The Unmet Need in Chronic Lymphocytic Leukemia: Impact of Comorbidity Burden on Treatment Patterns and Outcomes in Elderly Patients

doi:10.4236/jct.2013.48156

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Journal of Cancer Therapy, 2013, 4, 1321-1329

http://dx.doi.org/10.4236/jct.2013.48156 Published Online October 2013 (http://www.scirp.org/journal/jct)

1321

The Unmet Need in Chronic Lymphocytic Leukemia:

Impact of Comorbidity Burden on Treatment

Patterns and Outcomes in Elderly Patients*

Sacha Satram-Hoang1#, Carolina Reyes2,3, Khang Q. Hoang1, Faiyaz Momin1, Sandra Skettino2

1Q. D. Research, Inc., Granite Bay, USA; 2Genentech, Inc., South San Francisco, USA; 3University of California San Francisco, San

Francisco, USA.

Email: #[email protected]

Received September 18th, 2013; revised October 15th, 2013; accepted October 22nd, 2013

License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

ABSTRACT

Introduction: Chronic lymphocytic leukemia (CLL) is a disease of the elderly. Elderly patients often have increased

comorbidity burden and loss of organ reserve that may impact their ability to tolerate cancer therapy. We described real-

world characteristics of typical CLL patients and identified factors predictive of receiving treatment. Methods: A ret-

rospective cohort analysis of 8343 first primary CLL patients was performed using the linked Surveillance, Epidemiol-

ogy, and End Results-Medicare database. Patients were diagnosed from 1/1/1998 to 12/31/2007, >66 years, and con-

tinuously enrolled in Medicare Parts A and B in the year prior to diagnosis. Comorbidity was examined using the Na-

tional Cancer Institute comorbidity index and the Cumulative Illness Rating Scale. Cox and Logistic regression model-

ing assessed patient characteristics predictive of receiving treatment within the first year after diagnosis. Results: Me-

dian follow-up time from diagnosis was 782 days. During the study time period, there were 3366 (40%) treated patients

and 4977 (60%) untreated. Even among those diagnosed with advanced stage (n = 4213), 57% were not treated. Treated

patients were younger at diagnosis compared to untreated (76 vs. 79; p < 0.0001). In general, as age increased, the inci-

dence and severity of comorbidities increased. In multivariate regression analyses, the treatment rate was significantly

lower among patients >80 years, females, and with early stage disease; and significantly decreased with increasing co-

morbidity burden. Conclusions: Age, gender, comorbidity and stage were predictive of receiving treatment. Among

patients with advanced stage, 57% were not being treated possibly due to older age and/or higher comorbidity burden.

Keywords: Chronic Lymphocytic Leukemia; Elderly Patients; Comorbidities; Treatment; Survival

1. Introduction

Chronic lymphocytic leukemia (CLL) is the most com-

mon type of leukemia diagnosed in older adults [1-3],

with 68% of new cases diagnosed in individuals 65 years

or older and median age at diagnosis of 72 years [3,4].

Elderly patients are frequently compromised by concur-

rent pathologic conditions and/or physiological decline

of major organ systems; little is known about the spec-

trum or frequency of comorbidities in CLL patients. Loss

of organ reserve and the comorbidities associated with

aging are considered important determinants of patients’

ability to tolerate the side effects of cancer therapy [5].

However, the majority of CLL clinical trials primarily

enroll younger patients who are otherwise in good health

and are better able to tolerate treatment-related adverse

events [6-9], and this makes optimal treatment strategies

and disease management unclear for typical patients.

Both age and comorbidities are significantly associ-

ated with the prognosis of patients with CLL, with older

age being one of the most significant predictors of over-

all survival [6,10]. Fludarabine, cyclophosphamide, and

rituximab (FCR) is considered the gold standard first-line

treatment for physically fit CLL patients [6,11], but those

with comorbid conditions may receive alternative thera-

pies or a chemotherapy dose reduction in the FCR regi-

men [12-14].

*Funding Source: This study was funded by Genentech, Inc. through a

contract with Q.D. Research, Inc.

Financial Disclosure: Dr. Satram-Hoang, Dr. Hoang, and Mr. Momin

work for Q.D. Research, Inc. in a research and consulting capacity. Dr.

Reyes and Dr. Skettino are employees and shareholders of Genentech

Inc.

