医疗成本分布参数
本数据集提供基于中国深圳女性乳腺癌筛查成本效益研究的医疗成本分布参数,用于马尔可夫模型分析。

基本信息
资源简介
医疗成本分布参数
【数据集背景】
本数据集源站标题为《Distribution parameters for medical costs.》。源站首次发布:2026-03-12。
【数据内容】
源站原始描述:Background Early detection through breast cancer screening significantly enhances survival rates and reduces mortality. However, financial constraints in low- and middle-income countries often limit the implementation of large-scale screening programs. This study evaluates the cost-effectiveness of a combined Clinical Breast Examination (CBE), Breast Ultrasound (BUS), and supplementary Mammography (MAM), screening strategy for women aged 35–65 in Shenzhen, China. It further identifies optimal sc…
【数据结构与技术规格】
文件数 1 个,合计 12.77 KB。pone.0344253.s004.xlsx:application/vnd.openxmlformats-officedocument.spreadsheetml.sheet,12.77 KB。数据集 DOI:10.1371/journal.pone.0344253.s004。
【主题与分类】
源站学科分类:Medicine、Biotechnology、Cancer。主题标签:per capita gdp、adjusted life years、49 per 100、triennial ), age、45 ), age、scale screening programs、varying screening frequency、current strategy versus、bus )+ mam、screening frequency。
【适用方向】
结构化表格数据可直接用于统计建模、特征工程与队列分析。
【获取与许可】
源站页面:https://plos.figshare.com/articles/dataset/_p_Distribution_parameters_for_medical_costs_p_/31686792
使用许可:CC BY 4.0(https://creativecommons.org/licenses/by/4.0/)。
规范引用:Tu, Changqing; Zhong, Yuke; Li, Huan; Qi, Haifeng; Lu, Qian; He, Xuesen (2026). Distribution parameters for medical costs.. PLOS ONE. Dataset
下载信息
注册下载
需要注册 Kaggle 账号并登录后下载,适合需要跟踪下载记录和使用 API 的用户。
暂未开放公开下载
无需注册即可直接获取公开样本或文档,适合快速预览和评估数据集质量。
免登录有偿下载
公开数据集受托下载与技术交付服务。
提供高速下载与技术交付服务(收技术服务费,非数据销售)
暂未开放当前数据集主要来源为 Kaggle 公开托管,完整影像包建议通过原始链接或 Kaggle API 获取。
使用方式
数据集获取(Figshare)
- 源站标题:<p>Distribution parameters for medical costs.</p>
- DOI:10.1371/journal.pone.0344253.s004
- 发布日期:2026-03-12
- 文件数:1 个
- 文件总体积:12.77 KB
- 源站页面:https://plos.figshare.com/articles/dataset/_p_Distribution_parameters_for_medical_costs_p_/31686792
命令行下载
curl -L -o "pone.0344253.s004.xlsx" "https://ndownloader.figshare.com/files/62726457"
文件清单
pone.0344253.s004.xlsx(12.77 KB)
文件总体积 12.77 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
Background
Early detection through breast cancer screening significantly enhances survival rates and reduces mortality. However, financial constraints in low- and middle-income countries often limit the implementation of large-scale screening programs. This study evaluates the cost-effectiveness of a combined Clinical Breast Examination (CBE), Breast Ultrasound (BUS), and supplementary Mammography (MAM), screening strategy for women aged 35–65 in Shenzhen, China. It further identifies optimal screening protocols by analyzing variations in screening frequency, starting/ending ages, and long-term health outcomes.
Methods
A Markov model was developed from a societal perspective to assess the lifetime cost-effectiveness of biennial (CBE + BUS)+MAM screening for women aged 35–65. A total of 27 strategies were simulated, varying screening frequency (annual, biennial, triennial), age at initiation (35, 40, 45), age at cessation (65, 69, 70), and modality combinations. Quality-Adjusted Life Years (QALYs) served as the primary health outcome metric. Incremental Cost-Utility Ratios (ICURs) were calculated, with one-way and second-order Monte Carlo sensitivity analyses conducted to evaluate parameter uncertainty.
Results
Among 699,600 participants, 724 breast cancer cases were detected (detection rate: 103.49 per 100,000), with 88% diagnosed at early stages. The current Shenzhen strategy – biennial Clinical Breast Examination combined with Breast Ultrasound and supplementary Mammography ((CBE + BUS)+MAM/2year/35_65) – demonstrated an ICUR of 140,915 CNY/QALY compared to no screening, below one times the per capita GDP (indicating cost-effectiveness). In various scenarios, while the (CBE + BUS)+MAM/3year/45_65 strategy had a lower ICUR (95,545 CNY/QALY), the ICUR for the current strategy versus this alternative was 518,121 CNY/QALY, still below the willingness-to-pay threshold of 537,000 CNY (three times GDP). Second-order Monte Carlo simulations confirmed the robustness of the current strategy in 76% of scenarios.
Conclusion
The (CBE + BUS) +MAM/2year/35_65 strategy was identified as the optimal choice among 27 alternatives, providing a cost-effective balance between early
许可
CC BY 4.0
引用
学术使用请引用 DOI 10.1371/journal.pone.0344253.s004(source: https://plos.figshare.com/articles/dataset/_p_Distribution_parameters_for_medical_costs_p_/31686792)。
数据缺失?
依托陕西、四川两大基地,我们与超过十家三甲医院建立直接合作关系,覆盖合规授权、采集治理、专业标注、数据交付的全流程,为AI医疗团队提供即拿即用的高质量临床数据。
⚡️ 需要数据支持或标注服务?立即联系我们获取专业方案。




