SEARCH

SEARCH BY CITATION

Keywords:

  • breast cancer;
  • survivorship;
  • quality of life;
  • chemotherapy

Abstract

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. Conflict of Interest Disclosures
  8. References

BACKGROUND:

The Survivor's Health and Reaction (SHARE) study examined health-related quality of life (HRQL) in breast cancer patients who had participated in Cancer and Leukemia Group B Trial 8541 from 1985 to 1991.

METHODS:

In total, 245 survivors (78% of eligible patients) who were 9.4 to 16.5 years postdiagnosis (mean, 12.5 years postdiagnosis) completed HRQL surveys relating to 5 domains. Analyses examined HRQL domains according to 3 different chemotherapy dose levels that were administered in the original treatment trial: low-dose cyclophosphamide, doxorubicin, and fluorouracil (CAF) at 300 mg/m2, 30 mg/m2, and 300×2 mg/m2, respectively, over 4 cycles; standard-dose CAF at 400 mg/m2, 40 mg/m2, and 400×2 mg/m2, respectively, over 6 cycles; and high-dose CAF at 600 mg/m2, 60 mg/m2 and 600×2 mg/m2, respectively, over 4 cycles.

RESULTS:

In univariate analyses, a statistically significant difference was observed on the Medical Outcomes Study 36-item short form Physical Role Functioning subscale by treatment group, with lower mean scores in the standard treatment arm (mean, 65.05) compared with mean scores in the low-dose arm (mean, 74.66) and the high-dose arm (mean, 84.94; P.0001). However, multivariate analysis revealed that treatment arm no longer was statistically significant, whereas the following factors were associated with decreased physical role functioning: age ≥60 years (odds ratio [OR], 3.55; P = .006), increased comorbidity interference total score (OR, 1.64; P = .005), lower vitality (OR, 1.05; P = .0002), and increased menopausal symptoms (OR, 1.04 P = .02).

CONCLUSIONS:

At 9.4-16.5 years after their original diagnosis, differences in physical role functioning among breast cancer survivors who had received 3 different dose levels of chemotherapy were explained by clinical and demographic variables, such as age, fatigue, menopausal symptoms, and comorbidities. Prospective studies are needed to further assess the role of these factors in explaining HRQL and physical role functioning among long-term survivors. Cancer 2009. © 2009 American Cancer Society.

Advances in early detection and treatment have led to increased numbers of breast cancer survivors, totaling approximately 2.4 million in 2007.1, 2 This increase in survivors raises concerns about the long-term effects of cancer treatment on health-related quality of life (HRQL).

Several studies have reported good overall HRQL among long-term survivors but have identified issues, such as sexual concerns, psychosocial problems, and physical symptoms, including pain and lymphedema.3-7 It has been demonstrated that the adverse effects of systemic adjuvant therapy (chemotherapy) on global HRQL, physical functioning, bodily pain, and sexual functioning worsen 5 to 10 years after the initial diagnosis in patients with breast cancer.3, 6

Ahles et al. revealed gaps in knowledge regarding the effects of cancer treatment in long-term breast cancer survivors, because few studies exist.8 Ganz et al. observed few differences in the effects of adjuvant treatment on HRQL and emotional functioning in breast cancer survivors 3 years post-treatment but discovered significant differences in global HRQL, general health, and physical and social functioning after 6 years of follow-up.9 Bottomley et al. reported declines in HRQL 3 months after treatment but observed that these effects largely had diminished 3 years post-treatment.10 Ahles et al. also emphasized the importance of assessing the impact of chemotherapy on HRQL to make cancer survivors aware of potentially negative outcomes of cancer treatment and for the development of interventions to cope with negative side effects of treatment.8 Thus, past studies have produced inconsistent results regarding the effects of adjuvant chemotherapy on long-term HRQL. This issue has important implications for breast cancer survivors and, thus, needs further study.

The theoretical framework for this study was derived from the quality-of-life model adapted for cancer survivors by Dow et al. and Ferrell et al (Fig. 1).5, 11 The model identifies 4 major areas of HRQL in cancer patients: physical, psychological, social, and spiritual well being. It has been tested in several studies with specific issues identified within each domain.12, 13 In the current study, the social well being area was subdivided into social and economic well being. Thus, 5 domains plus medical and demographic variables were assessed.

thumbnail image

Figure 1. The quality-of-life (QOL) model was adapted for breast cancer survivors (adapted from Dow et al.5 and Ferrell et al.11)

