分化型甲状腺癌术后淋巴结受累预测列线图：一项观察性研究

数据集获取（Figshare）

• 源站标题：Postoperative nomogram for predicting involved lymph node in differentiated thyroid carcinoma: an observational study
• DOI：10.6084/m9.figshare.29875825.v1
• 发布日期：2025-08-09
• 文件数：2 个
• 文件总体积：60.10 KB
• 源站页面：https://tandf.figshare.com/articles/dataset/Postoperative_nomogram_for_predicting_involved_lymph_node_in_differentiated_thyroid_carcinoma_an_observational_study/29875825

命令行下载

curl -L -o "19-Jul-STROBE-checklist.docx" "https://ndownloader.figshare.com/files/57066457"
curl -L -o "Table_S1_flow_chart.docx" "https://ndownloader.figshare.com/files/57066460"

文件清单

• 19-Jul-STROBE-checklist.docx（38.83 KB）
• Table_S1_flow_chart.docx（21.27 KB）

文件总体积 60.10 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

This study aims to develop a comprehensive nomogram to accurately predict differentiated thyroid cancer (DTC) involved lymph node, enabling the personalization of treatment plans and optimizing patient outcomes.
The nomogram was developed through an analysis of data obtained from derivation cohorts. To identify independent predictors of involved lymph node, we utilized the Least Absolute Shrinkage and Selection Operator (LASSO) method in conjunction with multivariable logistic regression. These predictive factors were subsequently integrated into the nomogram’s design. To ensure the tool’s robustness and clinical applicability, we assessed its discriminative ability, calibration, and clinical utility in both the derivation cohort and an independent validation cohort.
The identification of four key parameters – Thyroglobulin, Lymphocyte count, BRAFV600E, and the number of tumor foci – emerged as robust predictors of involved lymph node. The nomogram demonstrated outstanding performance across calibration, discrimination, and clinical applicability, with predictive accuracies of 0.992 in the derivation cohort and 0.920 in the validation cohort.
Peripheral lymphocyte counts have been found to correlate with involved lymph node in DTC patients. A nomogram tailored specifically for predicting involved lymph node in DTC guides personalized postoperative radioactive iodine (RAI) and plays a critical role in the preoperative assessment.
Lymph node involvement is a big dealwhen figuring out how serious someone’s thyroid cancer is. It affects threeimportant medical decisions: 1.How much of the thyroid to remove duringsurgery. 2. Whether to use radioactive iodine treatment after surgery. 3. Howoften to check for cancer returning later
Doctors now use something called”nomograms” - which are like scoring charts – to help predict whatmight happen to patients. This study created a special scoring chart just forthyroid cancer patients, to predict if their cancer has spread to lymph nodes.This helps doctors create personalized treatment plans.
Using special math methods, we foundfour main things that predict lymph node involvement: Thyroglobulin levels (aprotein made by th

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.6084/m9.figshare.29875825.v1（source: https://tandf.figshare.com/articles/dataset/Postoperative_nomogram_for_predicting_involved_lymph_node_in_differentiated_thyroid_carcinoma_an_observational_study/29875825）。