Article
Oncology
Ruiliang Wang, Zongtai Zheng, Shiyu Mao, Wentao Zhang, Ji Liu, Cheng Li, Shenghua Liu, Xudong Yao
Summary: By analyzing RNA-Sequence data and gene co-expression network, researchers established a novel eight-gene risk signature that can predict the progression and prognosis of bladder cancer patients. The study found that this signature was closely related to the malignant clinical features of BC.
FRONTIERS IN ONCOLOGY
(2021)
Article
Endocrinology & Metabolism
Zhuce Shao, Zilong Wang, Shuxiong Bi, Jianguo Zhang
Summary: Based on LASSO regression analysis, the influential factors and model for the progression of diabetic foot in elderly diabetic patients were established. The model can effectively predict the progression of diabetic foot in elderly diabetic patients and provide personalized interventions in a timely manner.
FRONTIERS IN ENDOCRINOLOGY
(2023)
Article
Oncology
Jian Liu, Li Wei
Summary: This study constructs a prognostic risk model for lung adenocarcinoma (LUAD) based on efferocytosis-related genes (ERGs), and validates its predictive accuracy through external validation sets. The high-risk group shows significantly worse survival outcomes and has fewer immune cell infiltrates and higher gene mutations. Additionally, the model provides potential therapeutic drugs for different patient risk groups.
JOURNAL OF CANCER RESEARCH AND CLINICAL ONCOLOGY
(2023)
Article
Endocrinology & Metabolism
Jingning Cheng, Yong Lv, Ling Zhang, Yafeng Liu
Summary: This study aimed to construct and validate a predictive model for the risk of hypocalcemia following parathyroidectomy in patients with secondary hyperparathyroidism. The predictive model based on preoperative PTH, Ca, and ALP showed high discrimination and calibration levels.
FRONTIERS IN ENDOCRINOLOGY
(2022)
Article
Biotechnology & Applied Microbiology
Xiaofei Liu, Junbo Zhao, Zhiwei Sun, Guangwei Wang
Summary: A retrospective analysis was conducted on data from 11,519 patients with G3 EACs to construct a nomogram for decision-making and prognosis prediction. Cox regression analysis identified age, race, tumor size, lymph node resection, stage, and adjuvant therapy as prognostic factors. The nomogram accurately predicted survival rates and will aid clinicians in managing patients more effectively.
Article
Urology & Nephrology
Han Wu, Pengfei Zhou, Liang Hu, Min Xu, Daxue Tian
Summary: This study aims to analyze risk factors for CKD stage 1 and develop a prediction model for disease progression. The results revealed that hypertension, diabetes, and urinary albumin were essential factors in the progression of CKD stage 1. The risk model accurately predicted the progression of CKD stage 1, which is of great significance to developing personalized treatment for patients in clinical practice.
Article
Medicine, General & Internal
Li Cheng, Wen-Hui Bai, Jing-Jing Yang, Peng Chou, Wan-Shan Ning, Qiang Cai, Chen-Liang Zhou
Summary: A nomograph model for predicting death risk of patients with severe/critical COVID-19 was established and showed good prediction performance, providing clinical value for making appropriate decisions.
Article
Orthopedics
Shouliang Lu, Yanhua Wang, Guangfei Liu, Lu Wang, Pengfei Wu, Yong Li, Cai Cheng
Summary: A nomogram for evaluating metastasis of osteosarcoma was successfully developed using data from the SEER database, with identified risk factors including age, primary site, grade, T stage, and surgery. The nomogram showed good prediction performance, accurately predicting metastasis in patients with osteosarcoma.
JOURNAL OF ORTHOPAEDIC SURGERY AND RESEARCH
(2021)
Article
Reproductive Biology
Qingyuan Cheng, Liman Li, Mingxia Yu
Summary: A prognostic signature based on transcription factors (TFs) has been developed for ovarian cancer (OC), which has been proven effective in predicting patients' survival. This study may contribute to clinical decision-making for OC patients and help elucidate the underlying mechanisms of TFs in OC.
