Evidence map›Paper›PMID 28717728›Full record

ReviewJournal of global oncology2016

Prevalence of Triple-Negative Breast Cancer in India: Systematic Review and Meta-Analysis.

Gurprataap S Sandhu, Sebhat Erqou, Heidi Patterson, Aju Mathew

Abstract readReview
In one paragraph

Review in Journal of global oncology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
56citing papers in PubMed, 1 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

56 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  17. Lest we forget… Breast cancer & beyond….The Indian journal of medical research · 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

4 authors.

Gurprataap S Sandhu, , and , University of Pittsburgh Medical Center, Pittsburgh, PA; and , Markey Cancer Center, University of Kentucky, Lexington, KY.
Sebhat Erqou, , and , University of Pittsburgh Medical Center, Pittsburgh, PA; and , Markey Cancer Center, University of Kentucky, Lexington, KY.
Heidi Patterson, , and , University of Pittsburgh Medical Center, Pittsburgh, PA; and , Markey Cancer Center, University of Kentucky, Lexington, KY.
Aju Mathew, , and , University of Pittsburgh Medical Center, Pittsburgh, PA; and , Markey Cancer Center, University of Kentucky, Lexington, KY.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThere is considerable variation in prevalence rates of triple-negative breast cancer (TNBC) reported by various studies from India. We performed a systematic review and literature-based meta-analysis of these studies.

methodsWe searched databases of Medline, Scopus, EMBASE, and Web of Science for studies that reported on the prevalence of TNBC in India that were published between January 1, 1999, and December 31, 2015. We extracted relevant information from each study by using a standardized form. We pooled study-specific estimates by using random-effects meta-analysis to provide summary estimates. We explored sources of heterogeneity by using subgroup analyses and metaregression.

resultsData were obtained from 17 studies that involved 7,237 patients with breast cancer. Overall combined prevalence of TNBC was 31% (95% CI, 27% to 35%). There was substantial heterogeneity across the studies (I

conclusionPrevalence of TNBC in India is considerably higher compared with that seen in Western populations. As many as as one in three women with breast cancer could have triple-negative disease. This finding has significant clinical relevance as it may contribute to poor outcomes in patients with breast cancer in India. Additional research is needed to understand the determinants of TNBC in India.

Identifiers

PMID28717728
PMCPMC5493252

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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.