Dataset Information

Patient-reported causes of distress predict disparities in time to evaluation and time to treatment after breast cancer diagnosis.

ABSTRACT:

Background

We examined whether the National Comprehensive Cancer Network distress thermometer (DT), a patient-reported outcome measure, could be used to identify levels and causes of distress associated with racial/ethnic disparities in time to care among patients with breast cancer.

Methods

We identified women aged ≥18 years with stage 0-IV breast cancer who were diagnosed in a single health system between January 2014 and July 2016. The baseline visit was defined as the first postdiagnosis, pretreatment clinical evaluation. Zero-inflated negative binomial (ZINB) regression (modeling non-zero DT scores and DT scores = 0) and logistic regression (modeling DT score ≥ 4, threshold for social services referral) were used to examine associations between baseline score (0 = none to 10 = extreme) and types of stressors (emotional, familial, practical, physical, spiritual) after adjustment for race/ethnicity and other characteristics. Linear regression with log transformation was used to identify predictors of time to evaluation and time to treatment.

Results

A total of 1029 women were included (median baseline DT score = 4). Emotional, physical, and practical stressors were associated with distress in both the ZINB and logistic models (all P < .05). Black patients (n = 258) were more likely to report no distress than Whites (n = 675; ZINB zero model odds ratio, 2.72; 95% CI, 1.68-4.40; P < .001) despite reporting a similar number of stressors (P = .07). Higher DT scores were associated with shorter time to evaluation and time to treatment while being Black and having physical or practical stressors were associated with delays in both (all P < .05).

Conclusions

Patient-reported stressors predicted delays in time to care, but patient-reported levels of distress did not, with Black patients having delayed time to care despite reporting low levels of distress. We describe anticipatory, culturally responsive strategies for using patient-reported outcomes to address observed disparities.

SUBMITTER: Fayanju OM

PROVIDER: S-EPMC7897266 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature

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Publications

Patient-reported causes of distress predict disparities in time to evaluation and time to treatment after breast cancer diagnosis.

Fayanju Oluwadamilola M OM Ren Yi Y Stashko Ilona I Power Steve S Thornton Madeline J MJ Marcom P Kelly PK Hyslop Terry T Hwang E Shelley ES

Cancer 20201111 5

<h4>Background</h4>We examined whether the National Comprehensive Cancer Network distress thermometer (DT), a patient-reported outcome measure, could be used to identify levels and causes of distress associated with racial/ethnic disparities in time to care among patients with breast cancer.<h4>Methods</h4>We identified women aged ≥18 years with stage 0-IV breast cancer who were diagnosed in a single health system between January 2014 and July 2016. The baseline visit was defined as the first po ...[more]

PMID: 33175437

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Project description:BACKGROUND:The National Comprehensive Cancer Network (NCCN) Distress Thermometer (DT) uses a 10-point scale (in which 0 indicates no distress and 10 indicates extreme distress) to measure patient-reported distress. In the current study, the authors sought to examine the relationship between treatment and NCCN DT scores in patients with breast cancer over time. METHODS:The authors included women aged ≥18 years who were diagnosed with stage 0 to stage IV breast cancer (according to the seventh edition of the American Joint Commission on Cancer staging system) at a 3-hospital health system from January 2014 to July 2016. Linear mixed effects models adjusted for covariates including stage of disease, race/ethnicity, insurance, and treatment sequence (neoadjuvant vs adjuvant) were used to estimate adjusted mean changes in the DT score (MSCs) per week for patients undergoing lumpectomy, mastectomy only, and mastectomy with reconstruction (MR). RESULTS:The authors analyzed 12,569 encounters for 1029 unique patients (median score, 4; median follow-up, 67 weeks). Patients treated with MR (118 patients) were younger and more likely to be married, white, and privately insured compared with patients undergoing lumpectomy (620 patients) and mastectomy only (291 patients) (all P < .01). After adjusting for covariates, distress scores were found to decline significantly across all 3 surgical cohorts, with patients undergoing MR found to have both the most preoperative distress and the greatest decline in distress prior to surgery (MSC/week: -0.073 for MR vs -0.031 for lumpectomy vs -0.033 for mastectomy only; P = .001). Neoadjuvant therapy was associated with a longitudinal decline in distress for patients treated with lumpectomy (-1.023) and mastectomy only (-0.964). Over time, ductal carcinoma in situ (-0.503) and black race (-1.198) were found to be associated with declining distress among patients treated with lumpectomy and MR, respectively, whereas divorced patients who were treated with mastectomy only (0.948) and single patients treated with lumpectomy (0.476) experienced increased distress (all P < .05). CONCLUSIONS:When examined longitudinally in consecutive patients, the NCCN DT can provide patient-reported data to inform expectations and guide targeted support for patients with breast cancer.

