Race, poverty, and survival in multiple myeloma

Race, Poverty, and Survival in Multiple Myeloma

DAVID SAVAGE, MD,* JOHN LINDENBAUM, MD,'.t JOHN VAN RYZIN, PHD,* ELMER STRUENING, P H D , ~ AND T. J. GARRETT, MD'

To identify possible interracial differences in the behavior of multiple myeloma, the records of 52 black myeloma patients at Harlem Hospital Center (HHC) and 46 black and 46 white patients at Columbia- Presbyterian Medical Center (CPMC) were reviewed. In addition to clinical variables such as tumor burden, azotemia, and hypoalbuminemia, the effect of poverty on prognosis was examined, using socioeconomic indices from the United States census block group data of each patient. The median survival of CPMC black and white patients was comparable (34 and 29 months, respectively) whereas that of the HHC group was 12 months (Breslow test, P < 0.0001). Overcrowding and hypoalbuminemia were the most significant prognostic factors by multivariate regression analysis on all 144 patients (P = 0.001); for HHC patients, overcrowding was the single significant variable affecting survival (P = 0.004). By all socioeconomic indices, HHC patients were more impoverished than CPMC patients (P < 0.001); they also presented with more advanced disease. Race is not a significant prognostic factor in myeloma, whereas the effect of socioeconomic status on survival appears to equal that of previously described clinical features.

Cancer 54:3085-3094, 1984.

ULTIPLE MYELOMA is the most common lym- M phohematopoietic malignancy in blacks. ' Its incidence is twice that seen in whites,'-3 and may be increasing at a more rapid rate.' It has been reported that the disease has a younger age of onset and that IgA myeloma is more frequent in black population^.',^ The possibility has been raised that these differences may be attributable to interracial variations in immunoregulation or chronic antigenic 10ad.l.~ It has also been suggested that survival in black patients may be shorter' or longer6 than in whites. Detailed and controlled analysis of myeloma in blacks in the literature has been limited, however.

Because of these considerations and our impression over the years that black myeloma patients at Harlem Hospital Center (HHC) fared less well with their disease

From the *Department of Medicine, Harlem Hospital Center and the ?Department of Medicine, the $School of Public Health and the §Psychiatric Institute, College of Physicians and Surgeons, Columbia University, New York, New York.

Supported in part by Grants AM-07373, CA-21112, and GM-28405 from the National Institutes of Health.

Address for reprints: T. J. Garrett, MD, Department of Medicine, Harlem Hospital Center, 506 Lenox Avenue, New York, NY 10037.

The authors thank Dr. Elliott Osserman for vital diagnostic support and for generously providing access to his patients' files, Mr. Whitney Martin of the Harlem Hospital Tumor Registry and Ms. Julia Johnson of the Harlem Hospital Records Department for aid in retrieving patients' records, Dr. Jay Dobkin and Dr. Thomas Mattimore for reviewing the manuscript and for useful suggestions, and Ms. Gwendolyn Williams and Ms. Maxine Joyner for secretarial assistance.

Accepted for publication October 31, 1983.

than whites described elsewhere, we undertook a comparative study of black patients at HHC and black and white patients at Columbia-Presbyterian Medical Center (CPMC). The Central Harlem area served by HHC is the health district with the highest rates of low birth weight, infant mortality, and death due to stroke, hepatic cirrhosis, trauma, and malignancy in New York City'; it is also one of the most economically distressed neighborhoods. In light of the previously reported adverse effect of poverty on survival in cancer patients,*-" we included an analysis of the potential contribution of socioeconomic factors to prognosis, in addition to the classic clinical prognostic variables in myeloma. This enabled us to examine the relationship between race, clinical findings, poverty, and survival in patients with multiple myeloma.

Methods

HHC is a municipal, university-affiliated hospital serving the predominantly black community of Central Harlem in New York City. Of 57 patients with the diagnosis of multiple myeloma at HHC during the 1965- 1980 period, the records of 52 were available for review; all were black. Control groups consisted of age- and sex-matched white and black myeloma patients at CPMC, a university-affiliated hospital in Upper Man- hattan serving an ethnically heterogeneous population of black, white, and Hispanic people from West Harlem and Washington Heights and a large referral group from

3085

3086 CANCER December 15 1984 Vol. 54

TABLE 1 . Race, Sex, Age, and Outcome of 144 Myeloma Patients at Columbia-Presbyterian Medical Center and Harlem Hospital Center

Mean age Median in yr Early Lost to survival

Patient group No. M F (range) Died deaths* follow-up Alive (mo) ~

CPMC whites 46 21 25 63 (43-90) 42 13 0 4 29

Combined CPMC CPMC blacks 46 21 25 63 (41-84) 38 10 3 5 34

group 92 42 50 63 (41-90) 80 23 3 9 33 HHC patients 52 23 29 67 (42-97) 45 28 4 3 12

* Deaths occumng within the first year of diagnosis.

other centers. During the years from 1958 to 1980, the diagnosis of myeloma was established in 53 blacks and 71 whites at CPMC; from these two groups, 46 blacks and 46 whites could be matched with patients from the HHC group. The remaining six HHC cases were not matched, primarily because of a lack of comparable elderly cases in the CPMC group; because of the absence of an effect of age and sex on survival by multivariate analysis, as discussed below, these six patients were included in the entire analysis. CPMC and HHC have had a joint hematology-oncology fellowship program since 1968. Thus, although the patients at HHC and CPMC were seen by the separate house staff and attend- ings of each institution, most of the patients were evaluated and followed in detail by fellows from the joint program. Characterization of monoclonal proteins of all patients was performed in a single laboratory. All patients met previously described criteria for the diagnosis of myeloma. I I

