Podcast: Dr. Derek Raghavan Has a Remedy to Mitigate Financial Toxicity in Cancer Treatment

2021 ◽  
Keyword(s):  
Cancer Treatment ◽  
Financial Toxicity

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.

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 influence of race on financial toxicity among cancer patients.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 1525-1525
Author(s):  
John Panzone ◽  
Christopher Welch ◽  
Ruben Pinkhasov ◽  
Joseph M Jacob ◽  
Oleg Shapiro ◽  
...  
Keyword(s):  
Cancer Treatment ◽  
Cancer Patients ◽  
Cross Sectional Study ◽  
Financial Toxicity ◽  
Cancer Awareness ◽  
Cross Sectional ◽  
History Of ◽  
Using Data ◽  
National Trends ◽  
To Receive

1525 Background: Studies show that cancer patients and survivors are likely to endure financial toxicity long after being diagnosed. Methods: To examine the influence of race on financial toxicity among individuals with a history of cancer, a US based cross sectional study was conducted using data on 1,328 cancer patients collected from the Health Information National Trends Survey. Multivariable logistic regression analyses were used to analyze the relationship between race and financial toxicity, adjusting for known confounders. Results: Blacks, Hispanics and other races were shown to have a lower rate of insurance compared to Whites. Whites were also more likely to receive cancer treatment than other races (6.1% received no treatment vs 15.0% of Blacks, 17.8% of Hispanics, and 9.7% of other races, p<0.001). Considerably more Whites underwent surgical treatment of their cancer (77%) vs. 60% of Blacks, 55% of Hispanics and 74.2% of other races, p<0.001. Blacks were found to be over 5 times more likely to be denied insurance (OR 5.003, 95% CI 2.451-10.213, p<0.001) and more than twice as likely to be hurt financially than Whites (OR 2.448, 95% CI 1.520-3.941, p<0.001). Other racial minorities were also more than twice as likely to be hurt financially than Whites (OR 2.421, 95% CI 1.248-4.698, p=0.009) (Table). Conclusions: These data suggest that race is significantly associated with increased rates of being hurt financially and being denied insurance due to cancer. Awareness of race inequality should be raised so that equal cancer treatment can be provided, irrespective of race, gender or socioeconomic status.[Table: see text]

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.

Financial toxicity and its associated patient and cancer factors among women with breast cancer in China.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e19402-e19402
Author(s):  
Jingfeng Jing ◽  
Ran Feng ◽  
Xiaojun Zhang ◽  
Ming Li ◽  
Jinnan Gao
Keyword(s):  
Breast Cancer ◽  
Regression Analysis ◽  
Linear Regression ◽  
Cancer Treatment ◽  
Cancer Patients ◽  
Linear Regression Analysis ◽  
Cancer Stage ◽  
Financial Toxicity ◽  
Medical Expenses ◽  
The Cost

e19402 Background: The term “Financial toxicity(FT)” is widely used to describe the distress or hardship patients suffering from the financial burden of cancer treatment[1]. Increased evidences have showed that cancer-associated FT is common and has a negative impact on patients’ mental health, quality and length of life[1,2]. The scale of COmprehensive Score for financial Toxicity-Functional Assessment of Chronic Illness Therapy (COST-FACIT) was used to assess the FT of cancer patients, which has been validated and widely used internationally [3] and China [4]. To our knowledge, little is known about the FT of breast cancer patients in China. The aim of this study is to assess the FT and to investigate patients and cancer characteristic that associated with it in patients in central China. Methods: This was a cross-sectional study among 188 patients with stage 0-III women breast cancer admitted in Bethune hospital in Taiyuan, Shanxi province during January - May 2019. FT was self-reported using the COST-FACIT. Patients’ socio-demographic factors, clinical examination, and cancer treatment were collected from questionnaire and hospital record. The financial concern and coping strategy was self-reported. Factors associated with FT was identified using linear regression analysis. Results: One hundred and sixty-six (88.2%) completed the questionnaire. The COST score ranged 0-40 with a mean of 21.2 (median 22.5, standard deviation 8.1). On multivariate linear regression analysis, older age (β coefficient: 0.19, 95% CI: 0.10-0.29, p<0.001), higher household income (β coefficient: 3000-5000 Yuan: 6.48, 95% CI: 2.78-10.17, p =0.001; ≥ 5000 Yuan: 11.17, 95% CI: 7.25-15.09, p<0.001) were positively associated with COST scores. Advanced cancer stage was the strongest predictor of FT among the cancer characteristics (β coefficient: -1.81, 95% CI: -3.17, -0.46, p=0.009). To cope with the FT, 131 (78.8%) patients decreased non-medical expenses, and 56 (33.7%) reduced or quit treatment. Conclusions: FT was significantly associated with patient’s age, income, and cancer stage. Women having financial concerns after diagnosis were more likely to reduce their non-medical expenses and even quit treatments. Clinicians should take into account the FT levels in all patients and work out appropriate treatment strategies for optimal clinical outcome.

scholarly journals “I’m Dealing With That”: Illness Concerns of African American and White Cancer Patients While Undergoing Active Cancer Treatments

2020 ◽  
pp. 104990912096912
Author(s):  
Salimah H. Meghani ◽  
Kristin Levoy ◽  
Kristin Corey Magan ◽  
Lauren T. Starr ◽  
Liana Yocavitch ◽  
...  
Keyword(s):  
Palliative Care ◽  
African American ◽  
Cancer Treatment ◽  
Cancer Patients ◽  
Risk Mitigation ◽  
Care Delivery ◽  
Care Transitions ◽  
Financial Toxicity ◽  
Cancer Treatments ◽  
Illness Trajectory

Background: National oncology guidelines recommend early integration of palliative care for patients with cancer. However, drivers for this integration remain understudied. Understanding illness concerns at the time of cancer treatment may help facilitate integration earlier in the cancer illness trajectory. Objective: To describe cancer patients’ concerns while undergoing cancer treatment, and determine if concerns differ among African Americans and Whites. Methods: A 1-time, semi-structured qualitative interview was conducted with a purposive subsample of cancer patients participating in a larger study of illness concerns. Eligible patients were undergoing cancer treatments and had self-reported moderate-to-severe pain in the last week. Analysis encompassed a qualitative descriptive approach with inductive thematic analysis. Results: Participants (16 African American, 16 White) had a median age of 53 and were predominantly females (72%) with stage III/IV cancer (53%). Illness concerns were largely consistent across participants and converged on 3 themes: symptom experience (pain, options to manage pain), cancer care delivery (communication, care coordination and care transitions), and practical concerns (access to community and health system resources, financial toxicity). Conclusions: The findings extend the scope of factors that could be utilized to integrate palliative care earlier in the cancer illness trajectory, moving beyond the symptoms- and prognosis-based triggers that typify current referrals to also consider diverse logistical concerns. Using this larger set of concerns aids anticipatory risk mitigation and planning (e.g. care transitions, financial toxicity), helps patients receive a larger complement of support services, and builds cancer patients’ capacity toward a more patient-centered treatment and care experience.

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.

Patient-reported benefit from proposed interventions to reduce financial toxicity during cancer treatment

2021 ◽  
Author(s):  
Emeline M. Aviki ◽  
Bridgette Thom ◽  
Kenya Braxton ◽  
Andrew J. Chi ◽  
Beryl Manning-Geist ◽  
...  
Keyword(s):  
Cancer Treatment ◽  
Financial Toxicity ◽  
Patient Reported

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.

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