Introduction to prognostication

I always avoid prophesying beforehand because it is much better to prophesy after the event has already taken place. Winston Churchill

Prognostication is the act of foretelling or prophesying future events. Along with diagnosis and treatment, it has served as one of the three pillars of medicine for hundreds of years. Once central to the role of physicians, the skill of prognostication, however, has received less emphasis in today’s medicine. Instead, the focus has been on more and more complex methods of both diagnosis and treatment.

There are a number of reasons for this shift in focus. Often eliciting powerful and distressing emotions, discussing prognosis can certainly be uncomfortable for both the patient and the physician. Furthermore, there is considerable room for error, especially in time-based estimates of prognosis. Finally, prognostication is not entirely “scientific.” There is an element of intuition—something that those focused on data and facts alone may find unsettling.

And yet, despite these challenges, the ability to effectively prognosticate remains a critical skill. Individuals are now living longer with serious, complex, and ultimately fatal illness. As a consequence, there is a growing need for accurate prognostication in order for patients and their families to make important decisions. Neither considering nor discussing prognosis clearly brings considerable risk. Poor communication by the physician may easily contribute to patients and families making poor choices. Indeed, one study found that terminally ill patients who hold unduly optimistic assessments of their survival prospects often request futile, aggressive care rather than perhaps more beneficial palliative care.

Physicians’ attitudes and biases toward the communication of prognosis further complicate this issue. This was illustrated in a study by Christakis and Lamont where investigators asked clinicians referring terminally ill cancer patients for hospice care what prognosis, if any, they would communicate to the patient. The median survival that clinicians estimated for their patients was 75 days. The median survival that clinicians would communicate to patients was 90 days and the median survival was actually only 24 days. Such practices can clearly have a devastating impact on patients and their families.

General principles of prognostication

When discussing prognostication, it is important to keep in mind certain fundamental principles. In that way, one can better interpret available data and communicate a prognosis.

The first principle is that the data from which one formulates a prognosis are based upon a cohort of individuals with similar characteristics. Although valuable in that it provides general information about the course of a disease and the effect of an intervention, the evidence from these studies does not easily translate to the physician advising his individual patient. Why? As we move from the population to the individual, there is increased “noise.” Comorbidities, psychological states, social supports, spiritual factors, and general frailty, all can have a profound impact on the prognosis of an individual.

The second principle is that prognostication is not a “static” event. It is a process which evolves just as the patient’s condition evolves. For example, early in the course of a cancer diagnosis, prognosis may be driven by biologic characteristics of the malignancy such as tumor stage and histologic grade. By contrast, prognostic variables in patients with more advanced disease typically consist of clinically related factors such as performance status, dyspnea, anorexia-cachexia, and cognitive failure. To further complicate matters, a patient’s prognosis may change with treatment response, acute oncologic complications, or complications of other comorbidities.

The third principle is that the prognostic accuracy for a given prognostic factor or tool depends upon the definition of accuracy and the patient population studied. Applying a particular model to the wrong patient can result in error.

Strategies for estimating prognosis

There is no perfect method for estimating a prognosis for an individual patient. Rather, one can use a number of strategies or tools to paint a picture of the likely course of a patient’s disease. These methods include consulting clinical databases, utilizing clinical factors such as signs, symptoms, and laboratory studies, or using prognostic models.

The SEER database

Clinical databases can provide excellent information on the expected course of a malignancy in a particular population. Funded by the National Cancer Institute (NCI) since 1973, the Surveillance Epidemiology and End Results (SEER) program of the NCI collects and publishes cancer incidence and survival data from population-based cancer registries covering approximately a third of the United States population. These registries routinely collect data on patient demographics, primary tumor site, tumor morphology, stage at diagnosis, first course of treatment, and follow-up for survival. As a clinical tool, the SEER Cancer Statistics Review includes tables and figures showing 5-year survival and relative survival by race, sex, age, and year of diagnosis for the major cancer sites and for all cancers combined.

Clinical factors related to prognosis

As noted earlier, in the more advanced stages of cancer, a number of clinical factors take on a greater role in determining a patient’s prognosis. These include clinical prediction of survival (CPS), performance status, dyspnea, anorexia-cachexia, and delirium.

Clinical prediction of survival

Based upon medical knowledge, clinical experience, and “gut instinct,” a clinician’s CPS is a frequently used tool in the estimation of prognosis. However, it is important to keep in mind that in most instances, CPS tends to be overoptimistic. In fact, CPS is more than twice as likely to be overoptimistic versus overpessimistic and to overestimate the length of survival by a factor of between 3 and 5.

In a classic study, Chistakis et al. asked 343 physicians to estimate the survival of 468 patients at the time of hospice referral. The medial survival in this cohort was 24 days. A total of 20% of predictions were accurate, 63% were overly optimistic, and 17% were overly pessimistic. On average, physicians tended to overestimate prognosis by a factor of 5. In addition, the study found that the tendency of doctors to make prognostic errors was lower among experienced doctors and those who had less of an emotional attachment to the patient. Surprisingly, the better the doctor knew the patient—as measured by the length and recentness of their contact—the more likely the doctor was to err. A later study by Poses et al. demonstrated that averaging the CPS across multiple physicians may be more accurate than one physician alone.

In summary, the CPS is a generally useful and valid tool but is subject to a series of factors that limit its accuracy. The CPS should not be used alone. Rather, clinicians should consider using CPS in combination with other prognostic factors or scores to improve the accuracy of their predictions.

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