Abstract Introduction: Women living in disadvantaged neighborhoods consistently having worse breast cancer survival. Recent studies have identified that disparities by neighborhood disadvantage persist after controlling for patient, tumor, and National Comprehensive Cancer Network-guideline concordant treatment. This suggests unaccounted mechanisms by which neighborhood disadvantage “gets under the skin” to impact to shorter breast cancer survival. Methods: Women with stage 0-3 breast cancer between 1998-2005 were enrolled in a clinical trial for stress management 2-10 weeks post-surgery and before initiating adjuvant treatment. At baseline, women provided an evening-time serum cortisol sample and were administered a structured clinical interview of anxiety symptoms (Hamilton Anxiety Rating Scale; HAM-A). Of the 240 women who enrolled in the study and completed baseline procedures, home addresses were provided by 225 women (93.8%). The addresses were used to determine the Area Deprivation Index (ADI), a validated measure of neighborhood disadvantage. Women were categorized as low (1-3) versus high (4-10) ADI. Linear regression analysis was used to assess the relationship between ADI and serum cortisol and logistic regression to assess whether ADI group predicted the presence of clinically significant anxiety per the HAM-A. Cox regression analysis was used to determine predictors of breast cancer-specific survival. Results: The average age of our population was 50.4 years old (range 23-70 years) and the majority were non-Hispanic White (63.6%). Most patients had stage 1 (37.8%) or 2 (38.2%) disease. The majority lived in advantaged neighborhoods (low ADI, 77.8%). On the HAM-A, 46.8% of women reported clinically significant anxiety symptoms. When controlling for age, stage, and type of surgery, women with a high ADI had higher cortisol levels than women in with a low ADI (Beta=.19, t(117)=2.18, p=.031). Moreover, accounting for age, stage, and type of surgery, women with a high ADI were nearly two times as likely to have clinically significant anxiety symptoms in the HAM-A clinical interview (OR 1.99, 95%CI 1.01, 3.90, p=.046). Moreover, after controlling for study condition (stress intervention vs. control), age, stage, Black race, and treatment, women with living in neighborhoods with an increasing ADI (disadvantaged neighborhoods) had shorter 5-year breast cancer-specific survival (HR=.096 95%CI 0.02, 0.64) compared to women living in neighborhoods with a lower ADI (advantaged neighborhoods). Conclusion: This study identified that neighborhood disadvantage is significantly associated with higher levels of cortisol, clinical anxiety, and shorter 5-year breast cancer-specific survival. Future studies need to evaluate stress pathways as a potential mechanism by which neighborhood disadvantage impacts breast cancer-specific survival. Table 1. Multiple Regression Illustrating Relationship between ADI and Serum Cortisol. Table 2. Logistic Regression Illustrating Relationship between ADI and Anxiety on HAM-A Clinical Interview. Citation Format: Neha Goel, Molly Ream, Alexandra Hernandez, Estaez Clarke, Daniel S. O’Neil, Michael Antoni. Impact of Neighborhood Disadvantage on Biological and Clinical Indicators of Anxiety and Breast Cancer Survival [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr PD8-09.
Abstract Introduction In the South African Breast Cancer and HIV Outcomes (SABCHO) study, we previously found that breast cancer patients living with HIV and treated with neoadjuvant chemotherapy achieve lower rates of complete pathologic response than patients without HIV. We now assess the impact of comorbid HIV on receipt of timely and complete neoadjuvant and adjuvant chemotherapy. Materials and Methods Since June 2015, the SABCHO study has collected data on women diagnosed with breast cancer at 6 South African hospitals. We selected a sample of participants with stages I-III cancer who received ≥2 doses of neoadjuvant or adjuvant chemotherapy. Data on chemotherapies prescribed and received, filgrastim receipt, and laboratory values measured during treatment were captured from patients’ medical records. We calculated the mean relative dose intensity (RDI) for all prescribed chemotherapies. We tested for association between full regimen RDI and HIV status, using linear regression to control for demographic and clinical covariates, and for association of HIV with laboratory abnormalities. Results The 166 participants living with HIV and 159 without HIV did not differ in median chemotherapy RDI: 0.89 (interquartile range (IQR) 0.77-0.95) among those living with HIV and 0.87 (IQR 0.77-0.94) among women without HIV. Patients living with HIV experienced more grade 3+ anemia and leukopenia than those without HIV (anemia: 10.8% vs. 1.9%, P = .001; leukopenia: 8.4% vs. 1.9%, P = .008) and were more likely to receive filgrastim (24.7% vs. 10.7%, P = .001). Conclusions HIV status did not impact neoadjuvant or adjuvant chemotherapy RDI, although patients with breast cancer living with HIV experienced more myelotoxicity during treatment.
