以SEER为基础的列线图构建和胰腺癌病人生存预测

doi:10.16139/j.1007-9610.2024.01.08

摘要/Abstract

摘要：

目的：基于监测、流行病学和最终结果（surveillance, epidemiology, and end results, SEER）数据库，分析影响胰腺癌预后的独立因素并构建预测模型。方法：本研究从SEER数据库获取2010—2015年美国7 801例胰腺癌病人的临床资料，以7∶3的比例随机分为建模组、验证组。对建模组临床变量进行多因素COX回归分析获得影响生存的独立因素，构建列线图。通过受试者操作特性（receiver operating characteristic, ROC）曲线和校准曲线验证模型的准确性。结果：年龄、原发部位、病理分级、T分期、N分期、M分期、手术方式、放疗、化疗与胰腺癌的预后相关，总生存的3年、5年ROC曲线下面积（area under cure, AUC）分别为0.90、0.91，癌症特异性生存分别为0.91、0.91。校准曲线显示观察值与预测值之间具有良好的一致性。经筛选得到的临床变量确实对胰腺癌预后有影响。结论：所构建的模型具有较好的预测准确性，有助于胰腺癌病人的临床决策和个性化治疗。

关键词: 胰腺癌, 监测、流行病学和最终结果数据库, 癌症特异性生存率, 总生存率, 列线图

Abstract:

Objective To analyze the independent factors affecting the prognosis of pancreatic cancer and construct a prediction model based on surveillance, epidemiology, and end results (SEER) database. Methods The clinical data of 7 801 American pancreatic cancer patients from 2010 to 2015 were obtained from SEER database. They were randomly divided into training group and validation group in a ratio of 7:3. The nomogram was constructed after multivariate COX regression analysis of clinical variables in the training group. The accuracy of the model was verified by receiver operating characteristic(ROC) curve and calibration curve. Results Age, primary-site, grade, T-stage, N-stage, M-stage，surgery, radiotherapy and chemotherapy were related to the prognosis of the patients with pancreatic cancer. The area under curve(AUC) of overall survival(OS) ROC curve of 3- and 5-year were 0.90 and 0.91 respectively. The AUC of cancer specific survival(CSS) ROC curve were 0.91 and 0.91 respectively. The calibration curve showed a good consistency between the observed and predicted values. The selected clinical variables did have an impact on the prognosis of the patients with pancreatic cancer. Conclusions The model had good prediction accuracy and was helpful for clinical decision-making and personalized treatment of the patients with pancreatic cancer.

Key words: Pancreatic cancer, Surveillance, epidemiology, and end results (SEER), Cancer specific survival rate, Overall survival rate, Nomogram

中图分类号:

R735.9

陆忠晓, 汤杰, 黄文海. 以SEER为基础的列线图构建和胰腺癌病人生存预测[J]. 外科理论与实践, 2024, 29(01): 46-53.

LU Zhongxiao, TANG Jie, HUANG Wenhai. Nomogram construction based on SEER and survival prediction of pancreatic cancer patients[J]. Journal of Surgery Concepts & Practice, 2024, 29(01): 46-53.