The year of diagnosis; street address; birthplace; duration and types of symptoms; initial hematocrit, serum albumin, corrected serum calcium,” uric acid, and blood urea nitrogen (BUN) levels; bone marrow mor- phologic findings; radiographic findings; serum and urine protein electrophoresis and immunoelectrophoresis findings; treatment regimen; and survival from the time of diagnosis were recorded. Patients were classified as having high, intermediate, or low tumor load using the criteria of Durie and Salmon.13 In addition, major complications were recorded, including infection, plasmacytomas, symptomatic bone disease, spinal cord compression, and hyperviscosity syndrome.

Since the records usually contained little data regarding socioeconomic status, US census data were used to delineate the socioeconomic setting of each patient’s immediate neighborhood. The home address of each person residing in New York City was identified in a dictionary provided by the US Census. Each address was coded into a census block group which, on the average, contained approximately 1000 residents. By referring to 1970 census data describing the block group populations and their housing characteristics, it was

CPMC: Columbia-Presbyterian Medical Center; HHC Harlem Hos- pital Center.

possible to select a set of variables that characterized the neighborhood of the patient, including median family income, percentage of families below the poverty level (income below $4000/year), adult male unemployment rate, low education level (percentage of adults with less than 9 years of education), prevalence of separation or divorce, and overcrowding (mean occupancy of more than 1.5 persons/room). Socioeconomic analysis was performed only on the 123 patients residing in New York City.

The statistical analysis employed a variety of tech- niques. These included Student’s t test, the chi-square method for fourfold tables with Yates correction, and the Pearson product-moment coefficient of correlation. In addition, Kaplan-Meier plots of survival curves’4 for each of the three hospital patient groups and their median survival times were calculated. A comparison of these three survival curves was made by the Breslow test,15 which adjusts for varying patient follow-up times. To study the effect of each prognostic variable singly, survival curve plots and median survivals of all patients dichotomized into groups by each variable were then compared statistically by the Gehan test,I6 which also adjusts for varying patient follow-up times. To study the combined influence of various prognostic variables on survival, a stepwise regression procedure was applied using the proportional hazard model of Cox.” This procedure accounts for the varying patient follow-up times and adjusts the regression coefficient of each prognostic variable for the effects of the others. The degree of association of each prognostic variable with survival is assessed by the degree of statistical significance of the related individual regression coefficient, which is estimated by the method of maximum partial likelihood.

Results

Patient Characteristics and Survival

Patient characteristics and mortality of the HHC patients and the two CPMC groups are shown in Tables 1, 2, and 3. As shown in Figure 1, the survival of black and white patients at CPMC was comparable, whereas

No. 12 RACE, POVERTY, AND SURVIVAL IN MULTIPLE MYELOMA * Savage et a/. 3087

that of HHC patients was significantly poorer ( P < 0.0001); the median survival of 12 months for the HHC group was less than half that of the CPMC black (34 months) and white patients (29 months). Among the known HHC deaths, 62% occurred in the first year after diagnosis (defined as "early deaths"), in contrast to 29% in the CPMC group (x2 = 12.00; P < 0.0001); 14 of 45 HHC deaths (31%) occurred in the first three months versus only 7 of 80 CPMC mortalities (9%) (x2 = 8.75; P = 0.003). Among the patients who died more than 1 year after diagnosis, the mean ( + 1 standard deviation [SD]) survival of the HHC group was 28 ? 12 months in contrast to 45 4 24 months for the CPMC patients ( 2 = 2.75, P = 0.01).

Effects of Clinical Variables on Survival

When the combined clinical data of all 144 cases were analyzed by the Gehan test, significantly shortened survival was noted in patients with hypoalbuminemia, high tumor load, and marked anemia (hematocnt I 25%), as shown in Figures 2A to 2C. In addition, patients with serum calcium concentrations 2 11.5 mg/dl(2.9 mmol/l) had a median survival of 12 months compared to 29 months in those with serum calcium levels < 1 1.5 mg/dl (Gehan test, P < 0.00 1). Also, those with initial BUN values 2 40 mg/dl (14.2 mmol/liter) had a median survival of 1 1 months compared to 27 months in those with BUN values < 40 mg/dl (Gehan test, P = 0.01). Hyperuncemia (serum urate > 7.5 mg/dl or 0.45 mmol/l) was also associated with a shorter survival, but the difference was not significant.

Eflect of Socioeconomic Variables on Survival

As can be seen in Figures 3A to 3C, survival was significantly shorter among those patients from block groups with overcrowding (P < 0.0001), more families below the poverty level (P = 0.01), and high unemployment (P = 0.01). Similarly, patients from block groups with low educational background had a shorter median survival (14 months) than those with a higher educational level (27 months) (Gehan test, P = 0.02); those from block groups with a low family income had a shorter median survival (18 months) than those from higher income areas (28 months) (Gehan test, P = 0.02); a shorter median survival time was also noted for patients from neighborhoods with a high prevalence of separation and divorce (19 months) than those from block groups with a low prevalence (36 months) (Gehan test, P = 0.01).

