Metastatic Breast Cancer Treatment Planning
Study Details
Study Description
Brief Summary
The overarching objective of this study is to close clinical knowledge and performance gaps by providing oncology clinicians with the latest advances and emerging research in the evidence-based and personalized treatment of metastatic breast cancer patients. In addition, the research team seeks to meet quality measures relevant to value-based care delivery through IT infrastructure and clinical workflow processes. The research team also hopes to gain insights into clinician practice patterns related to metastatic breast cancer, and the correlation between the reported goals of care for patients with metastatic breast cancer, and the patients' fit/frailty status and treatment decisions.
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Detailed Description
Breast cancer is one of the most commonly diagnosed cancers for women in the United States, with an estimated 246,660 cases of invasive breast cancer and 61,000 cases of in situ breast cancer to be diagnosed in 2016. It is also the second leading cause of cancer death for women, with an estimated 40,450 deaths to occur this year. The therapeutic environment for the treatment of MBC is evolving rapidly. Clinicians are challenged with understanding new molecular targets, and identifying ongoing clinical trial opportunities for this patient population. Healthcare providers are required to be aware of the mechanisms of action, safety, and efficacy of promising novel agents and regimens on the horizon for the treatment of advanced breast cancer. Furthermore, central to individualizing therapy is an assessment of patients' goals of treatment prior to developing a plan of care.
It is nearly impossible for the modern-day oncologist to remain current regarding the clinical tsunami of research to personalize MBC treatment. The tremendous pressures cancer centers and their oncology providers face in quantifiably demonstrating value in the care delivered compounds this problem. Almost instantly, government and commercial payers are demanding a change from pay for quantity to pay for value. In April 2016, CMMI implemented the Oncology Care Model (OCM). The new OCM program is complementary to other value-based payment initiatives in which oncologists may participate, including the Bundled Payment for Care Initiative, Chronic Care Management Program, Transforming Clinical Practices Initiative, Transitional Care Management Program, ACO/Medicare Shared Savings Program, and Medicare Care Choice Model, and others rapidly being introduced by commercial payers. These payment programs are transforming oncology care so that it is more pro-active, coordinated, vigilant and patient focused. At the center of this payment reform is the patient, as the ultimate consumer of health care services. Until recently, patients have been relatively blind to the actual cost and quality of the care they receive. Now, out-of-pocket costs are rising steeply and patients have instant access to a trove of health information as they are forced to become better-educated consumers regarding the costs and likely outcomes of their treatment. A recent JAMA Op-Ed piece receiving significant attention highlights that delivering value-based care requires an understanding of what the patient values. To that end, all the current cancer valued-based models require that oncology providers document their patient's goals of care and that the treatment course is evidence-based and commensurate with patient goals.
Another significant component of value is ensuring that a patient is "fit" enough for the treatment selected. The priorities of frail patients, whose care is the costliest, are often not noticed nor met. The issue of fit/frailty status in breast cancer is highly relevant, given that the median age at diagnosis is 62 with 57% cases of invasive breast cancer in females being diagnosed at age 60 or older. When older adults are ill, they are more prone to hospitalization; higher health care utilization due to cancer toxicities drives up the cost of health care. Older adults have an 11-fold increased incidence of cancer and a 16-fold increased incidence in cancer mortality compared to younger patients. Comprehensive geriatric assessment (CGA) is recommended to stratify elderly patients with advanced breast cancer to ensure treatment dosing that balances efficacy and toxicity.
Historically GAs are not routinely performed because they are complex and time-consuming, the optimal tools for administering the GA accurately and efficiently have not been established, many clinicians lack knowledge about how to incorporate GA into decision-making and care of older adults, and integration of a GA into a Health Information System platform has not been adequately studied for feasibility and usage. Hurria and colleagues developed the Cancer Specific Geriatric Assessment (CSGA), a shorter assessment that specifically captures data from seven domains (functional status, comorbid medical conditions, psychological state, cognition, nutritional status, social support, and medications). The CSGA requires nearly 30 minutes to complete which lessens its usefulness in a busy clinic.
A modified Geriatric Assessment (mGA) tool that utilizes age, functional status as determined by assessment of activities of daily living (ADLs) and instrumental activities of daily living (IADLs), plus comorbidity status was used to develop the Palumbo Frailty Index (FI). The FI categorizes patients into groups of fit, intermediate fit, and frail. In a retrospective analysis of data in 867 older adults with MM, toxicity, treatment discontinuation, and survival rates were correlated with the FI. As a result of this retrospective validation work, fit/frailty status is now being evaluated in the clinical setting by gathering information from a mGA and providing the data to the care provider to guide treatment decisions. Predictors of toxicity in elderly patients include age, tumor/treatment variables, labs, and geriatric assessment variables. The mCGA used in this study includes assessment of activities of daily living (ADLs), instrumental ADLS (IADLs), risk for toxicity using the Cancer and Aging Research Group's (CARG) "Chemotherapy Toxicity Calculator" and additional variables such as age, falls in the past six months, hearing, peripheral neuropathy, , stage and date of diagnosis.
The science of value-based cancer care is in its infancy. The association of quality and patient outcomes are still largely a thing of the future-to be informed by longitudinal studies to come that will involve a new generation of better-structured big data. Thus, aligning evidence-based treatment decisions with patient goals and patient's performance/fit status is an imperfect science.
Study Design
Outcome Measures
Primary Outcome Measures
- Adherence (by providers) to evidence-based treatment recommendations for patients with metastatic breast cancer. [Year 1]
Data collected on the Carevive CPS will be analyzed in order to correlate evidence-based guidelines to individual practice patterns
Secondary Outcome Measures
- Number of patients who are fit, intermediate fit, or frail as assessed by a modified geriatric assessment and a description of the chemotherapy regimens they are prescribed [Year 1]
Clinician practice patterns of medical oncologists managing older patients with metastatic breast cancer, including sub-analyses of practice patterns for those who are considered "fit," "intermediate fit," or "frail" will occur
- ER utilization and hospitalization in elderly patients with metastatic breast cancer [Year 1]
To explore how frequently older adults with metastatic breast cancer are hospitalized or visit the ER as a result of their breast cancer
Eligibility Criteria
Criteria
Inclusion Criteria:
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18 years of age or older
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diagnosis of metastatic breast cancer
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newly diagnosed or needing a new line of therapy and have not yet made a treatment decision
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able to understand English
Exclusion Criteria:
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any patient who cannot understand English
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any prisoner and/or other vulnerable person as defined by NIH (45 CFR 46, Subpart B, C, and D)
Contacts and Locations
Locations
No locations specified.Sponsors and Collaborators
- Carevive Systems, Inc.
Investigators
None specified.Study Documents (Full-Text)
None provided.More Information
Publications
None provided.- G413