临床试验搜索原始数据
包含18名癌症患者临床试验搜索的原始数据，用于分析搜索引擎局限性。
基本信息
资源简介
临床试验搜索原始数据
【一句话概览】
本数据集是 figshare 公开的结构化表格数据集，收录 1 个文件、合计 18.42 KB，主题涵盖 health care professionals、enable healthcare professionals、binomial confidence interval、alternative websites yet、canadian cancer trials，可用于统计建模、特征工程与队列分析，CC BY 4.0 许可开放获取。
【数据集背景】
本数据集源站标题为《Raw Data.》。源站首次发布：2025-06-25。
【数据内容】
源站原始描述：Background Clinical trials play a critical role in providing patients with access to novel treatments and therapies. However, limitations in clinical trial search engines impede healthcare professionals and patients from accessing the most suitable clinical trials. This study aimed to address this issue by conducting a critical analysis of several prominent clinical trial search websites, including ClinicalTrials.gov, Canadian Cancer Trials, Clinical Trials Ontario, Canadian Cancer Clinical Tria…
【数据结构与技术规格】
文件数 1 个，合计 18.42 KB。pone.0326139.s002.xlsx：application/vnd.openxmlformats-officedocument.spreadsheetml.sheet，18.42 KB。数据集 DOI：10.1371/journal.pone.0326139.s002。
【主题与分类】
源站学科分类：Space Science、Medicine、Biotechnology、Cancer、Science Policy、Infectious Diseases。主题标签：health care professionals、enable healthcare professionals、binomial confidence interval、alternative websites yet、canadian cancer trials、140 eligible trials、enhanced search engines、enhance patient outcomes、cross sectional analysis、clinical trials ontario。
【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/Raw_Data_/29405476
使用许可：CC BY 4.0（https://creativecommons.org/licenses/by/4.0/）。
规范引用：Paunic, Milica; Rim, Sanghyuk; Hilal, Olla; Nassar, Renée; Driedger, Zoe; Zaib, Farwa; et al. (2025). Raw Data.. 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。
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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。
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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：Raw Data.
- DOI：10.1371/journal.pone.0326139.s002
- 发布日期：2025-06-25
- 文件数：1 个
- 文件总体积：18.42 KB
- 源站页面：https://plos.figshare.com/articles/dataset/Raw_Data_/29405476
命令行下载
curl -L -o "pone.0326139.s002.xlsx" "https://ndownloader.figshare.com/files/55649323"
文件清单
pone.0326139.s002.xlsx（18.42 KB）
文件总体积 18.42 KB（源站 API 实测）。
数据说明
Background
Clinical trials play a critical role in providing patients with access to novel treatments and therapies. However, limitations in clinical trial search engines impede healthcare professionals and patients from accessing the most suitable clinical trials. This study aimed to address this issue by conducting a critical analysis of several prominent clinical trial search websites, including ClinicalTrials.gov, Canadian Cancer Trials, Clinical Trials Ontario, Canadian Cancer Clinical Trials Network, and Q-CROC.
Methods
To identify areas for improvement, three skilled clinical trials navigators independently curated clinical trial searches for 18 cancer patients over a 2-month period. After verifying patients’ eligibility for enrollment in clinical trials, the navigators documented their search outcomes and identified several limitations in the current search engines.
Results
Careful curation of clinical trials for 18 patients revealed 247 trials. However, 140 eligible trials out of 247 (57% with 95% binomial confidence interval [50%, 63%]) were found only on alternative websites yet not discoverable on the initial ClinicalTrials.gov searches, even though they were listed on ClinicalTrials.gov. Our study revealed multiple deficiencies in available clinical trials search engines. Lack of reliability was repeatedly identified in all search engines.
Discussion
This study highlights that the current clinical trial search system needs improvement to enhance patient outcomes. It needs to be highlighted that these searches were performed by trained and dedicated clinical trials navigators. The challenges facing patients and health care professionals in navigating would be much greater. The findings from this study can serve as a foundation for the development of enhanced search engines with improved functionality, which will enable healthcare professionals and patients to find and access the most suitable clinical trials with greater ease and accuracy.
许可
CC BY 4.0
引用
学术使用请引用 DOI 10.1371/journal.pone.0326139.s002（source: https://plos.figshare.com/articles/dataset/Raw_Data_/29405476）。
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。
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