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Travel, Treatment Choice, and Survival Among Breast Cancer Patients: A Population-Based Analysis.

ABSTRACT: Background: Travel distance to care facilities may shape urban-rural cancer survival disparities by creating barriers to specific treatments. Guideline-supported treatment options for women with early stage breast cancer involves considerations of breast conservation and travel burden: Mastectomy requires travel for surgery, whereas breast-conserving surgery (BCS) with adjuvant radiation therapy (RT) requires travel for both surgery and RT. This provides a unique opportunity to evaluate the impact of travel distance on surgical decisions and receipt of guideline-concordant treatment. Materials and Methods: We included 61,169 women diagnosed with early stage breast cancer between 2004 and 2013 from the Surveillance Epidemiology and End Results (SEER)-Medicare database. Driving distances to the nearest radiation facility were calculated by using Google Maps. We used multivariable regression to model treatment choice as a function of distance to radiation and Cox regression to model survival. Results: Women living farthest from radiation facilities (>50 miles vs. <10 miles) were more likely to undergo mastectomy versus BCS (odds ratio [OR]: 1.48, 95% confidence interval [CI]: 1.22-1.79). Among only those who underwent BCS, women living farther from radiation facilities were less likely to receive guideline-concordant RT (OR: 1.72, 95% CI: 1.32-2.23). These guideline-discordant women had worse overall (hazards ratio [HR]: 1.50, 95% CI: 1.42-1.57) and breast-cancer specific survival (HR: 1.44, 95% CI: 1.29-1.60). Conclusions: We report two breast cancer treatments with different clinical and travel implications to show the association between travel distance, treatment decisions, and receipt of guideline-concordant treatment. Differential access to guideline-concordant treatment resulting from excess travel burden among rural patients may contribute to rural-urban survival disparities among cancer patients.

SUBMITTER: Longacre CF

PROVIDER: S-EPMC7957915 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundThe number of elderly patients diagnosed with breast cancer is increasing worldwide. However, treatment decisions for these patients are highly variable. Although researchers have identified the effects of surgery, radiotherapy, endocrine therapy, and chemotherapy in elderly patients with breast cancer, clinicians still struggle to make appropriate decisions for these patients.MethodsWe identified 75,525 female breast cancer patients aged ≥ 70 years in the Surveillance, Epidemiology, and End Results (SEER) database treated between January 1, 2010, and December 31, 2016. The patients were further divided into training and testing cohorts. The cumulative occurrence of breast cancer-specific deaths (BCSDs) and other cause-specific deaths (OCSD) was calculated using the cumulative incidence function. In the univariate analysis, risk factors were screened using the Fine-Gray model. In the multivariate analysis for competing risks, the sub-distribution hazard ratio with a 95% confidence interval for each independent predictor associated with BCSD was calculated for the construction of nomograms. Based on the above analyses, a competing risk nomogram was constructed to predict the probability of BCSD in the 1st, 3rd, and 5th years after treatment. During validation, the concordance index (C-index) was selected to quantify the predictive ability of the competing risk model.ResultsA total of 33,118 patients were included in this study, with 24,838 in the training group and 8,280 in the testing group. Age, race, marital status, cancer grade, tumor stage, node stage, estrogen receptor status, progesterone receptor status, human epidermal growth factor receptor--2 status, and treatment including surgery, radiation, and chemotherapy were used to establish a nomogram. The C-index of 0.852 (0.842-0.862) in the training cohort and 0.876 (0.868-0.892) in the testing cohort indicated satisfactory discriminative ability of the nomogram. Calibration plots showed favorable consistency between the nomogram predictions and actual observations in both the training and validation cohorts.ConclusionsOur study identified independent predictors of BCSD in elderly patients with breast cancer. A prognostic nomogram was developed and validated to aid clinical decision-making.

Project description:BackgroundThe relation between breast cancer molecular subtype and survival has been studied in several jurisdictions, but limited information is available for Ontario. The aim of this study was to determine breast cancer survival by molecular subtype and to assess the effect on survival of selected demographic and tumour-based characteristics.MethodsWe extracted 29 833 breast cancer cases (in 26 538 girls and women aged ≥ 15 yr) diagnosed between 2010 and 2012 from the Ontario Cancer Registry. Cancers were categorized into 4 molecular subtypes: 1) luminal A (estrogen-receptor-positive and/or progesterone-receptor-positive [ER+ and/or PR+] and negative for human epidermal growth factor receptor 2 [HER2-]), 2) luminal B (ER+ and/or PR+/HER2+), 3) HER2-enriched (ER- and PR-/HER2+) and 4) triple-negative (ER- and PR-/HER2-). We estimated associations with predictor variables (age, stage at diagnosis, histologic type, comorbidity and place of residence [urban or rural]) using a multivariate Cox proportional hazards model. Likelihood ratio testing was used to evaluate differences in risk of death.ResultsLuminal A was the most commonly diagnosed subtype (59.0%) and had the greatest survival, whereas triple-negative had the poorest survival. For all subtypes, a dose-response effect was observed between the hazard of death and age and stage at diagnosis, with the greatest effect found for the HER2-enriched subtype (age: hazard ratio [HR] 7.87 [95% confidence interval (CI) 3.68-11.81]; stage at diagnosis: HR 37.71 [95% CI 34.64-41.27]). Moderate comorbidity (Charlson Comorbidity Index score 1 or 2) was associated with increased risk of death for triple-negative cancers (HR 2.42 [95% CI 1.36-4.31]), and severe comorbidity (Charlson Comorbidity Index score ≥ 3) increased the risk for all molecular subtypes.InterpretationThe results indicate the importance of including molecular subtype, along with age, stage at diagnosis and comorbidity, in assessing breast cancer survival. They highlight the need to address outcomes related to hormone-receptor-negative cancers, for which survival lags behind that for hormone-receptor-positive cancers.

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Travel, Treatment Choice, and Survival Among Breast Cancer Patients: A Population-Based Analysis.

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