1992—2021年上海市徐汇区户籍居民胰腺癌死亡率趋势分析

doi:10.16139/j.1007-9610.2025.01.07

摘要/Abstract

摘要：

目的： 研究1992—2021年上海市徐汇区户籍居民胰腺癌死亡现况，分析其变化趋势，为胰腺癌防治提供依据。方法： 根据1992—2021年上海市死亡登记系统数据,计算徐汇区户籍居民胰腺癌粗死亡率、标化死亡率、年龄别死亡率等指标,运用Joinpoint软件分析胰腺癌死亡率的平均年度百分比变化（AAPC）趋势,运用年龄-时期-队列模型分析年龄效应、时期效应和出生队列效应对胰腺癌死亡率的变化显著性。结果： 2021年上海市徐汇区户籍胰腺癌死亡居恶性肿瘤第4位，全人群、男性及女性的中标率和世标率分别为8.34/10万（8.81/10万、7.98/10万）和7.28/10万（7.69/10万、6.96/10万），男性均高于女性。粗死亡率、标化（6普）死亡率AAPC男性均高于女性。年龄别死亡率随年龄的增大而增长，60~84岁组为最高。年龄-时期-队列模型显示，1992—2021年上海市徐汇区户籍居民全人群、男性及女性胰腺癌死亡率每年净漂移=1.22%、1.58%、1.15%（P=0.20、0.19、0.45），时间趋势不显著。全人群和男性年龄偏差随着年龄的增长变化趋势显著（P<0.05），女性年龄效应趋势不显著。全人群、男性及女性时期偏差均不显著（P>0.05）。从队列效应来看，全人群和男性队列偏差效应差异均显著（P<0.05），女性人群未见显著队列效应。结论： 1992—2021上海市徐汇区户籍居民胰腺癌死亡率呈上升趋势，60~84岁组及男性尤为明显。胰腺癌防控工作需要针对相应人群制定有效的防疫措施。

关键词: 胰腺癌, 标化死亡率, 年度变化百分比, 年龄-时期-队列模型

Abstract:

Objective To study the death status of pancreatic cancer among residents in Xuhui district, Shanghai, from 1992 to 2021, and analyze its trends of change, so as to provide evidence for the prevention and treatment of pancreatic cancer. Methods Based on the database of Shanghai death registration system from 1992 to 2021, the crude mortality rate, standardized mortality rate, age-specific mortality rate and other indicators of pancreatic cancer among registered residents in Xuhui district were calculated. The Joinpoint software was used to analyze the trends of average annual percent change (AAPC) of pancreatic cancer mortality rate, and the age-period-cohort model was used to analyze the age effect, period effect and birth cohort effect pairs significant changes in pancreatic cancer mortality. Results In 2021, the mortality rate of pancreatic cancer in Xuhui district, Shanghai, ranked fourth among malignant tumors, and the winning rate and world standard rate of the whole population, males and females were 8.34/100 000 (8.81/100 000, 7.98/100 000) and 7.28/100 000 (7.69/100 000, 6.96/100 000), respectively, with males higher than females. AAPC of crude mortality rate and the standardized (6) mortality rate were higher in males than that in females. The age-specific mortality rate increased with the increase of age, and the highest mortality rate was found in 60-84 years old group. The age-period-cohort model showed that from 1992 to 2021, the annual net shift of pancreatic cancer mortality among the whole population, male and female residents in Xuhui district, Shanghai, was 1.22%, 1.58%, 1.15% (P=0.20, 0.19, 0.45) respectively, and the time trend was not significant. From the perspective of age effect, the risk of death from pancreatic cancer in the whole population and with age deviation in males had an obvious trend with increasing age (P<0.05), while the age effect in females had no obvious trend. From the perspective of period effect, no period deviation was significant in the whole population, males and females (P>0.05). In terms of cohort effects, there were significant differences in the whole population and the male cohort deviations(P<0.05). No significant cohort effect was observed in the female population. Conclusions The mortality rate of pancreatic cancer among registered residents in Xuhui district, Shanghai from 1992 to 2021, was on the rise, especially in the 60-84 years old group and male. The prevention and control of pancreatic cancer needs to develop effective epidemic prevention measures for corresponding populations.

