Point-of-Care Guides

Determining Prognosis for Patients with Terminal Cancer



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Am Fam Physician. 2005 Aug 15;72(4):668-669.

Clinical Question

What is the prognosis for a patient with terminal cancer?

Evidence Summary

An accurate prognosis enables patients with terminal cancer to make plans, put their affairs in order, and decide how they want to spend the time they have left. A prognosis also may help the primary care physician refer the patient for hospice care at a time when the patient would most benefit from the service.

Traditionally, physicians have estimated prognosis using their clinical experience. A study1 of 196 patients with non–small cell lung cancer found that physicians were able to correctly predict the date of death within one month for only 10 percent of patients. However, they were able to correctly predict the date of death within three months for 59 percent of patients.1 Another study2 found that physicians usually overestimate survival.2 Physicians also commonly use the Karnofsky Performance Scale to predict the prognosis of a patient with terminal cancer. Using the Karnofsky Scale, a score of 50 percent or less in a patient with progressive underlying cancer predicts a median life expectancy of two months.3

Researchers have developed more objective and reproducible clinical rules to assist physicians in estimating prognosis. A systematic review4 identified 24 rules, of which only three were prospectively validated in a study group of patients who were not involved in the rules’ development. A search of recent literature did not identify any additional rules. Perhaps the best-validated clinical rule is the Palliative Prognosis Score (PPS). It was developed based on a study of over 500 Italian patients with terminal cancer who were admitted to 14 hospitals.5 The rule was prospectively validated in a second group of over 500 patients admitted to the same hospitals as the original group. In the validation group, the median age was 70 years; 56 percent had metastatic disease and 65 percent had locally advanced disease. The most common malignancies were lung (19 percent); colorectal (15 percent); stomach (12 percent); and pancreas, liver, or gallbladder (12 percent). Another group of researchers successfully validated the rule in 100 Australian patients with advanced cancer who were admitted to a palliative care unit and in 100 patients with advanced cancer who were admitted to an Australian teaching hospital.6  The PPS combines objective measures with the physician’s global estimate to predict a more accurate prognosis. Table 1 shows the PPS rule and its interpretation.

TABLE 1

Palliative Prognosis Score

Clinical factor Points

Dyspnea present

1

Anorexia present

1.5

Karnofsky Performance Scale (KPS) score of 10 to 20*

2.5

Clinical prediction of survival (weeks)

More than 12

0

11 to 12

2.0

7 to 10

2.5

5 to 6

4.5

3 to 4

6.0

1 to 2

8.5

Total white blood cell count

8,500 cells per mm3 or less (8.5 × 109 cells per L)

0

8,501 to 11,000 cells per mm3 (8.5 to 11 × 109 cells per L)

1.0

Greater than 11,000 cells per mm3

2.5

Lymphocyte percentage

20 or greater

0

12.0 to 19.9

1.0

Less than 12 percent

2.5

Total points:

Score Risk group Median survival (days) (95% CI) Probability of 30-day survival (%)

0 to 5.5

Low

76 (67 to 87)

87

5.6 to 11.0

Moderate

32 (28 to 39)

52

11.1 to 17.5

High

14 (11 to 18)

17


*A patient with a KPS score of 10 to 20 is very sick (i.e., hospitalization is necessary, active supportive treatment is necessary, or moribund)

Adapted with permission from Maltoni M, Nanni O, Pirovano M, Scarpi E, Indelli M, Martini C, et al. Successful validation of the palliative prognostic score in terminally ill cancer patients. J Pain Symptom Manage 1999;17:242.

