Evidence map›Paper›PMID 32359212›Full record

ArticleCancer communications (London, England)2020

Cancer burden of major cancers in China: A need for sustainable actions.

Maomao Cao, He Li, Dianqin Sun, Wanqing Chen

Abstract read
In one paragraph

Article in Cancer communications (London, England), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 256 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
256citing papers in PubMed, 2 pooled it
–field-weighted citation impact
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

256 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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196 more citing papers are in PubMed but not listed here.

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

4 authors.

Maomao CaoOffice of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, P. R. China.
He LiOffice of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, P. R. China.
Dianqin SunOffice of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, P. R. China.
Wanqing ChenOffice of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, P. R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer is still a major health problem in China although numerous efforts have been made for its prevention and control. Findings from this study showed that lung cancer remains the most common type of cancer diagnosed, and was attributed to nearly 30% of all cancer-related deaths. The incidence of the five most common cancers, in China, in 2015, including cancers of the lungs, stomach, colorectum, liver and breast, accounted for almost 60% of all cancers diagnosed. The high cancer burden in China highlights the need for further improvement in health education, professional training and the building up an anti-cancer network for introducing and implementing sustainable actions for cancer control.

Indexed as

Cost of IllnessAdultAgedAged, 80 and overBreast NeoplasmsChinaColorectal NeoplasmsFemaleHealth Services Needs and DemandHumansIncidenceLiver NeoplasmsLung NeoplasmsMaleMiddle AgedRegistriesactionsburdencancer epidemiologyChinaincidencemortality

Identifiers

PMID32359212
PMCPMC7667573

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.