新诊断MDS/CMML患者依治疗策略(等待观察、支持治疗、积极治疗)的健康结局

该数据集来自clinicaltrials.gov,为一项观察性、前瞻性、上市后多中心研究,纳入新诊断(<3个月)的MDS或CMML患者,按临床实践接受立即积极/支持治疗或初始采用观察等待策略

CelgeneCelgene
clinicaltrials
浏览 4
其他预测Myelodysplastic SyndromeLeukemia, Myelomonocytic, Chronic
Health Outcomes of Recently Diagnosed Myelodysplastic Syndrome (MDS)/Chronic Myelomonocytic Leukemia (CMML) Patients Depending on Treatment Strategy (Wait and See, Support, Active Treatment)

基本信息

模态
其他
任务类型
预测
创建/更新时间
2026-10-12

资源简介

新诊断MDS/CMML患者依治疗策略(等待观察、支持治疗、积极治疗)的健康结局

该数据集来自clinicaltrials.gov,为一项观察性、前瞻性、上市后多中心研究,纳入新诊断(<3个月)的MDS或CMML患者,按临床实践接受立即积极/支持治疗或初始采用观察等待策略。患者最短随访36个月直至记录生存,积极治疗阶段每3个月或发生事件时采集数据,初始治疗结束后进入治疗后随访阶段每6个月采集一次。数据可用于比较不同治疗策略下的健康结局与生存预测(来源 clinicaltrials.gov)。

【数据内容】

源站描述(机器翻译,仅供参考):条件:骨髓增生异常综合征、慢性粒单核细胞白血病。观察性、前瞻性、上市后多中心研究。该研究将纳入近期诊断(< 3个月)为MDS或CMML的患者,这些患者接受立即积极/支持治疗,或根据各参与中心的常规临床实践最初采用观察方法(“等待观察”)。参与患者的最短随访期为自招募起36个月,直至能够记录生存情况,并区分以下情况:1. 开始立即积极治疗的患者:在积极治疗阶段,每3个月或每当发生事件时收集数据。在初始治疗方案的末次给药后,在治疗后随访阶段,无论患者就诊次数如何,将每6个月进行一次数据收集。

【主题与分类】

主题标签:Myelodysplastic Syndrome、Leukemia, Myelomonocytic, Chronic。本站分类:肿瘤/白血病。

【获取与许可】

源站页面:https://clinicaltrials.gov/study/NCT02085798

官方服务

专家保障全链路合规授权与标注交付

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从合规授权、采集治理、专业标注到数据集交付,我们提供全链路闭环服务,让高质量临床数据即拿即用。

⚡️ 需要原始数据或标注支持?联系我们获取定制方案。

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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

源站:https://clinicaltrials.gov/study/NCT02085798

标准获取流程:

  1. 访问源站链接,注册/登录账号;
  2. 进入数据集详情页,按页面指引申请权限或直接下载;
  3. 部分平台提供 SDK,例如:
    • OpenDataLab: pip install openxlab 后 openxlab.dataset.get(...)
    • ModelScope: pip install modelscope 后 modelscope download
    • 天池: 登录后页面提供直链下载
      以源站「数据下载/使用文档」页面为准。

数据说明

Conditions: Myelodysplastic Syndrome, Leukemia, Myelomonocytic, Chronic. Observational, prospective, post-authorisation multicentre study. The study will include patients with a recent diagnosis (< 3 months) of MDS or CMML, receiving immediate active/support treatment or for whom an observation approach (“wait and see”) is initially adopted, as per normal clinical practice in each participating site. The minimum follow-up period of a participant patient will be 36 months from recruitment, until survival can be documented, differentiating between 1. Patients starting immediate active treatment: data will be collected every 3 months or every time an event arises during the active treatment phase. After the final dose of the initial treatment therapy, data collection will take place every 6 months during the post-treatment follow-up phase, regardless of the number of times the patient attends medical appointments, up to a minimum of 36 months’ follow-up from the start of active treatment. 2. Patients for whom initial treatment strategy is support treatment or observation: a minimum follow-up period of 36 months will be established from the date of inclusion in the study, with data collection every 6 months or whenever an event occurs, regardless of the number of times the patient attends a medical appointment. The need for treatment for MDS (o CMML, where applicable) during this period will be considered an event, after which data will be collected every 3 months or each time an event occurs during the entire active treatment phase. After the final dose of the initial treatment therapy, data collection will take place every 6 months during the post-treatment follow-up phase, regardless of the number of times the patient attends medical appointments, up to a minimum of 36 months’ follow-up from the start of active treatment. Patients will be included consecutively, without the treatment prescription decisions affecting the decision to include the patient in the study. Indeed, in order to ensure the presence of patients with MDS of different

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。

数据缺失?

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