Bing–Neel syndrome is a rare manifestation of Waldenström macroglobulinemia characterized by lymphoplasmacytic cells’ infiltration into the central nervous system. We present a case of a 74-year-old patient with a known diagnosis of Waldenström macroglobulinemia and newly depressed consciousness. Flow cytology of his cerebral spinal fluid demonstrated a lambda light chain-restricted population of B-cells consistent with a CD5+ CD10+ B-cell lymphoma. Magnetic resonance imaging suggested involvement of the left optic nerve sheath and the bilateral orbital and parietal parenchyma and leptomeninges. He was diagnosed with Bing–Neel syndrome and treated with intrathecal liposomal cytarabine, intravenous high-dose methotrexate, and rituximab without improvement. Subsequently, he started treatment with ibrutinib 560 mg daily and concurrent rituximab. Within three months, he showed clinical and radiologic improvement. The patient has continued on ibrutinib and has now been stable for over 36 months. This represents the longest reported period of successful treatment of Bing–Neel syndrome with ibrutinib.
Abstract 81 Purpose Surgery is the mainstay of treatment for nonmetastatic breast cancer. Little is known about the quality of breast surgical care in sub-Saharan Africa. Research at the Butaro Cancer Center of Excellence (BCCOE), Rwanda’s first public cancer center, has suggested that access to timely surgery is inadequate, but barriers have not been systematically examined. The aim of the current study was to gain an understanding of the barriers to breast cancer surgery among patients who were diagnosed at BCCOE by investigating delays and interruptions in care. Methods We used a standardized chart abstraction instrument to collect demographic, treatment, and outcome data as of November 2017 for all patients who were diagnosed with breast cancer at BCCOE in 2014 and 2015. We recorded all visits and treatments received until surgery, disease progression, or loss to follow-up for all patients with stage I to III breast cancer. Results During 2014 and 2015, 91 patients were diagnosed with stage I to III breast cancer and were treated with curative intent—67 patients (74%) underwent surgery, with 22 undergoing surgery at BCCOE and 45 elsewhere. Of the 24 patients with no surgery, 16 were lost to follow-up and eight experienced disease progression before surgical evaluation. Median time from diagnosis to surgery was 103 days (range, 30 to 826 days) for patients without neoadjuvant chemotherapy (NAC) and 268 days (range, 108 to 794 days) for patients with NAC. We defined surgical delays as > 120 days from diagnosis without NAC or > 365 days from diagnosis if NAC was administered. Of the 67 patients who had surgery, 26 patients (39%) experienced delays. When documented, reasons for delay included patient factors, such as social and/or financial issues (n = 5), seeking alternate treatment (n = 2), refusing referral to Kigali (n = 3), or any surgery (n = 1); system factors, such as surgeon nonavailability (n = 1); and changes in clinical status, such as pregnancy (n = 5), treatment-associated adverse events (n = 4), or the need for a second surgical opinion (n = 2). Unexplained failure to complete the initial surgical referral (n = 5) and missed NAC treatment appointments (n = 6) were frequent contributors. Some patients had multiple reasons for delay. For five patients, there was no documented explanation. Conclusion We observed high rates of loss to follow-up, surgical delays, and lapses in care at the point of surgical referral. Identification of the barriers to completing referrals could guide strategies for improving access to timely surgery. Efforts are needed to address social and financial barriers and explore patients’ refusals to undergo surgery. AUTHORS' DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST No COIs from the authors.