Download figure to PowerPoint

The primary objective of the current study was to assess whether adjuvant chemotherapy dose of a commonly used breast cancer treatment regimen (combined cyclophosphamide, doxorubicin, and fluorouracil [CAF]) was associated with differences in 5 HRQL domains (physical, psychological, social, spiritual, and economic) among long-term breast cancer survivors (9-16 years after their initial diagnosis) who had participated in Cancer and Leukemia Group B (CALGB) Treatment Trial 8541. Because of conflicting evidence from past studies and because these women had survived for 9 to 16 years, we hypothesized that there would be differences among the treatment arms that could result in higher or lower HRQL. Our secondary objective was to identify factors that currently exhibited significant differences by treatment arm, such as comorbidities, treatment variables, and demographic variables, including age, education, and socioeconomic status (SES). The identification of these factors may be useful for interventions to improve HRQL among long-term survivors.

MATERIALS AND METHODS

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. Conflict of Interest Disclosures
  8. References

Setting

The current study (CALGB 79804) examined HRQL in breast cancer patients who had participated in CALGB 8541 from 1985 to 1991. The objective of CALGB 8541 was to determine whether a dose-dependent relation existed between disease-free survival, dose, and dose intensity for patients with stage II breast cancer who were assigned randomly to receive 1 of the following CAF adjuvant therapy regimens for surgically resected breast cancer: low-dose CAF (cyclophosphamide 300 mg/m2, doxorubicin 30 mg/m2, and fluorouracil 300×2 mg/m2 over 4 cycles), standard-dose CAF (400 mg/m2, 40 mg/m2, and 400×2 mg/m2, respectively, over 6 cycles), and high-dose CAF (600 mg/m2, 60 mg/m2, and 600×2 mg/m2, respectively, over 4 cycles).14, 15

The results of the trial indicated that, after a median follow-up of 3.4 years, women who received high- or standard-dose/intensity CAF had significantly longer disease-free survival (P < .001) and overall survival (P = .004) than women who received low-dose/intensity CAF in log-rank comparisons with 3 degrees of freedom.14, 15 The difference in survival between the 2 groups that received standard- and high-dose/intensity was not significant.

Of 1572 women who were randomized in the CALGB 8541 trial, approximately 618 women were alive and cancer-free when the current study began in 1999. Because accrual for CALGB 8541 occurred from 1985 to 1991, participants in this study were 9.4 to 16.5 years postdiagnosis (mean, 12.5 years postdiagnosis). The study was approved by the institutional review boards of each participating institution, and all patients provided informed consent before participating in this study.

Procedures

Details of the study methods have been provided elsewhere.16 In brief, clinical research associates (CRAs) at CALGB treating institutions were notified of patient eligibility by the CALGB Statistical Center. CRAs confirmed patient disease status (alive and disease-free) and informed the treating physician of the study. Next, either the CRA contacted the patient about the study, or an introductory letter was sent from the principal investigator (E.P.) noting the physician's permission to contact the patient. A consent form and questionnaire were sent, which were completed, signed, and returned by the women who wished to participate. Nonrespondents were contacted by telephone to complete the survey (N = 8), if necessary. When they completed the questionnaire, patients were registered with the CALGB Statistical Center.

In total, 618 women from 42 CALGB institutions were identified by the CALGB Statistical Center for potential participation in this study. Eligibility criteria consisted of participation in CALGB 8541, breast cancer-free for 12 months, free of other cancers in the past 5 years (except basal/squamous skin or in situ cervical cancers), physician approval to participate, and ability to complete the English-language questionnaire. Figure 2 shows the exclusions that were made. Reasons for ineligibility included death or disease recurrence and lack of physician approval. Thus, 314 women were eligible to participate, and 245 women (78%) returned the surveys. Participants did not differ significantly from nonparticipants (CALGB 8541 survivors who were not eligible to participate in the follow-up study) by age, treatment arm, number of positive lymph nodes, or age/year of entry in CALGB 8541 (data not shown). However, more white survivors than nonwhite survivors chose to participate (93% vs 81%; P < .0001).

thumbnail image

Figure 2. This chart illustrates accrual to and eligibility for the Survivor's Health and Reaction Study. CALGB indicates Cancer and Leukemia Group B.

Download figure to PowerPoint

Measures

The following questionnaires were used to assess HRQL domains by treatment arm in this study, and higher scores represented increased levels of the outcome assessed.

Quality of life
The Medical Outcomes Study 36-item short form

Overall HRQL was assessed using 8 dimensions on the Medical Outcomes Study (MOS) 36-item short form (SF-36): physical functioning, role limitations, bodily pain, general health perceptions, vitality (fatigue), social functioning, emotional well being, and perceived changes in health status.17, 18 Subscales were scored from 0 to 100, and higher scores indicated better HRQL. Lower vitality scores indicated greater fatigue.

