Objective To establish a predictive model for long-term tumor-specific survival after surgery for patients with intermediate to advanced medullary thyroid cancer (MTC) based on American Joint Committee on Cancer (AJCC) TNM staging, by using the Surveillance, Epidemiology, and End Results (SEER) Database. Methods The data of 692 patients with intermediate to advanced MTC who underwent total thyroidectomy and cervical lymph node dissection registered in the SEER database during 2004–2017 were extracted and screened, and were randomly divided into 484 cases in the modeling group and 208 cases in the validation group according to 7∶3. Cox proportional hazard regression was used to screen predictors of tumor-specific survival after surgery for intermediate to advanced stage MTC and to develop a Nomogram model. The accuracy and usefulness of the model were tested by using the consistency index (C-index), calibration curve, time-dependent ROC curve and decision curve analysis (DSA). Results In the modeling group, the multivariate Cox proportional hazard regression model indicated that the factors affecting tumor-specific survival after surgery in patients with intermediate to advanced MTC were AJCC TNM staging, age, lymph node ratio (LNR), and tumor diameter, and the Nomogram model was developed based on these results. The modeling group had a C-index of 0.827 and its area under the 5-year and 10-year time-dependent ROC curves were 0.865 [95%CI (0.817, 0.913)], 0.845 [95%CI (0.787, 0.904)], respectively, and the validation group had a C-index of 0.866 and its area under the 5-year and 10-year time-dependent ROC curves were 0.866 [95%CI (0.798, 0.935)] and 0.923 [95%CI (0.863, 0.983)], respectively. Good agreement between the model-predicted 5- and 10-year tumor-specific survival rates and the actual 5- and 10-year tumor-specific survival rates were showed in both the modeling and validation groups. Based on the DCA curve, the new model based on AJCC TNM staging was developed with a significant advantage over the former model containing only AJCC TNM staging in terms of net benefits obtained by patients at 5 years and 10 years after surgery. Conclusion The prognostic model based on AJCC TNM staging for predicting tumor-specific survival after surgery for intermediate to advanced MTC established in this study has good predictive effect and practicality, which can help guide personalized, precise and comprehensive treatment decisions and can be used in clinical practice.
Objective To analyze the impact of age on surgical reaction and postoperative complications of patients with colorectal cancer served by West China Hospital of Sichuan University as a regional center in the Database from Colorectal Cancer (DACCA). Methods The data of DACCA was updated on January 5, 2022. All data items included age, surgical trauma reaction, elevated body temperature time, exhaust time, pain, mental status, and postoperative hospital complications. According to the age segmentation method in China, the patients can be divided into 3 groups: ≤35 years old (including infant, toddler, child, teenager and youth, set as the younger group), 36–59 years old (set as the middle-aged group), and ≥60 years old (set as the elderly group). Results After scanning, 5 224 data rows were analyzed. There was no significant difference in surgical trauma reaction (H=0.352, P=0.838), elevated body temperature time (H=3.999, P=0.135), exhaust time (H=1.940, P=0.379), mental status (H=2.075, P=0.354), incidence of postoperative complications (χ2=2.078, P=0.354), incidence of anastomotic bleeding (χ2=1.737, P=0.420), incidence of anastomotic leakage (χ2=0.573, P=0.751), and incidence of pulmonary infection (P=0.410) among different age groups, but the younger group had more severe pain (H=12.985, P=0.002) and higher incidence of inflammatory obstruction (χ2=7.789, P=0.020). Conclusions Age has little effect on trauma reaction related parameters and overall incidence of complications in colorectal cancer patients. However, younger patients with colorectal cancer showed increased pain levels and increased incidence of inflammatory obstruction after surgery. These clinical manifestations can provide clinicians with evidence for intervention, but more prospective intervention trials are needed.
