Evidence map›Paper›PMID 42310991›Full record

ArticleEuropean journal of breast health2026

Cost of Breast Cancer Treatment by Comorbidity in Dubai, the United Arab Emirates: A Retrospective Data Analytical Approach.

Meenu Mahak Soni, Noora Almulla, Heba Mohammed Mamdouh

Abstract read
In one paragraph

Article in European journal of breast health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Meenu Mahak SoniDepartment of Health Economics and Insurance Policies, Dubai Health Authority, Dubai, United Arab Emirates.ORCID 0009-0003-0795-5387
Noora AlmullaDepartment of Health Insurance Providers Permits, Dubai Health Authority, Dubai, United Arab Emirates.
Heba Mohammed MamdouhDepartment of Family Health, Alexandria University, Alexandria, Egypt.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Breast cancer is the most common malignancy among women in Dubai, yet the economic burden of its treatment remains understudied. This study aimed to estimate the direct medical costs of breast cancer care in Dubai in 2024 and to examine variations by encounter type, comorbidity burden, and provider setting. Materials and Methods: A retrospective cross-sectional analysis of insurance claims was conducted for January-December 2024. Breast cancer cases were identified using International Classification of Diseases, 10 Results: A total of 8,967 patients (mean age 51.8 years) with 81,248 claims were identified. Outpatient visits constituted 86% of encounters and accounted for 81% of total expenditure (USD 48.7M). Inpatient admissions accounted for 6% of encounters and had the highest mean cost per patient (USD 10,808). The total expenditure was USD 60.0M. Costs increased significantly with comorbidity severity: patients with CCI ≥5 incurred 6.4-fold higher costs compared to those without comorbidities (p<0.0001). Hospital-based care increased costs by 16%, and pharmacy claims contributed an additional 31% to expenditures. Conclusion: Breast cancer treatment in Dubai imposes a substantial economic burden, largely driven by outpatient services, hospital-based care, and medication costs. Comorbidity significantly increases expenditures. These findings highlight the importance of integrated, risk-stratified care pathways and sustainable strategies to optimize resource allocation for breast cancer management in the United Arab Emirates.

Indexed as

breast cancercomorbidityDubaiTreatment costUnited Arab Emirates

Identifiers

PMID42310991
PMCPMC13280605

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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.