522 Background: South African (SA) women living with comorbid estrogen receptor positive (ER+) breast cancer (BC) and HIV have higher mortality than other SA women with ER+ BC. We aimed to evaluate for associations between HIV status, psychosocial factors, and adjuvant endocrine therapy (AET) adherence as a potential contributor to this disparity. Methods: From Chris Hani Baragwanath Hospital, Johannesburg, we enrolled adult women with stage I-III ER+ BC in remission and currently prescribed tamoxifen or an aromatase inhibitor to a prospective cohort study. We performed AET pill counts at enrollment, 12 weeks, and 24 weeks, and calculated adherence ratios from the difference in pills between visits divided by the number of days between visits. Women completed questionnaires on sources of social support, beliefs about medication, health literacy, and self-efficacy at enrollment and questionnaires about mental health (depression, anxiety, and acute stress) symptom burden and AET-related side effects at the 12- and 24-week visits. We also collected household wealth data and clinical data on BC and HIV. AET adherence ratios were compared between women with and without comorbid HIV using Wilcoxon rank sum testing. We also used structural equation modeling techniques to refine and evaluate an a priori model of AET adherence with latent variables for mental health, socioeconomic (SES) status, healthcare savvy, and AET side effect burden and subgroup analyses of the resulting model in women with and without HIV. Results: Between April 26, 2022, and July 11, 2023, we enrolled 239 women, 63 (26.4%) of whom had co-morbid HIV. Adherence data was available from 106 women at 12 and 24 weeks, from 22 women at 12 weeks only, and from 111 women at 24 weeks only. Comparing women with and without HIV, median AET adherence ratio was 0.88 vs 0.89, respectively (p = 0.65). Our final model of AET adherence achieved good fit (comparative fit index = 0.96, RMSEA 90% CI: 0.03-0.06). In the full cohort, SES quintile showed a trend towards association with AET adherence (β 0.02, SE 0.01, p=0.09); mental health, healthcare savvy, and side effect burden latent variables were not significantly associated with adherence. In the subgroup of women living with HIV, SES quintile (β 0.04, SE 0.02, p=0.08) and mental health (β -0.02, SE 0.01, p=0.10) showed trends toward association with adherence; these relationships did not persist for women without HIV. Conclusions: HIV status is not predictive of AET adherence among SA women with ER+ BC, but in women with both diagnoses, decreasing SES status and increasing mental health symptoms trended towards an association with decreased adherence. Interventions to improve the mental health of SA breast cancer patients living with HIV may promote AET adherence.
Abstract Background Breast cancer survival in South Africa is low, but when diagnosed with breast cancer, many women in South Africa also have other chronic conditions. We investigated the impact of multimorbidity (≥ 2 other chronic conditions) on overall survival among women with breast cancer in South Africa. Methods Between 1 July 2015 and 31 December 2019, we enrolled women newly diagnosed with breast cancer at six public hospitals participating in the South African Breast Cancer and HIV Outcomes (SABCHO) Study. We examined seven chronic conditions (obesity, hypertension, diabetes, HIV, cerebrovascular diseases (CVD), asthma/chronic obstructive pulmonary disease, and tuberculosis), and we compared socio-demographic, clinical, and treatment factors between patients with and without each condition, and with and without multimorbidity. We investigated the association of multimorbidity with overall survival using multivariable Cox proportional hazard models. Results Of 3,261 women included in the analysis, 45% had multimorbidity; obesity (53%), hypertension (41%), HIV (22%), and diabetes (13%) were the most common individual conditions. Women with multimorbidity had poorer overall survival at 3 years than women without multimorbidity in both the full cohort (60.8% vs. 64.3%, p = 0.036) and stage groups: stages I–II, 80.7% vs. 86.3% ( p = 0.005), and stage III, 53.0% vs. 59.4% ( p = 0.024). In an adjusted model, women with diabetes (hazard ratio (HR) = 1.20, 95% confidence interval (CI) = 1.03–1.41), CVD (HR = 1.43, 95% CI = 1.17–1.76), HIV (HR = 1.21, 95% CI = 1.06–1.38), obesity + HIV (HR = 1.24 95% CI = 1.04–1.48), and multimorbidity (HR = 1.26, 95% CI = 1.13–1.40) had poorer overall survival than women without these conditions. Conclusions Irrespective of the stage, multimorbidity at breast cancer diagnosis was an important prognostic factor for survival in our SABCHO cohort. The high prevalence of multimorbidity in our cohort calls for more comprehensive care to improve outcomes for South African women with breast cancer.