图/表 7

表1

表2

表3

图1

图2

图3

图4

参考文献 32

[1]	SIEGEL R L, MILLER K D, FUCHS H E, et al. Cancer Statistics, 2021[J]. CA Cancer J Clin, 2021, 71(1):7-33.
[2]	RAWLA P, SUNKARA T, GADUPUTI V. Epidemiology of pancreatic cancer: global trends, etiology and risk factors[J]. World J Oncol, 2019, 10(1):10-27. doi: 10.14740/wjon1166 pmid: 30834048
[3]	DEPLANQUE G, DEMARTINES N. Pancreatic cancer: are more chemotherapy and surgery needed?[J]. Lancet, 2017, 389(10073):985-986. doi: S0140-6736(17)30126-5 pmid: 28129986
[4]	ZHU H, LI T, DU Y, et al. Pancreatic cancer: challenges and opportunities[J]. BMC Med, 2018, 16(1):214. doi: 10.1186/s12916-018-1215-3 pmid: 30463539
[5]	ZHANG G H, LIU Y J, DE JI M. Risk factors, prognosis, and a new nomogram for predicting cancer-specific survival among lung cancer patients with brain metastasis: a retrospective study based on SEER[J]. Lung, 2022, 200(1):83-93. doi: 10.1007/s00408-021-00503-0 pmid: 35067758
[6]	WANG Z M, XIANG Z L. Establishment and validation of prognostic nomograms for patients with parotid gland adenocarcinoma not otherwise specified: a SEER analysis from 2004 to 2016[J]. Front Surg, 2022,8:799452.
[7]	VAN DEN HOVEN I, VAN KLAVEREN D, VERHEUVEL N C, et al. Predicting the extent of nodal involvement for node positive breast cancer patients: development and validation of a novel tool[J]. J Surg Oncol, 2019, 120(4):578-586. doi: 10.1002/jso.25644 pmid: 31338839
[8]	ZHANG Y, ZHENG D, XIE J, et al. Development and validation of web-based nomograms to precisely predict conditional risk of site-specific recurrence for patients with completely resected non-small cell lung cancer: a multiinstitutional study[J]. Chest, 2018, 154(3):501-511.
[9]	HU T, WANG S, HUANG L, et al. A clinical-radiomics nomogram for the preoperative prediction of lung metastasis in colorectal cancer patients with indeterminate pulmonary nodules[J]. Eur Radiol, 2019, 29(1):439-449. doi: 10.1007/s00330-018-5539-3 pmid: 29948074
[10]	GROOT V P, GEMENETZIS G, BLAIR A B, et al. Defi-ning and predicting early recurrence in 957 patients with resected pancreatic ductal adenocarcinoma[J]. Ann Surg, 2019, 269(6):1154-1162.
[11]	JONES R P, PSARELLI E E, JACKSON R, et al. Patterns of recurrence after resection of pancreatic ductal adenocarcinoma: a secondary analysis of the ESPAC-4 randomized adjuvant chemotherapy trial[J]. JAMA Surg, 2019, 154(11):1038-1048. doi: 10.1001/jamasurg.2019.3337 pmid: 31483448
[12]	THALER J, AY C, MACKMAN N, et al. Microparticle-associated tissue factor activity, venous thromboembolism and mortality in pancreatic, gastric, colorectal and brain cancer patients[J]. J Thromb Haemost, 2012, 10(7):1363-1370. doi: 10.1111/j.1538-7836.2012.04754.x pmid: 22520016
[13]	YANG Y, LU Y, JIANG W, et al. Individualized prediction of survival benefit from primary tumor resection for patients with unresectable metastatic colorectal cancer[J]. World J Surg Oncol, 2020, 18(1):193. doi: 10.1186/s12957-020-01972-y pmid: 32746835
[14]	LIANG S W, CHEN G, LUO Y G, et al. Nomogram for predicting overall survival in children with neuroblastoma based on SEER database[J]. Ann Surg Treat Res, 2020, 99(2):118-126.
[15]	PILLERON S, MARINGE C, CHARVAT H, et al. The impact of timely cancer diagnosis on age disparities in colon cancer survival[J]. J Geriatr Oncol, 2021, 12(7):1044-1051. doi: 10.1016/j.jgo.2021.04.003 pmid: 33863698
[16]	KUAI L, ZHANG Y, LUO Y, et al. Prognostic nomogram for liver metastatic colon cancer based on histological type, tumor differentiation, and tumor deposit: a TRIPOD compliant large-scale survival study[J]. Front Oncol, 2021,11:604882.
[17]	GROOT V P, REZAEE N, WU W, et al. Patterns, timing, and predictors of recurrence following pancreatectomy for pancreatic ductal adenocarcinoma[J]. Ann Surg, 2018, 267(5):936-945. doi: 10.1097/SLA.0000000000002234 pmid: 28338509
[18]	MOLLBERG N, RAHBARI N N, KOCH M, et al. Arterial resection during pancreatectomy for pancreatic cancer: a systematic review and meta-analysis[J]. Ann Surg, 2011, 254(6):882-893. doi: 10.1097/SLA.0b013e31823ac299 pmid: 22064622
[19]	NAKAMURA T, HIRANO S, NOJI T, et al. Distal pancreatectomy with en bloc celiac axis resection (modified appleby procedure) for locally advanced pancreatic body cancer: a single-center review of 80 consecutive patients[J]. Ann Surg Oncol, 2016, 23(Suppl 5):969-975. pmid: 27495282
[20]	GURUSAMY K S, KUMAR S, DAVIDSON B R, et al. Resection versus other treatments for locally advanced pancreatic cancer[J]. Cochrane Database Syst Rev, 2014,2:CD010244.
[21]	NEOPTOLEMOS J P, KLEEFF J, MICHL P, et al. Therapeutic developments in pancreatic cancer: current and future perspectives[J]. Nat Rev Gastroenterol Hepatol, 2018, 15(6):333-348. doi: 10.1038/s41575-018-0005-x pmid: 29717230
[22]	CHEN-ZHAO X, HERNANDO O, LÓPEZ M, et al. A prospective observational study of the clinical and pathological impact of stereotactic body radiotherapy (SBRT) as a neoadjuvant strategy of chemoradiation in pancreatic cancer[J]. Clin Transl Oncol, 2020, 22(9):1499-1505.
[23]	WANG Z, REN Z G, MA N Y, et al. Intensity modulated radiotherapy for locally advanced and metastatic pancrea-tic cancer: a mono-institutional retrospective analysis[J]. Radiat Oncol, 2015,10:14.
[24]	BORAZANCI E, VON HOFF D D. Nab-paclitaxel and gemcitabine for the treatment of patients with metastatic pancreatic cancer[J]. Expert Rev Gastroenterol Hepatol, 2014, 8(7):739-747.
[25]	KOZUCH P, PETRYK M, EVANS A, et al. Treatment of metastatic pancreatic adenocarcinoma: a comprehensive review[J]. Surg Clin North Am, 2001, 81(3):683-690.
[26]	SOHAL D P, MANGU P B, KHORANA A A, et al. Metastatic pancreatic cancer: American Society of Clinical Oncology clinical practice guideline[J]. J Clin Oncol, 2016, 34(23):2784-2796. doi: 10.1200/JCO.2016.67.1412 pmid: 27247222
[27]	LIU J H, WANG S F, LI B R, et al. Development and validation of an individualized nomogram for predicting pancreatic adenocarcinoma-specific survival: a SEER population analysis of 5,805 patients. Eur Rev Med Pharmacol Sci, 2020, 24(20):10483-10495.
[28]	LI C, REN Z, HAN D, et al. A prognostic nomogram for pancreatic ductal adenocarcinoma patients' all-cause survival in a Surveillance, Epidemiology, and End Results analysis[J]. Transl Cancer Res, 2020, 9(5):3586-3599. doi: 10.21037/tcr-19-2962 pmid: 35117722
[29]	LI G, CHEN J Z, CHEN S, et al. Development and validation of novel nomograms for predicting the survival of patients after surgical resection of pancreatic ductal adenocarcinoma[J]. Cancer Med, 2020, 9(10):3353-3370.
[30]	SHI H, CHEN Z, DONG S, et al. A nomogram for predic-ting survival in patients with advanced (stage Ⅲ/Ⅳ) pancreatic body tail cancer: a SEER-based study[J]. BMC Gastroenterol, 2022, 22(1):279.
[31]	MA X, GUO J, ZHANG C, et al. Development of a prognostic nomogram for metastatic pancreatic ductal adenocarcinoma integrating marital status[J]. Sci Rep, 2022, 12(1):7124. doi: 10.1038/s41598-022-11318-1 pmid: 35504988
[32]	ZHANG W, XU L, CHE X. Nomogram for predicting the prognoses of patients with pancreatic head cancer after pancreaticoduodenectomy: a population-based study on SEER data[J]. Front Oncol, 2021,11:766071.

