原发性自身免疫性溶血性贫血复发预测模型的构建：一项回顾性队列研究

数据集获取（Figshare）

• 源站标题：Construction of a predictive model for relapse of primary autoimmune hemolytic anemia: a retrospective cohort study
• DOI：10.6084/m9.figshare.29126407.v1
• 发布日期：2025-05-22
• 文件数：1 个
• 文件总体积：111.10 KB
• 源站页面：https://tandf.figshare.com/articles/dataset/Construction_of_a_predictive_model_for_relapse_of_primary_autoimmune_hemolytic_anemia_a_retrospective_cohort_study/29126407

命令行下载

curl -L -o "iann_a_2506482_sm4766.xls" "https://ndownloader.figshare.com/files/54728737"

文件清单

• iann_a_2506482_sm4766.xls（111.10 KB）

文件总体积 111.10 KB（源站 API 实测）。

数据加载示例（图像类）

from PIL import Image
import glob, os

files = (glob.glob(os.path.join(path, "**", "*.png"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.jpg"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.tif"), recursive=True))
print("图像文件数:", len(files))
img = Image.open(files[0]); print("尺寸/模式:", img.size, img.mode)

# torchvision Dataset 方式:
# from torchvision import datasets
# ds = datasets.ImageFolder(path)  # 要求 子目录=类别

目录组织与标注格式以源站说明和下载后实际文件为准。

数据说明

To develop a machine learning-based model to predict the relapse risk of Primary Autoimmune Haemolytic Anaemia (AIHA) after the last remission.
A retrospective study was conducted on primary AIHA cases who visited the Affiliated Hospital of Southwest Medical University and Xuyong County People’s Hospital from May 2017 to May 2022. Cases were categorized as relapsed or non-relapsed based on the 1-year outcomes. Twenty-two features were analyzed to identify relapse risk factors. The least absolute shrinkage and selection operator (LASSO) regression model and multivariate logistic regression analysis were used to establish a predictive model. The C-index, Calibration curves, ROC, and Decision curve analysis (DCA) were used to evaluate the discriminatory, corrective, accurate, and clinical effectiveness of the predictive model.
A total of 232 cases of primary AIHA were included, and five potential variables including ‘DAT results’, ‘Hb’, ‘Multiline therapy’, ‘Complicating ITP’, and ‘Complicating infection’, have been screened for constructing a 1-year relapse risk prediction nomogram for primary AIHA. The nomogram has a C-index of 0.852 (95% CI: 0.797–0.907), confirmed by bootstrapping validation as 0.829. The area under the ROC was 0.846. The DCA shows that when the threshold probability is in the range of 1 ∼ 91%.
By following the current diagnostic and treatment criteria for AIHA in China, we retrospectively collect a multitude of medical records and analyze several relevant variables of AIHA, construct a predictive model by machine learning. Using this 1-year relapse risk nomogram can effectively predict the risk of relapse within 1 year after remission of primary AIHA.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.6084/m9.figshare.29126407.v1（source: https://tandf.figshare.com/articles/dataset/Construction_of_a_predictive_model_for_relapse_of_primary_autoimmune_hemolytic_anemia_a_retrospective_cohort_study/29126407）。