Multicenter Study

. 2022 Jul 26;6(14):4320-4329.

doi: 10.1182/bloodadvances.2022007226.

Developing and validating a mortality prediction model for ICH in ITP: a nationwide representative multicenter study

Shan Chong^{1

2

3

4}, Peng Zhao^{1

2

3

4}, Rui-Bin Huang⁵, Hu Zhou⁶, Jia-Ning Zhang⁷, Ming Hou⁸, Yi Liu⁹, Hong-Xia Yao¹⁰, Ting Niu¹¹, Jun Peng⁸, Ming Jiang¹², Yan-Qiu Han¹³, Jian-Da Hu¹⁴, Ze-Ping Zhou¹⁵, Lin Qiu¹⁶, Lian-Sheng Zhang¹⁷, Xin Wang¹⁸, Hua-Quan Wang¹⁹, Ru Feng²⁰, Lin-Hua Yang²¹, Liang-Ming Ma²², Shun-Qing Wang²³, Pei-Yan Kong²⁴, Wen-Sheng Wang²⁵, Hui-Ping Sun²⁶, Jing Sun²⁷, He-Bing Zhou²⁸, Tie-Nan Zhu²⁹, Li-Ru Wang³⁰, Jing-Yu Zhang³¹, Qiu-Sha Huang^{1

4}, Hai-Xia Fu^{1

2

3

4}, Ye-Jun Wu^{1

2

3

4}, Yue-Ying Li³², Qian-Fei Wang³², Qian Jiang^{1

2

3

4}, Hao Jiang^{1

2

3

4}, Jin Lu^{1

2

3

4}, Xiao-Jun Huang^{1

2

3

4}, Xiao-Hui Zhang^{1

2

3

4}

Affiliations

¹ Peking University People's Hospital, Peking University Institute of Hematology, Beijing, China.
² National Clinical Research Center for Hematologic Disease, Beijing, China.
³ Beijing Key Laboratory of Hematopoietic Stem Cell Transplantation, Beijing, China.
⁴ Collaborative Innovation Center of Hematology, Peking University, Beijing, China.
⁵ Department of Hematology, The First Affiliated Hospital of Nanchang University, Nanchang, China.
⁶ Department of Hematology, Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, China.
⁷ Peking University Cancer Hospital and Institute, Beijing, China.
⁸ Department of Hematology, Qilu Hospital, Shandong University, Jinan, China.
⁹ Department of Geriatric Hematology, Chinese People's Liberation Army General Hospital, Beijing, China.
¹⁰ Department of Hematology, Hainan General Hospital, Haikou, China.
¹¹ Department of Hemotology, West China Hospital, Sichuan University, Chengdu, China.
¹² Department of Hematology, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China.
¹³ Department of Hematology, The Affiliated Hospital of Inner Mongolia Medical University, Hohhot, China.
¹⁴ Fujian Institute of Hematology, Fujian Medical University Union Hospital, Fuzhou, China.
¹⁵ Department of Hematology, The Second Affiliated Hospital of Kunming Medical University, Kunming, China.
¹⁶ Department of Hematology, The First Hospital of Jilin University, Changchun, China.
¹⁷ Department of Hematology, Lanzhou University Second Hospital, Lanzhou, China.
¹⁸ Department of Hematology, Shandong Provincial Hospital Affiliated to Shandong University, Jinan, China.
¹⁹ Department of Hematology, Tianjin Medical University General Hospital, Tianjin, China.
²⁰ Department of Hematology, Beijing Hospital, Ministry of Health, Beijing, China.
²¹ Department of Hematology, Second Affiliated Hospital of Shanxi Medical University, Taiyuan, China.
²² Department of Hematology, Affiliated Shanxi Big Hospital of Shanxi Medical University, Taiyuan, China.
²³ Department of Hematology, Guangzhou First People's Hospital, Guangzhou, China.
²⁴ Xinqiao Hospital, The Third Military Medical University, Chongqing, China.
²⁵ Department of Hematology, Peking University First Hospital, Beijing, China.
²⁶ Rui Jin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
²⁷ Nanfang Hospital, Nanfang Medical University, Guangzhou, China.
²⁸ Beijing Luhe Hospital, Capital Medical University, Beijing, China.
²⁹ Department of Hematology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
³⁰ Fuxing Hospital, Capital Medical University, Beijing, China.
³¹ Department of Hematology, Second Hospital of Hebei Medical University, Shijiazhuang, China; and.
³² Key Laboratory of Genomic and Precision Medicine, Collaborative Innovation Center of Genetics and Development, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China.

PMID: 35679462
PMCID: PMC9327537
DOI: 10.1182/bloodadvances.2022007226

Multicenter Study

Developing and validating a mortality prediction model for ICH in ITP: a nationwide representative multicenter study

Shan Chong et al. Blood Adv. 2022.

. 2022 Jul 26;6(14):4320-4329.

doi: 10.1182/bloodadvances.2022007226.