#Corresponding author.

The Unmet Need in Chronic Lymphocytic Leukemia: Impact of Comorbidity Burden

on Treatment Patterns and Outcomes in Elderly Patients

1322

Given that elderly, unfit CLL patients have more lim-

ited treatment options, the goal of this study was to un-

derstand the unmet need in a real-world elderly (age-

eligible for Medicare) cohort of patients. First, we char-

acterized who received treatment in terms of demogra-

phic and clinical characteristics, including comorbidities.

Second, we evaluated the patient factors associated with

the likelihood of receiving treatment.

2. Methods

2.1. Data Sources

We utilized population-based claims data from the Sur-

veillance, Epidemiology, and End Results (SEER)-Me-

dicare linked database. Institutional review board appro-

val was waived due to the absence of personal identifiers

in the SEER-Medicare database. As described elsewhere

[15], this database provides information on Medicare pa-

tients included in SEER, a nationally representative col-

lection of 18 population-based registries of all incident

cancers from diverse geographic areas covering approxi-

mately 26% of the United States population. All incident

cancer patients who are reported to the SEER registries

are cross-matched with a master file of Medicare enroll-

ment [16]. Approximately 97% of individuals 65 years or

older are eligible for Medicare and receive Part A cover-

age for inpatient care, skilled nursing care, home health-

care, and hospice care. Approximately 95% of benefici-

aries also subscribe to Part B, which covers physician

services and outpatient care [17]. The SEER-Medicare

linkage includes all persons eligible for Medicare who

were reported to the SEER database through 2007 and

their Medicare claims for inpatient services covered un-

der Part A and outpatient and physician services covered

by Part B through 2009.

2.2. Study Population

Patients eligible for this study were 1) diagnosed with a

first primary CLL from January 1, 1998 to December 31,

2007, 2) age 66 years or older at diagnosis, and 3) con-

tinuously enrolled in Medicare Part A and B during the

12 months prior to diagnosis. Patients were excluded if

their date of death was recorded prior to or during the

same month as the month of diagnosis, if they were en-

rolled in a health maintenance organization (HMO) at

any time during the 12 months prior to diagnosis (be-

cause data were unavailable for these periods), and if

there was documentation of 2 or more claims for chemo-

therapy prior to their diagnosis of CLL (to ensure that

they were previously untreated).

2.3. Study Variables

Registries reporting to the SEER program routinely col-

lect data on: patient demographics (age, race/ethnicity,

residence, and socioeconomic status based on income

and education per census tract); primary tumor site, tu-

mor morphology, and stage at diagnosis; first course of

treatment; and follow-up for vital status. Median annual

household income at the census tract level and the per-

centage of the population who completed specific levels

of education at the ZIP code level were used as a proxy

for socioeconomic status. The SEER site code was used

to identify patients with a diagnosis of CLL. The SEER

database does not provide stage at diagnosis for CLL.

Based on the Rai and Binet staging systems for CLL [18,

19], we created a proxy for stage at diagnosis by classi-

fying patients as “advanced stage disease” if anemia

and/or thrombocytopenia were present in the claims da-

tabase [20].

To identify treated patients, claims for chemotherapy

and immunotherapy administration [21], data were ab-

stracted from 5 merged SEER-Medicare files including

Medicare provider analysis and review (MEDPAR), car-

rier claims (NCH), outpatient claims (OUTSAF), durable

medical equipment (DME), and prescription drug event

(PDE) files. In July 2006, Medicare coverage was ex-

panded to include prescription drugs under Medicare Part

D. Chlorambucil is covered by Medicare Part D and data

for its use were only available from 2007 to 2009 in the

PDE file. Chemotherapy and immunotherapy was char-

acterized and quantified using International Classifica-

tion of Disease (ICD) diagnosis codes, ICD procedural

codes, Current Procedural Terminology (CPT) codes,

Healthcare Common Procedure Coding System (HCPCS)

codes, and revenue center codes. We searched claims for

specific drug codes to identify the type of chemotherapy

or immunotherapy used. The absence of these claims was

interpreted as lack of treatment while the first chemo-

therapy/immunotherapy claim following the date of di-

agnosis indicated the start of therapy.