Psychological well being
Center for Epidemiologic Studies Depression Scale (20 items)

Depression was measured with a total score that was dichotomized using a score ≥16 to reflect the possible presence of depression.19

Breast Cancer Anxiety and Screening Behavior Scale

This modified 21-item scale assessed the emotional and cognitive aspects of breast cancer20 and demonstrated high validity with breast cancer worries and generalized anxiety scales.20-23 All subscales were examined, including intrusive and avoidant thoughts and total cognitive distress.

Social well being
Medical Outcomes Study Social Support Survey

This validated, 20-item survey measured 4 areas of perceived social support: emotional/informational, tangible, affectionate, and positive social interaction.24, 25 All subscale scores and the total score were examined.

Life Events Scale

Stressful life events were assessed with this 11-item survey, which has been used in past studies.26 Both the number and frequency of events were examined.

Spiritual well being
System of Beliefs Inventory

Religious/spiritual beliefs were measured with this 15-item scale.27 Two subscales, Spiritual Beliefs Practices and Community Social Support, and the total score were examined.

Economic well being
Employment and insurance difficulties attributed to cancer

The overall impact of breast cancer diagnosis on employment and insurance was assessed with 2 questions from this survey,28 which were developed for previous CALGB survivor studies.7, 29

Physical well being
Your Health-short form

This modified version of the validated Older Americans Resources and Services comorbidity scale30 assessed the following illnesses/comorbidities (no/yes): heart disease, osteoporosis, high blood pressure, diabetes, circulation problems in arms/legs, stroke, depression, chronic liver/kidney disease, stomach/intestinal disorders, osteoporosis, arthritis, glaucoma, and emphysema. An ‘interference score’ (ie, interference with daily activities) was assessed using a 3-point scale (1, not at all; 2, somewhat; 3, a great deal).30

Pain and Lymphedema Questionnaire

This 12-item module documented the occurrence and duration of treatment-related swelling and pain in the arms/hands.31

Menopause and Reproductive Health Questionnaire

This 47-item survey asked participants whether they had experienced particular physical symptoms (yes/no) and whether the severity was mild, moderate, or severe. A total score assessed both frequency and severity.

Medical information/demographics

The medical file in the CALGB 8541 database provided demographics and the following information: date of study entry, treatment arm, menopausal status (at diagnosis), the number of positive lymph nodes at diagnosis, tumor size, histologic grade, estrogen receptor (ER) status, and performance status (according to the Karnofsky performance scale32). Current demographics, such as age, education, income, and insurance status, were obtained from a supplemental demographic survey for the current study.

Analysis

Statistical analyses were performed by statisticians at the CALGB Statistical Center (J.H. and K.D.). Descriptive statistics were used to characterize HRQL domains and clinical characteristics of survivors by treatment arm. Power analyses for this study revealed 90% power to detect a clinically significant difference in physical role functioning, in which 1 group differed from the other groups by >0.5 standard deviations, assuming α = .05 (2-sided) and sample sizes of 74 patients, 93 patients, and 8 patients for the low-, standard-, and high-dose groups, respectively.33

Because of skewed distributions and a ceiling effect for many of the survey scores, the nonparametric Kruskal-Wallis test was used to compare survey scores by treatment arm. All other categorical data were analyzed using the Fisher exact test. The Jonckhere-Terpstra34 test was used to test for a dose-response relation between treatment dose and survey score. Statistical tests were calculated using exact methods from Monte Carlo simulations and were 2-sided, using α = .05. The null hypothesis in these comparisons was that there were no differences in survey scores between treatment arms. The alternative hypothesis was that at least 1 arm had a significantly higher or lower score compared with the other arms.

The correlation between treatment arm and physical role functioning was analyzed using logistic regression. Physical role functioning, which was the outcome for this analysis because it was the only HRQL variable that demonstrated a statistically significant association with treatment arm (P = .001), was dichotomized (100 vs <100) because of the discrete nature of the distribution. Higher SES was defined as having private health insurance, having a household income ≥$20,000, and being a high school graduate; otherwise, women were classified as having lower SES.35 Other variables in the logistic regression analysis were age at interview (≥60 years vs <60 years), the number of comorbidities (0 vs ≥1), the type of surgery (lumpectomy vs mastectomy), ER status (negative vs positive), hormone therapy (no vs yes), radiation therapy (no vs yes), high blood pressure interfering with daily life (no/not applicable vs yes), diabetes interfering with daily life (no/not applicable vs yes), vitality score, menopausal symptom score, comorbidity interference total score, and time since diagnosis, which was stratified by its median (12.3 years). Variables that were significant at the 25% level based on the Wald chi-square test were included in the multivariate model using stepwise selection methods. The selection criterion was based on the score chi-square statistic, using α = .05. The Wald chi-square statistic was used to determine whether a factor should remain in the model (α = .05).