Patient-reported outcome measures (PROM) for monitoring treatment toxicity improve quality of life (QoL) and clinical outcomes. However, no such PROMs exist for sub-Saharan African cancer patients. We aimed to validate the Patient Reported Symptoms-South Africa (PRS-SA) survey, a novel PROM for measuring distress and chemotherapy-related symptoms in South African cancer patients. We enrolled patients at the oncology clinic at Charlotte Maxeke Hospital, Johannesburg. At three separate visits, participants simultaneously completed the PRS-SA survey and several previously validated questionnaires. We constructed a receiver operator characteristics curve for distress levels predicting a Hospital Anxiety and Depression Scale (HADS) score ≥15. We evaluated construct validity for symptom items by comparing severity to the EORTC Core Quality of Life Questionnaire (QLQ-C30) summary score (Pearson correlation tests) and ECOG performance status (Mann-Whitney U tests). We assessed symptom item responsiveness by comparing change in severity to change in QLQ-C30 summary score and comparing standardized mean scores with negative, no, or positive change on the Global Impression of Change (GIC) questionnaire (Jockheere-Terpstra trend test). Overall, 196 participants with solid tumors completed instruments. A distress score of 4 had 82% sensitivity and 55% specificity for clinical depression/anxiety. All symptom items showed construct validity by association with either QLQ-C30 score or performance status (highest
6541 Background: Oral anticancer drug (OACD) prescriptions require coordination between clinicians, payers, specialty pharmacies, and financial assistance (FA) groups, which may delay patient receipt of the drug. Factors associated with delay in receipt of OACDs are unknown. Methods: We prospectively collected data on all new OACD prescriptions (RXs) from the medical oncology practice at the Herbert Irving Comprehensive Cancer Center from 1/1/2018 to 12/1/2018. We collected patient demographic, insurance and clinical information; date of prescription; date of drug delivery; and staff interactions with payers and FA groups. Federal Drug Association (FDA) labels and Micromedex were reviewed for initial drug approval dates, approved indications and average wholesale price. We used multivariable linear and logistic regression to determine factors associated with number of days from prescription to receipt of OACD. Results: During the study period 510 OACD RXs were evaluated. Of these, 84 (16%) were never filled. The most common OACDs were capecitabine (90, 18%), abiraterone (45, 9%), palbociclib (35, 7%) and osimertinib (28, 6%). Of 426 filled RXs, the median time from prescription to receipt was 8 days (IQR 5-13), with 193 RXs (46%) received in ≤7 days, 145 (34%) in 8-14 days and 65 (15%) in 14-28 days, and 23 (5%) at > 28 days. Linear regression showed time to receipt of OACD (log transformed) was associated with having commercial primary insurance (p = 0.02), pursing FA (p = < 0.001), RX of a drug approved by the FDA < 2 years earlier (p = 0.008), drugs without an approved indication for the primary tumor (p = 0.03) and estimated drug cost (p = 0.002). The other included covariates, patient age and prior authorization, were not associated with time to receipt. Logistic regression comparing receipt at ≤14 versus > 14 days found association with FA (OR 3.17; 95%CI 1.78-5.65), FDA approval within 2 years (OR 3.52; 95%CI 1.31-9.45) and off-label use (OR 2.30; 95%CI 1.18-4.50). Conclusions: Over 20% of new OACDs were received 14 days or longer from the date of RX. Financial and insurance related factors; and more expensive and recently approved drugs were associated with longer delays in receipt of therapy. Policy changes to improve the timeliness of OACD access are needed.
