- Email: [email protected]
White blood cell count as a predictor of mortality: Results over 18 years from the normative aging study
J ch &idmb! Vol. 43. No. 2, pp. Printi
153457, in Great Britain. All rights remvcd
0895-4356/9053.00+ 0.00
1990
Copyright Q 1990 Pcrgamon Pm8 pk
WHITE BLOOD CELL COUNT AS A PREDICTOR OF MORTALITY: RESULTS OVER 18 YEARS FROM THE NORMATIVE AGING STUDY LORRAINE 0. DE LABRY,‘** EDWARD W. CAMPION,? ROBERT J. GLYNN~
and
PANTEL S. VOKONAS’*~ ‘Normative Aging Study, Veterans Administration Outpatient Clinic, and Section of Epidemiology and Biostatistics. School of Public Health. Boston Universitv School of Medicine. ‘Massachnsetts General Hospital and Division on Aging,. Harvard Medical-School, ‘Epidemiology Unit, Massachusetts Eye and Ear Infirmary, and The Department of Ophthalmology, Harvard Medical School, Boston, MA 02115 and ‘Section of Preventive Medicine and Epidemiology, and Evans Memorial Department of Clinical Research, Department of Medicine, University Hospital, Boston University School of Medicine, Boston, MA 02118, U.S.A. (Received in revisedform 11 July 1989)
Abstrict--The ubiquitous white blood cell count (WBC) has rarely been analyzed as a predictor of future mortality. We examined WBC measured in prospective examinations of 2011 initially healthy men in the Normative Aging Study (mean age 47.5), followed for an average of 13.6 years with 27,402 man-years of observation. Between 1970 and 1987, 183 participants died. Mortality rates for men with baseline WBC over 9000 were 12.2/1000 man-years, 1.8-2.5 times those of men with lower WBC in each of three age groups. Proportional hazards models controlling for established risk factors including age, systolic blood pressure, cholesterol and smoking status, found WBC at the baseline exam to be an independent predictor of mortality over the following years. Even within the normal range, a difference of 1000 in the initial WBC increased the risk ratio by 1.2 (95% CI 1.l, 1.3). The relation of initial WBC to mortality was not affected by baseline age, body mass index (BMI), smoking or blood pressure. These findings are not explained by medication effects. We conclude that the WBC is an independent predictor of all-cause mortality.
White blood cell count
Mortality
INTRODUCTION The white blood
cell count (WBC) is universally performed but not recognized as having predictive value as a risk factor for future mortality. A few epidemiologic studies have indicated possible relationships between WBC levels and subsequent risk for specific clinical outcomes [l-7]. Ernst related leukocytosis with risk of myocardial re-infarction and in-hospital death [5J In a subset of participants in the Multiple *All correspondence should be address4 to: Lorraine de Labry, M.A. Nonnative Aging Study, VAOPC. 17 Court Street, Boston, MA 02108, U.S.A.
Survival
Follow-up study
Risk Factor Intervention Trial (MRFIT), a decrease in WBC counts was associated with lower risk of cardiac events short term, independent of smoking status. Cancer deaths have been associated with elevated WBC [6]. The few studies to date describe associations between changes in the WBC that were relatively close to the time of death, leaving the distinct possibility that such changes were simply a manifestation of pre-terminal illness. In this longitudinal study with prospectively gathered data on healthy males, we evaluate the relation of routine WBC to long term mortality over 18 subsequent years. 153
LORRAINE 0. DELABRYet al.
