Fourth Issue, Series Two
Personalized Treatment Planning: A Nurse’s Perspective
It is projected there will be 18.1 million cancer survivors in 2020, with an estimated $173 billion of associated cancer care costs in the initial and last year of life.1 The cost of healthcare has grown exponentially since the 1990s due, in part, to improved diagnostic techniques, better treatments, and an aging population. Cancer patients are increasingly involved in healthcare decisions and faced with many options in determining the best course of therapy with the hope that the treatment they decide upon will provide the best personal outcome. Quality of life, ease of treatment administration, and convenience may be the most important factors when selecting anticancer therapy for individuals of older age, poorer health, or with advanced disease. Few cancer types have a standard approach that produces definite results, and many uncertainties are attached to most anticancer treatments. National guidelines exist but do not often take into account personalized factors in their recommendations. It is also likely that patients will be given several treatment recommendations to consider before effective anticancer therapy can be initiated.
When a cancer diagnosis is made, the patient and providers go through various aspects of a decision-making process to select the best treatment for the individual. Nurses and healthcare providers are often the primary sources of information for patients. However, resources such as the Internet, social networks, and additional miscellaneous influences have been cited as determining factors for patients who are balancing one cancer treatment decision over another.2 In this fourth installment of Conquering the Cancer Care Continuum, we will discuss a patient case that illustrates the importance of treatment planning and decision making in the era of personalized medicine.
Mr P is a 78-year-old male who initially presented to his primary care provider (PCP) for an annual physical. He had a history of cigarette smoking, 1 pack per day for 45 years, but quit smoking when he underwent a 3-vessel coronary artery bypass graft procedure at the age of 60 years. He has moderate chronic obstructive pulmonary disease, although his symptoms are currently controlled with a combination inhaler daily. He has a “rescue” inhaler that is used for dyspnea on exertion. He has been using his inhaler a few more times a week than in the past. He is a retired autoworker but remains active at home and in the garden. He lives with his wife, aged 76 years, who is in general good health.
On evaluation, the patient had a routine complete blood count and differential (CBC+diff) performed. Results showed mild anemia (hemoglobin 10.3 g/dL). His white blood cell (WBC) count was slightly low (2.8). Blood platelet count was normal (151). The PCP repeated the CBC 1 month later, and results were similar. The patient had no specific complaints and was scheduled for follow-up evaluation 6 months later.
At the next visit, the blood hemoglobin was 10.4 g/dL, WBC 2.1, and platelets 98. A routine anemia panel did not suggest bleeding (normal ferritin, folate, vitamin B12, and methylmalonic acid). He was referred to a hematologist. A bone marrow biopsy was obtained that showed 10% blasts and unilineage dysplasia (megakaryocytes). Interphase fluorescence in situ hybridization (FISH) analysis for selected genetic abnormalities associated with myelodysplasia was performed. FISH was positive for an abnormal clone that was characterized by a deletion of the long arm of chromosome 20, del(20q). He was diagnosed with myelodysplastic syndrome (MDS), Revised International Prognostic Scoring System (IPSS-R) stage low-intermediate risk.3,4
To determine whether to initiate chemotherapy for treatment of MDS, the National Comprehensive Cancer Network (NCCN) guidelines for treatment of patients with MDS were consulted. The NCCN has established treatment algorithms to guide practitioners in the care of patients with MDS and take into account patient attributes (age, performance status, comorbidities, and general health) and disease characteristics (cytogenetic abnormalities and risk of progression) to determine an appropriate course of action.5
With knowledge of patient and disease characteristics, a meeting of the patient, family, physician, nurses, and nurse practitioner (the treatment team) took place. The treatment team informed the patient of the risks, benefits, and alternatives to treatment. The options included starting a hypomethylating agent (HMA) or watchful waiting with routine office visits every 2 months. Mr P had researched the diagnosis of MDS on the Internet and was concerned about the cost of the medications as he is on a fixed income. He also learned from the Internet that frequent trips to the hospital would be required. Transportation to the hospital would be a challenge as his wife does not drive and his children live out of state. For these reasons the patient did not want to begin HMA treatment, which was reasonable given the low risk to progress to acute myelogenous leukemia (AML) at the time of diagnosis.
After the family meeting, a treatment plan was created in which Mr P would be watched closely by the nurse practitioner. The patient was to return for an office visit and labs that included a CBC+diff every 2 months to assess for symptoms of progressive anemia or leukopenia. Should he develop progressive anemia or leukopenia, the plan was to initiate hematopoietic growth factors. If growth factors did not help to raise the blood hemoglobin and leukocyte counts, the patient would then consider other options such as chemotherapy “when I really need it.”
The case example illustrates key components of the decision-making process in this era of personalized medicine in which treatment decisions are made in collaboration with healthcare providers, spouses or significant others, family members, and friends. Treatment decisions are rarely made independently by the patient alone.