TABLE 1   Palliative Prognosis Score

View Table

TABLE 1

Palliative Prognosis Score

Clinical factor Points

Dyspnea present

1

Anorexia present

1.5

Karnofsky Performance Scale (KPS) score of 10 to 20*

2.5

Clinical prediction of survival (weeks)

More than 12

0

11 to 12

2.0

7 to 10

2.5

5 to 6

4.5

3 to 4

6.0

1 to 2

8.5

Total white blood cell count

8,500 cells per mm3 or less (8.5 × 109 cells per L)

0

8,501 to 11,000 cells per mm3 (8.5 to 11 × 109 cells per L)

1.0

Greater than 11,000 cells per mm3

2.5

Lymphocyte percentage

20 or greater

0

12.0 to 19.9

1.0

Less than 12 percent

2.5

Total points:

Score Risk group Median survival (days) (95% CI) Probability of 30-day survival (%)

0 to 5.5

Low

76 (67 to 87)

87

5.6 to 11.0

Moderate

32 (28 to 39)

52

11.1 to 17.5

High

14 (11 to 18)

17


*A patient with a KPS score of 10 to 20 is very sick (i.e., hospitalization is necessary, active supportive treatment is necessary, or moribund)

Adapted with permission from Maltoni M, Nanni O, Pirovano M, Scarpi E, Indelli M, Martini C, et al. Successful validation of the palliative prognostic score in terminally ill cancer patients. J Pain Symptom Manage 1999;17:242.

Another clinical scoring system was developed based on a study7 of 150 patients with terminal cancer who were admitted to a palliative care unit. It used a very similar set of variables as the PPS, but because it was validated in a smaller group of 95 patients,7 it is not discussed in this article.

In previous validations of the PPS, scores were only determined by oncologists and palliative care specialists.57 Therefore, it should be used primarily by physicians with experience caring for patients who are older and who have a terminal illness. In addition, it is always important to remember that scores such as the PPS are meant to support decision making, not replace it. Rules should be used in the context of the physician’s knowledge of the patient.

Applying the Evidence

Your patient is a 63-year-old woman with terminal colon cancer who would like a more specific prognosis. She has some dyspnea and anorexia but is able to care for herself. Her white blood cell count is 4,000 cells per mm3 (4 × 109 cells per L) with 15 percent lymphocytes. You estimate that she will likely live approximately three or four months (i.e., more than 12 weeks).

Answer: Using the PPS, your patient receives 3.5 points (1 + 1.5 + 0 + 0 + 0 + 1), putting her in the low-risk group. She has a median survival of 76 days and an 87 percent likelihood of surviving at least one month.

The Author

MARK H. EBELL, M.D., M.S., is in private practice in Athens, Ga., and is associate professor in the Department of Family Practice at Michigan State University College of Human Medicine, East Lansing. He is also deputy editor for evidence-based medicine of American Family Physician.

Address correspondence to Mark H. Ebell, M.D., M.S., 150 Yonah Dr., Athens, GA 30606 (e-mail: ebell@msu.edu). Reprints are not available from the author.

REFERENCES

1. Muers MF, Shevlin P, Brown J. Prognosis in lung cancer: physicians’ opinions compared with outcome and a predictive model. Thorax. 1996;51:894–902.

2. Glare P, Virik K. Independent prospective validation of the PaP score in terminally ill patients referred to a hospital-based palliative medicine consultation service. J Pain Symptom Manage. 2001;22:891–8.

3. Miller RJ. Predicting survival in the advanced cancer patient. Henry Ford Hosp Med J. 1991;39:81–4.

4. Vigano A, Dorgan M, Buckingham J, Bruera E, Suarez-Almazor ME. Survival prediction in terminal cancer patients: a systematic review of the medical literature. Palliat Med. 2000;14:363–74.

5. Maltoni M, Nanni O, Pirovano M, Scarpi E, Indelli M, Martini C, et al. Successful validation of the palliative prognostic score in terminally ill cancer patients. J Pain Symptom Manage. 1999;17:240–7.

6. Glare PA, Eychmueller S, McMahon P. Diagnostic accuracy of the palliative prognostic score in hospitalized patients with advanced cancer [published correction appears in J Clin Oncol 2005;23:248]. J Clin Oncol. 2004;22:4823–8.

7. Morita T, Tsunoda J, Inoue S, Chihara S. The Palliative Prognostic Index: a scoring system for survival prediction of the terminally ill cancer patients. Support Care Cancer. 1999;7:128–33.

This guide is one in a series that offers evidence-based tools to assist family physicians in improving their decision making at the point of care.



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