Variables	Total (n=7 801)	Training group (n=5 461)	Validation group (n=2 340)	P value
Age				0.41
<65	3 122(40.02)	2 169(39.72)	953(40.73)
≥65	4 679(59.98)	3 292(60.28)	1387(59.27)
Race				0.58
White	6 130(78.58)	4 294(78.63)	1 836(78.46)
African descent	1 003(12.86)	691(12.65)	312(13.33)
Other	668(8.56)	476(8.72)	192(8.21)
Sex				0.88
Male	4 094(52.48)	2 863(52.43)	1 231(52.61)
Female	3 707(47.52)	2 598(47.57)	1 109(47.39)
Primary site				0.67
Head	4 043(51.83)	2 839(51.99)	1 204(51.45)
Body and tail	3 758(48.17)	2 622(48.01)	1 136(48.55)
Grade				0.29
Ⅰ+Ⅱ	4 608(59.07)	3 247(59.46)	1 361(58.16)
Ⅲ+Ⅳ	3 193(40.93)	2 214(40.54)	979(41.84)
T stage				0.42
T1+T2	2 766(35.46)	1 952(35.74)	814(34.79)
T3+T4	5 035(64.54)	3 509(64.26)	1 526(65.21)
N stage				0.60
N0	4 993(64.00)	3 485(63.82)	1 508(64.44)
N1	2 808(36.00)	1 976(36.18)	832(35.56)
M stage				0.12
M0	4 749(60.88)	3 294(60.32)	1 455(62.18)
M1	3 052(39.12)	2 167(39.68)	885(37.82)
Surgery				0.70
No	5 505(70.57)	3 862(70.72)	1 643(70.22)
Palliative	67(0.86)	44(0.81)	23(0.98)
Radical	2 229(28.57)	1 555(28.47)	674(28.80)
Radiotherapy				0.20
No	2 296(29.43)	1 631(29.87)	665(28.42)
Yes	5 505(70.57)	3 830(70.13)	1 675(71.58)
Chemotherapy				>0.05
No	584(7.49)	428(7.84)	156(6.67)
Yes	7 217(92.51)	5 033(92.16)	2 184(93.33)

