Database research part <b>Ⅵ</b>: staging strategies for colorectal cancer_CHINESE JOURNAL OF BASES AND CLINICS IN GENERAL SURGERY

Authors：

WANG Xiaodong ¹ , LIU Jianbo ^1,2 , HE Xinlin ^1,2 , ZOU Yuheng ^1,2 ,  LI Li ¹

1. Department of Gastrointestinal Surgery, West China Hospital of Sichuan University, Chengdu 610041, P. R. China;
2. West China School of Medicine, Sichuan University, Chengdu 610041, P. R. China;

Corresponding?author：

LI Li, Email: drlili116@126.com

Keywords：

colorectal cancer; database; bigdata; staging; pathology; imageology

DOI：

10.7507/1007-9424.202005023

Video：

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Objective To analyze the staging methods of colorectal cancer data in the current version of the Database from Colorectal Cancer (DACCA).Methods The DACCA version selected for this data analysis was updated at April 16th, 2020. The columns included stage during surgery, comprehensive stage of clinical, pathologic and imaging (cpi comprehensive stage), TNM stage, pathologic T stage, imaging T stage, nerves involvement, pathologic anus stage, clinical anus stage, imaging anus stage, pathologic mesentery stage, clinical mesentery stage, imaging mesentery stage, pathologic N stage, imaging N stage, positive lymph nodes ratio, cancerous nodules, M stage, cancerous emboli, pathologic vessel stage, clinical vessel stage, imaging vessel stage, cancerous contamination, and high-risk factors. Extracted data were statistically analyzed.Results The total number of data medical records (data rows) that met the criteria was 6 474, the valid data of TNM stage was 4 511 (69.7%), the valid data of stage during surgery was 5 684 (87.8%), and the valid data of cpi comprehensive stage was 4 045 (62.5%). 1 540 data (41.6%) were consistent with stage during surgery and TNM stage, and 2 884 data (76.7%) were consistent with cpi comprehensive stage and TNM stage. According to the data of T, N, and M stage, the proportion of patients with pathologic T4a stage was the highest (40.5%), followed by T3 stage (24.8%); the most T4a stage (31.9%) on the image, followed by T4b stage (28.7%). The pathologic N stage with lymph node metastasis was about 41.9% (N1 and N2), and the imaging N stage lymph node metastasis was about 51.4%. There were a total of 4 745 valid data in the M stage (73.3%). There were 4 313 valid data in the nerves involvement (66.7%), suspected involvement and confirmed involvement, were 691 (16.0%) and 253 (5.9%) respectively. The valid data of anal pathology, clinical, and imaging stage were 4 115 (63.6%), 599 (9.3%), and 598 (9.2%), and only 30 (0.7%), 8 (1.3%), and 13 (2.2%) on muscle involvement respectively. The valid data of pathologic, clinical, and imaging mesentery stage were 732 (11.3%), 589 (9.1%), and 592 (9.1%). There were 4 458 (68.9%) valid data of positive lymph nodes ratio, and 2 908 (44.9%) valid data of cancerous nodules. There were 4 286 valid data of cancerous emboli (66.2%). A total of 244 data (41.1%) of increased blood vessels around tumors in the imaging vessel stage, 274 data (46.4%) of that in clinical vessel stage, and only 1 063 (27.7%) of pathologic vessel stage. There were 3 865 valid data (59.7%) of the cancerous contamination, and the proportion of the third level (746/2 753, 27.1%) in the high-risk factors was the highest.Conclusion Through detailed analysis of the DACCA database, it is hoped that a more complete and accurate evaluation system of tumor severity can be established, and high-risk factors can provide some ideas for judging prognosis.

Citation： WANG Xiaodong, LIU Jianbo, HE Xinlin, ZOU Yuheng, LI Li. Database research part Ⅵ: staging strategies for colorectal cancer. CHINESE JOURNAL OF BASES AND CLINICS IN GENERAL SURGERY, 2020, 27(6): 739-746. doi: 10.7507/1007-9424.202005023 Copy

