Evidence map›Paper›PMID 40989698›Full record

ArticleFrontiers in oncology2025

Mathematical modeling of the effect of early detection in breast cancer treatment.

Farouk Tijjani Saad, Yusuf Ya'u Gambo, Phollakrit Wongsantisuk, Idris Ahmed, Jessada Tariboon

Abstract read
In one paragraph

Article in Frontiers in oncology, 2025. 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
–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

1 citing paper in PubMed.

  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

5 authors.

Farouk Tijjani SaadDepartment of Mathematics, Northwest University, Kano, Nigeria.
Yusuf Ya'u GamboDepartment of Mathematics, Northwest University, Kano, Nigeria.
Phollakrit WongsantisukDepartment of Electronics Engineering Technology, College of Industrial Technology, King Mongkut's University of Technology North Bangkok, Bangkok, Thailand.
Idris AhmedDepartment of Mathematics, Faculty of Natural and Applied Sciences, Sule Lamido University, Kafin Hausa, Jigawa, Nigeria.
Jessada TariboonIntelligent and Nonlinear Dynamics Innovation Research Center, Department of Mathematics, Faculty of Applied Science, King Mongkut's University of Technology North Bangkok, Bangkok, Thailand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Early detection is a cornerstone of cancer control, yet its quantitative influence on tumor-immune interactions remains underexplored in mathematical oncology. Methods: We formulated a nonlinear tumor-immune interaction model consisting of two coupled ordinary differential equations for tumor growth and immune response. Early detection was represented by a saturating function (Michealis-Menten term) dependent on tumor size and awareness level. The system was nondimensionalized to reduce parameters and ease analysis. Equilibria were derived, and both local and global stability were analyzed. Numerical simulations, phase portraits, bifurcation and sensitivity analyses were conducted to assess system behavior and parameter influence. Results: Two biologically meaningful equilibria were identified. Stability analyses established the conditions for sustained tumor-free states. Simulations demonstrated that higher awareness significantly enhances early detection, thereby suppressing tumor growth. Phase portraits revealed stable tumor-immune dynamics, while sensitivity results highlighted awareness- and detection-related parameters as the most critical for tumor control. Discussion: The model quantifies the role of awareness-driven early detection in shaping tumor-immune outcomes. Results underscore the importance of public awareness campaigns, screening initiatives, and early intervention strategies for effective cancer management. This framework bridges mathematical modeling and policy, offering understanding into optimizing awareness-based control measures.

Indexed as

awarenessbreast cancerearly detectionimmune responsemodelingsensitivity analysis

Identifiers

PMID40989698
PMCPMC12450656

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.