ObjectiveScreening the Database from Colorectal Cancer (DACCA) based on West China Hospial data by " Operation Date”, we purposed to analyze the population characteristics of colorectal cancer patients in regional medical center within recent Database Version.MethodsThe DACCA Version was updated in December 12th, 2018. Personal data (including sex, age, blood type, height, weight, and BMI), location data (including provinces, cities, and subordinate areas in Chengdu), occupation and education data, and main diagnosis data were included in the items. Characteristic analysis was performed on each selected data item.ResultsAccording to screening, 9 633 analytical data rows were obtained. Based on the database information, there were 24 consecutive years from 1995 to 2018 into every year. We set 2005 to 2006 as the time node for the database construction. The contribution to database before 2005 (including) was 1 358, while after 2005 (not including) were 8 275. The contribution rate (contribution numbers/years) after 2005 was higher than before 2005 ［1 358/11 vs. 8 275/13, 95% CI was (–625.337, –400.831), P<0.001］. According to gender distribution, total male data were 4 669, female were 3 340, non-checked were 1 624. According to age distribution, age were from 13 to 104 ［(59±13) years］. Linear prediction was used to predict the age distribution with the " year” as the time axis. The results showed the stable linear prediction (\begin{document}$\hat y$\end{document}=0.016 1x+26.54, R2=3.42×105, P=0.601 108). According to height, height were from 138 cm to 192 cm ［(161±7)cm］, linear prediction results showed that the linear variation with height changes by value (\begin{document}$\hat y$\end{document}=0.110 5 x–60.911, R2=0.002 6, P=0.000 272). According to weight, weight were from 27.5 kg to 80.5 kg ［(59.38±10.27) kg］, linear prediction results showed that the linear variation with height changes by value (\begin{document}$\hat y$\end{document}=0.296 5x–537.24, R2=0.010 625, P=2.37×1014). Available 6 884 data showed the difference between serving areas by West China Hospital and official definition of western region. A total of 9 209 data obtained by analyzing main diagnosis, showed that the main site of disease was rectum (68.64%). Sigmoid was the main location of colon cancer (68.64%), and anal-rectal cancer was main of rectal cancer (27.06%).ConclusionPopulation characteristics from DACCA database could initially reflect the trend of increasing weight and BMI of colorectal cancer patients, and also reflect the regional distribution characteristics based on geographic information. They would be the clues for further database research.
ObjectiveTo analyze the geographical distribution of patients with colorectal cancer by screening the current Database from Colorectal Cancer (DACCA) version in West China Hospital.MethodsThe selected DACCA database version of this data analysis was updated on September 5, 2019, and the two data of the " date of operation” and " address” were selected as the main research items. The characteristics of each selected data item were analyzed, and then the selected data were used as a joint feature analysis.ResultsAccording to the condition of selection by " address”, 7 096 valid data rows from the whole nation were obtained, 6 551 valid data rows from Sichuan province were obtained, and 2 954 valid data rows from Chengdu city were obtained. The geographic information provided by the DACCA database showed that, with the year changing, the provincial distribution area of patients was mainly the southwest region with middle-east of Sichuan province as center, mainly including the parts of Chongqing, Yunnan, and Guizhou; The distribution area of the municipal level in Sichuan province was mainly the east region with axis of the " Mianyang-Chengdu-Ya’an”, and Chengdu was the core; The regional distribution of patients in the Chengdu was mainly within the third ring load with Wuhou District, the Jinniu District, and the Qingyang District as the core area.ConclusionThegeographical information provided by DACCA database shows the geographical distribution characteristics of patients in the past 20 years, reflecting the basic characteristics and changes of the service area of West China Hospital, and can provide a basis for medical policy makers in screening, diagnosing and treating of colorectal cancer, and key management areas of following-up.
ObjectiveTo elaborate constitute, definition, and interpretation of operative characteristics of colorectal cancer in the Database from Colorectal Cancer (DACCA) in the West China Hospital.MethodThe article was described in the words.ResultsIn the DACCA, the operative characteristics module of colorectal cancer mainly included five parts: surgical characteristics, surgical methods, operative skills in details, surgical difficulties, and surgical quality evaluation. Then the surgical characteristics were detailed for their definition, form, label and structure, error correction and update, and how to be used in the analysis of data in the DACCA.ConclusionsThrough detailed description and speci-fication of surgical characteristics of colorectal cancer in DACCA in West China Hospital, it can provide a reference for standar-dized treatment of colorectal cancer and also provide experiences for the peers who wish to build a colorectal cancer database.