154 METHODS
The population The Normative Aging Study is a longitudinal study of aging, begun in 1963 and conducted at the Veterans Administration Outpatient Clinic in Boston. Six thousand men from the Boston area were recruited through radio and newspaper advertisements and by appeals through companies whose employees were likely to remain in the area (Police and Fire departments and insurance companies). After initial screening, 2280 healthy men, (mean age 42, range 21-81) were selected. These men were judged at initial physical examination to be free of heart disease, cancer, peptic ulcer, gout, hypertension, pancreatitis, cirrhosis, recurrent diabetes, asthma, bronchitis, and sinusitis. Acceptable conditions included childhood diseases, and other generally acute conditions from which there were no sequelae. Mean levels of education and social class were slightly higher than in the general population as 28% were college graduates, and 54% were in white-collar occupations. A detailed description of the Normative Aging Study has been published elsewhere [8]. The specific hypothesis that white blood cell count would affect survival was not an a priori hypothesis of the NAS. The decision to evaluate this hypothesis was made on the basis of the evidence summarized in the Introduction. The baseline physical exam
After the initial screening examination, men younger than age 52 have reported for physical examinations every 5 years; men older than 52 have reported every 3 years. Two hundred twenty-three men never returned after their initial screening and have been excluded from the present longitudinal study for two reasons. First, follow up information and outcome data for these 223 men is of inconsistent quality since they dropped out before information necessary for later tracking, such as Social Security number and the name of next-of-kin, could be obtained. Second, data on risk factors for these analyses were not gathered contemporaneously until the baseline examination. Most of the men had no earlier measure of smoking-an important potential confounder. Each baseline examination was done in the out-patient clinic on a scheduled basis, and postponed whenever a participant was acutely ill. A uniform medical history was obtained and a complete physical
examination done by a board-certified internist. Systolic blood pressure was the average of the right and left arm readings in the sitting position. Total serum cholesterol was measured by the calorimetric method of Sperry [9]. BMI was defined as weight (kg)/height (m’). The number of cigarettes smoked per day was recorded by a Normative Aging Study interviewer as a categorical variable from 0 (nonsmoker) to 8 (> 2 packs per day). Medications were also recorded at each examination. The Normative Aging Study examiner was unaware of the participants’ WBC levels measured on the same day. All participants were required to be fasting at the time blood was drawn for laboratory analyses including cholesterol and WBC. WBCs for this study were done by Coulter Counter [lo]. The Normative Aging Study uses laboratory standards provided by the College of American Pathologists, and over the past 20 years has passed all quarterly quality control testing, including determinations on standard unknowns. In this study, only the WBC done at the baseline physical exam is used in the analysis. Records of death
The Normative Aging Study has remained in close contact with nearly all its participants by periodic physical exams, frequent mailings and phone calls. Only 41 (2%) of 2057 men have been lost to followup since their baseline examination. Death certificates have been obtained on decedents in addition to personal physician records, discharge summaries and autopsy reports. In these analyses, 8 deaths due to accidents were omitted from analyses. These people were considered withdrawn alive at time of death. Data analysis
The study population consists of the 2016 participants who returned after the initial screening for their baseline examination and for whom status at followup was known. Records of all participants with deaths due to malignancies were reviewed to determine whether the participant had any possible evidence of cancer apparent at the time of the baseline exam. Four participants were excluded from analyses for this reason. Record review found only one individual on medication at baseline which may have affected his WBC; he was also excluded from analyses. Therefore, 2011 participants are considered in analyses.
155
White Blood Cell Count and Mortality
Table 3. Proportional hazards mode1 predicting mortality
Table l.Causesofdaath 19 65 12 6 4 4 4 3 2 1
Iscllemic heart disease Canar Other heart diaeasc Ccrcbrovascular
Risk factor
disease
Pneumonia Digestive disorders Unknown causes Infections Blood disorders Pulmonary infarct Cirrhosis Kidney disease Central nervous system disease
Age (Yr) Cholastarol (mg/dl) Systolic blood pressure (mmHg) Cigarette smoking (c&s/day) WBC (in lOOOs/mm~
The objectives of data analyses were two-fold: to establish death rates in relation to participants’ WBC count at baseline, and to examine independence of any risk attributable to the WBC by controlling for age, systolic blood pressure, cholesterol, and smoking status. The probability of remaining alive between baseline exam and followup, given an initial WBC count was estimated using the Kaplan-Meier life-table approach [l 11.Relative rates of mortality across age and WBC categories were estimated by the Mantel-Haenszel test [ 121. Adjusted relative mortality rates, accounting for age, systolic blood pressure, cholesterol and cigarette smoking were obtained assuming a proportional hazards model [13]. Parameters were estimated by maximizing the partial likelihood. A proportional hazards model accounts for varying intervals in followup between subjects and allows control for confounding effects of other risk factors.
