Financial Toxicity During Breast Cancer Treatment: A Qualitative Analysis to Inform Strategies for Mitigation

2021 ◽  
pp. OP.21.00182
Author(s):  
Laila A. Gharzai ◽  
Kerry A. Ryan ◽  
Lauren Szczygiel ◽  
Susan Goold ◽  
Grace Smith ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Treatment ◽  
Financial Distress ◽  
Ductal Carcinoma ◽  
Financial Burden ◽  
Unmet Need ◽  
Metastatic Breast ◽  
Financial Toxicity ◽  
Knowledge Gaps ◽  
Treatment Expectations

PURPOSE: Financial toxicity from cancer treatment is a growing concern. Its impact on patients requires refining our understanding of this phenomenon. We sought to characterize patients' experiences of financial toxicity in the context of an established framework to identify knowledge gaps and strategies for mitigation. METHODS: Semistructured interviews with patients with breast cancer who received financial aid from a philanthropic organization during treatment were conducted from February to May 2020. Interviews were transcribed and coded until thematic saturation was reached, and findings were contextualized within an existing financial toxicity framework. RESULTS: Thirty-two patients were interviewed, of whom 58% were non-Hispanic White. The mean age was 46 years. Diagnoses ranged from ductal carcinoma in situ to metastatic breast cancer. Concordant with an established framework, we found that direct and indirect costs determined objective financial burden and subjective financial distress stemmed from psychosocial, behavioral, and material impact of diagnosis and treatment. We identified expectations as a novel theme affecting financial toxicity. We identified knowledge gaps in treatment expectations, provider conversations, identification of resources, and support-finding and offer strategies for mitigating financial toxicity on the basis of participant responses, such as leveraging support from decision aids and allied providers. CONCLUSION: This qualitative study confirms an existing framework for understanding financial toxicity and identifies treatment expectations as a novel theme affecting both objective financial burden and subjective financial distress. Four knowledge gaps are identified, and strategies for mitigating financial toxicity are offered. Mitigating patients' financial toxicity is an important unmet need in optimizing cancer treatment.

Financial Toxicity in Cancer Treatment

2021 ◽  
pp. 616-620
Author(s):  
Victoria Blinder ◽  
Francesca M. Gany
Keyword(s):  
Cancer Treatment ◽  
Emotional Distress ◽  
Low Income ◽  
Financial Distress ◽  
Financial Burden ◽  
Symptom Burden ◽  
Indirect Costs ◽  
Young Female ◽  
Vulnerable Groups ◽  
Financial Toxicity

Financial toxicity is a preventable cancer treatment side effect, encompassing the subjective financial distress and objective financial burden that result from increased spending and decreased earning after diagnosis. The prevalence of financial toxicity has increased with new expensive cancer treatments and insurers gradually shifting costs to patients. Patients with financial toxicity experience increased symptom burden, treatment nonadherence, and cancer-related death. The patients at highest risk are young, female, and nonwhite. For low-income patients, the indirect costs of cancer care can be especially burdensome and include child/elder care, transportation, unpaid work absences or job loss, cancer-related comorbidity treatment costs, and fulfilling dietary requirements. Psychosocial impacts include depression, emotional distress, and reduced quality of life. Patients in palliative care have rated financial distress as more severe than physical, familial, and emotional distress. Interventions and policy changes are needed to ameliorate the effects of financial toxicity, especially for the most vulnerable groups.

scholarly journals Development of Machine Learning Algorithms for the Prediction of Financial Toxicity in Localized Breast Cancer Following Surgical Treatment

2021 ◽  
pp. 338-347
Author(s):  
Chris Sidey-Gibbons ◽  
André Pfob ◽  
Malke Asaad ◽  
Stefanos Boukovalas ◽  
Yu-Li Lin ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Machine Learning ◽  
Cancer Treatment ◽  
Linear Model ◽  
Financial Burden ◽  
Breast Cancer Treatment ◽  
Support Vector ◽  
Financial Toxicity ◽  
Operating Characteristics ◽  
Patient Reported

