Evidence map›Paper›PMID 27341638›Full record

ArticleScientific reports2016

Spatiotemporal Co-existence of Female Thyroid and Breast Cancers in Hangzhou, China.

Xufeng Fei, George Christakos, Zhaohan Lou, Yanjun Ren, Qingmin Liu, Jiaping Wu

Abstract read
In one paragraph

Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–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

4 citing papers in PubMed.

  1. Thyroid Metastasis from Primary Breast Cancer.Journal of clinical medicine · 2023
    Review
  2. Article
  3. Review
  4. Article
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

6 authors.

Xufeng FeiCollege of Environmental and Resource Sciences, Zhejiang University, Hangzhou, China.
George ChristakosInstitute of Islands and Coastal Ecosystems, Zhejiang University, Zhoushan, China.
Zhaohan LouInstitute of Islands and Coastal Ecosystems, Zhejiang University, Zhoushan, China.
Yanjun RenHangzhou Center for Disease Control and Prevention, Hangzhou, China.
Qingmin LiuHangzhou Center for Disease Control and Prevention, Hangzhou, China.
Jiaping WuInstitute of Islands and Coastal Ecosystems, Zhejiang University, Zhoushan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Thyroid and breast cancers (TC, BC) are common female malignant tumors worldwide. Studies suggest that TC patients have a higher BC risk, and vice versa. However, it has not been investigated quantitatively if there is an association between the space-time TC and BC incidence distributions at the population level. This work aims to answer this question. 5358 TC and 8784 BC (female) cases were diagnosed in Hangzhou (China, 2008-2012). Pearson and Spearman rank correlation coefficients of the TC and BC incidences were high, and their patterns were geographically similar. The spatiotemporal co-existence of TC and BC distributions was investigated using the integrative disease predictability (IDP) criterion: if TC-BC association is part of the disease mapping knowledge bases, it should yield improved space-time incidence predictions. Improved TC (BC) incidence predictions were generated when integrating both TC and BC data than when using only TC (BC) data. IDP consistently demonstrated the spatiotemporal co-existence of TC and BC distributions throughout Hangzhou (2008-2012), which means that when the population experiences high incidences of one kind of cancer attention should be paid to the other kind of cancer too. The strength of TC-BC association was measured by the IDP coefficients and incidence prediction accuracy.

Indexed as

AdultBreast NeoplasmsChinaFemaleHumansIncidenceMiddle AgedRisk FactorsSpatio-Temporal AnalysisThyroid Neoplasms

Identifiers

PMID27341638
PMCPMC4920092

What OpenQuestion holds

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Registered trials

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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.