RESULTS The mean age at baseline for the cohort of 2011 men considered in analyses was 47.5 years. Mean followup time for the sample was 13.6 years with a range of 0.28-18.87 years. Table 1 presents the causes for the 183 deaths. Death
rates+ for overall mortality according to age at entry and baseline WBC 2744
45-5 1
52-85
(n = 694)
(n = 678)
(n = 639)
RR
95% CI
<5000 5001-7ooo 7001-9ooot >9000
3.36 1.71 2.34 4.38
3.62 2.70 5.47 9.46
4.25 10.14 14.63 26.73
0.52 0.65 1 1.81
(0.26, I .05) (0.46, 0.92)
69QOO >!MOO
2.46 4.38
3.83 9.46
11.51 26.73
WBC
0.0088 0.0015 0.0050 0.027 0.039
and other information for 4 recently deceased participants were not available; those deaths are listed as “cause unknown”. Table 2 presents the incidence rates of total mortality per thousand man-years of followup. With baseline dam, we established 4 categories of WBC ( <5000/mm3, low; 5000-7000/mm3, medium-high; medium; 7000-9OOO/mm3, >9000/mm3, high) and 3 age categories (27-44, 45-51 and 52-85 years). In all 3 age groups, those with the highest WBC at baseline had the highest subsequent mortality rates. For the 2 younger age groups, those with medium baseline WBC levels had the lowest rates. In the oldest age group, those men with low baseline WBC had the lowest rate. The lower half of Table 2 shows the total mortality rates for subjects above and below WBC of 9000/mm3 at the outset. Again, by the 3 age groups, the mortality rates for those with an initial WBC over 9000/mm3 were consistently higher by 78, 147, and 132% respectively. Table 3 presents a proportional hazards regression analysis showing age at entry, smoking and initial WBC to be significant predictors of total mortality. Neither baseline cholesterol nor systolic blood pressure emerged as independent predictors; however initial screening criteria had eliminated subjects with a major degree of hypertension. A rise in the WBC by 1000 cells/mm3 increases the mortality rate a factor of 1.2. For example, compared with a similar man with a WBC of 6000/mm3, the rate of mortality for a man with a WBC of 7000/mm3 was 1.2 times
certificates
1 I 183
Table 2. Incidena
0.088+** 0.0025 0.0089 0.080** 0.15+**
SE
‘p < 0.05; *p < 0.01; l**p < 0.001.
1
Total
Cc&cicnt
N = 2011; digths = 183. llnnidena rates per 1000 man-years of followup tReferent group.
(1.25-2.62)
156
LORRAINE 0.
g
2.6 -
i :
s E :!
1.5-
_
1.0 -.
J
z
I
I
Medium
High
high
Medium
P 0.6
-
__ Low
-
t
Chi-square test for trend: 11.98 with Idf p < 0.001
Fig. I. Mortality rates according to Baseline WBC (adjusted for age, systolic blood pressure, cholesterol, and smoking). Low-WBC c 5000/mm3; medium-WBC 5000-7000/mm3; medium-high-WBC 7t)00-9000/mm3 (referent group); high-WBC > 9C90/mm3. Bars indicate 95% confidence interval.