Project description:BackgroundDisparities in health outcome exist among patients according to socioeconomic status. However, little is known regarding the differences in healthcare experiences across the various levels of income of patients. In a nationally representative US adult population, we evaluate the differences in healthcare experiences based on patient level of income.ObjectivesTo evaluate the differences in patient healthcare experiences based on level of income.Patients and methodsWe identified 68,447 individuals (mean age, 48 ± 18 years; 55% female) representing 176.8 million US adults, who had an established healthcare provider in the 2010-2013 Medical Expenditure Panel Survey cohort. This retrospective study examined the differences in all five patient-reported healthcare experience measures (access to care, provider responsiveness, patient-provider communication, shared decision-making, and patient satisfaction) under the Consumer Assessment of Healthcare Providers and Systems (CAHPS) survey. We examined the relationship between patient income and their healthcare experience.ResultsOverall, 32% of the study participants were high-income earners while 23% had very-low income. Lower income was consistently associated with poor patient report on healthcare experience. Compared with those with high income, very-low-income-earning participants had 1.63 times greater odds (OR 1.63, 95% CI 1.45-1.82) of experiencing difficulty accessing care, had 1.34 times higher odds (OR 1.34, 95% CI 1.25-1.45) of experiencing poor communication, had higher odds (OR 1.68, 95% CI 1.46-1.92) of experiencing delays in healthcare delivery, and were more likely to report poor provider satisfaction (OR 1.48, 95% CI 1.37-1.61).ConclusionLower income-earning patients have poorer healthcare experience in all aspects of access and quality of care. Targeted policies focusing on improving communication, engagement, and satisfaction are needed to enhance patient healthcare experience for this vulnerable population.

Project description:BackgroundAbemaciclib is a CDK4/6 inhibitor used to treat hormone receptor-positive, human epidermal growth factor receptor 2-negative advanced breast cancer. The prognostic value of patient-reported outcomes (PROs) has been minimally explored for treatment outcomes with CDK4/6 inhibitors. The performance of PROs compared with Eastern Cooperative Oncology Group performance status (ECOG-PS) is unknown.Materials and methodsThis study pooled data from single-arm trial, MONARCH 1, and randomized trials, MONARCH 2 and 3. In total, 900 patients initiated abemaciclib and 384 comparator therapy. Pretreatment PRO association with progression-free survival (PFS) was modeled using Cox proportional hazards regression. Prediction performance was assessed via the C-statistic (c). PROs were recorded via the European Organisation for Research and Treatment of Cancer QLQ-C30.ResultsPatient-reported physical function, pain, role function, fatigue, and appetite loss were associated with PFS on univariable and adjusted analysis (p < .05). Physical function (c = 0.55) was most predictive, superior to ECOG-PS (c = 0.54), with multivariable analysis indicating both provide independent information (p < .02). In the pooled randomized arms of MONARCH 2 and 3, the PFS treatment benefit (hazard ratio [95% confidence interval]) of abemaciclib (vs. comparators) was 0.75 (0.57-1.0) for low physical function, compared with 0.48 (0.40-0.59) for intermediate/high (p[interaction] = .01).ConclusionPROs were identified as prognostic factors for PFS in patients initiating abemaciclib, with patient-reported physical function containing independent predictive information beyond ECOG-PS. Low physical function was associated with a decrease in the magnitude of PFS benefit from abemaciclib. PROs should be explored as prognostic, predictive, and stratification factors for clinical use and research trials of CDK4/6 inhibitors.Implications for practiceFor the first time, pretreatment patient-reported outcomes have been shown to be independent prognostic markers for progression-free survival (PFS) in patients diagnosed with hormone receptor-positive, human epidermal growth factor receptor 2-negative (HR+/HER2-) advanced breast cancer treated with abemaciclib. Importantly, patients with low physical function had a smaller PFS benefit from abemaciclib (vs. comparator) than patients with intermediate/high physical function. The present study demonstrates patient-reported outcomes as a simple, effective, inexpensive, and independent prognostic marker for patients with HR+/HER2- advanced breast cancer treated with abemaciclib.