Abstract Background Breast cancer survival in sub-Saharan Africa (SSA) is low, but when diagnosed with breast cancer, many women in SSA also have other chronic conditions. We investigated the impact of multimorbidity (≥ 2 other chronic conditions) on overall survival among women with breast cancer in South Africa. Methods Between July 1, 2015 and December 31, 2019, we enrolled women newly diagnosed with breast cancer at six public hospitals participating in the South African Breast Cancer and HIV Outcomes (SABCHO) Study. We examined seven chronic conditions (obesity, hypertension, diabetes, HIV, cerebrovascular diseases (CVD), asthma/chronic obstructive pulmonary disease, and tuberculosis), and we compared socio-demographic, clinical, and treatment factors between patients with and without each condition, and with and without multimorbidity. We investigated the association of multimorbidity with overall survival using multivariable Cox proportional hazard models. Results Of 3,261 women included in the analysis, 45% had multimorbidity; obesity (53%), hypertension (41%), HIV (22%), and diabetes (13%) were the most common individual conditions. Women with multimorbidity had poorer overall survival at 3 years than women without multimorbidity in both the full cohort (60.8% vs. 64.3%, P = 0.036) and stage groups: stages I-II, 80.7% vs. 86.3% (p = 0.005), and in stage III, 53.0% vs. 59.4% (p = 0.024). In an adjusted model, women with diabetes (hazard ratio (HR) = 1.20, 95% confidence interval (CI) = 1.03–1.41), CVD (HR = 1.43, 95% CI = 1.17–1.76), HIV (HR = 1.21, 95% CI = 1.06–1.38), obesity + HIV (HR = 1.24 95% CI = 1.04–1.48), and multimorbidity (HR = 1.26, 95% CI = 1.13–1.40) had poorer overall survival than women without these conditions. Conclusions Irrespective of stage, multimorbidity at breast cancer diagnosis was an important prognostic factor for survival in our SABCHO cohort. The high prevalence of multimorbidity in our cohort calls for more comprehensive care to improve outcomes for South African women with breast cancer.
'%3e%3cpath fill='%23001489' d='M0 0v6h9V0z'/%3e%3cpath fill='%23e03c31' d='M0 0v3h9V0z'/%3e%3cg stroke='%23fff' stroke-width='2'%3e%3cpath id='d' d='m0 0 4.5 3L0 6m4.5-3H9'/%3e%3cuse xlink:href='%23b' stroke='%23ffb81c' clip-path='url(%23c)'/%3e%3c/g%3e%3cuse xlink:href='%23d' fill='none' stroke='%23007749' stroke-width='1.2'/%3e%3c/g%3e%3c/svg%3e)
'%3e%3cg id='b'%3e%3cpath id='a' fill='%23E5BE01' d='M116.1 0 35.692 4.699l76.452 25.35L33.26 13.777l67.286 44.273L28.56 21.915l53.534 60.18-60.18-53.534 36.135 71.985L13.777 33.26l16.272 78.884-25.35-76.452L0 116.1-1-1z'/%3e%3cuse xlink:href='%23a' transform='scale(1 -1)'/%3e%3c/g%3e%3cuse xlink:href='%23b' transform='scale(-1 1)'/%3e%3ccircle r='34.3' fill='%23E5BE01' stroke='%2300A1DE' stroke-width='3.4'/%3e%3c/g%3e%3c/svg%3e)