| Literature DB >> 23840209 |
Ketan Sharma1, Ainhoa Costas, Ruth Damuse, Jean Hamiltong-Pierre, Jordan Pyda, Cecilia T Ong, Lawrence N Shulman, John G Meara.
Abstract
Background. In Haiti, breast cancer patients present at such advanced stages that even modern therapies offer modest survival benefit. Identifying the personal, sociocultural, and economic barriers-to-care delaying patient presentation is crucial to controlling disease. Methods. Patients presenting to the Hôpital Bon Sauveur in Cange were prospectively accrued. Delay was defined as 12 weeks or longer from initial sign/symptom discovery to presentation, as durations greater than this cutoff correlate with reduced survival. A matched case-control analysis with multivariate logistic regression was used to identify factors predicting delay. Results. Of N = 123 patients accrued, 90 (73%) reported symptom-presentation duration and formed the basis of this study: 52 patients presented within 12 weeks of symptoms, while 38 patients waited longer than 12 weeks. On logistic regression, lower education status (OR = 5.6, P = 0.03), failure to initially recognize mass as important (OR = 13.0, P < 0.01), and fear of treatment cost (OR = 8.3, P = 0.03) were shown to independently predict delayed patient presentation. Conclusion. To reduce stage at presentation, future interventions must educate patients on the recognition of initial breast cancer signs and symptoms and address cost concerns by providing care free of charge and/or advertising that existing care is already free.Entities:
Year: 2013 PMID: 23840209 PMCID: PMC3687503 DOI: 10.1155/2013/206367
Source DB: PubMed Journal: J Oncol ISSN: 1687-8450 Impact factor: 4.375
Potential risk factors for delayed patient presentation (barriers-to-care).
| Personal | Sociocultural | Economic |
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| Age | Breast cancer awareness | Fear of cost of travel |
Note: variables in bold were shown to predict patient delay in the multivariate logistic regression analysis (see Figure 2).
Barriers-to-care survey: did any of the following prevent you from coming to clinic sooner?
| Survey response | Patients without delay | Patients with delay |
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| I had or knew someone who had a bad experience at a hospital before | 0 (0%) | 0 (0%) | n/a |
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| I did not know I needed to see a doctor and thought it would go away | 10 (20%) | 13 (34%) | 0.11 |
| I did not know where an appropriate medical facility was | 1 (2%) | 2 (5%) | 0.38 |
| I was too busy at my home or job | 0 (0%) | 1 (3%) | 0.24 |
| I was afraid of treatments, including potentially losing my breast | 0 (0%) | 2 (5%) | 0.10 |
| I did not want anyone knowing that I had a mass | 0 (0%) | 1 (3%) | 0.24 |
| I tried another treatment or visited another healer first | 0 (0%) | 1 (3%) | 0.24 |
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| I was afraid it might be cancer | 0 (0%) | 2 (5%) | 0.10 |
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| It was too expensive to travel to the clinic | 0 (0%) | 0 (0%) | n/a |
| The clinic was too far away for me to travel to | 0 (0%) | 0 (0%) | n/a |
Figure 1HBCI patient flowchart. Note: patients in red boxes reported symptom-presentation interval and formed the basis of our study.
Patient characteristics.
| Presentation not delayed | Presentation delayed |
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| Marital status | |||
| Single, divorced, widowed | 18 (35%) | 17 (45%) | 0.48 |
| Married | 21 (40%) | 15 (39%) | |
| Not reported | 13 (25%) | 6 (16%) | |
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| Employment status | |||
| Unemployed | 30 (58%) | 28 (74%) | 0.29 |
| Employed | 20 (38%) | 9 (24%) | |
| Not reported | 2 (4%) | 1 (3%) | |
| Prior history of breast cancer | |||
| None | 47 (90%) | 36 (95%) | 0.22 |
| Yes | 0 | 1 (3%) | |
| Not reported | 5 (10%) | 1 (3%) | |
| Time to reach clinic (hrs)1 | 3 (3-4) | 3 (3-4) | 0.71 |
| Method of reaching clinic | |||
| Walk | 0 (0%) | 1 (3%) | |
| Car | 3 (7%) | 3 (8%) | 0.53 |
| Public transportation | 40 (89%) | 32 (86%) | |
| Not reported | 2 (4%) | 1 (3%) |
1Median (interquartile range).
Figure 2Logistic regression analysis. Note: univariate logistic regression for covariates not meeting the inclusion criteria into the multivariate model is shown for reference. Only covariates that exhibit significance in the multivariate analysis are considered as independent risk factors for delayed patient presentation (barriers-to-care). Multivariate logistic regression model: c statistic = 0.807, concordant pair percentage = 80.7%, discordant pair percentage = 19.3%, Hosmer-Lemeshow Goodness-of-Fit test: χ 2 = 3.95, P = 0.86 (df = 8).