Comparison of Clinical Variables in Patient Subgroups

As shown in Table 2, levels of hematocrit, serum albumin, urate, calcium, BUN, and incidence of high


TABLE 3. Socioeconomic Characteristics of Census Block Groups of 123 Myeloma Patients at Columbia-Presbyterian Medical Center and Harlem Hospital Center Residing in New York City*

Mean values ( + I SD)

Median Separation NYC Overcrowdingt poverty level$ Unemployment educational family and divorce

Families below Low

Patient group residents (%) (%) (%) levels (%) income ($) (%)

CPMC whites 32 1.9 k 2.0 6 f 6 14 * 10 24 f 12 12000 f 8000 6 k 5 CPMC blacks 40 2.5 * 2.1 1 8 k 9 26 f 14 3 5 + 9 7200 f 1600 15 f 6 Combined CPMC group 72 2.2 f 2.1 13 ? 10 20 + 14 31 f I 1 9300 k 6000 1 I f 7 HHC patients 51 3.8 ? 2.4 19* 8 34 f 14 3 9 + 8 6700 ? 2700 1 7 f 6

* Fourteen CPMC whites and five CPMC blacks resided outside N Y C addresses were not listed for one HHC and one CPMC black patient.

t Families with more than 1.5 persons per room. $ Income of less than $4000 per yr.

tumor load at presentation were comparable for the CPMC white and black groups. Abnormalities in these risk factors among the HHC population were consistently greater than in the two CPMC groups. When compared with the combined data of all 92 CPMC patients, the HHC population had significantly lower mean serum albumin ( t = 4.34; P < 0.001) and higher uric acid levels (t = 3.65; P < 0.001). In the total CPMC group, the hematocrit was less than 32% in 51 of 92 cases (55%) in contrast to 41 of 52 HHC patients (79%) (x2 = 6.91; P = 0.008). Similarly, only 11 of 9 1 CPMC patients (12%) had a BUN greater than 40 mg/dl (14.2 mmol/l), whereas 14 of 52 HHC cases (26%) exceeded this level (x2 = 4.07; P = 0.04). High tumor load and

I00 k.... W HHC Blacks

80 5 5 3 60

40

v)

0 p: 2 20

0 20 40 60 80 100

SURVIVAL TIME (months 1 FIG. 1 . Kaplan-Meier plots of survival curves of 52 Harlem Hospital

Center (HHC) black myeloma patients and 46 white and 46 black controls at Columbia-Presbyterian Medical Center (CPMC), analyzed by the Gehan test (P < 0.0001).

0 Adults with less than 9 yr of education. SD: Standard deviation: CPMC: Columbia-Presbyterian Medical

Center, HHC: Harlem Hospital Center; NYC: New York City.

hypercalcemia were also more prevalent in the HHC group but the differences were not significant. The three groups did not vary significantly in the mean duration of symptoms, degree of marrow plasmacytosis, amount or type of paraprotein, severity of x-ray changes, or the incidence of weight loss, hyperviscosity syndrome, infec- tious complications, or spinal cord compression; there were no cases of solitary plasmacytoma. There was also no difference in the incidence of alcoholism and drug addiction between the three groups.

Patients With High Tumor Load

Among HHC cases with a high tumor load, the mean (+1 SD) serum albumin (2.9 + 0.8 g/dl) was lower than that of the CPMC high-tumor-load group (3.3 f 0.8 g/dl) ( t = 2.48; P = 0.008); the mean serum uric acid levels of the HHC (10.2 +. 2.8 mg/dl; 0.61 f 0.17 mmol/ 1) and CPMC patients (8.1 k 2.8 mg/dl; 0.49 + 0.17 mmol/l) with high tumor loads also differed ( t = 3.05; P = 0.002). The same trends were noted for the seventy of anemia and azotemia among the high-tumor-load patients of the two hospitals, but the differences were not significant.

Comparison of Socioeconomic Variables in Patient Subgroups

In the HHC group, mean block socioeconomic indices were consistently less favorable than those of the CPMC patients, as seen in Table 3. Seventeen of 51 HHC patients (33%) came from block groups with greater than 5% overcrowding versus only 5 of 72 CPMC cases (7%) (x2 = 12.35; P < 0.001); the median family income was ~ $ 7 0 0 0 per year in 41 of the 51 HHC patients’ block groups (80%) in contrast to 29 of the 72 CPMC block groups (40%) (x2 = 17.92; P < 0.001). Similarly, compared with those of the CPMC patients, the neighborhoods of HHC patients had a higher incidence of families below the poverty level ( P < 0.001), greater

No. 12 RACE, POVERTY, AND SURVIVAL IN MULTIPLE MYELOMA 6 Savage et aZ. 3089

FIG. 2. Kaplan-Meier plots of survival curves, analyzed by the Gehan test, of 144 myeloma patients with (A) serum albumin levels 53 g/dl (n = 59; median survival, 14 months) and >3 g/dl (n = 85; median, 31 months) (P<O.OOI); (B) high tumor load (n = 10 1 ; median survival, I8 months) compared with intermediate and low tumor load (n = 43; median, 41 months) (P < 0.001); and (C) hematocrit values 525% (n = 49; median survival, 11 months) versus >25% (n = 95; median, 29 months) (P = 0.001).

