巴西公共医疗系统中无法获得抗EGFR酪氨酸激酶抑制剂治疗肺癌导致的潜在生命年损失：预算影响与改善策略——一项药物经济学研究

数据集获取（Figshare）

• 源站标题：Potential life years not saved due to lack of access to anti-EGFR tyrosine kinase inhibitors for lung cancer treatment in the Brazilian public healthcare system: Budget impact and strategies to improve access. A pharmacoeconomic study
• DOI：10.6084/m9.figshare.11966040.v1
• 发布日期：2020-03-11
• 文件数：2 个
• 文件总体积：28.14 KB
• 源站页面：https://scielo.figshare.com/articles/dataset/Potential_life_years_not_saved_due_to_lack_of_access_to_anti-EGFR_tyrosine_kinase_inhibitors_for_lung_cancer_treatment_in_the_Brazilian_public_healthcare_system_Budget_impact_and_strategies_to_improve_access_A_pharmacoeconomic_study/11966040

命令行下载

curl -L -o "1806-9460-spmj-137-06-505-gf1.png" "https://ndownloader.figshare.com/files/21969852"
curl -L -o "Table_1.xls" "https://ndownloader.figshare.com/files/21969858"

文件清单

• 1806-9460-spmj-137-06-505-gf1.png（22.50 KB）
• Table_1.xls（5.63 KB）

文件总体积 28.14 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

ABSTRACT BACKGROUND: Lung cancer is the fourth most common cancer in Brazil. In the 2000s, better understanding of molecular pathways led to development of epidermal growth factor receptor (EGFR)-targeted treatments that have improved outcomes. However, these treatments are unavailable in most Brazilian public healthcare services (Sistema Único de Saúde, SUS). OBJECTIVE: To assess the potential number of years of life not saved, the budget impact of the treatment and strategies to improve access. DESIGN AND SETTING: Pharmacoeconomic study assessing the potential societal and economic impact of adopting EGFR-targeted therapy within SUS. METHODS: We estimated the number of cases eligible for treatment, using epidemiological data from the National Cancer Institute. We used data from a single meta-analysis and from the Lung Cancer Mutation Consortium (LCMC) study as the basis for assessing differences in patients’ survival between use of targeted therapy and use of chemotherapy. The costs of targeted treatment were based on the national reference and were compared with the amount reimbursed for chemotherapy through SUS. RESULTS: There was no life-year gain with EGFR-targeted therapy in the single meta-analysis (hazard ratio, HR, 1.01). The LCMC showed that 1,556 potential life-years were not saved annually. We estimated that the annual budget impact was 125 million Brazilian reais (BRL) with erlotinib, 48 million BRL with gefitinib and 52 million BRL with afatinib. Their incremental costs over chemotherapy per life-year saved were 80,329 BRL, 31,011 BRL and 33,225 BRL, respectively. A drug acquisition discount may decrease the budget impact by 30% (with a 20% discount). A fixed cost of 1,000 BRL may decrease the budget impact by 95%. CONCLUSION: Reducing drug acquisition costs may improve access to EGFR-targeted therapy for lung cancer.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.6084/m9.figshare.11966040.v1（source: https://scielo.figshare.com/articles/dataset/Potential_life_years_not_saved_due_to_lack_of_access_to_anti-EGFR_tyrosine_kinase_inhibitors_for_lung_cancer_treatment_in_the_Brazilian_public_healthcare_system_Budget_impact_and_strategies_to_improve_access_A_pharmacoeconomic_study/11966040）。