局部晚期直肠乙状结肠癌术后预后列线图辅助化疗患者选择数据集

数据集获取（Figshare）

• 源站标题：Table_1_A Postsurgical Prognostic Nomogram for Locally Advanced Rectosigmoid Cancer to Assist in Patient Selection for Adjuvant Chemotherapy.docx
• DOI：10.3389/fonc.2021.772482.s001
• 发布日期：2021-12-24
• 文件数：1 个
• 文件总体积：20.48 KB
• 源站页面：https://frontiersin.figshare.com/articles/dataset/Table_1_A_Postsurgical_Prognostic_Nomogram_for_Locally_Advanced_Rectosigmoid_Cancer_to_Assist_in_Patient_Selection_for_Adjuvant_Chemotherapy_docx/17471729

命令行下载

curl -L -o "Table_1_A Postsurgical Prognostic Nomogram for Locally Advanced Rectosigmoid Cancer to Assist in Patient Selection for Adjuvant Chemotherapy.docx" "https://ndownloader.figshare.com/files/32160449"

文件清单

• Table_1_A Postsurgical Prognostic Nomogram for Locally Advanced Rectosigmoid Cancer to Assist in Patient Selection for Adjuvant Chemotherapy.docx（20.48 KB）

文件总体积 20.48 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

BackgroundThe perioperative treatment model for locally advanced rectosigmoid junction cancer (LARSC) has not been finalized; whether this model should refer to the treatment model for rectal cancer remains controversial.
MethodsWe screened 10,188 patients with stage II/III rectosigmoid junction adenocarcinoma who underwent surgery between 2004 and 2016 from the National Cancer Institute Surveillance, Epidemiology, and End Results database. Among them, 4,960 did not receive adjuvant chemotherapy, while 5,228 did receive adjuvant chemotherapy. Propensity score matching was used to balance the two groups for confounding factors, and the Kaplan-Meier method and log-rank test were used for survival analysis. Cox proportional hazards regression analysis was used to identify independent prognostic factors and build a predictive nomogram of survival for LARSC. X-tile software was used to divide the patients into three groups (low, medium, and high) according to their risk scores. 726 patients in our hospital were included for external validation.
ResultsLARSC patients did not show a benefit from neoadjuvant radiotherapy (P>0.05). After further excluding patients who received neoadjuvant radiotherapy, multivariate analysis found that age, grade, tumor size, T stage, and log odds of positive lymph nodes were independent prognostic factors for patients without adjuvant chemotherapy and were included in the nomogram. The C-index of the model was 0.690 (95% confidence interval: 0.668–0.712). We divided the patients into low, moderate, and high risk subgroups based on prediction scores of the nomogram. We found that adjuvant chemotherapy did not improve the prognosis of low risk patients, while moderate and high risk patients benefited from adjuvant therapy. External validation data found that moderate, and high risk patients also benefited from AT.
ConclusionDirect surgery plus adjuvant chemotherapy may be the best perioperative treatment for LARSC. Moreover, adjuvant chemotherapy is only recommended for moderate and high risk patients as it did not benefit low risk patients.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.3389/fonc.2021.772482.s001（source: https://frontiersin.figshare.com/articles/dataset/Table_1_A_Postsurgical_Prognostic_Nomogram_for_Locally_Advanced_Rectosigmoid_Cancer_to_Assist_in_Patient_Selection_for_Adjuvant_Chemotherapy_docx/17471729）。