ObjectiveTo analyze the current version of the West China Database from Colorectal Cancer (DACCA) and explore how the occupational background of colorectal cancer patients affects the complexity of surgical difficulty and postoperative complications. MethodsWhen using the updated version of DACCA data on May 28, 2023 for analysis, the data items concerned covered occupation, operative duration, anatomical difficulty, pelvic stenosis, abdominal obesity, adhesion in surgical area, abnormal mesenteric status, tissue or organ hypertrophy, intestinal quality in surgical area, postoperative complications in hospital, short-term postoperative complications and long-term postoperative complications. According to the “Occupational Classification Code of the People’s Republic of China”, the occupations of patients were divided into professional and technical personnel, staff, service personal, production personnel, manufacturing personnel and retirees according to different occupations. The operative difficulty and postoperative complications of 6 groups were analyzed. ResultsAccording to the screening conditions, 5 734 valid data rows were obtained from DACCA. The results of occupation analysis showed that there were significant difference in operative duration (H=11.609, P=0.041), anatomical difficulty (H=29.166, P<0.001), pelvic stenosis (H=16.412, P=0.006), abdominal obesity (H=44.622, P<0.001), adhesion in surgical area (H=23.695, P<0.001), abnormal mesenteric status (χ2=39.252, P=0.035), tissue or organ hypertrophy (χ2=58.284, P<0.001) and intestinal quality in surgical area (H=21.041, P=0.001) between different groups. There were no significant differences in the occurrence of complications in hospital, near and short-term and long-term after operation among different occupations (P>0.05). Further subgroup analysis showed that only the difference of fever (χ2=10.969, P=0.041) and intestinal obstruction (χ2=12.025, P=0.021) were statistically significant among different occupations. ConclusionThe occupation of patients may affect the difficulty of colon cancer surgery, and the occurrence of postoperative complications is nothing to do with the occupation of patients, but the occurrence of postoperative fever and postoperative intestinal obstruction is related to occupations, and the possible causes need to be further explored.
Objective To establish the Chinese Evidence-Based Medicine/Cochrane Centre Database of Clinical Trials and Diagnostic Tests to provide reliable scientific data for clinical practice, teaching, research and systematic reviewers and submit the results of randomised controlled trials (RCTs) and controlled clinical trials (CCTs) to The Cochrane Collaboration. Methods Data were collected by handsearching and electronic searching based on the criterion of the Collaboration and clinical epidemiology. Results Up to December 2003, there were 16 652 RCTs /CCTs and 3 786 DT included in the database. A total of 4 966 RCTs and CCTs were submitted to the Collaboration. Nineteen specialized databases were set up. Conclusions The first phase of the Chinese Evidence-Based Medicine/Cochrane Centre Database of Clinical Trials and Diagnostic Tests has been completed. The database has provided advice for contributiors both at home and abroad.
ObjectiveTo explore the influencing factors of cancer-specific survival of patients with large hepatocellular carcinoma, and draw a nomogram to predict the cancer-specific survival rate of large hepatocellular carcinoma patients.MethodsThe clinicopathological data of patients with large hepatocellular carcinoma during the period from 1975 to 2017 in the Surveillance, Epidemiology, and End Results (SEER) database were searched and randomly divided into training group and validation group at 1∶1. Using the training data, the Cox proportional hazard regression model was used to explore the influencing factors of cancer-specific survival and construct the nomogram; finally, the receiver operating characteristic curve (ROC curve) and the calibration curve were drawn to verify the nomogram internally and externally.ResultsThe results of the multivariate Cox proportional hazard regression model showed that the degree of liver cirrhosis, tumor differentiation, tumor diameter, T stage, M stage, surgery, and chemotherapy were independent influencing factors that affect the specific survival of patients with large hepatocellular carcinoma (P<0.05), and then these factors were enrolled into the nomogram of the prediction model. The areas under the 1, 3, and 5-year curves of the training group were 0.800, 0.827, and 0.814, respectively; the areas under the 1, 3, and 5-year curves of the validation group were 0.800, 0.824, and 0.801, respectively. The C index of the training group was 0.779, and the verification group was 0.777. The calibration curve of the training group and the verification group was close to the ideal curve of the actual situation.ConclusionThe nomogram of the prediction model drawn in this study can be used to predict the specific survival of patients with large hepatocellular carcinoma in the clinic.