The National Cancer Institute (NCI) comorbidity in-

dex [22] was calculated for each patient using diagnosis

and procedure codes in the Medicare Parts A and B

claims files to identify the 15 non-cancer comorbidities

from the Charlson Comorbidity Index (CCI) [23]. A

weight is assigned to each condition based on its poten-

tial influence on 2-year mortality, and the weights are

summed to obtain a comorbidity index for each patient.

The CCI accounts for the number and severity of the

conditions with higher scores indicating a greater burden

of comorbid disease.

Comorbidity was also examined using the organ sys-

tems in the Cumulative Illness Rating Scale (CIRS) [24,

25]. The CIRS uses physician ratings of the degree of

pathology and impairment in 14 major organ groups.

Disease severity data were not available in this claims-

based analysis to calculate the total CIRS score. There-

The Unmet Need in Chronic Lymphocytic Leukemia: Impact of Comorbidity Burden

on Treatment Patterns and Outcomes in Elderly Patients

1323

fore, we used diagnosis codes in the Medicare Parts A

and B claims files to identify specific conditions that

belong to each organ system category, and calculated the

“number of involved organ systems” (CIRS-SYS) for

each patient.

The CCI and the CIRS are among the most valid and

reliable measures of multi-morbidity [26]. For both co-

morbidity definitions, Medicare claims during the year

prior to diagnosis were used to determine the baseline

comorbidity burden for each patient. Specific conditions

must have appeared on at least 2 different claims that

were more than 30 days apart to ensure that “rule out”

diagnoses were not counted as comorbid conditions.

The date of death was assigned by using the Medicare

date or SEER date of death if the Medicare date was

missing. All other patients were assumed to be alive at

the end of the follow-up period on December 31, 2009,

although they may have been censored earlier for other

reasons such as development of a second primary cancer

or Medicare claims data no longer available.

2.4. Statistical Analysis

All statistical analyses were performed using SAS soft-

ware, version 9.1.3 (SAS Institute Inc., Cary, North

Carolina). Using the frequency procedure in SAS, we

examined the distribution of patient demographic and

clinical characteristics by treatment status for all CLL

patients and a subset of patients diagnosed at advanced

stage. Differences by treatment status were assessed us-

ing Chi-square tests for categorical variables and analysis

of variance (ANOVA) or t-tests for continuous variables.

We used two methods to determine the predictors of re-

ceiving treatment within the first year after diagnosis.

The Cox Proportional Hazards regression modeled time

to treatment and the logistic regression modeled the odds

of receiving treatment. Predictor variables in the models

were selected from demographic and clinical characteris-

tics. Kaplan-Meier survival curves and corresponding

log-rank tests were generated to determine unadjusted

OS by comorbidity burden. Follow-up was calculated

from the date of diagnosis up until the first occurrence of

a censoring event including date of death, development

of a second primary tumor, the last date for which Medi-

care claims were available, or the end of the follow-up

period (December 31, 2009). Differences with a prob-

ability of p < 0.05 were considered statistically signifi-

cant.

3. Results

3.1. Demographic & Clinical Characteristics

Of the 8343 CLL patients who met all the study eligibil-

ity criteria, the mean age at diagnosis was 78, with 57%

of the cohort age 75 years or older. The majority were

male (54%) and white (92%). There were 3366 (40%)

patients who received treatment and 4977 (60%) who

never received treatment during follow-up. The mean age

at diagnosis was 76 for those administered treatment

compared with 79 in the untreated group (p < 0.0001).

Patients older than 80 years comprised 40% of the un-

treated cohort compared with 23% in the treated cohort.

Treated patients were more likely to present with ad-

vanced stage (65%) than those who were not treated

(48%).

Approximately half of all CLL patients were diag-

nosed with advanced disease (n = 4213). There was a

slightly higher mean age at diagnosis (79 years) in this

subset compared to all CLL patients. Of patients who

were diagnosed with advanced disease 1805 (43%) re-

ceived treatment while 2408 (57%) did not. Similar to

the overall treated population, patients with advanced

disease who received treatment were also more likely to

be younger (77 vs 80 years; p < 0.0001) and male (57%

vs 49%; p < 0.0001). (Table 1)

3.2. Comorbidity Burden

Treated patients were generally healthier than those who

were not treated as indicted by the lower NCI comorbid-

ity scores and number of CIRS organ systems affected (p

< 0.0001; Table 1). As age increased, the incidence and

severity of comorbidities as assessed by both the NCI

and CIRS-SYS comorbidity scores increased (Figure 1).

