ArticleCureus2025
Critical Diagnostic Delay Thresholds in Breast Cancer: A Molecular Subtype-Based Causal Analysis From Saudi Arabia.
Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- Subtype-specific health and economic impact of delayed breast cancer diagnosis during the early COVID-19 pandemic in Belgium: a Markov model analysis.Breast cancer research : BCR · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction Diagnostic delays in breast cancer can significantly affect treatment outcomes. Currently, the causal mechanisms and critical time thresholds remain poorly defined across the different molecular subtypes of breast cancer. We investigated the relationship between diagnostic delays and breast cancer outcomes based on the data from our center, with a focus on identifying actionable intervention points within the diagnostic pathway. Methods We conducted a retrospective cohort study of 802 breast cancer patients treated at King Fahad Specialist Hospital in Qassim Province, Saudi Arabia (2017-2024). Using directed acyclic graphs and mediation analysis, we quantified the causal pathways through which delays impact the outcomes. Markov chain modeling was utilized to determine the molecular subtype-specific critical thresholds where stage migration probability exceeds 10%. Results We found that 589 patients (73.5%) experienced high-risk delays (over two months). Stage migration emerged as the primary mediator, accounting for 67.3% (95% CI: 58.4-76.1%) of the total effect of delays on survival. We have identified multiple critical thresholds across molecular subtypes: 38 days for triple-negative, 52 days for HER2-positive, and 85 days for ER+/PR+/HER2- tumors. Hazard ratios for mortality increased progressively with delay duration, from 1.18 (95% CI: 1.05-1.32) for delays of two weeks to one month to 2.35 (95% CI: 2.06-2.67) for delays that are equal to or more than one year, translating to an average 3.40 life years lost per patient. Conclusions The impact of diagnostic delays on breast cancer outcomes is fundamentally governed by tumor biology, with significant vulnerability thresholds aligned with molecular aggressiveness. Our findings support applying a biologically informed triage system where molecular characteristics determine maximum acceptable diagnostic intervals. Using the suggested approach, we may achieve a better balance in the resource constraints with biological imperatives, and possibly improve survival outcomes without proportional increases in healthcare expenditure.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.