1.	劉健博, 呂炘沂, 鄒雨恒, 等. 多周期新輔助化療聯合阿帕替尼對進展期直腸癌的療效評價: 基于DACCA數據庫的輔助研究. 中國普外基礎與臨床雜志, 2019, 26(6): 728-734.
2.	劉健博, 由屹先, 鄒雨恒, 等. 數據庫輔助研究: 結直腸癌新輔助治療的應用—基于DACCA的華西真實世界數據報道. 中國普外基礎與臨床雜志, 2019, 26(12): 1467-1475.
3.	汪曉東, 安麗珉, 李立. 數據庫研究第二部分: 結直腸癌的住院流程管理. 中國普外基礎與臨床雜志, 2019, 26(4): 469-475.
4.	汪曉東, 李立. 數據庫建設第一部分: 個人數據的標簽與結構化. 中國普外基礎與臨床雜志, 2019, 26(3): 335-342.
5.	汪曉東, 李立. 真實場景與大數據下的整體微創理念, 大幅提高結直腸癌遠期生存率. 中國普外基礎與臨床雜志, 2019, 26(1): 92-95.
6.	汪曉東, 李希, 何欣林, 等. 數據庫研究第一部分: 區域性醫療中心的結直腸癌與人群特征. 中國普外基礎與臨床雜志, 2019, 26(2): 212-220.
7.	汪曉東, 劉健博, 安麗珉, 等. 數據庫建設第四部分: 結直腸癌的術前專科檢查與評估的標簽與結構化. 中國普外基礎與臨床雜志, 2019, 26(11): 1337-1341.
8.	汪曉東, 劉健博, 安麗珉, 等. 數據庫研究第四部分: 結直腸癌的術前專科檢查與評估. 中國普外基礎與臨床雜志, 2019, 26(10): 1230-1238.
9.	汪曉東, 劉健博, 李立. 數據庫建設第三部分: 結直腸癌內外科合并癥及術前體質狀態的標簽與結構化. 中國普外基礎與臨床雜志, 2019, 26(9): 1110-1115.
10.	汪曉東, 劉健博, 張詩, 等. 數據庫研究第三部分: 結直腸癌的內外科合并癥及術前體質狀態. 中國普外基礎與臨床雜志, 2019, 26(8): 985-991.
11.	汪曉東, 呂炘沂, 黃明君, 等. 數據庫建設第二部分: 結直腸癌住院流程管理的標簽與結構化. 中國普外基礎與臨床雜志, 2019, 26(7): 852-855.
12.	于瑞璇, 何欣林, 張秋露, 等. 華西DACCA的輔助研究: 單獨的新輔助化療不會影響直腸癌術后近期的肛門功能. 中國普外基礎與臨床雜志, 2019, 26(5): 595-601.
13.	汪曉東, 陳夢然, 曾渝, 等. 數據庫研究第五部分: 結直腸癌的腫瘤特征. 中國普外基礎與臨床雜志, 2020, 27(2): 196-208.
14.	汪曉東, 劉健博, 李立. 數據庫建設第五部分·結直腸癌的腫瘤特征—模塊的設計 (二). 中國普外基礎與臨床雜志, 2020, 27(4): 483-488.
15.	汪曉東, 劉健博, 李立. 數據庫建設第五部分: 結直腸癌的腫瘤特征—模塊的設計 (一). 中國普外基礎與臨床雜志, 2020, 27(3): 345-349.
16.	Weiser MR. AJCC 8th edition: colorectal cancer. Ann Surg Oncol, 2018, 25(6): 1454-1455.
17.	Rudy DR, Zdon MJ. Update on colorectal cancer. Am Fam Physician, 2000, 61(6): 1759-1770, 1773-1774.
18.	Brenner H, Kloor M, Pox CP. Colorectal cancer. Lancet, 2014, 383(9927): 1490-1502.
19.	Maguire A, Sheahan K. Controversies in the pathological assessment of colorectal cancer. World J Gastroenterol, 2014, 20(29): 9850-9861.
20.	Shia J, Klimstra DS, Bagci P, et al. TNM staging of colorectal carcinoma: issues and caveats. Semin Diagn Pathol, 2012, 29(3): 142-153.
21.	Berho M, Bejarano PA. Rectal cancer and the pathologist. Minerva Chir, 2018, 73(6): 534-547.
22.	Tizhoosh HR, Pantanowitz L. Artificial intelligence and digital pathology: challenges and opportunities. J Pathol Inform, 2018, 9: 38.
23.	Nayak J, Goel S. Revised TNM staging for colorectal cancer: did we miss the golden opportunity to do right by the staging? Clin Colorectal Cancer, 2011, 10(3): 207-209.
24.	Cavallaro U, Christofori G. Molecular mechanisms of tumor angiogenesis and tumor progression. J Neurooncol, 2000, 50(1-2): 63-70.
25.	Wang X, Yu Y, Meng W, et al. Total neoadjuvant treatment (CAPOX plus radiotherapy) for patients with locally advanced rectal cancer with high risk factors: a phase 2 trial. Radiother Oncol, 2018, 129(2): 300-305.