ObjectiveTo elaborate constitute, definition, and interpretation of tumor characteristics module of colorectal cancer in the Database from Colorectal Cancer (DACCA) in the West China Hospital.MethodThe article was described in the words.ResultsThe tumor features module of colorectal cancer in the DACCA included the precancerous lesion, cancer family, location of tumor, distance to the dentate line, morphology of tumor, size, position, happening and origination, differentiation, pathology of tumor, Ki-67 protein, obstruction, intussusception, perforation, pain, edema, and hemorrhage. The exact definitions of morphology of tumor, size, position, differentiation, pathology of tumor, Ki-67 protein and complication (included obstruction, intussusception, perforation, pain, edema, and hemorrhage), tag and structure, corrective precautions and update of these columns, and how to use these tumor characteristics in the DACCA when analysis was carried out were described in detail.ConclusionThrough detailed description and specification of current tumor characteristics module of colorectal cancer in DACCA in West China Hospital, it can provide a reference for standardized treatment of colorectal cancer and also provide experiences for the peers who wish to build a colorectal cancer database.
ObjectiveTo explain in detail hospitalization process management of colorectal cancer as well as its tag and structure of Database from Colorectal Cancer (DACCA) in the West China Hospital.MethodThe article was described in the words.ResultsThe definition and setting of 8 classification items involved in the hospitalization process management from DACCA in the West China Hospital were set. The items were included the date of first out-patient meeting, admitted date, operative date, discharged date, waiting time before the admission, preoperative staying days, total hospital staying days, and manage protocol. The relevant data tag of each item and the structured way needed at the big data application stage were elaborated and the corrective precautions of classification items were described.ConclusionsBased on description about hospitalization process management from DACCA in West China Hospital, it is provided a clinical standard and guidance for analyzing of DACCA in West China Hospital in future. It also could provide enough experiences for construction of colorectal cancer database by staff from same occupation.
ObjectiveBased on the current version of Database from Colorectal Cancer (DACCA), we aimed to analyze the comorbidities and preoperative physical status of colorectal cancer patients.MethodsThe DACCA version selected for this data analysis was updated on May 9, 2019. The data items included: surgical comorbidities and classified by systems, surgical history, pelvic disease history, medical comorbidities, and some important subdivision types, infectious disease status, allergic history, nutrition risk screening 2002 (NRS2002) score, amount of weight loss after illness, anemia, low protein status, preoperative ascites status, preoperative pleural effusion status, immune system disease and immunocompromised status, and preoperative nutritional support. Characteristic analysis was performed on each selected data item.ResultsA total of 6 166 admitted data were filtered from the DACCA database. Among them, surgical comorbidities, surgical history, medical comorbidities, and allergy history had 6 166 admitted data, and weight loss had admitted 4 703. There were 2 923 (47.4%) with surgical comorbidities. According to the system, the most common one was digestive system (2 005, 68.6%), and the least one was skin tissue system (24, 0.8%). There were 4 361 (70.7%) patients without surgical history and 1 805 (29.3%) patients had surgical history. There were 2 397 (38.9%) patients without medical comorbidities and 3 769 (61.1%) had medical comorbidities, of which pneumonia/pulmonary infection/chronic bronchopneumonia/lung indeterminate nodules were the most common(2 330, 37.8%), the least was cerebral infarction (unspecified type, 63, 1.0%). There were 5 813 (94.3%) without allergy history and 353 (5.7%) had allergy history. According to the NRS2002 nutrition screening criteria, the scores ranged from 1 to 7 points, with an average of 1.22 points, which could be classified as non-nutrition risk (5 279, 85.6%, included 1 point of 4 310, 2 points of 969), nutritional risk (887, 14.4%, included 3 points of 415, 4 points of 358, 5 points of 100, 6 points of 12, and 7 points of 2), the result of linear regression analysis of NRS2002 scores with the trend of the year showed that: ŷ=0.000 2x–6.275 8, R2=0.716 2, P<0.001. A total of 2 840 (60.4%) had no weight loss while 1 863 (39.6%) had, and weight loss with the trend of year were analyzed by linear regression analysis: ŷ=0.000 2x–3.956, R2=0.685 7, P<0.001. The number of cases of other physical status and the proportion of valid data were anemia (1 194, 33.1%), preoperative ascites (1829, 51.7%), preoperative pleural effusion (171, 5.7%), hypoproteinemia (1 206, 33.6%), immune system disease and immunocompromised status (495, 56.6%), and nutritional support (824, 25.0%).ConclusionsThrough the analysis of the DACCA database, nearly 1/2 of colorectal cancer surgery patients have surgical comorbidities before surgery, more than 1/2 of the patients have medical comorbidities, and the types of diseases are various. Preoperative nutritional status in patients with colorectal cancer also shows certain characteristics, suggesting the state of preoperative risk. These data will provide a detailed big data basis for future preoperative risk assessment of colorectal cancer.