Among patients in the highest comorbidity categories

(CIRS-SYS ≥ 4 and NCI Score ≥ 3), 39% to 43% respec-

tively were > 80 years old.

More than half of the patients had comorbidities in-

volving the Blood Pressure System, followed by 44% of

patients with comorbidities related to the Vascular Sys-

tem and/or the Heart System (Table 2). In general,

treated patients had fewer affected organ systems com-

pared to untreated patients. Patients with advanced dis-

ease had higher rates of affected organ systems compared

to the general CLL population. The most common spe-

Figure 1. Comorbidity burden by age at diagnosis.

The Unmet Need in Chronic Lymphocytic Leukemia: Impact of Comorbidity Burden

on Treatment Patterns and Outcomes in Elderly Patients

1324

Table 1. Demographic and clinical characteristics at baseline.

All CLL Advanced Stage

Characteristics Total

(N = 8343) Treated

(N = 3366) Not Treated

(N = 4977) Treated

(N = 1805) Not Treated

(N = 2408)

Age at Diagnosis % % % P-value% % P-value

66 - 70 19.9 23.4 17.5 19.0 12.5

71 - 75 23.0 27.0 20.2 23.6 16.6

76 - 80 23.9 26.6 22.1 29.0 22.1

>80 33.2 22.9 40.1

<0.0001

28.4 48.9

<0.0001

Sex

Male 54.2 58.3 51.4 56.8 49.3

Female 45.8 41.7 48.6

<0.0001

43.2 50.7

<0.0001

Race/ethnicity

White 92.4 91.8 92.8 90.5 91.0

Non-white 7.6 8.2 7.2

0.1090

9.5 9.0

0.6177

Stage*

Non-advanced 49.5 46.4 51.6

Advanced 50.5 53.6 48.4

<0.0001

CIRS-SYS

0 11.9 12.7 11.4 10.0 6.4

1 - 3 47.4 50.7 45.2 44.7 38.2

≥4 40.7 36.6 43.4

<0.0001

45.3 55.4

<0.0001

NCI Comorbidity Score

0 57.7 61.4 55.2 54.4 45.5

1 24.1 23.3 24.6 25.0 26.5

2 10.5 9.1 11.4 11.2 13.9

≥3 7.7 6.2 8.8

<0.0001

9.4 14.1

<0.0001

Abbreviations: CIRS-SYS, number of organ systems involved in the Cumulative Illness Rating Scale; NCI, National Cancer Institute; Note: *Advanced stage

disease was approximated by the presence of anemia and/or thrombocytopenia in the claims data.

cific comorbidities were hypertension (53%), hyperlipi-

demia (38%), coronary artery disease (24%), diabetes

(21%), and osteoarthritis (21%), and these rates were

higher for advanced stage patients compared to the gen-

eral CLL population, and in the untreated subgroups

(Supplementary Table 1). In the unadjusted overall sur-

vival analysis, as CIRS-SYS and NCI comorbidity scores

increased, unadjusted overall survival decreased (log

rank p < 0.0001; Figure 2).

In patients diagnosed with advanced disease, treated

patients had lower NCI and CIRS-SYS comorbidity

scores (Table 1) and a lower proportion of each type of

CIRS organ system involved (Ta ble 2) compared with

untreated patients.

3.3. Predictors of Treatment

In the Cox multivariate regression analysis of time to

treatment within the first year after diagnosis (Table 3),

the treatment rate was significantly lower among patients

>80 years old (HR = 0.51; 95% CI = 0.46 - 0.56) and

among females (HR = 0.86; 95% CI = 0.80 - 0.92). The

treatment rate significantly decreased with higher CIRS-

SYS. In a sensitivity analysis, the models were virtually

unchanged when replacing CIRS-SYS with NCI comor-

bidity score. Compared to patients diagnosed at an earlier

stage disease, advanced stage patients had a significantly

higher treatment rate (HR = 1.47; 95% CI = 1.37 - 1.58).

Findings from the logistic regression analysis of treat-

ment within the first year after diagnosis were generally

consistent with those from the Cox regression analysis.

4. Discussion

This observational study revealed that about 60% of all

CLL patients are not receiving treatment for their disease.