ObjectiveTo analyze the association between preoperative staging (cTNM) and neoadjuvant therapy regimen decision-making and efficacy in patients with rectal cancer in the current version of Database from Colorectal Cancer (DACCA). MethodsThe data analysis for this study selected the DACCA version updated on April 20, 2024. The patient information was collected and categorized into three stages (Ⅱ, Ⅲ, and Ⅳ). The differences in neoadjuvant treatment decision-making and therapeutic effects, including gross changes, imaging changes, and tumor regression grade (TRG), were analyzed. ResultsA total of 3 158 eligible cases were collected in this study, with complete preoperative staging and neoadjuvant therapy decision-making data available for 2 370 patients. There were statistically significant differences in the overall comparison among the patients with rectal cancer in terms of the selection of combined targeted therapy, radiotherapy regimens, and the intensity of neoadjuvant chemotherapy by patients at different preoperative stages (χ2=42.239, P<0.001; χ2=41.615, P<0.001; H=1.161, P=0.004). Specifically, the proportion of patients choosing combined targeted therapy and combined radiotherapy gradually increased as the stage advanced. Among patients at different stages, the proportion of those choosing medium-course chemotherapy was the highest, and the proportion of patients choosing long-course chemotherapy was the highest among those with more advanced stages. Regarding the gross changes, imaging changes, and TRG results after neoadjuvant treatment in the patients at different preoperative stages, there were statistically significant differences in the overall comparison among patients with stage Ⅱ, Ⅲ, and Ⅳ rectal cancer (H=7.860, P=0.020; H=9.845, P=0.007; H=6.680, P=0.035). The proportion of partial response was the highest across all response metrics (macroscopic, radiographic, and TRG) in each stage. Notably, stage Ⅱ patients demonstrated the highest rate of complete response. For TRG evaluation, grade 2 (TRG2) was the most common outcome across all stages. ConclusionsData analysis from DACCA reveals that patients with advanced stages are more likely to choose chemotherapy combined with targeted therapy or radiotherapy, and had a higher proportion of intermediate range chemotherapy and the intensity of neoadjuvant chemotherapy is stronger. In terms of neoadjuvant treatment effects, the earlier the staging, the better the gross and imaging changes, and the lower the TRG level.
ObjectiveTo analyze the association between the cultural level and hospitalization management process and length of hospitalization of the colorectal patients served by West China Hospital of Sichuan University as a regional center in the current version of the Database from Colorectal Cancer (DACCA). MethodAccording to the established screening criteria, eligible colorectal cancer patients were collected from the updated version of DACCA on June 29, 2022. The analyzed data items included gender, age, BMI, blood type, marriage, waiting time before admission, preoperative hospitalization time, postoperative hospitalization time, total hospitalization time, and management process, and patients were divided into illiterate group, primary education group, medium education group, and higher education group according to their educational level, then compared the hospitalization management process and length of hospitalization of each group. ResultsA total of 4 765 eligible data were screened, with secondary education being the most prevalent (2 792, 58.6%), followed by primary (1 337, 28.1%) and higher education (417, 8.7%), and illiteracy being the least prevalent (219, 4.6%). In the classification of management processes, “regular” account for the majority (4 219, 88.5%), followed by “enhanced”(274, 5.8%), “individual” was third (231, 4.8%), and “rapid” was the least (41, 0.9%). There was no statistically significant difference in the comparison of waiting time before admission, preoperative hospitalisation time and postoperative hospitalisation time among patients with different literacy levels (P=0.371, P=0.095, P=0.352), but there was a statistically significant difference in total hospitalisation time (P=0.021), with a significant difference in total hospitalisation length between illiterate patients and patients with medium education (P=0.041). There was no statistically significant difference in the comparison of inpatient management processes of patients in different literacy groups (χ2=15.2, P=0.085). ConclusionsAnalysis of the DACCA data revealed a statistically significant difference in total hospitalisation time between patients with illiteracy and those with medium education. However, the choice of hospitalisation management process was similar for patients with different literacy levels, which needs to be further analysed for the reasons.