ObjectiveTo elaborate constitute, definition, and interpretation of stage module of colorectal cancer in the Database from Colorectal Cancer (DACCA) in the West China Hospital.MethodThe article was described in the words.ResultsIn the DACCA, the columns were selected by the colorectal cancer staging module. The overall stages included: the stage during surgery, cpi comprehensive stage, and TNM stage. The classified stages included: the T, N, and M stages of pathology, clinical, and imaging; The risk factors included the cancerous contamination and high-risk factors. Then these items were subdivided and detailed for their definition, form, label and structure, error correction and update, and how to be used in the analysis of data in the DACCA.ConclusionsThrough detailed description and specification of current stage module of colorectal cancer in DACCA in West China Hospital, it can provide a reference for standardized treatment of colorectal cancer and also provide experiences for the peers who wish to build a colorectal cancer database.
ObjectiveTo explain details of colorectal cancer surgery in detail as well as their tags and structures of Database from Colorectal Cancer (DACCA) in the West China Hospital.MethodThe article was described in words.ResultsThe details of colorectal cancer surgery module included procedure of anastomosis, shape of anastomosis, type of staple, enhanced suture for anastomosis, stuffing, drainage, coverage of major omentum, anti-adhesion material, reconstruction of pelvic peritoneum, contaminate, drug implants, and nano of the DACCA in the West China Hospital were defined. The data labels corresponding to each item in the database and the structured ways needed for the big data application stage in detail were explained. And the error correction notes for all classification items were described.ConclusionsThrough the detailed description of the details of colorectal cancer surgery of DACCA in West China Hospital, it provides the standard and basis for the clinical application of DACCA in the future, and provides reference for other peers who wish to build a colorectal cancer database.
ObjectiveTo elaborate the contents and concrete concepts of preoperative specialized examination and evaluation of colorectal cancer of the Database from Colorectal Cancer (DACCA) in the West China Hospital. MethodThe article was described in the words.ResultsThe components, stage, accuracy, preoperative comprehensive evaluation, clinical factors of initial diagnosis, misdiagnosis and mistreatment of colorectal cancer in the DACCA were defined and elaborated in the detail. The data label corresponding to each item in the database and the required structured way in the application stage of large data were also described in detail, and the corrective precautions for all classified items were described.ConclusionsThrough the detailed description of the preoperative specialized examination and evaluation of colorectal cancer of DACCA in West China Hospital, it might provide the standard and basis for the clinical application of database in the future, and provide reference for other peers who wish to build a colorectal cancer database.
ObjectiveTo explain surgery reaction and perioperative complications of colorectal cancer in detail as well as their tags and structures of Database from Colorectal Cancer (DACCA) in the West China Hospital.MethodThe article was described in words.ResultsThe surgery reaction and perioperative complications of colorectal cancer module including temperature, flatus, pain, and mental status, as well as preoperative complications, intraoperative complications, postoperative complications (short-term complications and long-term complications) of the DACCA in the West China Hospital were defined. The data label corresponding to each item in the database and the structured way needed for the big data application stage in detail were explained. And the error correction notes for all classification items were described.ConclusionsThrough the detailed description of the surgery reaction and perioperative complications of colorectal cancer of DACCA in West China Hospital, it provides standard and basis for clinical application of DACCA in future, and provides reference for other peers who wish to build a colorectal cancer database.