greater, for a man with a WBC of 8000/mm3 was 1.4 times greater, and for a man with a WBC of 10,000, the rate was 1.8 times greater (95% CI: 1.34, 2.47). Figure 1 displays results from this same proportional hazards analysis, with initial WBC considered by 4 categories: low, medium, medium-high and high. Those with high WBC had an adjusted relative mortality rate of 1.62 compared to those in the medium-high group. While the low and medium groups had lower rates than those in the medium-high group, the confidence intervals contained one. A chisquare test for trend, with 1 u” was 11.98 (p < 0.001). DISCUSSION
This longitudinal study of males, specifically selected for health, finds that baseline WBC is an independent predictor of subsequent mortality after an average of 13 years of followup. Only 7 of the 183 deaths occurred within the first 2 years of the study. None of the study group had evidence at baseline of cancer or hematologic malignancy of any kind; none were on chemotherapy or corticosteroids. The only deaths excluded were those due to accidents on the assumption that such deaths should bear no meaningful relation to measurable biological variables. To be certain, the proportional hazards model was refitted to include those few deaths due to accidents. The comparable coefficient for WBC was identical to that shown in Table 3 for WBC.
DE LABRY
et 01.
WBC remained an important predictor of mortality after controlling for the established risk factors blood pressure, cholesterol, smoking status and age. In fact, in our cohort the baseline WBC proves to be a stronger predictor of mortality than all of these except age. The effect we observed was apparent within the normal range of WBC counts, not just at the extremes. We found no increase in mortality at the lowest WBC levels, but that is explained by the healthy nature of this selected cohort. That the WBC relates to immediate prognosis in acute illness is beyond dispute. The curve is U-shaped. Mortality associated with leukopenia reflects the effects of hematologic malignancies, immunologic disorders or immunosuppression by medication, as well as to bone marrow suppression from severe illness, myelophthisis or overwhelming infection. In acute illness, leukocytosis is a predictor of mortality principally due to infection, but it may also reflect tissue injury, drug effects, adrenergic stimulation or increased secretion of steroid hormones. We can only speculate as to the mechanism by which higher WBC levels relate to mortality years later. If our findings can be confirmed by others, further investigation of the biology that underlies this apparent statistical relation will be warranted. It may be that elevation of the WBC is caused by specific diseases such as coronary heart disease, chronic obstructive lung disease or cancer even at a subclinical stage. Increasing WBC might reflect endothelial damage or the degree of adrenergic activity, either of which could be a cause or a consequence of systemic disease. The WBC may well integrate several other environmental and physiologic risk factors and acquire its surprising predictive power from being further along the chain of pathophysiologic causation than some of the traditionally assessed epidemiologic risk factors. REFERENCES Friedman GD, Klatsky AL, Siegelaub AB. The leukocyte count as a predictor of myocardial infarction. N Engl J Med. 1974; 290: 1275-1278. Zalokar JB, Richards JL, Blaude JR. Leukocyte count, smoking and myocardial infarction. N Engl J Med 1981; 394: 465468. Prentice RL, Shimizu Y, Lin CH ef al. Leukocyte counts and coronary heart disease in a Japanese cohort. Am J Epitlemld 1982; 116: 496506. Prentice RL. Szatrowski TP, Kato H er al. Leukocyte counts and cerebrovascular disease. J Chron Dla 1982; 35: 703-714.
White Blood Cell Count and Mortality Ernst E, Hammerschmidt DE, Bagge U et al. Leukocytes and the risk of ischemic diseases. JAMA 1987; 257: 2318-2324. Grimm RH, Neaton JD, Ludwig W. Prognostic importance of the white blood cell count for coronary, cancer, and all-cause mortality. JAMA 1985; 254: 1932-1937. Bender BS, Jagel JE, Adler WH et al. Absolute peripheral blood lymphocyte count and subsequent mortality of elderly men. J Ant Geriatr Sot 1986; 34:
649-654:
-
Bosse R, Ekerdt DJ, Silbert JE. The Veterans Administration Normative Aging study. In: Mednick S, Harway M, Fine110 KM, Eds. Ha&oak of Longitudinal Resureb. New York: Praeger; 1984: 273-295.
9.
10. 11. 12. 13.