PURPOSE Financial burden caused by cancer treatment is associated with material loss, distress, and poorer outcomes. Financial resources exist to support patients but identification of need is difficult. We sought to develop and test a tool to accurately predict an individual's risk of financial toxicity based on clinical, demographic, and patient-reported data prior to initiation of breast cancer treatment. PATIENTS AND METHODS We surveyed 611 patients undergoing breast cancer therapy at MD Anderson Cancer Center. We collected data using the validated COmprehensive Score for financial Toxicity (COST) patient-reported outcome measure alongside other financial indicators (credit score, income, and insurance status). We also collected clinical and perioperative data. We trained and tested an ensemble of machine learning (ML) algorithms (neural network, regularized linear model, support vector machines, and a classification tree) to predict financial toxicity. Data were randomly partitioned into training and test samples (2:1 ratio). Predictive performance was assessed using area-under-the-receiver-operating-characteristics-curve (AUROC), accuracy, sensitivity, and specificity. RESULTS In our test sample (N = 203), 48 of 203 women (23.6%) reported significant financial burden. The algorithm ensemble performed well to predict financial burden with an AUROC of 0.85, accuracy of 0.82, sensitivity of 0.85, and specificity of 0.81. Key clinical predictors of financial burden from the linear model were neoadjuvant therapy (βregularized, .11) and autologous, rather than implant-based, reconstruction (βregularized, .06). Notably, radiation and clinical tumor stage had no effect on financial burden. CONCLUSION ML models accurately predicted financial toxicity related to breast cancer treatment. These predictions may inform decision making and care planning to avoid financial distress during cancer treatment or enable targeted financial support. Further research is warranted to validate this tool and assess applicability for other types of cancer.

Machine learning algorithms to predict financial toxicity associated with breast cancer treatment.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. 2047-2047 ◽  
Author(s):  
Chris Sidey-Gibbons ◽  
Malke Asaad ◽  
André Pfob ◽  
Stefanos Boukovalas ◽  
Yu-Li Lin ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Machine Learning ◽  
Decision Making ◽  
Cancer Treatment ◽  
Financial Burden ◽  
Breast Cancer Treatment ◽  
Support Vector ◽  
Financial Toxicity ◽  
Operating Characteristics ◽  
Patient Reported

2047 Background: Financial burden caused by cancer treatment is associated with material loss, distress, and poorer outcomes. Financial resources exist to support patients but objective identification of individuals in need is difficult. Accurate predictions of an individual’s risk of financial toxicity prior to initiation of breast cancer treatment may facilitate informed clinical decision making, reduce financial burden, and improve patient outcomes. Methods: We retrospectively surveyed 611 patients who had undergone breast cancer therapy at MD Anderson Cancer Center to assess the financial impact of their care. All patients were over 18 and received either a lumpectomy or a mastectomy. We collected data using the FACT-COST patient-reported outcome measures alongside other financial indicators including income and insurance status. We extracted clinical and perioperative data from the electronic health record. Missing data were imputed using multiple imputation. We used this data to train and validate a neural network, LASSO-regularized linear model, and support vector machines. Data were randomly partitioned into training and validation samples (3:1 ratio). Analyses were informed by international PROBAST recommendations for developing multivariate predictors. We combined algorithms into a voting ensemble and assessed predictive performance using area under the receiver operating characteristics curve (AUROC), accuracy, sensitivity, and specificity. Results: In our validation sample, 48 of 203 (23.6%) women reported FACT-COST scores commensurate with significant financial burden. The algorithm predicted significant financial burden relating to cancer treatment with high accuracy (Accuracy = .83, AUROC = .82, sensitivity = .81, specificity = .82). Key clinical predictors of financial burden from linear models were neo-adjuvant therapy (βregularized 0.12) and autologous, rather than implant-based, reconstruction (βregularized 0.10). Conclusions: Machine learning models were able to accurately predict the occurrence of financial toxicity related to breast cancer treatment. These predictions may be used to inform decision making and care planning to avoid financial distress during cancer treatment or to enable targeted financial support for individuals. Further research is warranted to further improve this tool and assess applicability for other types of cancer.

