.673


  5 in total

1.  Comparative analysis of causes and predictors of early death in elderly and young patients with acute promyelocytic leukemia treated with arsenic trioxide.

Authors:  Bo Jin; Yingmei Zhang; Wenyi Hou; Fenglin Cao; Ming Lu; Huiyuan Yang; Xuanyu Tian; Yuan Wang; Jinxiao Hou; Jinyue Fu; Haitao Li; Jin Zhou
Journal:  J Cancer Res Clin Oncol       Date:  2019-11-04       Impact factor: 4.553

2.  High Risk Acute Promyelocytic Leukemia - An Enigma for Hematologists: Optimizing Treatment with APML-4 Protocol.

Authors:  Jyotsna Kapoor; Sumeet Prakash Mirgh; Narendra Agrawal; Vishvdeep Khushoo; Narender Tejwani; Reema Singh; Pallavi Mehta; Dinesh Bhurani; Rayaz Ahmed
Journal:  Indian J Hematol Blood Transfus       Date:  2021-09-03       Impact factor: 0.900

3.  Analysis of risk factors for early death in patients with acute promyelocytic leukaemia treated with arsenic trioxide.

Authors:  Yuan Wang; Wenyi Hou; Haitao Li; Xuanyu Tian; Jinqiao Li; Tianming Hu; Deli Shi; Yingmei Zhang
Journal:  Ann Hematol       Date:  2022-02-16       Impact factor: 3.673

4.  Predictors of early death, serious hemorrhage, and differentiation syndrome in Japanese patients with acute promyelocytic leukemia.

Authors:  Hitoshi Minamiguchi; Hiroyuki Fujita; Yoshiko Atsuta; Norio Asou; Toru Sakura; Yasunori Ueda; Masashi Sawa; Nobuaki Dobashi; Yasuhiro Taniguchi; Rikio Suzuki; Yoshihito Uchino; Akihiro Tomita; Shigehisa Tamaki; Maki Hagihara; Katsumichi Fujimaki; Masamitsu Yanada; Yoshinobu Maeda; Masako Iwanaga; Noriko Usui; Yukio Kobayashi; Shigeki Ohtake; Hitoshi Kiyoi; Itaru Matsumura; Yasushi Miyazaki; Tomoki Naoe; Akihiro Takeshita
Journal:  Ann Hematol       Date:  2020-09-02       Impact factor: 3.673

5.  A risk score based on real-world data to predict early death in acute promyelocytic leukemia.

Authors:  Albin Österroos; Tânia Maia; Anna Eriksson; Martin Jädersten; Vladimir Lazarevic; Lovisa Wennström; Petar Antunovic; Jörg Cammenga; Stefan Deneberg; Fryderyk Lorenz; Lars Möllgård; Bertil Uggla; Emma Ölander; Eliana Aguiar; Fernanda Trigo; Martin Höglund; Gunnar Juliusson; Sören Lehmann
Journal:  Haematologica       Date:  2022-07-01       Impact factor: 11.047

  5 in total

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