FIG. 3. Kaplan-Meier plots of survival curves, analyzed by the Gehan test, of 123 myeloma patients from block groups with (A) overcrowding levels of >5% (n = 22; median survival, 10 months) compared with crowding levels 5 5 % (n = 101; median, 27 months) (P < 0.001); (B) 10% or more families below the poverty level (poverty > 10%) (n = 82; median survival, 18 months) versus an incidence of less than 10% (poverty (10%) (n = 41; median, 29 months) (P = 0.01); and (C) an unemployment level >30% (n = 42; median survival, 18 months) compared with unemployment ~ 3 0 % (n = 81; median, 27 months) (P = 0.01).

100

80

$ 6 0

5 40

(I

$

t-

0 P 2 20

0

A

*---a Albumin > 3 q l d l

L. .._ 20 40 60 80 100

0 20 40 60 80 100

M Hematocril 5 2 5 %

O--+ Hematocril > 2 5 %

\--a ... -1. ....,

0 20 40 60 80 100

SURVIVAL TIME fmonthrl

100 o-+ Crowding > 5 %

(I s 2 5 P 3 v)

t- z w 0 P w a

0 20 40 60 80 100

100

(9 80 3 5 2 60 3 v)

40 z c,

M Poverty L 10%

e-0 Poverty < 10%

a....

-bL.. a.....

20 40 60 80 100 0 20 40 60 80 100 0

SURVIVAL TIME fmonfhr)

3090 CANCER December 15 1984 VOl. 54

unemployment (P < 0.00 I), lower educational background (P < 0.001), and more separation and divorce (P < 0.001) (data not shown).

The block groups of HHC patients also differed from those of the subgroup of CPMC black patients. Only 3 of 40 CPMC black patients (7%) resided in block groups with 25% overcrowding in contrast to 17 of 51 HHC patients (33%) (x2 = 7.27; P = 0.007); 24 of 40 CPMC black patients (60%) resided in block groups with a greater than 20% incidence of unemployment in contrast to 44 of 51 HHC patients (86%) (x2 = 6.85, P = 0.009). HHC patients’ block groups were, on the average, also below those of CPMC blacks in terms of family income and educational level, and above them in the incidence of separation and divorce, but these trends were not significant.

By chi-square analysis, the block groups of CPMC black patients differed from those of CPMC whites, with those of the blacks having more families below the poverty level (P < 0.001), lesser education (P < 0.001), lower median income (P < 0.05), and a higher incidence of separation and divorce (P < 0.001); unemployment and overcrowding also tended to be worse for CPMC blacks, but these trends were not significant.

Among patients who died, HHC patients whose block groups’ crowding levels were 55% had a longer mean (+1 SD) survival (17 f 15 months) than those from neighborhoods with greater crowding (8 f 12 months) ( t = 2.50; P = 0.008); similarly, CPMC patients from block groups with 55% crowding had a better mean survival (34 f 27 months) than CPMC patients with a crowding level >5% (19 k 15 months), although this difference was not significant.

Regression Analysis

Stepwise multivariate regression analysis with the proportional hazard model, which included all the clinical and socioeconomic variables, was applied to all cases. This analysis revealed the following to be significant prognostic factors for survival: serum albumin (P = O.OOl), overcrowding (P = 0.001), and hematocrit ( P = 0.03). This analysis also revealed that belonging to either the CPMC black or white groups appeared to provide a survival advantage, although this trend ap- proached significance only for the CPMC black group.

Considering only the HHC patients, a similar analysis revealed overcrowding to be the most important variable related to survival ( P = 0.004), followed by serum albumin (P = 0.10). Overcrowding also tended to be associated with shortened survival in the CPMC black group, although this trend was not significant; among CPMC whites, there was no association between any

socioeconomic factor and survival. Hypoalbuminemia was the most important factor affecting survival in both the CPMC blacks (P = 0.003) and the CPMC whites (P = 0.02) as well as in the combined CPMC population (P = 0.01); the serum calcium level was marginally significant in the combined CPMC group (P = 0.05).

After accounting for the effect of serum albumin, calcium, overcrowding, hematocrit, and hospital group, there was no significant relationship by multivariate analysis between survival and age, sex, tumor burden, serum urate, and BUN levels, radiographic changes, paraprotein type and level, urine light chain excretion, and socioeconomic variables other than overcrowding.

Correlation Between Variables

In the analysis of all 144 patients, the serum albumin was correlated with tumor burden ( r = -0.280; P <0.001) and levels of hematocrit ( r = 0.358; P < O.OOl), serum calcium ( r = -0.375; P < 0.001), and serum urate ( r = -0.222; P = 0.02). In addition, as summarized in Table 4, the albumin level and tumor load were each correlated with several socioeconomic variables; other clinical factors were not correlated with socioeconomic indices. Table 4 also shows the expected correlations between overcrowding and other poverty factors; a similar degree of correlation was noted between all socioeconomic variables (data not shown).

Chemotherapy

Ninety-two percent of patients received chemotherapy (Table 2). For the HHC group, the initial regimen consisted of “pulse” phenylalanine mustard and prednisone therapy’’; CPMC patients received continuous phenylalanine mustard or cyclophosphamide. Among the treated HHC group, 80% were defined as treatment failures because they: (1) failed to show a decrease in paraprotein level of 250% from the pretreatment value when measured 1 month or more after initiation of therapy or (2) died before a second paraprotein deter- mination could be made. In contrast, only 38% of CPMC patients were treatment failures (x2 = 23.94; P < 0.001).

