Evidence map›Paper›PMID 26131834›Full record

Observational studyMedicine2015

Epidemiological and Clinicopathological Trends of Breast Cancer in Chinese Patients During 1993 to 2013: A Retrospective Study.

Wen Si, Ying Li, Yingjie Han, Fan Zhang, Yingzhe Wang, Ying Li, Rui Xia Linghu, Xingyang Zhang, Junlan Yang

Abstract readObservational Study
In one paragraph

Observational study in Medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Sacituzumab govitecan in HRNature medicine · 2024
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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

9 authors.

Wen SiFrom the Department of Medical Oncology I, General Hospital of the Chinese People's Liberation Army, Beijing (WS, YH, FZ, YW, YL, RXL, XZ, JY); School of Medicine, Nankai University, Tianjin (WS, YH); and Department of Medical Oncology, Beijing Geriatric Hospital, Haidian District (YL).
Ying Li
Yingjie Han
Fan Zhang
Yingzhe Wang
Ying Li
Rui Xia Linghu
Xingyang Zhang
Junlan Yang

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to summarize the epidemiological and pathological trends of breast cancer in Chinese women.The clinical data of 4968 breast cancer patients treated at the Chinese PLA General Hospital from 1993 to 2013 were retrospectively reviewed.The mean ± standard deviation (SD) age was 47.4 ± 11.3 years before the year 2001, 49.2 ± 11.2 years during 2001 to 2010, and 50.6 ± 11.4 years after the year 2010, respectively (P < 0.001). The ratio of premenopausal women to postmenopausal women was 1.6 and no significant changes were found during the period (P = 0.121). The proportion of patients with Scarff Bloom Richardson III breast cancer showed significant increase along with time (P = 0.015). The breast cancer was accounting for 31.7% at stage I and DCIS/LCIS and tend to be diagnosed with early stage around time (P < 0.001). The proportion of DCIS/LCIS and stage I increased with time during the 20 years from 14.6% to 33.2%, whereas the proportion of stage III to IV decreased.The proportion of Luminal A-like subtype gradually reduced and Luminal B-like (HER2-negative) increased and developed to the predominant type. Older age and earlier stage at diagnosis, as well as the alternation of predominant molecular subtypes, have become the developed trends of breast cancer.

Indexed as

AdultAge FactorsAsian PeopleBreastBreast NeoplasmsCarcinoma, Ductal, BreastChinaErb-b2 Receptor Tyrosine KinasesFemaleHumansMaleMiddle AgedRetrospective StudiesERBB2 protein, humanErb-b2 Receptor Tyrosine Kinases

Identifiers

PMID26131834
PMCPMC4504600

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.