The Unmet Need in Chronic Lymphocytic Leukemia: Impact of Comorbidity Burden

on Treatment Patterns and Outcomes in Elderly Patients

1325

Table 2. Cumulative illness rating scale organ system type by treatment status.

All CLL Advanced Stage

Total

(N = 8343) Treated

(N = 3366)

Not Treated

(N = 4977) Treated

(N = 1805)

Not Treated

(N = 2408)

Organ System

% % % P-value % % P-value

Blood Pressure 53.1 51.0 54.5 0.0017 68.6 74.4 <0.0001

Vascular 44.4 43.4 45.1 0.1360 67.0 67.1 0.9523

Heart 43.9 40.8 45.9 <0.0001 63.8 71.3 <0.0001

Endocrine/Metabolic 31.1 28.8 32.7 0.0002 46.5 50.7 0.0061

Genitourinary 29.6 29.8 29.6 0.8350 49.0 54.2 0.0009

Musculoskeletal 29.1 27.0 30.6 0.0004 43.5 52.2 <0.0001

Respiratory 21.0 19.9 21.7 0.0482 39.1 41.6 0.1081

Neurological 16.9 13.0 19.6 <0.0001 24.0 36.1 <0.0001

Upper GI 12.4 12.3 12.4 0.8197 27.5 28.4 0.5143

Lower GI 10.7 10.1 11.1 0.1727 26.6 28.4 0.2178

Psychiatric 9.5 5.2 12.4 <0.0001 11.2 26.9 <0.0001

Ear/Nose/Throat 6.6 7.3 6.1 0.0365 12.4 10.3 0.0316

Renal 5.7 4.3 6.7 <0.0001 13.2 18.8 <0.0001

Liver 2.3 2.3 2.2 0.7258 10.1 8.8 0.1727

No CIRS Comorbidity 11.9 12.7 11.4 0.0691 2.0 0.7 0.0001

Abbreviations: CLL, chronic lymphocytic leukemia; GI, gastrointestinal.

Figure 2. Unadjusted overall survival by comorbidity burden.

This high non-treatment rate may be partly explained by

the “watch and wait” strategy for asymptomatic disease.

Historically, patients with low- or intermediate-risk early

stage disease are managed with active surveillance

(watch and wait) while treatment is indicated for patients

with advanced disease [2,27]. However, understanding

the intent of treatment or no treatment is a challenge with

claims-based investigations. In our study, we used “ad-

vanced stage disease” as an indicator of higher risk status

and thus likely eligibility for treatment, making the high

non-treatment rate (57%) in this subgroup noteworthy.

The high proportion of advanced stage patients who went

untreated may be explained by the medical fitness of

patients. This is evidenced by the slightly older at diag-

The Unmet Need in Chronic Lymphocytic Leukemia: Impact of Comorbidity Burden

on Treatment Patterns and Outcomes in Elderly Patients

1326

Table 3. Multivariate analysis of treatment within the first year after diagnosis.

Cox Model of Time to Tr ea t ment Logistic Regression of Treatment

Characteristics N HR 95% CI OR 95% CI

Age at Diagnosis

66 - 70 (ref) 1661

71 - 75 1917 1.00 0.91 - 1.10 1.06 0.90 - 1.25

76 - 80 1996 0.91 0.83 - 1.01 0.97 0.83 - 1.15

>80 2769 0.51 0.46 - 0.56 0.62 0.53 - 0.73

Sex

Male (ref) 4521

Female 3822 0.86 0.80 - 0.92 0.76 0.68 - 0.86

Race/ethnicity

Non-White (ref) 632

White 7711 0.96 0.85 - 1.09 1.02 0.83 - 1.27

Stage*

Non-advanced (ref) 4130

Advanced 4213 1.47 1.37 - 1.58 2.29 2.04 - 2.58

CIRS-SYS

0 (ref) 993

1 - 3 3957 0.97 0.87 - 1.08 0.64 0.55 - 0.77

≥4 3393 0.79 0.70 - 0.88 0.56 0.47 - 0.67

Geographic region

MidWest (ref) 1077

Northeast 533 1.07 0.90 - 1.27 0.94 0.72 - 1.25

South 3760 1.08 0.97 - 1.21 0.95 0.80 - 1.13

West 2973 1.06 0.95 - 1.19 0.91 0.78 - 1.10

Median Income Quartiles

1-Low (ref) 2166

2 2059 1.06 0.96 - 1.17 1.09 0.93 - 1.29

3 2061 1.12 1.02 - 1.24 1.15 0.99 - 1.36

4-High 2057 1.12 1.01 - 1.23 1.12 0.96 - 1.33

Abbreviations: CIRS-SYS, number of organ systems involved in the Cumulative Illness Rating Scale; Note: *Advanced stage disease was approximated by the

presence of anemia and/or thrombocytopenia in the claims data.