Early Deaths Among HHC Patients

The records of the 28 HHC patients who died in the first 12 months were reviewed in detail to determine whether inadequacies in diagnosis, therapy, or supportive care contributed to early death. One patient refused chemotherapy; another accepted drug treatment but refused dialysis for uremia. In two cases, significant delay in diagnosis occurred. One patient, an alcoholic

No. 12 RACE, POVERTY, AND SURVIVAL IN MULTIPLE MYELOMA - Savage et aZ. 309 1

TABLE 4. Correlations Between Serum Albumin, Tumor Burden, Overcrowding, and Other Socioeconomic Variables in 123 New York City Residents With Multiple Myeloma*

% Families Low

level Overcrowding income Unemployment and divorce level educational below poverty Median Separation

Tumor load r = 0.199 r = 0.156 r = -0.212 r = 0.008 r = 0.180 r = 0.107 P = 0.03 P = 0.08 P = 0.02 P = 0.93 P < 0.05 P = 0.24

Albumin r = -0.158 r = -0.127 r = 0.207 r = -0.257 r = -0.291 r = -0.202 P = 0.08 P = 0.16 P = 0.02 P = 0.004 P = 0.001 P = 0.03

Overcrowding r = 0.447 - r = -0.291 r = 0.311 r = 0.391 r = 0.328 P < 0.001 - P = 0.001 P < 0.001 P < 0.001 P < 0.001

* Pearson product-moment method.

with severe liver disease who died of cavitary tuberculosis and aspiration pneumonia, remained untreated because hyperglobulinemia noted 3 years before death was attributed to liver disease and infection and not investigated further. In another patient who had a previously well- documented diagnosis of lymphocytic lymphoma and who died of pneumonia 7 weeks after the initiation of treatment with phenylalanine mustard and prednisone, an 8-week delay in diagnosis resulted from the loss of a protein electrophoresis specimen and the attribution of symptoms to recurrent lymphoma. In addition, early death occurred in a patient receiving phenylalanine mustard who was given cephalothin only for KlebsieiZa pneumonia in 1967. Excluding these five cases, the median survival of all the remaining HHC patients was 14 months. The other 23 patients who died in the first year were felt to have received optimal care. The most common cause of early death was infection. With the possible exception of the patient with tuberculosis men- tioned above, none of the early deaths were attributable to the presence of disorders unrelated to myeloma.

Clinical Diflerences Bet ween White and Combined Black Groups

In comparing the combined data of the CPMC and HHC blacks with the white group (Table l) , 23 of 98 blacks (24%) had IgA myeloma in contrast to 7 of 46 whites (14%). Similarly, a lambda light chain was identified in 44 of 97 black cases (45%) versus 16 of 44 whites (36%). In patients with IgG myeloma, paraprotein levels exceeded 7 g/dl in 6 of 30 whites (20%) in contrast to only 3 of 57 cases in the combined black group (5%). Seventeen of 46 CPMC blacks (37%) had a hematocrit level I 25% compared to 9 of 46 white patients (20%); among blacks at both hospitals with a BUN level c 30 mg/dl (10.8 mmol/l), 20 of 62 (32%) had a hematocrit level I 25% versus only 3 of 27 white patients ( 1 1%) with this level of renal function. None of these trends were significant.

Survival by Birthplace and Among Non-New York City Residents

Among blacks, the incidence of death in the first year of disease did not differ significantly among patients born in the Caribbean (36%) and the northern (41%) and southern US (38%). For patients who died, the mean (+I SD) survival of CPMC patients residing in New York City (33 f 3 1 months) was not different than that of CPMC patients referred from out of town (34 f 26 months).

Discussion

The comparable survival time of the white and black patients at Presbyterian Hospital suggests that race is not a significant prognostic factor in myeloma. The Southwest Oncology Group also observed no significant interracial difference in survival in a prospective study of 93 black and 389 white patients.12 The earlier age of peak incidence of myeloma reported in black Afri- Cans4.20-22 was not apparent in our series, nor in other reports of blacks in Jamaica' and the US.'2,23 Although our black patients had a slightly higher incidence of IgA paraprotein, as previously reported from South Africa: and of lambda light chains, these differences were not significant. We were unable, therefore, to demonstrate an important effect of race on the character of the disease in New York City patients.

On the other hand, striking differences in presentation, response to therapy, and outcome that were unrelated to race were apparent when the populations from the two hospitals were compared. Harlem Hospital patients, all of whom were black, had a median survival that was far less than that of both the white and the black CPMC groups. The survival of the Harlem patients was also less than that reported in other large series in the literature. 12*13*24-29 In addition, the pattern of the deaths among HHC cases showed that almost one third died in the first 3 months and one half within 1 year of


diagnosis. Failure to evidence even a transient response to standard chemotherapeutic regimens was also much more common in the Harlem group. These differences could be explained neither by a higher incidence of other co-morbid conditions such as alcoholism nor by poorer compliance to treatment in the Harlem Hospital population.

