Point-of-Care Guides

Predicting Four-Year Mortality Risk in Older Adults



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Am Fam Physician. 2006 Aug 15;74(4):633-634.

Clinical Question

What is the four-year mortality risk for community-dwelling older adults?

Evidence Summary

Survival prognoses for older adults may help patients and physicians make decisions about screening, treatment, and advance directives. Although a variety of prognostic tools have been developed, they have had limitations. For example, these tools require laboratory tests; are limited to recently hospitalized patients1 or patients with specific diagnoses2; only include functional status measures and do not address comorbidities3; or are largely limited to the presence or absence of comorbidities.4

A population-based study5  identified 19,710 community-dwelling persons older than 50 years. Information was collected via telephone interviews regarding comorbidities and functional status. During the four-year follow-up, 2,433 (12 percent) of the participants died. A prognostic index (Table 15) for predicting four-year mortality risk in community-dwelling older adults was developed using data from 11,701 of the study participants in eastern, western, and central regions of the United States and was validated in 8,009 participants in the southern region of the United States.5 The index performed as well in the validation group as it did in the original group.5

TABLE 1

Prognostic Index to Predict Four-Year Mortality Risk in Community-Dwelling Older Adults

Patient characteristic Points

Age (years)

60 to 64

1

65 to 69

2

70 to 74

3

75 to 79

4

80 to 84

5

≥85

7

Male sex

2

Diabetes

1

Cancer (other than minor skin cancer)

2

Chronic lung disease (disease limits activities or patient requires oxygen)

2

Heart failure

2

Body mass index < 25 kg per m2

1

Current smoker

2

Functional difficulties caused by health or memory problems:

2

Bathing

2

Managing money or finances

2

Walking several blocks

2

Pulling or pushing large objects (e.g., living room chair)

1

Total:

_________

Point total Predicted four-year mortality risk (%)

0 to 5

< 4

6 to 9

15

10 to 13

42

≥14

64


Adapted with permission from Lee SJ, Lindquist K, Segal MR, Covinsky KE. Development and validation of a prognostic index for 4-year mortality in older adults. JAMA 2006;295:805.

TABLE 1   Prognostic Index to Predict Four-Year Mortality Risk in Community-Dwelling Older Adults

View Table

TABLE 1

Prognostic Index to Predict Four-Year Mortality Risk in Community-Dwelling Older Adults

Patient characteristic Points

Age (years)

60 to 64

1

65 to 69

2

70 to 74

3

75 to 79

4

80 to 84

5

≥85

7

Male sex

2

Diabetes

1

Cancer (other than minor skin cancer)

2

Chronic lung disease (disease limits activities or patient requires oxygen)

2

Heart failure

2

Body mass index < 25 kg per m2

1

Current smoker

2

Functional difficulties caused by health or memory problems:

2

Bathing

2

Managing money or finances

2

Walking several blocks

2

Pulling or pushing large objects (e.g., living room chair)

1

Total:

_________

Point total Predicted four-year mortality risk (%)

0 to 5

< 4

6 to 9

15

10 to 13

42

≥14

64


Adapted with permission from Lee SJ, Lindquist K, Segal MR, Covinsky KE. Development and validation of a prognostic index for 4-year mortality in older adults. JAMA 2006;295:805.

The prognostic index is simple and quick to use and includes age, comorbidities, and functional status. The study showed that those in the lowest risk group had a four-year mortality risk of less than 4 percent, whereas the highest risk group had a four-year mortality risk of 64 percent.5

Applying the Evidence

A 77-year-old woman asks whether she should continue to receive annual mammograms. She has diabetes and chronic lung disease that somewhat limit her activities. She has difficulty walking several blocks and moving large objects such as the armchair in her living room. The patient no longer smokes and has a body mass index (BMI) of 21 kg per m2.

Answer: Using the prognostic index, you determine that the patient has a risk score of 11 points: she receives four points for age, one for diabetes, two for chronic lung disease, one for a low BMI, and three for functional limitations. Therefore, you predict that the patient has a four-year mortality risk of 42 percent. After you discuss the advantages and disadvantages of continued screening with her, she decides not to receive further mammograms. Instead, you and the patient discuss ways to optimize treatment for her chronic lung disease and how she can get help with home maintenance (e.g., cleaning, yard work) and with other activities of daily living.

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 also is deputy editor of evidence-based medicine forAmerican Family Physician.

E-mail correspondence to Mark H. Ebell, M.D., M.S., at ebell@msu.edu. Reprints are not available from the author.

REFERENCES

1. Walter LC, Brand RJ, Counsell SR, Palmer RM, Landefeld CS, Fortinsky RH, et al. Development and validation of a prognostic index for 1-year mortality in older adults after hospitalization. JAMA. 2001;285:2987–4.

2. Lee DS, Austin PC, Rouleau JL, Liu PP, Naimark D, Tu JV. Predicting mortality among patients hospitalized for heart failure: derivation and validation of a clinical model. JAMA. 2003;290:2581–7.

3. Carey EC, Walter LC, Lindquist K, Covinsky KE. Development and validation of a functional morbidity index to predict mortality in community-dwelling elders. J Gen Intern Med. 2004;19:1027–33.

4. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40:373–83.

5. Lee SJ, Lindquist K, Segal MR, Covinsky KE. Development and validation of a prognostic index for 4-year mortality in older adults. JAMA. 2006;295:801–8.

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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