Authors

Affiliations

¹ Peking University People's Hospital, Peking University Institute of Hematology, Beijing, China.
² National Clinical Research Center for Hematologic Disease, Beijing, China.
³ Beijing Key Laboratory of Hematopoietic Stem Cell Transplantation, Beijing, China.
⁴ Collaborative Innovation Center of Hematology, Peking University, Beijing, China.
⁵ Department of Hematology, The First Affiliated Hospital of Nanchang University, Nanchang, China.
⁶ Department of Hematology, Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, China.
⁷ Peking University Cancer Hospital and Institute, Beijing, China.
⁸ Department of Hematology, Qilu Hospital, Shandong University, Jinan, China.
⁹ Department of Geriatric Hematology, Chinese People's Liberation Army General Hospital, Beijing, China.
¹⁰ Department of Hematology, Hainan General Hospital, Haikou, China.
¹¹ Department of Hemotology, West China Hospital, Sichuan University, Chengdu, China.
¹² Department of Hematology, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China.
¹³ Department of Hematology, The Affiliated Hospital of Inner Mongolia Medical University, Hohhot, China.
¹⁴ Fujian Institute of Hematology, Fujian Medical University Union Hospital, Fuzhou, China.
¹⁵ Department of Hematology, The Second Affiliated Hospital of Kunming Medical University, Kunming, China.
¹⁶ Department of Hematology, The First Hospital of Jilin University, Changchun, China.
¹⁷ Department of Hematology, Lanzhou University Second Hospital, Lanzhou, China.
¹⁸ Department of Hematology, Shandong Provincial Hospital Affiliated to Shandong University, Jinan, China.
¹⁹ Department of Hematology, Tianjin Medical University General Hospital, Tianjin, China.
²⁰ Department of Hematology, Beijing Hospital, Ministry of Health, Beijing, China.
²¹ Department of Hematology, Second Affiliated Hospital of Shanxi Medical University, Taiyuan, China.
²² Department of Hematology, Affiliated Shanxi Big Hospital of Shanxi Medical University, Taiyuan, China.
²³ Department of Hematology, Guangzhou First People's Hospital, Guangzhou, China.
²⁴ Xinqiao Hospital, The Third Military Medical University, Chongqing, China.
²⁵ Department of Hematology, Peking University First Hospital, Beijing, China.
²⁶ Rui Jin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
²⁷ Nanfang Hospital, Nanfang Medical University, Guangzhou, China.
²⁸ Beijing Luhe Hospital, Capital Medical University, Beijing, China.
²⁹ Department of Hematology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
³⁰ Fuxing Hospital, Capital Medical University, Beijing, China.
³¹ Department of Hematology, Second Hospital of Hebei Medical University, Shijiazhuang, China; and.
³² Key Laboratory of Genomic and Precision Medicine, Collaborative Innovation Center of Genetics and Development, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China.

PMID: 35679462
PMCID: PMC9327537
DOI: 10.1182/bloodadvances.2022007226

Abstract

Intracranial hemorrhage (ICH) is a rare and life-threatening hemorrhagic event in patients with immune thrombocytopenia (ITP). However, its mortality and related risk factors remain unclear. Herein, we conducted a nationwide multicenter real-world study of ICH in adult ITP patients. According to data from 27 centers in China from 2005 to 2020, the mortality rate from ICH was 33.80% (48/142) in ITP adults. We identified risk factors by logistic univariate and multivariate logistic regression for 30-day mortality in a training cohort of 107 patients as follows: intraparenchymal hemorrhage (IPH), platelet count ≤10 × 109/L at ICH, a combination of serious infections, grade of preceding bleeding events, and Glasgow coma scale (GCS) level on admission. Accordingly, a prognostic model of 30-day mortality was developed based on the regression equation. Then, we evaluated the performance of the prognostic model through a bootstrap procedure for internal validation. Furthermore, an external validation with data from a test cohort with 35 patients from 11 other centers was conducted. The areas under the receiver operating characteristic (ROC) curves for the internal and external validation were 0.954 (95% confidence interval [CI], 0.910-0.998) and 0.942 (95% CI, 0.871-1.014), respectively. Both calibration plots illustrated a high degree of consistency in the estimated and observed risk. In addition, the decision curve analysis showed a considerable net benefit for patients. Thus, an application (47.94.162.105:8080/ich/) was established for users to predict 30-day mortality when ICH occurred in adult patients with ITP.

© 2022 by The American Society of Hematology. Licensed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0), permitting only noncommercial, nonderivative use with attribution. All other rights reserved.

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Figures

**Figure 1.**
**ROC curve of the prognostic model in the training and test cohorts.** (A) ROC curve of the prognostic model for the training. The area under the curve (AUC) was 0.954 (95% CI, 0.910-0.998). (B) ROC curve of the prognostic model for the test cohort. The AUC was 0.942 (95% CI, 0.871-1.014).

**Figure 2.**
**Calibration plot of the prognostic model in the training and test cohorts.** (A) Calibration plot of the prognostic model for the training cohort. (B) Calibration plot of the prognostic model system for the test cohort. The x-axis plots the predicted 30-day mortality of ICH in adult patients with ITP; the y-axis plots the observed 30-day mortality in our study. A 45° diagonal line represents the ideal calibration plot.

**Figure 3.**
**Decision curve analysis of the prognostic model in the training and test cohorts.** (A) Decision curve analysis of the prognostic model for the training cohort. (B) Decision curve analysis of the prognostic model for the test cohort. Black line: assuming no patient died within 30 days. Gray line: assuming all patients died within 30 days. These 2 lines served as references.

**Figure 4.**
**An application (47.94.162.105:8080/ich/) to predict the 30-day mortality of intracranial hemorrhage (ICH) in ITP patients.** Users can visit the site and fill in these associated clinical features. After submission, the application can automatically output the patient's risk of death within 30 days following ICH in the form of a percentage.

See this image and copyright information in PMC

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Developing and validating a mortality prediction model for ICH in ITP: a nationwide representative multicenter study

Affiliations

Developing and validating a mortality prediction model for ICH in ITP: a nationwide representative multicenter study

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