The short survival of the HHC patients could not be attributed to differences in the quality of care. Of the 28 early deaths at HHC, the course of only 5 appeared to be affected by inappropriate delays in diagnosis or supportive care; the median survival of the 23 other early deaths was not significantly different after exclusion of these 5 cases. The lack of effect of hospital per se on outcome by regression analysis also suggests that differences in ancillary services, such as laboratory facilities and nursing, did not contribute significantly to the interhospital difference in survival. In addition, we would be reluctant to attribute the short survival of the Harlem patients to the regimen of standard intermittent alkylating agent and prednisone therapy18 that this group was given, since prospective studies have previously shown continuous and “pulse” regimens to have comparable e f f i c a ~ y . ‘ ~ ? ~ ~ , ~ ~ Differences in care also clearly could not explain the uniformly more adverse prognostic findings of the HHC group at presentation.

Our analysis revealed two factors that either singly or together may account for the occurrence of early mortality in the Harlem Hospital group: (1) the presence of more extensive tumor at diagnosis; and (2) an adverse socioeconomic background which, surprisingly, exerted an effect on survival beyond that of clinical status at presentation.

Harlem Hospital patients had more advanced disease at presentation. In the overall series of 144 patients, shortened survival was associated with well-established adverse clinical features such as high tumor burden, hypoalbuminemia, and anemia. 1 2 , 1 3924-29 I n the HHC group, serum albumin, serum urate, hematocrit, and BUN values were all significantly less favorable than those found in CPMC patients; high tumor load and hypercalcemia also tended to be more common. When high-tumor-load patients only were compared, the Har- lem patients still had significantly poorer prognostic indicators, as reflected by serum albumin and urate levels.

In addition to having more advanced clinical disease at diagnosis, Harlem Hospital patients resided in neighborhoods that were considerably more impoverished. Because we were unable to acquire detailed personal data on patients retrospectively, we employed collective neighborhood data to obtain at least an approximation of their socioeconomic status. The degree to which

individual socioeconomic status can be extrapolated retrospectively from aggregate census block group data is that the overall characteristics of a neighborhood would reflect the socioeconomic standing of individuals, with inevitable inaccuracies in occa- sional subjects, seems a reasonable assumption, however.8,10,30-37 Various socioeconomic factors, such as overcrowding, unemployment, low education level, family income, and the incidence of separation and divorce, which were all strongly correlated with each other, were significantly less favorable for the Harlem Hospital group; even when compared to Presbyterian Hospital black population alone, Harlem Hospital patients resided in poorer areas. By multivariate analysis, one of the socioeconomic indices, overcrowding, was as significant in independently influencing prognosis as the leading clinical factor, hypoalbuminemia. In the HHC group, overcrowding was the only significant prognostic factor by multivariate analysis.

Previous investigators have reported an unfavorable relationship between poverty and survival in various malignancies. Using, as we did, census tract data as indicators of socioeconomic status, women with breast cancer l o and men with carcinoma of the prostate37 from impoverished areas in Virginia were found to have a shorter survival than controls from more affluent neighborhoods. In a study of several different types of neoplasm in Massachusetts, shortened survival was noted in patients from low-income census areas.8 Several in- vestigations using other means of estimating socioeconomic status have also indicated a relationship between poverty and outcome in malignancy. A number of studies have demonstrated better survival in a variety of cancers treated at private hospitals compared to municipal institution^.^^-^^ In an analysis of patients with 39 types of cancer given the same quality of care at the University of Iowa Hospital, indigent patients had a poorer survival in 38 of the tumors studied.’ Previous work has thus shown an effect of socioeconomic status on outcome in cancer but has not compared poverty indices with well-established biochemical indicators of prognosis as was possible in our myeloma patients. Our findings are striking in view of the relatively small size of the series and the admittedly approximate estimate of socioeconomic status afforded by our block group method.

The reason for the relationship between poverty and survival in our myeloma patients was not established. Two hypotheses can be considered: (1) poorer patients seek medical care at a later time after onset of symptoms; and (2) myeloma is a biologically more aggressive disease in the poor. Either explanation is consistent with our finding of more extensive disease, as reflected by clinical

No. 12 RACE, POVERTY, AND SURVIVAL IN MULTIPLE MYELOMA * ,sUVUge et uf. 3093

and biochemical variables, in the patients from impoverished neighborhoods. The survival of poor patients may be short because they are less able or less prone to seek care early in the course of i l l n e ~ s . ~ ’ - ~ ~ Residents of Central Harlem have the lowest per capita number of private physicians in the borough of Manhattan from whom to seek care.44 In an American Cancer Society study of low- and high-income blacks, the former group was less exposed to information about cancer, less aware of its “early warning” symptoms, and less likely to seek medical care when they experienced such sympt0ms.4~ On the other hand, the duration of symptoms before diagnosis did not differ significantly between the subgroups in our study, suggesting that delay in care was not a factor; it is possible, though, that inaccuracies in relating duration of illness might have contributed to this lack of variation.