nosis and/or higher comorbidity burden in advanced

stage patients compared to all CLL patients. Although

our multivariate regression models confirmed that ad-

vanced stage patients had a 47% higher likelihood of

receiving treatment compared to patients with non-ad-

vanced disease; both older age and higher comorbidity

were significant independent predictors of decreased

likelihood of receiving treatment and appear to carry

more weight, rather than disease stage, in clinicians’ de-

cisions to treat.

Major comorbidities were evident in 42% of the pa-

tients based on the NCI comorbidity index while 41%

had multiple comorbidities involving at least 4 organ

systems according to the CIRS. The frequency of comor-

bidities in our analysis is comparable to the rate of 46%

reported by Thurmes and colleagues in an analysis of

1195 patients newly diagnosed with CLL at the Mayo

Clinic from 1995 to 2006 [10]. The median age at diag-

nosis in that study was 68 years compared to 77 in the

current study. In the current analysis, a simple count of

affected organ systems based on the CIRS revealed at

least one coexisting medical condition (regardless of se-

verity) for 88% of patients. This was also consistent with

the 89% of patients with at least one coexisting medical

condition reported by Thurmes and colleagues [10].

The CIRS has been utilized as a tool for some clinical

The Unmet Need in Chronic Lymphocytic Leukemia: Impact of Comorbidity Burden

on Treatment Patterns and Outcomes in Elderly Patients

1327

investigators in order to identify patients with coexisting

medical conditions that might influence the efficacy and

safety of treatment [28].

Importantly, among patients in the highest comorbidity

categories (CIRS-SYS ≥ 4 and NCI Score ≥ 3), 39% to

43% respectively were >80 years old. We found that

higher comorbidity was associated with decreased unad-

justed overall survival. However, this finding may be

confounded by the fact that the presence of comorbidities

may have resulted in the decision to withhold treatment

due to tolerability concerns; and this lack of treatment

may have contributed to the lower overall survival.

Patient preferences, physicians’ tendencies to treat pa-

tients according to chronologic age and lack of evidence-

based guidelines for treating elderly patients are cited as

factors that lead to under-treatment [29]. There is a great

need in CLL to evaluate efficacy and safety of treatment

in trials that include more elderly patients so that treat-

ment strategies for elderly patients can be better sup-

ported by clinical trial results.

Study Strengths and Limitations

This study has several strengths, including the large

sample size from the SEER-Medicare database, a popu-

lation-based registry that includes a wide geographic

representation of patients with a diagnosis of CLL in the

United States. The database includes information about

inpatient and outpatient claims, covered services, all

claims regardless of residence or service area, and longi-

tudinal data with claims for services from the time a per-

son is eligible for Medicare until the date of death.

However, use of the SEER-Medicare data for this type of

analysis has some limitations, particularly for determin-

ing accurate utilization rates of oral chemotherapy. Medi-

care claims data more accurately identify agents that are

intravenously administered since oral agents are covered

under Medicare Part D [30] and it is estimated that only

53% of Medicare beneficiaries with cancer were enrolled

in Medicare Part D in 2009 [31]. Incomplete enrollment

in Medicare Part D may be a factor that contributed to

our finding of low treatment rates due to the lack of treat-

ment information for patients who only received oral

agents or who may have received these oral treatments

prior to their coverage from Medicare Part D.

The SEER registry does not collect staging informa-

tion for leukemia. We included claims for anemia and/or

thrombocytopenia as a surrogate for advanced stage and

this may not adequately assess stage for all patients in

our study. Also, the use of anemia as a marker of disease

severity may be subject to bias as there may be multiple

causes of anemia in elderly patients, such as renal im-

pairment. The incidence of renal impairment increases

significantly in this age group. However, <6% of our

entire cohort had renal impairment making it unlikely to

introduce significant bias into the analysis.