157
Fuldes RR, Wilson BL. Determination of cholesterol: an adaptation of the Schoenheimer-Sperry method of nhotoelectric instruments. Anal Cbem 1950: 22: 1210. Coulter WH. High speed automatic blood cell counter and cell size anaiyzer. Paper presented at the N&anal &e&c&a Canferraa. Chicano. Illinois. 1956. Kaplan EL, Meier P. Nonpar~metric estimation from incomplete observations. J Am Stat Amoc 1958; 53: 457481. Mantel N, Haenszel W. Statistical aspects of the analysis of data from retrospective studies of disease. J Natf Cancer Imt 1959; 22: 719-748. Cox DR. Regression models and life tables (with discussion). J R Stat Sot B 1972; 34: 187-220.
153457, in Great Britain. All rights remvcd
0895-4356/9053.00+ 0.00
1990
Copyright Q 1990 Pcrgamon Pm8 pk
WHITE BLOOD CELL COUNT AS A PREDICTOR OF MORTALITY: RESULTS OVER 18 YEARS FROM THE NORMATIVE AGING STUDY LORRAINE 0. DE LABRY,‘** EDWARD W. CAMPION,? ROBERT J. GLYNN~
and
PANTEL S. VOKONAS’*~ ‘Normative Aging Study, Veterans Administration Outpatient Clinic, and Section of Epidemiology and Biostatistics. School of Public Health. Boston Universitv School of Medicine. ‘Massachnsetts General Hospital and Division on Aging,. Harvard Medical-School, ‘Epidemiology Unit, Massachusetts Eye and Ear Infirmary, and The Department of Ophthalmology, Harvard Medical School, Boston, MA 02115 and ‘Section of Preventive Medicine and Epidemiology, and Evans Memorial Department of Clinical Research, Department of Medicine, University Hospital, Boston University School of Medicine, Boston, MA 02118, U.S.A. (Received in revisedform 11 July 1989)
Abstrict--The ubiquitous white blood cell count (WBC) has rarely been analyzed as a predictor of future mortality. We examined WBC measured in prospective examinations of 2011 initially healthy men in the Normative Aging Study (mean age 47.5), followed for an average of 13.6 years with 27,402 man-years of observation. Between 1970 and 1987, 183 participants died. Mortality rates for men with baseline WBC over 9000 were 12.2/1000 man-years, 1.8-2.5 times those of men with lower WBC in each of three age groups. Proportional hazards models controlling for established risk factors including age, systolic blood pressure, cholesterol and smoking status, found WBC at the baseline exam to be an independent predictor of mortality over the following years. Even within the normal range, a difference of 1000 in the initial WBC increased the risk ratio by 1.2 (95% CI 1.l, 1.3). The relation of initial WBC to mortality was not affected by baseline age, body mass index (BMI), smoking or blood pressure. These findings are not explained by medication effects. We conclude that the WBC is an independent predictor of all-cause mortality.
White blood cell count
Mortality
INTRODUCTION The white blood
cell count (WBC) is universally performed but not recognized as having predictive value as a risk factor for future mortality. A few epidemiologic studies have indicated possible relationships between WBC levels and subsequent risk for specific clinical outcomes [l-7]. Ernst related leukocytosis with risk of myocardial re-infarction and in-hospital death [5J In a subset of participants in the Multiple *All correspondence should be address4 to: Lorraine de Labry, M.A. Nonnative Aging Study, VAOPC. 17 Court Street, Boston, MA 02108, U.S.A.
Survival
Follow-up study
Risk Factor Intervention Trial (MRFIT), a decrease in WBC counts was associated with lower risk of cardiac events short term, independent of smoking status. Cancer deaths have been associated with elevated WBC [6]. The few studies to date describe associations between changes in the WBC that were relatively close to the time of death, leaving the distinct possibility that such changes were simply a manifestation of pre-terminal illness. In this longitudinal study with prospectively gathered data on healthy males, we evaluate the relation of routine WBC to long term mortality over 18 subsequent years. 153
LORRAINE 0. DELABRYet al.