Objective To collect and store all interactions relating to medical information between our center and allied specialized hospitals by constructing a database system for thoracic surgery and pulmonary tuberculosis. Methods We collected all related medical records of patients who had been clinically diagnosed with pulmonary tuberculosis and tuberculous empyema using the CouchBase Database, including outpatient and inpatient system of the Department of Thoracic Surgery at the Public Health Clinical Center of Chengdu between January 2017 to June 2023. Then, we integrated all medical records derived from the radiology information system, hospital information system, image archiving and communication systems, and the laboratory information management system. Finally, we used artificial intelligence to generate a database system for the application of thoracic surgery on pulmonary tuberculosis, which stored structured medical data from different hospitals along with data collected from patients via WeChat users. The new database could share medical data between our center and allied hospitals by using a front-end processor. ResultsWe finally included 124 patients with 86 males and 38 females aged 43 (26, 56) years. A structured database for the application of thoracic surgery on patients with pulmonary tuberculosis was successfully constructed. A follow-up list created by the database can help outpatient doctors to complete follow-up tasks on time. All structured data can be downloaded in the form of Microsoft Excel files to meet the needs of different clinical researchers. Conclusion Our new database allows medical data to be structured, stored and shared between our center and allied hospitals. The database represents a powerful platform for interactions relating to regional information concerning pulmonary tuberculosis.
Objective To develop a machine learning (ML) model to predict the risk of death in intensive care unit (ICU) patients with chronic obstructive pulmonary disease (COPD), explain the factors related to the risk of death in COPD patients, and solve the "black box" problem of ML model. Methods A total of 8088 patients with severe COPD were selected from the eICU Collaborative Research Database (eICU-CRD). Data within the initial 24 hours of each ICU stay were extracted and randomly divided, with 70% for model training and 30% for model validation. The LASSO regression was deployed for predictor variable selection to avoid overfitting. Five ML models were employed to predict in-hospital mortality. The prediction performance of the ML models was compared with alternative models using the area under curve (AUC), while SHAP (SHapley Additive exPlanations) method was used to explain this random forest (RF) model. Results The RF model performed best among the APACHE IVa scoring system and five ML models with the AUC of 0.830 (95%CI 0.806 - 0.855). The SHAP method detects the top 10 predictors according to the importance ranking and the minimum of non-invasive systolic blood pressure was recognized as the most significant predictor variable. Conclusion Leveraging ML model to capture risk factors and using the SHAP method to interpret the prediction outcome can predict the risk of death of patients early, which helps clinicians make accurate treatment plans and allocate medical resources rationally.
Objective To establishadatabase to fully investigate current situation of antiepileptic drugs among pregnant women with epilepsy in West China. Analyzing the epidemiological characteristics and correlated influence factors of anti-epileptic drugs use among women with epilepsy in this area to promote management quality for women with epilepsy. Methods Adigital registration system was established with JAVA andastandard registration procedure was formulated. Standard registration was implemented in different levels of hospital of West China with regular follow-up. Results Registration system about antiepileptic drugs among pregnant women with epilepsy in West China was successfully established, which wasadigital registration within local area network. Information about registration centre and pregnant women with epilepsy was collected in the West China registration network. And elementary database was successfully established. Conclusion This is the first extensive and standard pregnancy register of antiepileptic drugs in China which meet the need of not only patient information management but also the development of academic subject.