RESULTS

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. Conflict of Interest Disclosures
  8. References

Table 1 shows the distribution of demographic and clinical characteristics of the participants by treatment arm. Seventy-four patients (30%) had received low-dose chemotherapy, 93 patients (38%) had received the standard dose, and 78 patients (32%) had received the highest dose. Age and race did not differ significantly between the 3 groups. Differences were evident regarding education (patients who received standard therapy were somewhat less educated; P = .04). No significant differences were observed in the distribution of comorbidities that interfered with daily life by treatment group (results not shown).

Table 1. Demographic and Clinical Characteristics of Study Participants by Treatment Trial Arm*
VariableLow-Dose CAFNo. of Patients (%)
Treatment ArmP
Standard-Dose CAFIntensive-Dose CAFAll Patients
  • CAF indicates cyclophosphamide, doxorubicin, and fluorouracil; SD, standard deviation; SES, socioeconomic status; ER, estrogen receptor.

  • *

    Note: Frequencies within education, income, SES, tamoxifen use, ER status, and prior radiation therapy columns do not sum to column totals because of missing data.

Total no. of patients749378245 
Age, y    .31
 30-391 (1)0 (0)2 (3)3 (1) 
 40-494 (5)10 (11)6 (8)20 (8) 
 50-5928 (38)26 (28)24 (31)78 (32) 
 60-6930 (41)32 (34)30 (38)92 (38) 
 ≥7011 (15)25 (27)16 (21)52 (21) 
 Mean ± SD61.3 ± 8.863.4 ± 10.561.1 ± 9.862 ± 9.8 
Race    .34
 White70 (95)84 (90)75 (96)229 (94) 
 Other4 (5)9 (10)3 (4)16 (6) 
Education, y    .04
 0-1229 (41)54 (61)39 (54)122 (55) 
 ≥1342 (59)34 (39)33 (46)109 (47) 
Income, $US    .12
 <10,0004 (6)3 (4)5 (8)12 (6) 
 10,000-19,9999 (14)13 (16)8 (13)30 (14) 
 20,000-29,9994 (6)19 (24)7 (11)30 (14) 
 30,000-44,99910 (16)18 (23)10 (16)38 (18) 
 45,000-59,9999 (14)6 (8)11 (17)26 (13) 
 60,000-79,0008 (13)9 (11)10 (16)27 (13) 
 ≥80,00020 (31)12 (15)13 (20)45 (22) 
SES    .51
 Lower32 (47)47 (54)31 (46)110 (49) 
 Higher36 (53)40 (46)37 (54)113 (51) 
Type of treatment    .12
 Mastectomy62 (84)75 (81)55 (71)192 (78) 
 Breast conservation12 (16)18 (19)23 (29)53 (22) 
Received radiation therapy    .13
 Yes13 (18)19 (20)24 (31)56 (23) 
 No60 (82)74 (80)53 (69)187 (77) 
Received tamoxifen    .89
 Yes32 (44)42 (45)32 (42)106 (44) 
 No41 (56)51 (55)45 (58)137 (56) 
Received any hormone    .89
 Yes34 (46)44 (47)34 (44)112 (46) 
 No40 (54)49 (53)44 (56)133 (54) 
ER status    .55
 Negative26 (35)25 (27)25 (32)76 (31) 
 Positive46 (62)65 (70)48 (62)159 (65) 
 Borderline2 (3)3 (3)1 (1)6 (3) 
Time since diagnosis, y: Mean ± SD12.4 ± 1.912.5 ± 1.712.5 ± 1.912.5 ± 1.8.89

Table 2 shows the distribution of MOS SF-36 subscales by treatment arm. The mean scores were highest for the intensive treatment arm and lowest for the standard arm for all but the Mental Health subscale, and the only statistically significant difference was observed in Physical Role Functioning (P < .0001). Trends toward significance were observed for General Health Perceptions (P = .06), Emotional Role Functioning (P = .07), and Vitality (P = .09) subscales, with lower scores observed in the standard treatment arm. There were no significant dose-response relations by treatment arm (results not shown).

