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Prognosis Key Points Prognostication Is an Important but Underused Skill

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Prognosis Key Points Prognostication Is an Important but Underused Skill Prognosis Key Points Prognostication is an important but underused skill in clinical practice. It is a skill that highly impacts medical decision-making in daily clinical practice. In patients with advanced of terminal illness, prognostication aids in discussions about advanced care planning. With advance care planning, patients and families are better prepared for events that may occur at the end of life. This may help patients and families facing advance illness maintain a sense of control. Prognostication has influences on clinical administrative issues as well, such as the determination of hospice admission criteria for different disease states. Prognostication requires the clinician to be aware of the natural progression of diseases, while taking into account other patient-related factors such as comorbidities. An in-depth knowledge about the different therapeutic options, along with the risks and benefits of each option, is also required to determine prognosis. Another important factor is the communication of prognosis to the patient and family; news about prognosis should be delivered in a clear and compassionate manner. Clinicians tend to overestimate prognosis. There are many tools that can be used to aid in prognostication in many diseases; the clinician should be aware of the tools and resources to help improve accuracy. Overview The majority of advanced disease trajectories fall into one of three categories. • Cancer falls into category A, in which patient are often times able to maintain their functional status for months or even years, until there is an acute event (e.g. infection, pulmonary embolism) that leads to death. • The second model (category B) is characterized by slow decline of the patient due to episodes of acute decompensation with recovery to close off baseline. This type of trajectory is commonly seen in patients with congestive heart failure and in chronic obstructive pulmonary disease. • The third model (category C) usually has an onset with cognitive or functional deficits such in cases of dementia or some form of neurological disease, which then leads to progressive decline over a variable amount of time (see table below). Prognostication Tools Several prognostic tools and scales are available. The most commonly used ones are primarily based on the patient's functional status, and they include the following: • Eastern Cooperative Oncology Group (ECOG) scale • Karnofsky score • Palliative Performance Scale There are several disease-specific prognostication scales that are available for different organ specific diseases that have been validated: • Cardiac (NYHA Class, Seattle heart Failure Model) • Pulmonary (BODE Index) • Dementia (FAST staging, Mortality Risk Index) • Renal (age-modified Charleston Comorbidity Index) • Hepatic (MELD score in end-stage liver disease) The use of disease-specific prognostication tools can improve the clinician's accuracy in determining prognosis. In addition to the tools, the other variable that should be accounted for also includes physician experience and intuition. Approach to discussion about prognosis First, the clinician should establish patient's desire to discuss prognosis. Next, be sure to address emotional and informational concerns. The clinician should be open and honest, and the information should be delivered in a clear and concise manner. It is often times important and useful to be empathic and acknowledge uncertainty. The other important take-home point is that it is best to deliver prognosis in terms of timeframe, rather than specific time periods. Use terms like "hours to days," "days to weeks," "weeks to months," or "months to years." References Anderson, F., Downing, G.M., Hill, J. (1996). Palliative Performance Scale (PPS): a new tool. Journal of Palliative Care, 12(1): 5-11. Celli, B.R., Cote, C.G., Marin, J.M., et al. (2004). The Body-Mass Index, Airflow Obstruction, Dyspnea, and Exercise Capacity Index in Chronic Obstructive Pulmonary Disease. New England Journal of Medicine; 350(10) 1005-1012. Christakis, N.A., Lamont, E.B. (2000). Extent and Determinants of Error in Doctor's Prognoses in Terminally Ill Patients: Prospective Cohort Study. British Medical Journal; 320:469-472. Glare, P.A., Sinclair, C.T. (2008). Palliative Medicine Review: Prognostication. Journal of Palliative Medicine 11 (1) 84-103. Hemmelgarn, B.R., Manns, B.J., Hude, H., Ghali, W.A. (2003). Adapting the Charlson comorbidity index for use in patients with ESRD. American Journal of Kidney Disease; 42(1): 125–132. Lamont, E.B., & Christakis, N.A. (2003). Complexities in Prognostication in Advanced Cancer. Journal of the American Medical Association; 290: 98-104. Mitchell, S.L., Kiely, D.K., Hamel, M.B., et al. (2004). Estimating Prognosis for Nursing Home Residents with Advanced Dementia. Journal of the American Medical Association; 291:2734-2740. Morita, T., Tsunoda, J., Inoue, S., et al. (1999). Validity of the Palliative Performance Scale from a survival perspective. Journal of Pain Symptom Management, 18(1):2-3. Reisfield, G.M., & Wilson G.R. (2007). Prognostication in Heart Failure. Journal of Palliative Medicine; 10 (1):245-246. The SUPPORT Principal Investigators (1995). A Controlled Trial to Improve Care for Seriously Ill Hospitalized Patients. The study to understand prognoses and preferences for outcomes and risks of treatments (SUPPROT). Journal of the American Medical Association; 274: 1591-1598. Yourman, L.C., Lee, S.J., Schonberg, M.A., Widera, E.W., & Smith, A.K. (2012). Prognostic Indices for Older Adults: A Systematic Review. Journal of American Medical Association; 307(2): 182-192. Virik, K., Glare, P. (2002). Validation of the Palliative Performance Scale for inpatients admitted to a palliative care unit in Sydney, Australia. Journal of Pain Symptom Management, 23(6):455-7. .
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