Evidence map›Paper›PMID 28465647›Full record

Observational studyWorld journal of gastroenterology2017

Upper gastrointestinal cancer burden in Hebei Province, China: A population-based study.

Dao-Juan Li, Di Liang, Guo-Hui Song, Yong-Wei Li, Deng-Gui Wen, Jing Jin, Yu-Tong He

Open access · hybridAbstract readObservational Study
In one paragraph

Observational study in World journal of gastroenterology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.8field-weighted citation impact, top 25% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 7 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 4 institutions in 1 country.

Dao-Juan LiDao-Juan Li, Di Liang, Deng-Gui Wen, Jing Jin, Yu-Tong He, Cancer Institute, The Fourth Hospital of Hebei Medical University/The Tumour Hospital of Hebei Province, Shijiazhuang 050011, Hebei Province, China.
Di LiangDao-Juan Li, Di Liang, Deng-Gui Wen, Jing Jin, Yu-Tong He, Cancer Institute, The Fourth Hospital of Hebei Medical University/The Tumour Hospital of Hebei Province, Shijiazhuang 050011, Hebei Province, China.
Guo-Hui SongDao-Juan Li, Di Liang, Deng-Gui Wen, Jing Jin, Yu-Tong He, Cancer Institute, The Fourth Hospital of Hebei Medical University/The Tumour Hospital of Hebei Province, Shijiazhuang 050011, Hebei Province, China.
Yong-Wei LiDao-Juan Li, Di Liang, Deng-Gui Wen, Jing Jin, Yu-Tong He, Cancer Institute, The Fourth Hospital of Hebei Medical University/The Tumour Hospital of Hebei Province, Shijiazhuang 050011, Hebei Province, China.
Deng-Gui WenDao-Juan Li, Di Liang, Deng-Gui Wen, Jing Jin, Yu-Tong He, Cancer Institute, The Fourth Hospital of Hebei Medical University/The Tumour Hospital of Hebei Province, Shijiazhuang 050011, Hebei Province, China.
Jing JinDao-Juan Li, Di Liang, Deng-Gui Wen, Jing Jin, Yu-Tong He, Cancer Institute, The Fourth Hospital of Hebei Medical University/The Tumour Hospital of Hebei Province, Shijiazhuang 050011, Hebei Province, China.
Yu-Tong HeDao-Juan Li, Di Liang, Deng-Gui Wen, Jing Jin, Yu-Tong He, Cancer Institute, The Fourth Hospital of Hebei Medical University/The Tumour Hospital of Hebei Province, Shijiazhuang 050011, Hebei Province, China.
Hospital of Hebei Province · CNCixian People's Hospital · CNFourth Hospital of Hebei Medical University · CNHebei Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimTo investigate the incidence and mortality rates of upper gastrointestinal cancer (UGIC) in Hebei Province, China, and to identify high-risk populations to improve UGIC prevention and control.

methodsData for UGIC patients were collected from 21 population-based cancer registries covering 15.25% of the population in Hebei Province. Mortality data were extracted from three national retrospective death surveys (1973-1975, 1990-1992 and 2004-2005). The data were stratified by 5-year age groups, gender and area (high-risk/non-high-risk areas) for analysis. The age-period-cohort and grey system model were used.

resultsThe crude incidence rate of UGIC was 55.47/100000, and the adjusted rate (Segi's population) was 44.90/100000. Males in rural areas had the highest incidence rate (world age-standardized rate = 87.89/100000). The crude mortality rate of UGIC displayed a decreasing trend in Hebei Province from the 1970s to 2013, and the adjusted rate decreased by 43.81% from the 1970s (58.07/100000) to 2013 (32.63/100000). The mortality rate declined more significantly in the high-risk areas (57.26%) than in the non-high-risk areas (55.02%) from the 1970s to 2013. The median age at diagnosis of UGIC was 65.06 years in 2013. There was a notable delay in the median age at death from the 1970s (66.15 years) to 2013 (70.39 years), especially in the high-risk areas. In Cixian, the total trend of the cohort effect declined, and people aged 65-69 years were a population at relatively high risk for UGIC. We predicted that the crude mortality rates of UGIC in Cixian and Shexian would decrease to 98.80 and 133.99 per 100000 in 2018, respectively.

conclusionUGIC was the major cause of cancer death in Hebei Province, and males in rural areas were a high-risk population. We should strengthen early detection and treatment of UGIC in this population.

Indexed as

AdultAgedAged, 80 and overAge DistributionCause of DeathChinaEsophageal NeoplasmsFemaleHumansIncidenceMaleMiddle AgedRegistriesRetrospective StudiesRural HealthSex DistributionAge-period-cohortGrey system modelIncidenceMortalityUpper gastrointestinal cancer

Identifiers

PMID28465647
PMCPMC5394526
OpenAlexW2605482669

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.