Table 2. Medical Outcomes Study Short Form-36 Subscales and Treatment Arm for Patients Enrolled in Cancer and Leukemia Group B Study 79804
MOS SF-36 SubscaleLow, n = 74MedianTreatment ArmIntensive, n = 78P*
Standard, n = 93
Mean ± SDMean ± SDMedianMean ± SDMedian
  • Low indicates low-dose cyclophosphamide, doxorubicin, and fluorouracil (CAF); Standard, standard-dose CAF; Intensive, high-dose CAF; MOS SF-36, Medical Outcomes Study 36-item short form; SD, standard deviation.

  • *

    Kruskal-Wallis test.

Physical Function75.14 ± 30.648573.01 ± 30.748582.31 ± 22.9190.17
Role Functioning-Physical74.66 ± 39.4210065.05 ± 41.567584.94 ± 30.24100<.0001
Role Functioning-Emotional86.94 ± 31.1210077.78 ± 36.2310087.89 ± 26.99100.07
Social Function87.50 ± 23.7710082.07 ± 27.0610087.18 ± 21.13100.36
Bodily Pain73.69 ± 24.148471.37 ± 24.347477.27 ± 21.2284.32
Mental Health77.70 ± 16.568076.58 ± 17.358476.08 ± 15.8680.74
Vitality61.40 ± 22.656556.81 ± 22.065564.62 ± 17.3370.09
General Health Perceptions74.50 ± 21.497568.92 ± 20.587275.35 ± 17.9977.06

Table 3 displays the HRQL domain items examined by treatment arm. Overall, approximately 80% of women indicated having 1 or more comorbidities, and 20% of women had possible depression (a score ≥16 on the Center for Epidemiologic Studies Depression Scale). They also had high MOS Social Support scores (mean score, >78). In examining the Social Support Systems of Belief subscale, a trend toward significantly higher social support was observed in the standard treatment arm (P = .07). There were no significant dose-response relations by treatment arm (results not shown).

Table 3. Quality-of-Life Domains by Treatment Arm for Patients Enrolled in Cancer and Leukemia Group B Study 79804
Domain/ItemsTreatment Arm : Mean ± SD*P
Low, n = 74Standard, n = 93Intensive, n = 78
  • SD indicates standard deviation; Low, low-dose cyclophosphamide, doxorubicin, and fluorouracil (CAF); Standard, standard-dose CAF; Intensive, high-dose CAF; CES-D, Center for Epidemiologic Studies Depression Scale; BCAS , Breast Cancer Anxiety and Screening Scale; MOS, Medical Outcomes Study.

  • *

    Frequencies and percentages are displayed for categorical variables.

  • Kruskal-Wallis test.

  • Fisher exact test.

Physical well being
 Menopausal symptoms score22.53 ± 18.1624.53 ± 17.9921.21 ± 18.45.31
 Vitality (fatigue)61.40 ± 22.6556.81 ± 22.0664.62 ± 17.33.09
 Lymphedema and pain
  Swelling since surgery: No. (%)
   Yes26 (35)28 (30)21 (27).55
   No48 (64)65 (70)57 (73) 
  Arm/hand pain: No. (%)
   Yes18 (24)18 (19)18 (23)0.76
   No55 (74)73 (78)60 (77) 
  Comorbidities: No. (%)
   None15 (20)23 (25)18 (23).81
   ≥159 (80)70 (75)60 (77) 
 Interference total score1.35 ± 2.271.80 ± 2.341.10 ± 1.79.13
Psychological well being
 CES-D total score9.52 ± 9.969.78 ± 8.019.30 ± 7.79.64
  ≥16: No. (%)15 (20)21 (23)15 (19).88
  <16: No. (%)59 (80)72 (77)63 (81) 
 BCAS subscales
  Total Cognitive Distress10.88 ± 6.4411.31 ± 6.2110.57 ± 6.33.86
  Intrusive Thoughts4.16 ± 4.264.15 ± 3.704.00 ± 4.18.81
  Avoidant Thoughts2.90 ± 3.083.39 ± 3.132.69 ± 2.68.34
 Appearance Assessment26.09 ± 8.1226.16 ± 7.3524.97 ± 7.19.54
 Difficulty concentrating: No. (%)
  Yes10 (14)17 (18)17 (22).45
  No61 (82)75 (81)60 (77) 
Social well being
 MOS Social Support score83.04 ± 17.9677.53 ± 23.2779.16 ± 20.43.34
 MOS subscales
  Positive Interaction85.70 ± 17.9679.71 ± 24.9682.59 ± 22.32.44
  Affection85.59 ± 22.8981.54 ± 26.2083.33 ± 20.81.29
  Emotional Support83.24 ± 17.7978.14 ± 23.5178.41 ± 22.61.41
  Tangible Support80.07 ± 23.0373.12 ± 27.0476.12 ± 23.25.20
 Life Events score5.79 ± 5.797.26 ± 6.385.85 ± 4.91.14
Spiritual well being
 Systems of belief total score2.31 ± 0.782.39 ± 0.782.29 ± 0.73.12
  Religious-spiritual2.49 ± 0.792.54 ± 0.722.45 ± 0.72.30
  Social support1.96 ± 0.942.12 ± 1.01.95 ± 0.86.07
Economic well being
 Perceived negative socioeconomic impact0.01 ± 0.120.08 ± 0.270.06 ± 0.25.20
 Perceived positive socioeconomic impact0.03 ± 0.160.02 ± 0.030.03 ± 0.161.00