JOURNAL OF OVARIAN RESEARCH
(2022)
Article
Medicine, General & Internal
Xue-lian Li, Cen Wu, Jun-gang Xie, Bin Zhang, Xiao Kui, Dong Jia, Chao-nan Liang, Qiong Zhou, Qin Zhang, Yang Gao, Xiaoming Zhou, Gang Hou
Summary: A nomogram was developed to predict the disease progression of nonsevere COVID-19, achieving high accuracy in both development and validation cohorts. The simplified index could assist in identifying high-risk cases for timely therapeutic choices based on potential disease severity.
JOURNAL OF TRANSLATIONAL INTERNAL MEDICINE
(2021)
Article
Oncology
Yixin Cheng, Pengkun Zhang, Yulin Huang, Ru Tang, Lei Zhang, Jiayuan Sun, Feng Chi, San-Gang Wu, Zhenyu He
Summary: A nomogram was developed to accurately predict the prognosis of patients with breast sarcoma (BS), providing a tool for personalized treatment plans. The nomogram showed better predictive power than the AJCC8 stage, and was validated in an external validation group. It can stratify patients into different risk groups and help physicians make informed treatment decisions.
FRONTIERS IN ONCOLOGY
(2022)
Article
Surgery
Yimin Dai, Chang Han, Xisheng Weng
Summary: This study aimed to identify predictors for postoperative anemia after Total Knee Arthroplasty (TKA) and establish a corresponding nomogram. Five independent risk factors were found, including female, lower BMI, lower levels of preoperative hemoglobin, high levels of preoperative ESR, and simultaneous bilateral TKA. A practical nomogram was constructed to predict the risk of postoperative anemia based on these findings, and its relatively high practicality was demonstrated.
FRONTIERS IN SURGERY
(2022)
Article
Oncology
Xi-Lin Yang, Hong Huang, Ling-Na Kou, Hua Lai, Xiao-Pin Chen, Da-Jun Wu
Summary: This study aimed to explore the most predictive lymph node (LN) scheme for stage IIIC endometrial cancer (EC) patients and develop a scheme-based nomogram. The findings showed that FIGO staging was not an independent risk factor for survival in stage IIIC EC patients, while the log odds of positive lymph nodes (LODDS) had the best predictive ability. A nomogram based on LODDS was constructed and validated, showing a better predictive ability than the FIGO staging system.
Article
Oncology
Jiawen Luo, Cong Lai, Xiaoting Xu, Juanyi Shi, Jintao Hu, Kaixuan Guo, Yelisudan Mulati, Yunfei Xiao, Degeng Kong, Cheng Liu, Kewei Xu
Summary: This study found that SPOCK3 affects the malignant progression of prostate cancer and constructed a prognostic model for predicting patient outcomes. The results showed that SPOCK3 expression is significantly associated with immune cell infiltration, and the constructed model has excellent predictive performance.
Article
Health Care Sciences & Services
Alessandra Stella Caporale, Marco Nezzo, Maria Giovanna Di Trani, Alessandra Maiuro, Roberto Miano, Pierluigi Bove, Alessandro Mauriello, Guglielmo Manenti, Silvia Capuani
Summary: This study investigated the potential of Diffusion-Tensor-Imaging (DTI) in detecting microstructural changes in prostate cancer (PCa) using different diffusion weights (b-values) and diffusion lengths (l(D)). The results showed that DTI metrics were able to differentiate between benign and PCa tissue, with the best discrimination at b-values ≥ 1500 s/mm(2) and when l(D) was comparable to the size of the epithelial compartment. The strongest correlations between DTI metrics and Gleason Score (GS) were found at b = 2000 s/mm(2) and for the range 0-2000 s/mm(2).
JOURNAL OF PERSONALIZED MEDICINE
(2023)