Key words: Pancreatic cancer, Standardized mortality rate, Annual percent change (APC), Age-period-cohort model

中图分类号:

R735.9

徐荆庶, 施建华, 顾海雁, 陈蕾, 钱孝琳, 陆璐, 钮登. 1992—2021年上海市徐汇区户籍居民胰腺癌死亡率趋势分析[J]. 外科理论与实践, 2025, 30(01): 34-40.

XU Jingshu, SHI Jianhua, GU Haiyan, CHEN Lei, QIAN Xiaolin, LU Lu, NIU Deng. Trends analysis of pancreatic cancer mortality in Xuhui district, Shanghai from 1992 to 2021[J]. Journal of Surgery Concepts & Practice, 2025, 30(01): 34-40.

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Years	Group	Mortality			Crude mortality rate/10⁵			Age-standardized mortality rate a/10⁵			Age-standardized mortality rate b/10⁵
Years	Group	All	Male	Female	All	Male	Female	All	Male	Female	All	Male	Female
1992	0-44	1	1	0	1.59	3.01	0.00	0.15	0.28	0.00	0.10	0.20	0.00
	45-59	10	3	7	23.05	14.34	31.95	1.44	0.94	1.96	1.14	0.75	1.56
	60-84	36	16	20	194.46	172.74	205.81	3.94	3.65	4.23	3.49	3.23	3.74
	85-	2	2	0	43.43	126.90	0.00	0.25	0.53	0.00	0.26	0.56	0.00
	Total	49	22	27	6.53	5.78	7.30	5.77	5.41	6.19	4.99	4.67	5.35
2021	0-44	0	0	0	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00
	45-59	14	8	6	24.76	28.47	21.06	1.64	1.85	1.42	1.27	1.44	1.10
	60-84	144	79	65	311.19	314.80	305.34	6.12	6.67	5.65	5.39	5.87	4.97
	85-	36	10	26	102.40	69.99	124.59	0.59	0.29	0.91	0.61	0.31	0.96
	Total	194	97	97	20.71	21.32	20.14	8.34	8.81	7.98	7.28	7.69	6.96
AAPC%		-	-	-	4.13	4.27	4.02	1.38	1.41	1.36	1.39	1.42	1.37
95%CI		-	-	-	(2.2,6.1)	(2.0,6.6)	(2.2,5.9)	(-0.3,3.1)	(-0.6,3.5)	(-0.4,3.1)	(-0.3,3.1)	(-0.2,2.7)	(-0.2,2.7)
t value					-5.45	-4.67	-5.52	-1.93	-1.65	-1.86	-1.93	-1.65	-1.86
P value					0.41289	0.31600	0.70133	0.65422	0.46467	0.62978	0.56533	0.40153	0.54421

Item	All			Male			Female
Item	χ²	df	P Value	χ²	df	P Value	χ²	df	P Value
NetDrift = 0	1.673	1	0.196	1.732	1	0.188	0.564	1	0.453
All Age Deviations = 0	26.289	10	0.003	23.148	10	0.010	10.433	10	0.403
All Period Deviations = 0	7.606	4	0.107	5.604	4	0.231	4.423	4	0.352
All Cohort Deviations = 0	24.906	15	0.051	20.985	15	0.137	7.719	15	0.935
All Period RR = 1	9.631	5	0.086	7.264	5	0.202	5.395	5	0.370
All Cohort RR = 1	34.797	16	0.004	26.709	16	0.045	12.190	16	0.731
All Local Drifts = Net Drift	18.644	12	0.097	19.865	12	0.070	4.121	12	0.981