研究参与者的临床特征

数据集获取（Figshare）

• 源站标题：Clinical characteristics of study participants.
• DOI：10.1371/journal.pone.0311815.t003
• 发布日期：2024-10-09
• 文件数：1 个
• 文件总体积：9.73 KB
• 源站页面：https://plos.figshare.com/articles/dataset/Clinical_characteristics_of_study_participants_/27197505

命令行下载

curl -L -o "Table 3.xls" "https://ndownloader.figshare.com/files/49703562"

文件清单

• Table 3.xls（9.73 KB）

文件总体积 9.73 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

Cancer patients often grapple with substantial out-of-pocket (OOP) expenses and productivity loss, with the ramifications being particularly crucial for lower-income households. This study aims to estimate OOP costs incurred by cancer patients, assess their productivity loss, and analyse the financial coping mechanisms employed by individuals within the lower-income bracket. The study employed face-to-face interviews among cancer patients aged 40 years and above, currently undergoing treatment, and belonging to the lower-income group. Participants were recruited from six public cancer referral hospitals. OOP expenses, encompassing medical and non-medical costs, along with productivity loss, were measured. A generalized linear model was applied to identify potential OOP determinants. Additionally, the coping mechanisms employed by individuals to finance their cancer OOP expenses were also determined. Among the 430 participants recruited, predominantly female (63.5%), and aged 60 or older (53.9%). The annual mean total cancer costs per patient were US$ 2,398.28 (±2,168.74), including 15% for medical costs US$ 350.95 (±560.24), 34% for non-medical costs US$820.24 (±818.24), and 51% for productivity loss costs US$1,227.09 (±1,809.09). Transportation, nutritional supplements, outpatient treatment, and medical supplies were notable cost contributors to total OOP expenditures. Ethnicity (β = 1.44; 95%CI = 1.15–1.79), household income (β = 1.40; 95%CI = 1.10–1.78), annual outpatient visits (β = 1.00; 95%CI = 1.00–1.01), age (β = 0.74; 95%CI = 0.56–0.98), and employment status (β = 0.54; 95%CI = 0.72–1.34) were identified as significant predictors of OOP costs among cancer patients. Notably, 91% of participants relied on household salaries and savings, while 15% resorted to interest-free borrowing, 11% sold possessions, and 0.5% borrowed with interest to finance their expenses. This study offers crucial insights into the economic impact of cancer on individuals and their families, providing policymakers with valuable information to tackle challenges faced in their journey. Despite substantial public healthcare subsidies, the study revealed that cancer costs can remain a

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.1371/journal.pone.0311815.t003（source: https://plos.figshare.com/articles/dataset/Clinical_characteristics_of_study_participants_/27197505）。