Decision making is defined as the cognitive process of reaching a decision and includes weighing and balancing the risks and benefits among multiple options.6 Decision making in cancer is usually informed and shared. Informed decision making in cancer occurs when the individual has adequate knowledge about the risks, benefits, and limitations of the procedure, the ability to participate in decision making, and when one comes to a decision congruent with personal values.7 Shared decision making is a process in which the patient, family, and treatment team work to achieve mutual goals. If patients share in the decision-making process with a group, they are more likely to adhere to the treatment plan, and their quality of life can be increased.
Informed/shared decision-making practices commonly occur in patients with advanced cancer.8 Personalized medicine practices are integral to the health and well-being of cancer patients in today’s healthcare system. Costly therapies and longer survival can lead to physical and financial burdens to the patient and family. In addition, older adults and those with advanced cancer can experience a low level of health literacy due to concurrent comorbid conditions and polypharmacy use. Each of these factors can confound decision making.6 For many reasons, informed/shared decision-making processes become quite attractive, as the final decisions can be costly both physically and financially.
With knowledge gained through research, treatment can be personalized and tailored to the individual, as in our example of the patient with MDS. MDS represents a spectrum of hematologic malignancies characterized by dysplastic hematopoiesis that leads to peripheral cytopenias. The goals of therapy for MDS are based on individualized disease characteristics, patient characteristics, and risk category, as individuals such as our case example have cardiopulmonary comorbidities and advanced age.8,9 The treatment team in the example considered patient (older age, comorbidities, and transportation issues) and disease characteristics (cytogenetics, IPSS-R risk score) and employed a shared/informed decision-making approach.
Personalized treatments are a hallmark of MDS, yet a main challenge for the patient and provider is how to decide the best treatment from a wide variety of options. The IPSS-R risk categorization is a critical component of treatment selection. The IPSS was developed to reliably estimate survival and risk of transformation to AML. Risk category for transformation to AML, patient desire for treatment, and financial considerations were critical factors in the informed/shared decision-making process.
Last month Mr P complained of chest pain and went to the emergency department. A chest x-ray was obtained that showed right upper lobe pneumonia. His hemoglobin was 7.2 g/dL, WBC 0.8, and platelets 22. A bone marrow biopsy was performed that showed 35% bone marrow blasts. Cytogenetics, FISH, and flow cytometry analysis confirmed the diagnosis of AML. Mr P’s diagnosis was no longer MDS. He had transformed to a more aggressive AML.
Mr P was admitted to the hospital for combination chemotherapy for AML. He received supportive care (blood and platelet transfusions, fluids, and antibiotics). On day 10 of admission he was placed on telemetry as he was found to be in atrial fibrillation and developed congestive heart failure. He developed a severe fungal blood infection. At day 14, a bone marrow biopsy was performed to determine response and remission status. The bone marrow biopsy showed 46% bone marrow blasts. The patient, wife, and children met with the treatment team. The treatment team informed Mr P and his family that the chemotherapy must be repeated but that the response to chemotherapy would be low. Mr P would be placed at risk for further infections and heart problems. Mr P felt “too weak” to continue with another course of chemotherapy and didn’t want additional treatment unlikely to provide benefit. He wanted to enjoy what time he had left at home with his family. Mr P was discharged home to hospice the next day.
Treatment planning and decision making are key components of advanced cancer care. Knowledge of guidelines such as those developed by the NCCN provides an algorithmic framework but is not often prescriptive. A plethora of treatment or supportive options exist for any one cancer. Taking into account disease status, comorbid conditions, and, above all, patient preferences is critical. A strategy for providers would be to use informed/shared decision-making processes that will add to the value of personalized medicine and hopefully translate to improved outcomes.
- Mariotto AB, Yabroff KR, Shao Y, et al. Projections of the cost of cancer care in the United States: 2010-2020. J Natl Cancer Inst. 2011;103:117-128.
- Allen JD, Berry DL. Multi-media support for informed/shared decision-making before and after a cancer diagnosis. Semin Oncol Nurs. 2011;27:192-202.
- Schanz J, Tüchler H, Solé F, et al. New comprehensive cytogenetic scoring system for primary myelodysplastic syndromes (MDS) and oligoblastic acute myeloid leukemia after MDS derived from an international database merge. J Clin Oncol. 2012;30:820-829.
- Greenberg PL, Tuechler H, Schanz J, et al. Revised International Prognostic Scoring System for myelodysplastic syndromes. Blood. 2012;120:2454-2465.
- National Comprehensive Cancer Network. NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines). Myelodysplastic Syndrome. Version 2.2013. www.nccn.org/professionals/physician_gls/f_guidelines.asp#mds.
- Tariman JD, Berry DL, Cochrane B, et al. Physician, patient, and contextual factors affecting treatment decisions in older adults with cancer: a literature review. Oncol Nurs Forum. 2012;39:E70-E83.
- US Preventive Services Task Force. Screening for prostate cancer: US Preventive Services Task Force recommendation statement. Ann Intern Med. 2008;149:185-191.
- Stone RM. How I treat patients with myelodysplastic syndromes. Blood. 2009;113:6296-6303.
- Deschler B, de Witte T, Mertelsmann R, et al. Treatment decision-making for older patients with high-risk myelodysplastic syndrome or acute myeloid leukemia: problems and approaches. Haematologica. 2006;91:1513-1522.
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