154 METHODS
The population The Normative Aging Study is a longitudinal study of aging, begun in 1963 and conducted at the Veterans Administration Outpatient Clinic in Boston. Six thousand men from the Boston area were recruited through radio and newspaper advertisements and by appeals through companies whose employees were likely to remain in the area (Police and Fire departments and insurance companies). After initial screening, 2280 healthy men, (mean age 42, range 21-81) were selected. These men were judged at initial physical examination to be free of heart disease, cancer, peptic ulcer, gout, hypertension, pancreatitis, cirrhosis, recurrent diabetes, asthma, bronchitis, and sinusitis. Acceptable conditions included childhood diseases, and other generally acute conditions from which there were no sequelae. Mean levels of education and social class were slightly higher than in the general population as 28% were college graduates, and 54% were in white-collar occupations. A detailed description of the Normative Aging Study has been published elsewhere [8]. The specific hypothesis that white blood cell count would affect survival was not an a priori hypothesis of the NAS. The decision to evaluate this hypothesis was made on the basis of the evidence summarized in the Introduction. The baseline physical exam
After the initial screening examination, men younger than age 52 have reported for physical examinations every 5 years; men older than 52 have reported every 3 years. Two hundred twenty-three men never returned after their initial screening and have been excluded from the present longitudinal study for two reasons. First, follow up information and outcome data for these 223 men is of inconsistent quality since they dropped out before information necessary for later tracking, such as Social Security number and the name of next-of-kin, could be obtained. Second, data on risk factors for these analyses were not gathered contemporaneously until the baseline examination. Most of the men had no earlier measure of smoking-an important potential confounder. Each baseline examination was done in the out-patient clinic on a scheduled basis, and postponed whenever a participant was acutely ill. A uniform medical history was obtained and a complete physical
examination done by a board-certified internist. Systolic blood pressure was the average of the right and left arm readings in the sitting position. Total serum cholesterol was measured by the calorimetric method of Sperry [9]. BMI was defined as weight (kg)/height (m’). The number of cigarettes smoked per day was recorded by a Normative Aging Study interviewer as a categorical variable from 0 (nonsmoker) to 8 (> 2 packs per day). Medications were also recorded at each examination. The Normative Aging Study examiner was unaware of the participants’ WBC levels measured on the same day. All participants were required to be fasting at the time blood was drawn for laboratory analyses including cholesterol and WBC. WBCs for this study were done by Coulter Counter [lo]. The Normative Aging Study uses laboratory standards provided by the College of American Pathologists, and over the past 20 years has passed all quarterly quality control testing, including determinations on standard unknowns. In this study, only the WBC done at the baseline physical exam is used in the analysis. Records of death
The Normative Aging Study has remained in close contact with nearly all its participants by periodic physical exams, frequent mailings and phone calls. Only 41 (2%) of 2057 men have been lost to followup since their baseline examination. Death certificates have been obtained on decedents in addition to personal physician records, discharge summaries and autopsy reports. In these analyses, 8 deaths due to accidents were omitted from analyses. These people were considered withdrawn alive at time of death. Data analysis
The study population consists of the 2016 participants who returned after the initial screening for their baseline examination and for whom status at followup was known. Records of all participants with deaths due to malignancies were reviewed to determine whether the participant had any possible evidence of cancer apparent at the time of the baseline exam. Four participants were excluded from analyses for this reason. Record review found only one individual on medication at baseline which may have affected his WBC; he was also excluded from analyses. Therefore, 2011 participants are considered in analyses.
155
White Blood Cell Count and Mortality
Table 3. Proportional hazards mode1 predicting mortality
Table l.Causesofdaath 19 65 12 6 4 4 4 3 2 1
Iscllemic heart disease Canar Other heart diaeasc Ccrcbrovascular
Risk factor
disease
Pneumonia Digestive disorders Unknown causes Infections Blood disorders Pulmonary infarct Cirrhosis Kidney disease Central nervous system disease
Age (Yr) Cholastarol (mg/dl) Systolic blood pressure (mmHg) Cigarette smoking (c&s/day) WBC (in lOOOs/mm~
The objectives of data analyses were two-fold: to establish death rates in relation to participants’ WBC count at baseline, and to examine independence of any risk attributable to the WBC by controlling for age, systolic blood pressure, cholesterol, and smoking status. The probability of remaining alive between baseline exam and followup, given an initial WBC count was estimated using the Kaplan-Meier life-table approach [l 11.Relative rates of mortality across age and WBC categories were estimated by the Mantel-Haenszel test [ 121. Adjusted relative mortality rates, accounting for age, systolic blood pressure, cholesterol and cigarette smoking were obtained assuming a proportional hazards model [13]. Parameters were estimated by maximizing the partial likelihood. A proportional hazards model accounts for varying intervals in followup between subjects and allows control for confounding effects of other risk factors.
