Evidence map›Paper›PMID 38028182›Full record

ArticleOncology letters2024

Selection of breast cancer subtypes to improve benefits of intensive dose‑dense chemotherapy: A systematic meta‑analysis.

Dan Su, Tianqi Zhang, Huimin Huang, Xiaoyu Su, Ying Li, Xiuyan Wei, Yingshi Zhang

Open access · diamondAbstract read
In one paragraph

Article in Oncology letters, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 49% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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 1 institution in 1 country.

Dan SuDepartment of Clinical Pharmacy, Shenyang Pharmaceutical University, Shenyang, Liaoning 110016, P.R. China.
Tianqi ZhangDepartment of Clinical Pharmacy, Shenyang Pharmaceutical University, Shenyang, Liaoning 110016, P.R. China.
Huimin HuangDepartment of Clinical Pharmacy, Shenyang Pharmaceutical University, Shenyang, Liaoning 110016, P.R. China.
Xiaoyu SuDepartment of Clinical Pharmacy, Shenyang Pharmaceutical University, Shenyang, Liaoning 110016, P.R. China.
Ying LiDepartment of Clinical Pharmacy, Shenyang Pharmaceutical University, Shenyang, Liaoning 110016, P.R. China.
Xiuyan WeiDepartment of Clinical Pharmacy, Shenyang Pharmaceutical University, Shenyang, Liaoning 110016, P.R. China.
Yingshi ZhangDepartment of Clinical Pharmacy, Shenyang Pharmaceutical University, Shenyang, Liaoning 110016, P.R. China.
Shenyang Pharmaceutical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Breast cancer (BC) is the most commonly diagnosed cancer and the second leading cause of cancer mortality among women worldwide. A large number of patients experience recurrence and BC-associated mortality following adjuvant chemotherapy. The present study aimed to determine the most suitable pathological subtype of BC to benefit from intensive dose-dense (DD) chemotherapy. A total of four electronic databases were searched from inception up to March 10, 2023. Randomized controlled trials (RCTs) and retrospective studies comparing DD chemotherapy with standard chemotherapy in patients with BC were included. Pairwise random effects and network meta-analyses were performed to summarize efficacy and safety outcomes. A total of 27 original studies including 27,580 patients with BC were included. In terms of efficacy, the present study evaluated overall survival, disease-free survival, event-free survival, recurrence-free survival, pathological complete response and objective remission rate. Significant differences were identified in overall, hormone receptor

Indexed as

breast cancerintensive dose-dense chemotherapynetwork meta-analysispathological typesystematic review

Identifiers

PMID38028182
PMCPMC10665989
OpenAlexW4388463981

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.