Short and long term impact of financial toxicity on quality of life in the Carolina Breast Cancer study.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e18299-e18299 ◽  
Author(s):  
Jennifer Spencer ◽  
Katherine Elizabeth Reeder-Hayes ◽  
Laura C Pinheiro ◽  
Lisa A. Carey ◽  
Andrew F Olshan ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Quality Of Life ◽  
Cancer Treatment ◽  
Cancer Patients ◽  
Cancer Diagnosis ◽  
White Women ◽  
Financial Burden ◽  
Financial Toxicity ◽  
Breast Cancer Patients

e18299 Background: High cancer treatment costs are associated with considerable distress and worse outcomes in cancer patients, a phenomenon known as “financial toxicity”. We examined changes in health-related quality of life (HRQoL) among women experiencing financial toxicity after cancer diagnosis compared to cancer patients without financial toxicity in a racially diverse cohort of breast cancer patients. Methods: HRQoL was self-reported at approximately 5 and 25 months post-diagnosis using the Functional Assessment of Cancer Treatment (FACT-G) in a prospective, population-based, cohort study with oversampling of Black and young (<50 years old) women. Women reported on the financial burden of their breast cancer, including whether they had declined or delayed care due to cost or transportation barriers and whether they lost a job, experienced a reduction in household income, or lost insurance coverage after their cancer diagnosis. We assessed changes in HRQoL from 5 to 25 months according to financial toxicity experience. Results: 2,432 women completed 5- and 25-month HRQoL surveys and were included in analyses. Forty-nine percent were non-Hispanic Black and 51% were non-Hispanic White; other minorities were excluded due to small numbers. Overall, 49% of women reported at least one indicator of financial toxicity (59% Black vs. 39% White). Women who reported any financial toxicity had significantly lower scores on the FACT-G at baseline (75.5 vs 87.2, p<0.001) and reported significantly less improvement in HRQoL from 5- to 25-months than women who did not report financial toxicity (incremental difference: +1.4 vs +3.8, p=.01). Black women reported lower overall HRQoL than White women (p=0.03), but impact of financial toxicity on HRQOL was similar among black and white women in stratified analyses. Conclusions: Financial toxicity is associated with lower HRQoL and with less improvement in HRQoL in the two years following breast cancer diagnosis. [Table: see text]

scholarly journals Hydronephrosis Caused by Metastatic Breast Cancer

2021 ◽  
pp. 378-385
Author(s):  
Hitoshi Sugimoto ◽  
Goshi Oda ◽  
Minato Yokoyama ◽  
Kumiko Hayashi ◽  
Maho Yoshino ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Urinary Tract ◽  
Renal Dysfunction ◽  
Ductal Carcinoma ◽  
Lobular Carcinoma ◽  
Cancer Recurrence ◽  
Metastatic Breast ◽  
Ureteral Stent ◽  
High Care ◽  
Unilateral Case

Breast cancer metastasizes mainly to organs such as bone, lung, and liver, whereas metastases to the peritoneum and urinary tract are rare. Metastasis to the peritoneum or urinary tract may result in renal dysfunction, infection, and painful hydronephrosis. In our hospital, 1,409 breast cancer surgeries were performed between January 2004 and December 2015, and 7 cases of hydronephrosis associated with recurrence were observed. The median age of patients was 69 years (57–79 years). The median time from surgery to diagnosis of hydronephrosis was 47 months (20–70 months). Histology was invasive ductal carcinoma (IDC) in 6 cases and invasive lobular carcinoma (ILC) in 1 case. There were 6 bilateral cases and 1 unilateral case of hydronephrosis. The causes were retroperitoneal metastasis in 5 cases and lymph node metastasis in 2 cases. The hydronephrosis was untreated in 2 cases, and treated with a ureteral stent in 2 cases, nephrostomy in 1 case, and nephrostomy due to ureteral stent failure in 2 cases. The median survival from the onset of hydronephrosis was 12 months (3–57 months). Although the probability of hydronephrosis in breast cancer recurrence was not high, care must be taken to avoid renal dysfunction, infection, or pain, which may require treatment.

