Spatial Distribution and Clinicopathological Factors Associated  with Late-Stage Breast Cancer in Kelantan, Malaysia:  A Geographic Information Systems (GIS)-Based Analysis

Aishah Md Salleh; Wan Zainira Wan Zain; Zalina Zahari; Maya Mazuwin Yahya; Ahmad Filza Ismail

doi:10.31557/apjcc.2026.11.2.189-198

Authors

Aishah Md Salleh Department of Surgery, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian, Kelantan, Malaysia.
Wan Zainira Wan Zain Department of Surgery, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian, Kelantan, Malaysia. Department of Surgery, Hospital Pakar Universiti Sains Malaysia, Kubang Kerian, Kelantan, Malaysia.
Zalina Zahari Faculty of Pharmacy, Universiti Sultan Zainal Abidin (UniSZA), Besut Campus, Besut, Terengganu, Malaysia.
Maya Mazuwin Yahya Department of Surgery, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian, Kelantan, Malaysia. Department of Surgery, Hospital Pakar Universiti Sains Malaysia, Kubang Kerian, Kelantan, Malaysia.
Ahmad Filza Ismail Department of Community Medicine, Universiti Sains Malaysia, Kubang Kerian, Kelantan, Malaysia.

DOI:

https://doi.org/10.31557/apjcc.2026.11.2.189-198

Keywords:

Breast cancer; GIS (Geographic Information System); Late-stage breast cancer; Clinicopathological factors; Progesterone receptor (PR) positivity

Abstract

Introduction: Breast cancer remains the most common cancer in Malaysia, with 47.9% of cases diagnosed at late stages (stage III and IV). Geographic Information Systems (GIS) are used to analyse spatial data and understand the distribution of diseases. This study aimed to assess the spatial distribution of breast cancer and identify clinicopathological factors associated with metastatic disease (stage IV) among late-stage patients.

Materials and Methods: This retrospective study included female patients with histopathologically confirmed breast cancer. A total of 224 patients from Hospital Pakar Universiti Sains Malaysia (HPUSM), Kelantan, Malaysia were analysed. This study used GIS to assess spatial distribution patterns of breast cancer cases and logistic regression to determine clinicopathological factors associated with metastatic versus locally advanced (stage III) disease.

Results: Spatial analysis revealed significant clustering of late-stage breast cancer cases (NNR: 0.44, Z-score: − 13.18, P < 0.001). Late-stage patients were more likely to reside within 10 km of the nearest available hospitals (75.2%) compared to early-stage patients (45.1%) (χ² (1, N = 224) = 19.47, P < 0.001). Progesterone receptor (PR)-positive status was associated with 90% lower odds to present with stage IV disease rather than stage III compared to PR-negative patients (Adjusted odds ratio (AOR): 0.10, 95% CI: 0.01–0.89, P = 0.039).

Conclusions: Results from our study highlighted areas with a higher concentration of advanced disease and suggested that patients living closer to healthcare facilities may present with more advanced disease. Furthermore, PR positivity was identified as a significant predictor of metastatic disease among late-stage patients. These findings underscore the potential of GIS to guide hotspot-targeted screening initiatives, such as mobile mammography in high-risk areas, and highlight the value of PR status as a marker for risk stratification in late-stage patients, informing both clinical decision-making and targeted public health interventions.