The association of demographic and medical characteristics with decreased physical role functioning was analyzed using logistic regression. The univariate results (Table 4) showed a highly significant relation between treatment arm and decreased physical role functioning (odds ratio [OR], 3.17; P = .0009). Other factors that were associated with reduced physical role functioning were lower SES (OR, 2.76; P = .0004), age ≥60 years (OR, 1.85; P = .03), ≥1 comorbid condition(s) (OR, 4.76; P = .0001), lower vitality (OR, 1.06; P < .0001), increasing menopausal symptom score (OR, 1.07; P < .0001), higher comorbidity interference total score (OR, 2.81; P < .0001), and positive ER status (OR, 2.17; P = .009).

Table 4. Univariate Logistic Regression Analysis: Association of Demographic and Medical Characteristics With Decreased Physical Role Functioning
VariableOR95% CIP
  • OR indicates odds ratio; CI, confidence interval; NA, not available; ER, estrogen receptor; SES, socioeconomic status.

  • *

    Comorbidities that interfered with daily life included: other cancers/leukemia, arthritis/rheumatism/other connective tissue disorder, glaucoma, emphysema/chronic bronchitis, high blood pressure, heart disease, circulation problems in legs/arms, diabetes, stomach/intestinal disorders, osteoporosis, chronic liver/kidney disease, stroke, and depression.

Treatment arm
 Low dose vs high dose1.620.80-3.28.75
 Standard dose vs high dose3.171.64-6.12.0009
Age at time of interview: ≥60 y vs <60 y1.851.08-3.23.03
No. of comorbidities: None vs ≥1*4.762.13-10.0001
Type of surgery: Lumpectomy vs mastectomy0.970.52-1.79.91
ER status: Negative vs positive2.171.22-4.009
Hormone therapy: No vs yes0.640.38-1.09.10
Radiation therapy: No vs yes0.910.49-1.68.77
High blood pressure interference: No/NA vs yes0.110.04-0.33.0001
Diabetes interference: No or NA vs yes0.120.03-0.43.001
Vitality score (fatigue)1.061.05-1.09<.0001
Menopausal symptom total score1.071.05-1.09<.0001
SES: Lower vs higher2.761.57-4.85.0004
Time since diagnosis; <12.3 y vs ≥12.3 y1.140.68-1.920.62
Comorbidity interference total score2.812.10-3.76<.0001

Variables that were significant at the 25% level in the univariate analysis were included in the stepwise selection process to derive the multivariate model (Table 5). Vitality, menopausal symptoms, age, and comorbidity interference total scores all had significant associations with physical role functioning, but treatment arm and SES no longer were significant. Older patients (OR, 3.55; P = .006), patients with higher comorbidity total interference scores (OR, 1.64; P = .005), patients with higher menopausal symptom scores (OR, 1.04; P = .02), and women with reduced vitality (fatigue; OR, 1.05; P = .0002) were more likely to report decreased physical role functioning.

Table 5. Multivariate Logistic Regression Analysis: Association of Demographic and Medical Characteristics With Decreased Physical Role Functioning
VariableOR95% CIP
  1. OR indicates odds ratio; CI, confidence interval.

Age at time of interview: ≥60 y <60 y3.551.45,8.62.006
Vitality score, fatigue1.051.02,1.08.0002
Menopausal symptom total score1.041.01,1.07.02
Comorbidity interference total score1.641.17,2.31.005

In further exploring these associations, 2 specific comorbidities that reportedly interfered with daily life, high blood pressure and diabetes, were related highly to decreased physical role functioning in univariate analyses (P < .001). Patients with a high school education or less tended to have more health problems compared with patients who had at least some college education (results not shown). Significant differences by education level were observed in circulation trouble (P = .01), depression level (P = .01), and diabetes (P = .06) that interfered with daily life.