scholarly journals 945 Characterization of the immune landscape of malignant pleural effusion composition from patients with metastatic breast carcinoma: a pilot study

2021 ◽  
Vol 9 (Suppl 3) ◽  
pp. A993-A994
Author(s):  
Caddie Dy Laberiano ◽  
Edwin Parra ◽  
Qiong Gan ◽  
Heladio Ibarguen ◽  
Shanyu Zang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Carcinoma ◽  
Ductal Carcinoma ◽  
Cytotoxic T Cells ◽  
Metastatic Breast ◽  
Absolute Number ◽  
List Type ◽  
Clinicopathologic Features ◽  
Metastatic Breast Carcinoma ◽  
Promising Tool

BackgroundBreast cancer(BC) is the second most common cause after lung cancer of malignant pleural effusions(MPEs),in approximately one third of all MPEs.Although,MPEs are relativity easy to be collated are still not well characterized in their cellular compositions. This opens new avenues to characterize the cellular milieu comprising the MPE, as it has the potential to be highly informative about mutational markers and immune response –ultimately guiding targeted therapy and predicting therapeutic outcomes with their study. The proposed study will characterize immune landscape of the cellular composition of MPE from patients with metastatic breast carcinoma and characterize their relationship with clinicopathologic features in these patients.Abstract 945 Figure 1Comparison between the cell block in H-E and mIF expression CK, CD68 and CD3Abstract 945 Figure 2Composite image in mIF expressing 8 markers. In higher magnification is possible to observe the co expression of CK+Ki67+, CK PDL1, CD3+Foxp3+ and CD3+CD8+Abstract 945 Table 1Results: cell phenotypes in percentage in the six cases analyzedAbstract 945 Table 2Clinical data of the six patients. L: left . R: right , BR : Breast cáncer, CRC: Colorrectal cáncer, NE: No evaluable , IDC : Invasive ductal carcinoma , CT: chemotherapy and BT : biotherapy* Last appointment of the patient.MethodsFive microns thickness paraffin cell pellet blocks from six cases randomly selected of breast carcinoma MPE were stained using a quantitative multiplex immunofluorescence(mIF) panel containing 8 markers against pancytokeratin(CK), PD-L1, PD-1, CD3, CD8, Foxp3, CD68, Ki67, and DAPI (figure 1). Representative regions of interest were scanned using a multispectral scanner (Vectra Polaris) in high magnification (20x) to capture different cell populations. Markers co-expression were processed and analyzed using a quantitative image analysis software (InForm). The final results were obtained as absolute number of cells from each phenotype and were characterized with clinicopathologic features.ResultsWe analyzed and stained six breast cancer MPE cases with previously optimized and validated mIF panel for formalin fixed and paraffin embedded (FFPE) tumor tissues against CK, CD3, CD68, CD8, Foxp3, Ki67, PD1 and PD-L1 (figure 2). The median cellular density was 5870.53 cells. Median for each marker: CK+ was presented in 75.9% (between malignant cells and reactive mesothelial cells) in these cells the expression of Ki67 was 8% and PD-L1+ was present in 0.2%.CD3+ was 0.72% and being the cytotoxic T-cells CD3+CD8+ was 12.13% of these cells and it expression for CD3+PD1+ was in 1.14% without concomitant expression for PD-L1. The median of the macrophages CD68+ was 8.1% of the total cells (table 2).ConclusionsmIF is a promising tool to study diverse corporal effusion from different origin. Although more studies are needed, this new perspective can help us to resolve some clues and possible prognosis in advanced stages of BC.ReferenceNicholas D T, Matthew A. S. Diagnosis and Management of Pleural Metastases and Malignant Effusion in Breast Cancer.En: Kirby I B, Edward M C, V. Suzanne K, William J. G. The Breast (Fifth Edition): Elsevier; 2018. P 934.

Predictors of high financial distress in a national, multiethnic sample of patients with cancer.