Other considerations suggest that the biologic characteristics of the disease may have differed in the patients from poorer neighborhoods. The lack of response to chemotherapy was striking. When given regimens similar to those used at Harlem Hospital, myeloma patients with high tumor loads elsewhere have had a higher rate of objective in at least one series,12 the remission rate of high-tumor-load patients was comparable to that of patients with less extensive disease, although remission duration was shorter. A number of other investigators have found shortened survival in poor patients with a variety of malignancies even when corrections were made for the stage of disease at presen- t a t i ~ n . ~ - ” . ~ ~ Studies of Hodgkin’s disease have shown a relatively high prevalence of adverse histologic subtypes and onset in childhood in American and African blacks as well as in South Americans, possibly implicating socioeconomic factors in the biologic behavior of the d i ~ o r d e r . ~ ~ , ~ ~

The mechanisms whereby socioeconomic deprivation might affect the progress of a neoplasm are uncertain. In experimental animals, a stressful environment has been shown to enhance the growth of a variety of lymphoid neoplasms and solid turn0rs.4~ The striking association between hypoalbuminemia and short survival could indicate the poverty-related malnutrition was a critical risk factor, although protein depletion could equally well have been an effect rather than a cause of aggressive disease.48 Protein-malnourished cancer patients have a greater impairment of immunocompetence49 and respond less well to radiotherapy and chemotherapy in terms of toxicity and shrinkage of tumor mass.5o The reason for the strong association between overcrowding and short survival is not clear from our data, but an increase in other forms of pathologic findings has previously been noted both in experimental

and in various clinical settings in humans.34~52~53 Since an excellent animal model for studying the biologic features of myeloma is available,54 the effects of these various factors on tumor growth could be tested.

In summary, although myeloma is more common in blacks, our findings suggest that race itself does not affect the prognosis or clinical behavior of this disease. On the other hand, socioeconomic factors appear to have an impact on survival equivalent to or greater than that of long-established clinical variables such as tumor burden, anemia, hypercalcemia, and hypoalbuminemia. Further clinical observations are warranted; a prospective study should assess the socioeconomic status of individual patients with myeloma and include meticulous ques- tioning of patients and their families to identify duration of illness and delays in care. In addition, in the design of cancer chemotherapy trials, socioeconomic status may need to be considered in the randomization of patients to different regimens, and specific therapies may be required for impoverished patients. Although innovative treatment regimens might improve the outcome for this group of patients over the short run, however, addressing the fundamental socioeconomic disparities would appear to be a more rational approach on a long-term basis.

REFERENCES 1. Blattner WA. Epidemiology of multiple myeloma and related

plasma cell disorders: An analytic review. In: Potter M, ed. Progress in Myeloma. New York Elsevier North Holland, 1980; 1-65.

2. MacMahon B, Clark DW. The incidence of multiple myeloma. J Chronic Dis 1956; 4:508-515.

3. McPhedran P, Heath CW Jr, Garcia J. Multiple myeloma incidence in metropolitan Atlanta, Georgia: Racial and seasonal variations. BIuud 1972; 39:866-873.

4. Jacobson RJ, Shulman G. Plasma cell myeloma and Walden- strom’s macroglobulinemia in black and white South Africans. In: Potter M, ed. Progress in Myeloma. New York Elsevier North Holland, 1980 8 1-9 1.

5. Talerman A. Clinico-pathological study of multiple myeloma in Jamaica. Br J Cancer 1969; 23:285-293.

6. Axtell LM, Myers MH. Contrasts in survival of black and white cancer patients, 1960-1973. J Natl Cancer Inst 1978; 601209-1215.

7. Bureau of Health Statistics and Analysis. Summary of vital statistics 1980 City of New York. New York City Department of Health, 1980.

8. Lipworth L, Abelin T, Connelly RR. Socioeconomic factors in the prognosis of cancer patients. J Chronic Dis 1970; 23:105-116.

9. Berg JW, Ross R, Latourette HB. Economic status and survival of cancer patients. Cancer 1977; 39:467-477.

10. Dayal HH, Power RN, Chiu C. Race and socioeconomic status in survival from breast cancer. J Chronic Dis 1982; 35:675-683.

11. Committee of the Chronic Leukemia-Myeloma Task Force, National Cancer Institute. Proposed guidelines for protocol studies: 11. Plasma cell myeloma. Cancer Chemother Rep 1973; (Suppl)4: 145- 158.

12. Alexanian R, Balcerzak S, Bonnet JD et al. Prognostic factors in multiple myeloma. Cancer 1975; 36:1192-1201.

13. Dune BGM, Salmon SE. A clinical staging system for multiple myeloma: Correlation of measured myeloma cell mass with presenting clinical features, response to treatment, and survival. Cancer 1975; 36:842-854.

3094 CANCER December 15 1984 VOl. 54

14. Kaplan EL, Meier PM. Nonparametric estimation from incom- plete observations. J Am Stat Assoc 1958; 53:457-481.

15. Breslow N. A generalized Kruskal-Wallis test for comparing K samples subject to unequal patterns of censorship. Biometrika 1970; 57579-594.

16. Gehan EA. A generalized Wdcoxon test for comparing arbitrarily singly-censored samples. Biometrika 1965; 52:203-223.

17. Cox DR. Regression models and life-tables. J R Stat Soc [B]

18. Alexanian R, Haut A, Khan AU ez al. Treatment for multiple myeloma: Combination chemotherapy with different melphalan dose regimens. JAMA 1969; 208:1680-1685.

19. Farhangi M, Osserman EF. The treatment of multiple myeloma. Semin Hematol 1973; 10149-161.

20. lyun A, Isaacs-Sodeye A. Multiple myelomatosis in Ibadan: A comparative study. East Afr Med J 1976; 5358 1-586.

21. Otieno LS, Ogada T. Multiple myeloma at Kenyatta National Hospital 1973-1976. East Afr Med J 1977; 54574-578.

22. Mukiibi J, Karimi M, Kyobe J. Multiple myeloma in Kenyan Africans: A prospective study. East Afr Med J 1981; 58:171-180.

