The oncologist
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The phosphoinositide-3 kinase (PI3K) pathway has been identified as an important target in breast cancer research for a number of years, but is new to most clinicians responsible for the daily challenges of breast cancer management. In fact, the PI3K pathway is probably one of the most important pathways in cancer metabolism and growth. Mutations in the PI3K pathway are frequent in breast cancer, causing resistance to human epidermal growth factor receptor 2-targeted agents and, possibly, to hormonal agents as well. ⋯ Multiple PI3K inhibitors are currently under development, including pure PI3K inhibitors, compounds that block both PI3K and mTOR (dual inhibitors), pure catalytic mTOR inhibitors, and inhibitors that block Akt. It is likely that these agents will have to be given in combination with other signal inhibitors because anti-mTOR agents and PI3K inhibitors may result in the activation of compensatory feedback loops that would in turn result in decreased efficacy. This article reviews current data related to the PI3K pathway, its role in breast cancer, the frequency with which PI3K is aberrant in breast cancer, and the potential clinical implications of using agents that target the PI3K pathway.
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Clinicians have limited accuracy in the prediction of patient survival. We assessed the accuracy of probabilistic clinician prediction of survival (CPS) and temporal CPS for advanced cancer patients admitted to our acute palliative care unit, and identified factors associated with CPS accuracy. Eight physicians and 20 nurses provided their estimation of survival on admission by (a) the temporal approach, "What is the approximate survival for this patient (in days)?" and (b) the probabilistic approach, "What is the approximate probability that this patient will be alive (0%-100%)?" for ≥24 hours, 48 hours, 1 week, 2 weeks, 1 month, 3 months, and 6 months. ⋯ Probabilistic CPS was significantly more accurate than temporal CPS for both physicians and nurses, although this analysis was limited by the different criteria for determining accuracy. With the probabilistic approach, nurses were significantly more accurate at predicting survival at 24 hours and 48 hours, whereas physicians were significantly more accurate at predicting survival at 6 months. The probabilistic approach was associated with high accuracy and has practical implications.
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The Institute of Medicine's National Cancer Policy Forum recently convened a workshop on patient-centered cancer treatment planning, with the aim of raising awareness about this important but often overlooked aspect of cancer treatment. A primary goal of patient-centered treatment planning is to engage patients and their families in meaningful, thorough interactions with their health care providers to develop an accurate, well-conceived treatment plan, using all available medical information appropriately while also considering the medical, social, and cultural needs and desires of the patient and family. A cancer treatment plan can be shared among the patient, family, and care team in order to facilitate care coordination and provide a roadmap to help patients navigate the path of cancer treatment. ⋯ Others are a result of physician limitations, such as a lack of time to explain complex information and a lack of tools to facilitate treatment planning, as well as insensitivity to patients' informational, cultural, and emotional needs. Potential solutions to address these obstacles include better training of health care providers and patients in optimal communication and shared decision making, and greater use of support services and tools such as patient navigation and electronic health records. Other options include greater use of quality metrics and reimbursement for the time it takes to develop, discuss, and document a treatment plan.
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An existing and validated palliative prognostic (PaP) score predicts survival in terminally ill cancer patients based on dyspnea, anorexia, Karnofsky performance status score, clinical prediction of survival, total WBC, and lymphocyte percentage. The PaP score assigns patients to three different risk groups according to a 30-day survival probability--group A, >70%; group B, 30%-70%; group C, <30%. The impact of delirium is known but was not incorporated into the PaP score. ⋯ The revision of the PaP score was carried out by modifying the cutoff values used for prognostic grouping without, however, affecting the partial scores of the original tool. The performance of the D-PaP score was better than that of the PaP score and its key feature of simplicity was maintained.