RESULTS The mean age at baseline for the cohort of 2011 men considered in analyses was 47.5 years. Mean followup time for the sample was 13.6 years with a range of 0.28-18.87 years. Table 1 presents the causes for the 183 deaths. Death
rates+ for overall mortality according to age at entry and baseline WBC 2744
45-5 1
52-85
(n = 694)
(n = 678)
(n = 639)
RR
95% CI
<5000 5001-7ooo 7001-9ooot >9000
3.36 1.71 2.34 4.38
3.62 2.70 5.47 9.46
4.25 10.14 14.63 26.73
0.52 0.65 1 1.81
(0.26, I .05) (0.46, 0.92)
69QOO >!MOO
2.46 4.38
3.83 9.46
11.51 26.73
WBC
0.0088 0.0015 0.0050 0.027 0.039
and other information for 4 recently deceased participants were not available; those deaths are listed as “cause unknown”. Table 2 presents the incidence rates of total mortality per thousand man-years of followup. With baseline dam, we established 4 categories of WBC ( <5000/mm3, low; 5000-7000/mm3, medium-high; medium; 7000-9OOO/mm3, >9000/mm3, high) and 3 age categories (27-44, 45-51 and 52-85 years). In all 3 age groups, those with the highest WBC at baseline had the highest subsequent mortality rates. For the 2 younger age groups, those with medium baseline WBC levels had the lowest rates. In the oldest age group, those men with low baseline WBC had the lowest rate. The lower half of Table 2 shows the total mortality rates for subjects above and below WBC of 9000/mm3 at the outset. Again, by the 3 age groups, the mortality rates for those with an initial WBC over 9000/mm3 were consistently higher by 78, 147, and 132% respectively. Table 3 presents a proportional hazards regression analysis showing age at entry, smoking and initial WBC to be significant predictors of total mortality. Neither baseline cholesterol nor systolic blood pressure emerged as independent predictors; however initial screening criteria had eliminated subjects with a major degree of hypertension. A rise in the WBC by 1000 cells/mm3 increases the mortality rate a factor of 1.2. For example, compared with a similar man with a WBC of 6000/mm3, the rate of mortality for a man with a WBC of 7000/mm3 was 1.2 times
certificates
1 I 183
Table 2. Incidena
0.088+** 0.0025 0.0089 0.080** 0.15+**
SE
‘p < 0.05; *p < 0.01; l**p < 0.001.
1
Total
Cc&cicnt
N = 2011; digths = 183. llnnidena rates per 1000 man-years of followup tReferent group.
(1.25-2.62)
156
LORRAINE 0.
g
2.6 -
i :
s E :!
1.5-
_
1.0 -.
J
z
I
I
Medium
High
high
Medium
P 0.6
-
__ Low
-
t
Chi-square test for trend: 11.98 with Idf p < 0.001
Fig. I. Mortality rates according to Baseline WBC (adjusted for age, systolic blood pressure, cholesterol, and smoking). Low-WBC c 5000/mm3; medium-WBC 5000-7000/mm3; medium-high-WBC 7t)00-9000/mm3 (referent group); high-WBC > 9C90/mm3. Bars indicate 95% confidence interval.