1. 劉健博, 呂炘沂, 鄒雨恒, 等. 多周期新輔助化療聯合阿帕替尼對進展期直腸癌的療效評價: 基于DACCA數據庫的輔助研究. 中國普外基礎與臨床雜志, 2019, 26(6): 728-734.
2. 劉健博, 由屹先, 鄒雨恒, 等. 數據庫輔助研究: 結直腸癌新輔助治療的應用—基于DACCA的華西真實世界數據報道. 中國普外基礎與臨床雜志, 2019, 26(12): 1467-1475.
3. 汪曉東, 安麗珉, 李立. 數據庫研究第二部分: 結直腸癌的住院流程管理. 中國普外基礎與臨床雜志, 2019, 26(4): 469-475.
4. 汪曉東, 李立. 數據庫建設第一部分: 個人數據的標簽與結構化. 中國普外基礎與臨床雜志, 2019, 26(3): 335-342.
5. 汪曉東, 李立. 真實場景與大數據下的整體微創理念, 大幅提高結直腸癌遠期生存率. 中國普外基礎與臨床雜志, 2019, 26(1): 92-95.
6. 汪曉東, 李希, 何欣林, 等. 數據庫研究第一部分: 區域性醫療中心的結直腸癌與人群特征. 中國普外基礎與臨床雜志, 2019, 26(2): 212-220.
7. 汪曉東, 劉健博, 安麗珉, 等. 數據庫建設第四部分: 結直腸癌的術前專科檢查與評估的標簽與結構化. 中國普外基礎與臨床雜志, 2019, 26(11): 1337-1341.
8. 汪曉東, 劉健博, 安麗珉, 等. 數據庫研究第四部分: 結直腸癌的術前專科檢查與評估. 中國普外基礎與臨床雜志, 2019, 26(10): 1230-1238.
9. 汪曉東, 劉健博, 李立. 數據庫建設第三部分: 結直腸癌內外科合并癥及術前體質狀態的標簽與結構化. 中國普外基礎與臨床雜志, 2019, 26(9): 1110-1115.
10. 汪曉東, 劉健博, 張詩, 等. 數據庫研究第三部分: 結直腸癌的內外科合并癥及術前體質狀態. 中國普外基礎與臨床雜志, 2019, 26(8): 985-991.
11. 汪曉東, 呂炘沂, 黃明君, 等. 數據庫建設第二部分: 結直腸癌住院流程管理的標簽與結構化. 中國普外基礎與臨床雜志, 2019, 26(7): 852-855.
12. 于瑞璇, 何欣林, 張秋露, 等. 華西DACCA的輔助研究: 單獨的新輔助化療不會影響直腸癌術后近期的肛門功能. 中國普外基礎與臨床雜志, 2019, 26(5): 595-601.
13. 汪曉東, 陳夢然, 曾渝, 等. 數據庫研究第五部分: 結直腸癌的腫瘤特征. 中國普外基礎與臨床雜志, 2020, 27(2): 196-208.
14. 汪曉東, 劉健博, 李立. 數據庫建設第五部分·結直腸癌的腫瘤特征—模塊的設計 (二). 中國普外基礎與臨床雜志, 2020, 27(4): 483-488.
15. 汪曉東, 劉健博, 李立. 數據庫建設第五部分: 結直腸癌的腫瘤特征—模塊的設計 (一). 中國普外基礎與臨床雜志, 2020, 27(3): 345-349.
16. Weiser MR. AJCC 8th edition: colorectal cancer. Ann Surg Oncol, 2018, 25(6): 1454-1455.
17. Rudy DR, Zdon MJ. Update on colorectal cancer. Am Fam Physician, 2000, 61(6): 1759-1770, 1773-1774.
18. Brenner H, Kloor M, Pox CP. Colorectal cancer. Lancet, 2014, 383(9927): 1490-1502.
19. Maguire A, Sheahan K. Controversies in the pathological assessment of colorectal cancer. World J Gastroenterol, 2014, 20(29): 9850-9861.
20. Shia J, Klimstra DS, Bagci P, et al. TNM staging of colorectal carcinoma: issues and caveats. Semin Diagn Pathol, 2012, 29(3): 142-153.
21. Berho M, Bejarano PA. Rectal cancer and the pathologist. Minerva Chir, 2018, 73(6): 534-547.
22. Tizhoosh HR, Pantanowitz L. Artificial intelligence and digital pathology: challenges and opportunities. J Pathol Inform, 2018, 9: 38.
23. Nayak J, Goel S. Revised TNM staging for colorectal cancer: did we miss the golden opportunity to do right by the staging? Clin Colorectal Cancer, 2011, 10(3): 207-209.
24. Cavallaro U, Christofori G. Molecular mechanisms of tumor angiogenesis and tumor progression. J Neurooncol, 2000, 50(1-2): 63-70.
25. Wang X, Yu Y, Meng W, et al. Total neoadjuvant treatment (CAPOX plus radiotherapy) for patients with locally advanced rectal cancer with high risk factors: a phase 2 trial. Radiother Oncol, 2018, 129(2): 300-305.

CHINESE JOURNAL OF BASES AND CLINICS IN GENERAL SURGERY

Database research part Ⅵ: staging strategies for colorectal cancer

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