Evidence map›Paper›PMID 41819575›Full record

ArticleBMJ open2026

Ageing phenotypes and behavioural determinants of health on age acceleration: the Cancer Survivors' Trajectories of Ageing Research (C*STAR) study protocol.

Nur Afifah Mursyida Zaujan, Mohd Razif Shahril, Suzana Shahar, Ezanee Azlina Mohamad Hanif, Nur Fa'izah Ab Muin, Razinah Sharif, Ponnusamy Subramaniam, Azizi Abdullah, Michael Fenech

Abstract read
In one paragraph

Article in BMJ open, 2026. 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

9 authors.

Nur Afifah Mursyida ZaujanCentre for Healthy Ageing and Wellness (H-CARE), Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia.
Mohd Razif ShahrilCentre for Healthy Ageing and Wellness (H-CARE), Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia razifshahril@ukm.edu.my.ORCID http://orcid.org/0000-0002-8680-3087
Suzana ShaharCentre for Healthy Ageing and Wellness (H-CARE), Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia.ORCID http://orcid.org/0000-0002-7191-9212
Ezanee Azlina Mohamad HanifUKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Cheras, Kuala Lumpur, Malaysia.
Nur Fa'izah Ab MuinDepartment of Radiotherapy and Oncology, Hospital Canselor Tuanku Muhriz (HCTM), Universiti Kebangsaan Malaysia, Cheras, Kuala Lumpur, Malaysia.
Razinah SharifCentre for Healthy Ageing and Wellness (H-CARE), Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia.ORCID http://orcid.org/0000-0001-7174-7353
Ponnusamy SubramaniamCentre for Healthy Ageing and Wellness (H-CARE), Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia.ORCID http://orcid.org/0000-0002-2361-4780
Azizi AbdullahCentre for Artificial Intelligence Technology (CAIT), Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia.
Michael FenechSchool of Agriculture, Food and Wine, College of Sciences, Adelaide University, Adelaide, South Australia, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionAge acceleration in survivors of breast cancer is a critical issue because cancer and its treatment can increase structural and numerical chromosomal aberrations, while simultaneously shortening telomere length and changing ageing phenotype. Therefore, the current study will be using machine learning architectures to accurately predict the factors that contribute to age acceleration among survivors of breast cancer. METHODS AND ANALYSIS: The Cancer Survivors' Trajectories of Ageing Research (C*STAR) is a hospital-based cross-sectional study involving multi-ethnic Malaysian survivors of breast cancer and a non-breast cancer control group, frequency-matched by age group (±5 years), sex and ethnicity. The three main stages of this study will be conducted in the predictive model development. First, a set of validated questionnaires will be used to collect the data on modifiable factors of ageing phenotypes and behavioural determinants of health. Second, 3 mL non-fasting blood samples will be collected, and lymphocytes will be isolated to determine telomere length using real-time PCR as a biomarker of age acceleration. Lastly, a machine learning architecture will be deployed to identify modifiable factors that may contribute to age acceleration in survivors of breast cancer and controls, with these factors used as input and ageing biomarkers of telomere length as output. The study outcomes may serve as guidance to enhance the quality of life of survivors of breast cancer and hinder the recurrence of cancer while ageing successfully. ETHICS AND DISSEMINATION: Ethical approval was obtained from the Research Ethics Committee, Universiti Kebangsaan Malaysia (JEP-2022-700) to carry out this study. Written informed consent will be obtained from each survivor of breast cancer and each cancer-free woman prior to participation. The results of this study will be published for future research and clinical applications.

Indexed as

AgingBreast NeoplasmsCancer SurvivorsCross-Sectional StudiesFemaleHumansMachine LearningMalaysiaMiddle AgedPhenotypeResearch DesignSurveys and QuestionnairesAgingBehaviorBreast tumoursHealthMachine LearningSurvival

Identifiers

PMID41819575
PMCPMC12993301

What OpenQuestion holds

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LicenceCC BY-NC
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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.