greater, for a man with a WBC of 8000/mm3 was 1.4 times greater, and for a man with a WBC of 10,000, the rate was 1.8 times greater (95% CI: 1.34, 2.47). Figure 1 displays results from this same proportional hazards analysis, with initial WBC considered by 4 categories: low, medium, medium-high and high. Those with high WBC had an adjusted relative mortality rate of 1.62 compared to those in the medium-high group. While the low and medium groups had lower rates than those in the medium-high group, the confidence intervals contained one. A chisquare test for trend, with 1 u” was 11.98 (p < 0.001). DISCUSSION
This longitudinal study of males, specifically selected for health, finds that baseline WBC is an independent predictor of subsequent mortality after an average of 13 years of followup. Only 7 of the 183 deaths occurred within the first 2 years of the study. None of the study group had evidence at baseline of cancer or hematologic malignancy of any kind; none were on chemotherapy or corticosteroids. The only deaths excluded were those due to accidents on the assumption that such deaths should bear no meaningful relation to measurable biological variables. To be certain, the proportional hazards model was refitted to include those few deaths due to accidents. The comparable coefficient for WBC was identical to that shown in Table 3 for WBC.
DE LABRY
et 01.
WBC remained an important predictor of mortality after controlling for the established risk factors blood pressure, cholesterol, smoking status and age. In fact, in our cohort the baseline WBC proves to be a stronger predictor of mortality than all of these except age. The effect we observed was apparent within the normal range of WBC counts, not just at the extremes. We found no increase in mortality at the lowest WBC levels, but that is explained by the healthy nature of this selected cohort. That the WBC relates to immediate prognosis in acute illness is beyond dispute. The curve is U-shaped. Mortality associated with leukopenia reflects the effects of hematologic malignancies, immunologic disorders or immunosuppression by medication, as well as to bone marrow suppression from severe illness, myelophthisis or overwhelming infection. In acute illness, leukocytosis is a predictor of mortality principally due to infection, but it may also reflect tissue injury, drug effects, adrenergic stimulation or increased secretion of steroid hormones. We can only speculate as to the mechanism by which higher WBC levels relate to mortality years later. If our findings can be confirmed by others, further investigation of the biology that underlies this apparent statistical relation will be warranted. It may be that elevation of the WBC is caused by specific diseases such as coronary heart disease, chronic obstructive lung disease or cancer even at a subclinical stage. Increasing WBC might reflect endothelial damage or the degree of adrenergic activity, either of which could be a cause or a consequence of systemic disease. The WBC may well integrate several other environmental and physiologic risk factors and acquire its surprising predictive power from being further along the chain of pathophysiologic causation than some of the traditionally assessed epidemiologic risk factors. REFERENCES Friedman GD, Klatsky AL, Siegelaub AB. The leukocyte count as a predictor of myocardial infarction. N Engl J Med. 1974; 290: 1275-1278. Zalokar JB, Richards JL, Blaude JR. Leukocyte count, smoking and myocardial infarction. N Engl J Med 1981; 394: 465468. Prentice RL, Shimizu Y, Lin CH ef al. Leukocyte counts and coronary heart disease in a Japanese cohort. Am J Epitlemld 1982; 116: 496506. Prentice RL. Szatrowski TP, Kato H er al. Leukocyte counts and cerebrovascular disease. J Chron Dla 1982; 35: 703-714.
White Blood Cell Count and Mortality Ernst E, Hammerschmidt DE, Bagge U et al. Leukocytes and the risk of ischemic diseases. JAMA 1987; 257: 2318-2324. Grimm RH, Neaton JD, Ludwig W. Prognostic importance of the white blood cell count for coronary, cancer, and all-cause mortality. JAMA 1985; 254: 1932-1937. Bender BS, Jagel JE, Adler WH et al. Absolute peripheral blood lymphocyte count and subsequent mortality of elderly men. J Ant Geriatr Sot 1986; 34:
649-654:
-
Bosse R, Ekerdt DJ, Silbert JE. The Veterans Administration Normative Aging study. In: Mednick S, Harway M, Fine110 KM, Eds. Ha&oak of Longitudinal Resureb. New York: Praeger; 1984: 273-295.
9.
10. 11. 12. 13.
157
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