Risk Prediction Model for Radiation-induced Dermatitis in Patients with Cervical Carcinoma Undergoing Chemoradiotherapy.

Purpose: Radiation-induced dermatitis (RD) is a common side-effect of therapeutic ionizing radiation that can severely affect patient quality of life. This study aimed to develop a risk prediction model for the occurrence of RD in patients with cervical carcinoma undergoing chemoradiotherapy using electronic medical records (EMRs).

Methods: Using EMRs, the clinical data of patients who underwent simultaneous radiotherapy and chemotherapy at a tertiary cancer hospital between 2017 and 2022 were retrospectively collected, and the patients were divided into two groups: a training group and a validation group.

Corrigendum to "Evaluation of a whole process management model based on an information system for cancer patients with pain: A prospective nonrandomized controlled study" [Asia-Pacific J Oncol Nurs 9 (2022) 88-96].

[This corrects the article DOI: 10.1016/j.apjon.

Evaluation of a whole process management model based on an information system for cancer patients with pain: A prospective nonrandomized controlled study.

Objective: The aim of this study was to evaluate the effects of whole process management model interventions based on information system benefits reported by patients with cancer pain.

Methods: We performed a quantitative, prospective nonrandomized controlled design from June to October 2020. A total of 124 cancer patients with pain were enrolled.

Is Adjuvant Therapy a Better Option for Esophageal Squamous Cell Carcinoma Patients Treated With Esophagectomy? A Prognosis Prediction Model Based on Multicenter Real-World Data.

Objective: To construct a prediction model for more precise evaluation of prognosis which will allow personalized treatment recommendations for adjuvant therapy in patients following resection of ESCC.

Background: Marked heterogeneity of patient prognosis and limited evidence regarding survival benefit of various adjuvant therapy regimens pose challenges in the clinical treatment of ESCC.

Methods: Based on comprehensive clinical data obtained from 4129 consecutive patients with resected ESCC in a high-risk region in China, we identified predictors for overall survival through a 2-phase selection based on Cox proportional hazard regression and minimization of Akaike information criterion.

An enrichment model using regular health examination data for early detection of colorectal cancer.

Objective: Challenges remain in current practices of colorectal cancer (CRC) screening, such as low compliance, low specificities and expensive cost. This study aimed to identify high-risk groups for CRC from the general population using regular health examination data.

Methods: The study population consist of more than 7,000 CRC cases and more than 140,000 controls.

Demographic, occupational, and societal features associated with burnout among medical oncology staff members: Cross-sectional results of a Cancer Center in Beijing, China.

Background: There is a growing recognition that medical staff members are exposed to job and life stressors that increase the risk of burnout. This study aimed to investigate the potential stressors among medical staff members working at a Cancer Center in Beijing and to explore the demographic, occupational, and societal features associated with burnout.

Methods: This was a cross-sectional study.