The SEER-Medicare database also does not provide

data on performance status or lifestyle factors. These

factors could affect the treatment rates we observed or

clinicians’ decision to treat these patients. This analysis

also does not provide information about patients enrolled

in HMOs since claims data for these patients are not col-

lected by Medicare. It is conceivable that treatment pat-

terns, and prognosis may differ between HMO and Me-

dicare enrollees. Another area that warrants further re-

search is a comparison of the treatment patterns and out-

comes of patients enrolled in HMOs compared with

those in fee-for-service plans. Research is also required

to evaluate patterns and outcomes of care for patients

with varying performance status since this information is

not included in the SEER-Medicare database and we

were unable to examine possible interactions between

performance status and probability of receiving treat-

ment.

Furthermore, our assumption that patients with multi-

ple CIRS conditions have a higher comorbidity burden

may be subject to interpretation error since we had no

information about the severity of comorbidities. The da-

tabase did not provide information about the length of

time since the patient was diagnosed with a specific co-

morbid condition or the impact of comorbidity on per-

formance status and activities of daily living. However,

given the nature of the claims-based data source, we as-

sumed that the conditions were of sufficient severity

(moderate to severe) to warrant consultation with a phy-

sician or receipt of treatment for the condition that re-

sulted in a claim.

5. Conclusion

In summary, this real-world analysis of Medicare eligible

CLL patients showed that regardless of disease stage,

elderly patients with a high comorbidity burden are less

likely to receive treatment for their disease. The current

findings suggest an opportunity to improve treatment ap-

proaches of elderly patients with coexisting medical con-

ditions in order to achieve more favorable clinical out-

comes in an increasingly aging population.

6. Acknowledgements

The authors would like to thank Mr. Sridhar Guduru for

programming support, Dr. Michelle Byrtek for statistical

consult, Dr. Jia Li for thoughtful review of the manu-

script and Carole Alison Chrvala PhD, of Health Matters,

Inc. for editorial assistance. We acknowledge the efforts

of the Applied Research Program, NCI (Bethesda, MD),

the Office of Information Services and the Office of Stra-

tegic Planning, Health Care Financing Administration

The Unmet Need in Chronic Lymphocytic Leukemia: Impact of Comorbidity Burden

on Treatment Patterns and Outcomes in Elderly Patients

1328

(Baltimore, MD), Information Management Services, Inc.

(Silver Spring, MD), and the Surveillance, Epidemiology,

and End Results (SEER) Program tumor registries in the

creation of the SEER-Medicare database. The interpreta-

tion and reporting of these data are the sole responsibility

of the authors.

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Supplementary Table 1. Cumulative illness rating scale conditions by treatment status.

All CLL Advanced Stage

Top CIRS Conditions (Organ System) Total

(N = 8343) Treated

(N = 3366)

Not Treated

(N = 4977)

Treated

(N = 1805)

Not Treated

(N = 2408)

(%) (%) (%) (%) (%)

Hypertension (Blood Pressure) 53.1 51.0 54.5 55.3 60.8

Hyperlipidemia(Vascular) 37.5 38.9 36.6 43.1 40.3

Coronary Artery Disease (Heart) 23.8 23.3 24.2 28.0 30.7

Diabetes (Endocrine) 21.1 20.2 21.8 23.8 25.5

Osteoarthritis (Musculosketal) 20.9 19.5 21.8 22.8 25.8

Atrial Fibrillation (Heart) 19.8 17.9 21.0 21.4 26.5

Chronic Obstructive Pulmonary Disease (Respiratory) 15.6 14.5 16.4 17.3 20.3

BPH (Genitourinary) 14.1 16.0 12.8 17.3 14.1

Congestive Heart Failure (Heart) 13.6 9.9 16.1 13.9 22.3

Hypothyroid (Endocrine) 12.6 11.3 13.5 14.3 16.2

Urosepsis (Genitourinary) 12.2 10.0 13.6 12.1 18.0

Cerebral Vascular Accident (Neurological) 11.8 9.9 13.1 12.5 17.4

Osteoporosis (Musculoskeletal) 10.9 9.3 12.0 10.7 14.5

Valvular Disease (Heart) 10.3 9.6 10.8 12.5 14.7

Acute Urinary Retention (Genitourinary) 10.2 9.9 10.4 11.5 12.7

Abbreviations: CIRS, Cumulative Illness Rating Scale.