23. Rosenbaum L, Marquez C, Galarraga EC. Multiple myeloma in the Negro: A review of 23 cases. J Natl Med Assoc 1958; 50344- 346.

24. Hoogstraten B, Sheehe PR, Cuttner J et al. Melphalan in multiple myeloma. Blood 1967; 30:74-83.

25. Hoogstraten B, Costa J, Cuttner J et a/ . Intermittent melphalan therapy in multiple myeloma. JAMA 1969; 209:25 1-253.

26. Medical Research Council’s Working Party for Therapeutic Trials in Leukaemia. Report on the first myleomatosis trial: Part I. Analysis of presenting features of prognostic importance. Br J Haematol

27. Colls BM, Darlow BA. Multiple myeloma: Prognosis, treatment and survival in an eight year study. Aust NZ J Med 1979; 9:262-268.

28. Dune BGM, Salmon SE, Moon TE. Pretreatment tumor mass, cell kinetics and prognosis in multiple myeloma. Blood 1980; 55:364- 372.

29. Gobbi M, Cavo M, Savelli G, Baccarani M, Tura S. Prognostic factors and survival in multiple myeloma. Analysis of 9 1 cases treated by melphalan and prednisone. Haematologica 1980; 69437-445.

30. Kitagawa EM, Hauser PM. Differential Mortality in the United States: A Study in Socioeconomic Epidemiology. Cambridge: Harvard University Press, 1973.

31. Cohart EM. Socioeconomic distribution of stomach cancer in New Haven. Cancer 1954; 7:455-461.

32. Cohart EM. Socioeconomic distribution of cancer of the female sex organs in New Haven. Cancer 1955; 8:34-41.

33. Cohart EM. Socioeconomic distribution of cancer of the lung in New Haven. Cancer 1955; 8:1126-1129.

34. Struening EL, Rabkin JG, Cohen P, Raabe G, Muhlin GL, Cohen J. Family, ethnic and economic indicators of low birth weight

1972; 34: 187-202.

1973; 24: 123-1 39.

and infant mortality: A social area analysis. Ann NY Acad Sci 1973;

35. Ernster VL, Selvin S, Sacks ST, Austin DF, Brown SM, Win- kelstein W Jr. Prostatic cancer: Mortality and incidence rates by race and social class. Am J Epidemiol 1978; 107:311-320.

36. Devesa SS, Diamond EL. Association of breast cancer and cervical cancer incidences with income and education among whites and blacks. J Natl Cancer Inst 1980 65:515-528.

37. Dayal HH, Chiu C. Factors associated with racial differences in survival for prostatic carcinoma. J Chronic Dis 1982; 3533-560.

38. Linden G. The influence of social class in the survival of cancer patients. Am J Public Health 1969; 59:267-274.

39. Lipworth L, Bennett B, Parker P. Prognosis of nonpnvate cancer patients. J Natl Cancer Znst 1972; 48:ll-16.

40. Pendergrass TW, Hoover R, Godwin JD 11. Prognosis of black children with acute lymphocytic leukemia. Med Pediatr Oncol 1975;

41. Hackett TP, Cassem NH, Raker JW. Patient delay in cancer. N Engl J Med 1973; 289:14-20.

42. Syme SL, Berkman LF. Social class, susceptibility and sickness. Am J Epidemiol 1976; 104:l-8.

43. American Cancer Society. A study of black Americans’ attitudes toward cancer and cancer tests. American Cancer Society, 198 1.

44. Israel M, Roosma H. Determining the critical health problem areas of New York City. Stat Health Rev 1976; 2:27-34.

45. Correa P, O’Conor GT. Epidemiologic patterns of Hodgkin’s disease. lnt J Cancer 1971; 8:192-201.

46. Cohen C, Hamilton DG. Epidemiologic and histologic patterns of Hodgkin’s disease: Comparison of the black and white populations of Johannesburg, South Africa. Cancer 1980; 46: 186-189.

47. Riley V. Psychoneuroendocrine influences on immunocompetence and neoplasia. Science 198 1 ; 2 12: 1 100- 1 109.

48. Costa G. Cachexia, the metabolic component of neoplastic diseases. Cancer Res 1977; 37:2321-2335.

49. Richie E, Copeland EM 111. Nutrition and immunity. In: Van Eys J, Seelig MS, Nichols BL Jr, eds. Nutrition and Cancer. New York: Spectrum, 1979; 55-69.

50. Copeland EM Ill, Rodman CA, Dudrick SJ. Nutritional concepts of neoplastic disease. In: Van Eys J, Seelig MS, Nichols BL Jr, eds. Nutrition and Cancer. New York Spectrum, 1979; 133-156.

51. Calhoun JB. Population density and social pathology. Sci Am

52. Galle OR, Cove WR, McPherson JM. Population density and pathology: What are the relations for man? Science 1972; 176:23-30.

53. Booth A. Urban Crowding and its Consequences. New York: Praeger, 1976.

54. Morse HC 111, Hartley JW, Potter M. Genetic considerations in plasmacytomas of BALB/c, NZB, and (BALB/c X NZB)F, mice. In: Potter M, ed. Progress in Myeloma. New York: Elsevier North Holland, 1980; 263-279.

2 18:87-107.

1: 143-148.

1962; 206:139-148.

Documents

Race, poverty, and survival in multiple myeloma