Project description:BackgroundThe UK National Health Service's Predict is a clinical tool widely used to estimate the prognosis of early-stage breast cancer. The performance of Predict for a second primary breast cancer is unknown.MethodsWomen 18 years of age or older diagnosed with a first or second invasive breast cancer between 2000 and 2013 and followed for at least 5 years were identified from the US Surveillance, Epidemiology, and End Results (SEER) database. Model calibration of Predict was evaluated by comparing predicted and observed 5-year breast cancer-specific mortality separately by estrogen receptor status for first vs second breast cancer. Receiver operating characteristic curves and areas under the curve were used to assess model discrimination. Model performance was also evaluated for various races and ethnicities.ResultsThe study population included 6729 women diagnosed with a second breast cancer and 357 204 women with a first breast cancer. Overall, Predict demonstrated good discrimination for first and second breast cancers (areas under the curve ranging from 0.73 to 0.82). Predict statistically significantly underestimated 5-year breast cancer mortality for second estrogen receptor-positive breast cancers (predicted-observed = ‒6.24%, 95% CI = ‒6.96% to ‒5.49%). Among women with a first estrogen receptor-positive cancer, model calibration was good (predicted-observed = ‒0.22%, 95% CI = ‒0.29% to ‒0.15%), except in non-Hispanic Black women (predicted-observed = ‒2.33%, 95% CI = ‒2.65% to ‒2.01%) and women 80 years of age or older (predicted-observed = ‒3.75%, 95% CI = ‒4.12% to ‒3.41%). Predict performed well for second estrogen receptor-negative cancers overall (predicted-observed = ‒1.69%, 95% CI = ‒3.99% to 0.16%) but underestimated mortality among those who had previously received chemotherapy or had a first cancer with more aggressive tumor characteristics. In contrast, Predict overestimated mortality for first estrogen receptor-negative cancers (predicted-observed = 4.54%, 95% CI = 4.27% to 4.86%).ConclusionThe Predict tool underestimated 5-year mortality after a second estrogen receptor-positive breast cancer and in certain subgroups of women with a second estrogen receptor-negative breast cancer.

Project description:PurposeTo evaluate and quantify potential sociodemographic disparities in breast cancer screening, diagnosis, and treatment due to the COVID-19 pandemic, and the use of telemedicine.MethodsWe fielded a 52-item web-based questionnaire from 14 May 2020 to 1 July 2020 in partnership with several U.S.-based breast cancer advocacy groups. Individuals aged 18 or older were eligible for this study if they: (1) received routine breast cancer screening; OR (2) were undergoing diagnostic evaluation for breast cancer; OR (3) had ever been diagnosed with breast cancer. We used descriptive statistics to understand the extent of cancer care delay and telemedicine adoption and used multivariable logistic regression models to estimate the association of sociodemographic factors with odds of COVID-19-related delays in care and telemedicine use.ResultsOf 554 eligible survey participants, 493 provided complete data on demographic and socioeconomic factors and were included in the analysis. Approximately half (n = 248, 50.3%) had a personal history of breast cancer. Overall, 188 (38.1%) participants had experienced any COVID-19-related delay in care including screening, diagnosis, or treatment, and 339 (68.8) reported having at least one virtual appointment during the study period. Compared to other insurance types, participants with Medicaid insurance were 2.58 times more likely to report a COVID-19-related delay in care (OR 2.58, 95% Cl: 1.05, 6.32; p = 0.039). Compared to participants with a household income of less than USD 50,000, those with a household income of USD 150,000 or more were 2.38 (OR 2.38, 95% Cl: 1.09, 5.17; p = 0.029) times more likely to adopt virtual appointments. Self-insured participants were 70% less likely to use virtual appointment compared to those in other insurance categories (OR 0.28, 95% Cl: 0.11, 0.73; p = 0.009).ConclusionsThe COVID-19 pandemic has had a significant impact on breast cancer screening, diagnosis, and treatment, and accelerated the delivery of virtual care. Lower-income groups and patients with certain insurance categories such as Medicaid or self-insured could be more likely to experience care delay or less likely to use telemedicine. Careful attention must be paid to vulnerable groups to insure equity in breast cancer-related service utilization and telemedicine access during and beyond the COVID-19 pandemic.

Dataset Information

Patient-reported causes of distress predict disparities in time to evaluation and time to treatment after breast cancer diagnosis.

Background

Methods

Results

Conclusions

Publications

Patient-reported causes of distress predict disparities in time to evaluation and time to treatment after breast cancer diagnosis.

Similar Datasets

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