Evidence map›Paper›PMID 40696006›Full record

ArticleScientific reports2025

Exploring QSPR in breast cancer drugs via entire neighborhood indices and regression models.

Alaa Altassan, Anwar Saleh, Hanaa Alashwali, Marwa Hamed, Najat Muthana

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PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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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

2 citing papers in PubMed.

  1. Article
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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

5 authors.

Alaa AltassanDepartment of Mathematics, Faculty of Science, King Abdulaziz University, 21589, Jeddah, Saudi Arabia.
Anwar SalehDepartment of Mathematics and Statistics, College of Science, University of Jeddah, 23218, Jeddah, Saudi Arabia. asaleh1@uj.edu.sa.
Hanaa AlashwaliDepartment of Mathematics, Faculty of Science, King Abdulaziz University, 21589, Jeddah, Saudi Arabia.
Marwa HamedDepartment of Mathematics, Faculty of Science, King Abdulaziz University, 21589, Jeddah, Saudi Arabia.
Najat MuthanaDepartment of Mathematics and Statistics, College of Science, University of Jeddah, 23218, Jeddah, Saudi Arabia. nmuthana@uj.edu.sa.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer is a life-threatening disease that can attack humans at any part of the body as a consequence of abnormal cell growth and proliferation, leading to tumors that can be fatal. Breast cancer is one of the deadliest ailments in the world after lung cancer. Through hormonal and genetic changes that occur in DNA, breast cancer can affect women. The quantitative structural-property relationship (QSPR) is used to provide a comprehensive study of 16 drugs involved in the treatment of breast cancer. According to their chemical structure, the drugs being studied are modeled as molecular graphs. The purpose of this study is to examine the utility of new entire neighborhood topological indices in characterizing the physicochemical properties of a range of breast cancer drugs. Cubic regression analysis was initially employed, followed by multiple linear regression modeling to enhance the correlation between the entire neighborhood topological indices and some properties of the aforementioned drugs. The analysis results are presented and discussed, leading to conclusions about the potential of these new indices for pharmaceutical and chemical research on breast cancer treatments.

Indexed as

Antineoplastic AgentsBreast NeoplasmsQuantitative Structure-Activity RelationshipFemaleHumansRegression AnalysisAntineoplastic AgentsBreast cancer drugsEntire neighborhood topological indicesEntire topological indicesNeighborhood topological indicesQSPR analysis

Identifiers

PMID40696006
PMCPMC12284210

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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.