DISCUSSION

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. Conflict of Interest Disclosures
  8. References

The primary objective of the current study was to compare differences by treatment group in HRQL domains (physical, psychological, social, spiritual, and economic) among long-term breast cancer survivors. When HRQL measures were examined by treatment arm, physical role functioning emerged as the only statistically significant outcome. Trends toward significance were observed for variables such as general health perceptions, vitality, emotional role functioning, and social functioning. These results are similar to those reported by Ganz et al., who observed that 6-year survivors who received adjuvant therapy reported lower levels of physical role functioning as well as general health, bodily pain, physical functioning, and social functioning.6, 9 Ahles et al. also reported significantly lower scores in social and physical domains among 10-year survivors who received chemotherapy versus local therapy.8 Others have reported poorer physical role functioning among patients 5 years postchemotherapy compared with patients without cancer36 and patients who received adjuvant chemotherapy.3

Unlike previous studies in which a dose-response relation was observed, in the current study, we observed the lowest mean SF-36 subscale scores in the standard-dose group followed by the low-dose and high-dose groups. Survivors in the standard-dose group also had trends toward significantly higher levels of Systems of Belief Inventory Social Support in the spiritual domain. These findings may be because survivors in the standard group had less education or perhaps were less healthy than survivors in the other groups. Future studies should examine similar dose-intensities and their effect on HRQL.

In further examining the relation of physical role functioning by treatment arm, logistic regression analyses revealed that treatment arm no longer was associated significantly with HRQL after adjusting for factors such as age, fatigue, menopausal symptoms, and comorbidities that interfered with daily life. In a recent prospective study, lower levels of physical role functioning were observed among women 1 year after they received high-dose chemotherapy and remained stable for >4 years but had small effect sizes that were clinically irrelevant.37 In that study, when age and menopausal status were assessed as covariates, postmenopausal women exhibited lower physical role functioning scores. Other studies also reported lower levels of HRQL in physical/role functioning domains in patients who received high-dose chemotherapy, but those levels returned to baseline 1 year after treatment.10, 38, 39 The current results, however, provide information regarding which patients may be at risk for reduced physical role functioning after the receipt of any dose of this adjuvant therapy regimen.

Age was related significantly to physical role functioning in this study and typically was associated with lower HRQL in past studies. Older survivors have reported decreased physical role functioning,40, 41 more physical problems, depressed mood, and days affected by fatigue.42, 43

Comorbidities that interfered with daily life, which were related significantly to physical role functioning in this study, consistently affected HRQL. Depression, diabetes, and circulation trouble also were evident in women with lower education levels. Past studies have demonstrated that poorer HRQL among lower SES groups may be related to increased comorbidities and reduced access to care. Patients with lower education levels have reported more physical symptoms, such as tiredness, decreased sexual interest, and painful muscles.37

Fatigue was related significantly to physical role functioning in this study. Fatigue often is reported as a long-term side effect of breast cancer treatment that persists years after active treatment.6, 7, 44, 45 Comorbidities, such as high blood pressure, which were prevalent in this study, have been related to fatigue in previous studies.45 The presence of joint and muscle pain also has been associated with fatigue.46-48 Patients who most frequently reported symptoms like such as pain and fatigue 5 years post-treatment scored significantly lower on HRQL at baseline compared with other patients.37 Future studies should assess these domains at baseline and their possible interactions with other factors, because differences may be predictive of future outcomes.

Regarding menopausal symptoms, which had a statistically significantly association with physical role functioning, Schultz et al. concluded, that despite ‘complex interactions’ between HRQL indicators and physiologic effects of treatment, menopausal symptoms may not be different for breast cancer survivors and should not be confused with quality-of-life/psychosocial issues.49 Others have demonstrated that HRQL differences could not be explained by menopausal symptoms alone and that more research is needed in this area.36

There were several strengths of this study. First, it focused on the HRQL domain of physical role functioning and factors that influence this domain that have not been explored in previous studies. Second, it examined survivors 9 to 16 years after their primary diagnosis, which few studies have done. Third, the women were diagnosed at relatively the same disease stage and received 1 of 3 known chemotherapy regimens within the same clinical trial, thus reducing variability because of treatment and stage of diagnosis. Many previous studies have used heterogeneous populations in examining stage and treatment.

