Evidence map›Paper›PMID 36974369›Full record

ArticleMedeniyet medical journal2023

Does Apoptotic Index Predict the Response to Neoadjuvant Chemotherapy in Patients with Breast Carcinoma?

Gokce Askan, Oguzhan Okcu, Cigdem Ozturk, Seda Duman Ozturk, Bayram Sen, Recep Bedir

Open access · diamondAbstract read
In one paragraph

Article in Medeniyet medical journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 44% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. 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 at 1 institution in 1 country.

Gokce AskanRecep Tayyip Erdogan University Training and Research Hospital, Department of Pathology, Rize, Turkey.ORCID 0000-0002-9255-649X
Oguzhan OkcuRecep Tayyip Erdogan University Training and Research Hospital, Department of Pathology, Rize, Turkey.ORCID 0000-0001-7481-4718
Cigdem OzturkRecep Tayyip Erdogan University Training and Research Hospital, Department of Pathology, Rize, Turkey.ORCID 0000-0003-2587-214X
Seda Duman OzturkRecep Tayyip Erdogan University Training and Research Hospital, Department of Pathology, Rize, Turkey.ORCID 0000-0001-9113-1580
Bayram SenRecep Tayyip Erdogan University Training and Research Hospital, Department of Biochemistry, Rize, Turkey.ORCID 0000-0002-4541-881X
Recep BedirRecep Tayyip Erdogan University Training and Research Hospital, Department of Pathology, Rize, Turkey.ORCID 0000-0001-8247-3781
Recep Tayyip Erdoğan University · TR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Neoadjuvant chemotherapy (NACT) plays a major role in the treatment of patients with locally advanced breast carcinoma. Although most patients have benefited from NACT, the rate of residual tumors is still high after treatment (AT). An increase in apoptosis is expected in tru-cut biopsy (TCB) during treatment or AT as the mechanism of NACT is inducing apoptosis. This study aimed to investigate whether evaluating the apoptotic index (AI) from TCB can predict the response before treatment (TC-BT) and whether there is a correlation between AI and clinicopathologic parameters. Methods: Seventy cases of breast carcinomas were included. The AI was evaluated BT and AT by quantifying the apoptosis. The receiver operating characteristic analysis was performed with overall survival (OS) data, and low and high AI cut-offs were obtained. The relationship between AI and response and clinicopathological parameters was evaluated. Results: A significant relationship was found between low AI in TC-BT and at least partial response (p=0.025), longer OS (p=0.01) and disease-free survival (p=0.01), and progesterone receptor-positive tumors (p=0.03). Her2-negative tumors were more prone to low AI. A significant decline in AI (p=0.001) and Ki67 proliferation index (p<0.001) was observed in resections AT. Conclusions: These data suggested that the AI is a simple and cost-effective tool that may play an important role in determining response, and a low AI in TC-BT may have some value as a predictive marker in breast carcinomas.

Indexed as

Apoptosisapoptotic indexbreast cancerneoadjuvant chemotherapyresponse

Identifiers

PMID36974369
PMCPMC10064109
OpenAlexW4313500503

What OpenQuestion holds

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LicenceCC BY-NC
Read underepoch 390

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.