无症状个体他汀治疗终身获益的个性化预测：一项建模研究

数据集获取（Figshare）

• 源站标题：Personalized Prediction of Lifetime Benefits with Statin Therapy for Asymptomatic Individuals: A Modeling Study
• DOI：10.1371/journal.pmed.1001361
• 发布日期：2012-12-27
• 文件数：6 个
• 文件总体积：4.16 MB
• 源站页面：https://plos.figshare.com/articles/dataset/Personalized_Prediction_of_Lifetime_Benefits_with_Statin_Therapy_for_Asymptomatic_Individuals_A_Modeling_Study__/115131

命令行下载

curl -L -o "Figure_S1.tif" "https://ndownloader.figshare.com/files/279633"
curl -L -o "Figure_S2.tif" "https://ndownloader.figshare.com/files/279666"
curl -L -o "Figure_S3.tif" "https://ndownloader.figshare.com/files/279691"
curl -L -o "Table_S1.docx" "https://ndownloader.figshare.com/files/279724"
curl -L -o "Table_S2.docx" "https://ndownloader.figshare.com/files/279804"
curl -L -o "Text_S1.doc" "https://ndownloader.figshare.com/files/279866"

文件清单

• Figure_S1.tif（1.36 MB）
• Figure_S2.tif（1.36 MB）
• Figure_S3.tif（1.36 MB）
• Table_S1.docx（15.36 KB）
• Table_S2.docx（15.91 KB）
• Text_S1.doc（52.74 KB）

文件总体积 4.16 MB（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

Background
Physicians need to inform asymptomatic individuals about personalized outcomes of statin therapy for primary prevention of cardiovascular disease (CVD). However, current prediction models focus on short-term outcomes and ignore the competing risk of death due to other causes. We aimed to predict the potential lifetime benefits with statin therapy, taking into account competing risks.
Methods and Findings
A microsimulation model based on 5-y follow-up data from the Rotterdam Study, a population-based cohort of individuals aged 55 y and older living in the Ommoord district of Rotterdam, the Netherlands, was used to estimate lifetime outcomes with and without statin therapy. The model was validated in-sample using 10-y follow-up data. We used baseline variables and model output to construct (1) a web-based calculator for gains in total and CVD-free life expectancy and (2) color charts for comparing these gains to the Systematic Coronary Risk Evaluation (SCORE) charts. In 2,428 participants (mean age 67.7 y, 35.5% men), statin therapy increased total life expectancy by 0.3 y (SD 0.2) and CVD-free life expectancy by 0.7 y (SD 0.4). Age, sex, smoking, blood pressure, hypertension, lipids, diabetes, glucose, body mass index, waist-to-hip ratio, and creatinine were included in the calculator. Gains in total and CVD-free life expectancy increased with blood pressure, unfavorable lipid levels, and body mass index after multivariable adjustment. Gains decreased considerably with advancing age, while SCORE 10-y CVD mortality risk increased with age. Twenty-five percent of participants with a low SCORE risk achieved equal or larger gains in CVD-free life expectancy than the median gain in participants with a high SCORE risk.
Conclusions
We developed tools to predict personalized increases in total and CVD-free life expectancy with statin therapy. The predicted gains we found are small. If the underlying model is validated in an independent cohort, the tools may be useful in discussing with patients their individual outcomes with statin therapy.
Please see later in the article for the Editors’’ Summary

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.1371/journal.pmed.1001361（source: https://plos.figshare.com/articles/dataset/Personalized_Prediction_of_Lifetime_Benefits_with_Statin_Therapy_for_Asymptomatic_Individuals_A_Modeling_Study__/115131）。