2021 ◽  
Vol 39 (28_suppl) ◽  
pp. 149-149
Author(s):  
Meera Vimala Ragavan ◽  
Rosie Cunningham ◽  
Andrea Incudine ◽  
Hala Borno ◽  
Thomas Stivers
Keyword(s):  
Cancer Treatment ◽  
Financial Distress ◽  
Financial Support ◽  
Financial Stress ◽  
The United States ◽  
Financial Assistance ◽  
Financial Toxicity ◽  
Targeted Interventions ◽  
Patients With Cancer ◽  
Patient Reported

149 Background: Financial toxicity is characterized by financial burden that patients face. Patients and providers are seldom aware of available resource to help mitigate this growing problem. To date, our understanding of the myriad of financial repercussions of cancer treatment remains limited. Prior published research has largely been single center, thereby limiting generalizability across the United States. This study leveraged a national, multi-ethnic sample of patients who receive financial support services including comprehensive financial assistance, navigation, planning, and a guidebook with relevant resources from a non-profit entity (Family Reach) to evaluate financial stress in during cancer treatment. Methods: Patients were identified for study participation if they received at least one financial support resource from Family Reach between 1/1/2020-6/30/2020. An 11-item survey was sent electronically to all eligible participants who were given a one-month time frame to complete. A multivariate model was employed to identify sociodemographic predictors of high financial distress. Results: A total of 832 patients were contacted, of whom 330 (40%) completed the survey. Demographic information is included in table. Patient reported financial distress in the prior week was high, with 46% of patients reporting a distress level of seven or higher on a ten-point scale. In a multivariate regression, Hispanic/Latinx ethnicity was associated with a higher distress rating and higher patient reported financial stress. Lower annual household income was associated with lower reports of feeling in financial control, lower reports of meeting monthly expenses, and higher reports of financial stress. Conclusions: Patient-reported financial distress was high in a national sample of patients with cancer who had utilized at least one financial resource provided by Family Reach. Hispanic ethnicity and Lower Annual Income were predictors of higher patient-reported financial distress. Larger samples are needed to confirm these patterns. Delivery systems should develop targeted interventions, including referrals to organizations providing financial assistance, for patient populations at high risk for financial toxicity. [Table: see text]

The Significance of Patient-Reported Outcomes for Metastatic Breast Cancer Patients

2022 ◽  
Author(s):  
Larissa Elisabeth Hillebrand ◽  
Ulrike Söling ◽  
Norbert Marschner
Keyword(s):  
Breast Cancer ◽  
Decision Making ◽  
Metastatic Breast Cancer ◽  
Cancer Treatment ◽  
Patient Reported Outcomes ◽  
Metastatic Breast ◽  
Treatment Decision ◽  
Breast Cancer Patients ◽  
Treatment Decision Making ◽  
Patient Reported

Background: Breast cancer is still the most common malignancy in women worldwide. Once metastasized, breast cancer treatment primarily aims at reducing symptom burden, thereby trying to maintain and improve a patient´s quality of life (QoL), delaying disease progression, and prolonging survival. Curing the disease is not possible in the palliative setting. To better understand metastatic breast cancer patients, their symptoms and wishes, which are important for treatment-decision making and outcome, patient-reported outcomes (PROs) are of great importance, giving an impression of what really matters to and concerns a patient. Summary: Many advances have been made to implicate PROs in clinical trials, non-interventional studies, registries, and clinical routine care of metastatic breast cancer. For example, large phase III trials like PALOMA-3 (NCT01942135), MONALEESA-7 (NCT02278120), HER2CLIMB (NCT02614794), and KEYNOTE-119 (NCT02555657) trials implemented PROs in their trial design to assess the QoL of their trial patients. Also, non-interventional studies on metastatic breast cancer, like e.g., the NABUCCO study (IOM-02240), and prospective non-interventional, multicenter registries e.g., the tumor registry breast cancer (NCT01351584) or the breast cancer registry platform OPAL (NCT03417115), have implemented PROs to assess QoL during the anti-cancer treatment periods of the patients. Key Message: Using PROs in metastatic breast cancer can support shared treatment-decision making and management of symptoms, eventually leading to an improvement in QoL. Progressively, regulatory authorities take PROs into consideration for the approval of new drugs. Hence, the implication of PROs in cancer treatment, and especially in MBC, is of significant value.

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