Variables	HR(95%CI)	β value	P value
Age(years)
<65	-	-	-
≥65	1.55（1.46-1.65）	0.44	<0.001
Race
White	-	-	-
African descent	1.10（1.02-1.20）	0.10	0.02
Other	0.96（0.87-1.06）	-0.04	0.40
Gender
Male	-	-	-
Female	0.98（0.93-1.03）	-0.02	0.39
Primary site
Head	-	-	-
Body and tail	1.12（1.05-1.19）	0.11	<0.001
Grade
Ⅰ+Ⅱ	-	-	-
Ⅲ+Ⅳ	1.70（1.61-1.80）	0.53	<0.001
T stage
T1+T2	-	-	-
T3+T4	1.27（1.19-1.35）	0.24	<0.001
N stage
N0	-	-	-
N1	1.09（1.03-1.16）	0.09	<0.01
M stage
M0	-	-	-
M1	1.29（1.17-1.42）	0.25	<0.001
Surgery
No	-	-	-
Palliative	0.26（0.24-0.29）	-1.33	<0.001
Radical	0.21（0.14-0.32）	-1.57	<0.001
Radiotherapy
No	-	-
Yes	0.82（0.75-0.90）	-0.20	<0.001
Chemotherapy
No	-	-
Yes	0.81（0.73-0.89）	-0.21	<0.001

Variables	HR(95%CI)	β value	P value
Age(years)
<65	-	-	-
≥65	1.58（1.47-1.69）	0.46	<0.001
Race
White	-	-	-
African descent	1.11（1.01-1.22）	0.10	0.03
Other	0.94（0.83-1.06）	-0.06	0.30
Gender
Male	-	-	-
Female	0.99（0.93-1.06）	-0.01	0.85
Primary site
Head	-	-	-
Body and tail	1.16（1.08-1.25）	0.15	<0.001
Grade
Ⅰ+Ⅱ	-	-	-
Ⅲ+Ⅳ	1.70（1.59-1.82）	0.53	<0.001
T stage
T1+T2	-	-	-
T3+T4	1.30（1.21-1.40）	0.27	<0.001
N stage
N0	-	-	-
N1	1.11（1.03-1.19）	0.10	<0.01
M stage
M0	-	-	-
M1	1.34（1.20-1.50）	0.29	<0.001
Surgery
No	-	-	-
Palliative	0.27（0.24-0.30）	-1.30	<0.001
Radical	0.20（0.12-0.35）	-1.59	<0.001
Radiotherapy
No	-	-
Yes	0.84（0.75-0.94）	-0.18	<0.01
Chemotherapy
No	-	-
Yes	0.81（0.72-0.91）	-0.21	<0.001