Trends analysis of pancreatic cancer mortality in Xuhui district, Shanghai from 1992 to 2021

doi:10.16139/j.1007-9610.2025.01.07

Abstract

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

CLC Number:

R735.9

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.

Figures/Tables 4

Tab 1

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Fig 2

Tab 2

References 18

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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