Limitations of this study include reliance on self-reported comorbidities, such as lymphedema and osteoporosis. Information on temporal changes in HRQL was not assessed, because HRQL was examined at only 1 time point. In addition, a survival bias may have occurred whereby patients with better HRQL were more likely to be long-term survivors and, thus, eligible to participate in the follow-up study. However, analyses demonstrated few differences between CALGB 8541 survivors who did and did not participate in this study. These limitations emphasize the need for prospective, long-term studies of HRQL in breast cancer survivors from treatment through survivorship.

Although chemotherapy provides a great survival benefit for cancer patients, it provides potential long-term side effects that may have great impact on HRQL. The current study demonstrated that, whereas the adjuvant chemotherapy dose initially was related to lower HRQL in physical role functioning, this effect actually was explained by demographic and clinical factors, which can be used in targeting HRQL interventions for long-term survivors. The clinical significance of these factors and their role as potential areas for interventions in improving HRQL need to be explored further in prospective studies of HRQL in long-term breast cancer survivors.

Acknowledgements

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. Conflict of Interest Disclosures
  8. References

We acknowledge the following individuals for their contribution to the Survivor's Health and Reaction study: Eric Winer, MD; Charles Shapiro, MD; Gini Fleming, PhD; Marcy List, PhD; and Karleen Habin, RN

Conflict of Interest Disclosures

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. Conflict of Interest Disclosures
  8. References

Supported by National Institutes of Health grants AG16602, CA79883, and CA57707.

The Ohio State University Comprehensive Cancer Center was supported by grant CA77658. The CALGB Statistical Center at Duke University Medical Center was supported by grant CA33601. Wake Forest University School of Medicine was supported by grant CA03927. The Helen F. Graham Cancer Center, Delaware Christiana Care Community Clinical Oncology Program (CCOP) was supported by grant CA45418. The Southeast Cancer Control Consortium Inc. CCOP was supported by grant CA45808. Memorial Sloan-Kettering Cancer Center was supported by grant CA77651. The Dana-Farber Cancer Institute was supported by grant CA32291.

References

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. Conflict of Interest Disclosures
  8. References
  • 1
    American Cancer Society. Breast Cancer Facts & Figures 2007-2008. Atlanta, Ga: American Cancer Society, Inc.; 2008.
  • 2
    Jemal A, Siegel R, Ward E, et al. Cancer statistics, 2007. CA Cancer J Clin. 2007; 57: 43-66.
  • 3
    Casso D, Buist DS, Taplin S. Quality of life of 5-10 year breast cancer survivors diagnosed between age 40 and 49. Health Qual Life Outcomes. 2004; 2: 25.
  • 4
    Dorval M, Maunsell E, Deschenes L, et al. Long-term quality of life after breast cancer: comparison of 8-year survivors with population controls. J Clin Oncol. 1998; 16: 487-494.
  • 5
    Dow KH, Ferrell BR, Leigh S, et al. An evaluation of the quality of life among long-term survivors of breast cancer. Breast Cancer Res Treat. 1996; 39: 261-273.
  • 6
    Ganz PA, Desmond KA, Leedham B, et al. Quality of life in long-term disease-free survivors of breast cancer: a follow-up study. J Natl Cancer Inst. 2002; 94: 39-49.
  • 7
    Kornblith AB, Herndon JE, Weiss RB, et al. Long-term adjustment of survivors of early-stage breast carcinoma 20 years after adjuvant chemotherapy. Cancer. 2003; 98: 679-689.
  • 8
    Ahles TA, Saykin AJ, Furstenberg CT, et al. Quality of life of long-term survivors of breast cancer and lymphoma treated with standard-dose chemotherapy or local therapy. J Clin Oncol. 2005; 23: 4399-4405.
  • 9
    Ganz PA, Rowland JH, Merowitz BE, et al. Impact of different adjuvant therapy strategies on quality of life in breast cancer survivors. Recent Results Cancer Res. 1998; 16: 501-514.
  • 10
    Bottomley A, Therasse P, Piccart M, et al. Health-related quality of life in survivors of locally advanced breast cancer: an international randomised controlled phase III trial. Lancet Oncol. 2005; 6: 287-294.
  • 11
    Ferrell BR, Dow KH, Grant M. Measurement of the quality of life in cancer survivors. Qual Life Res. 1995; 4: 523-531.
  • 12
    Dow KH, Ferrell BR, Haberman MR, Eaton L. The meaning of quality of life in cancer survivorship. Oncol Nurs Forum. 1999; 26: 519-528.
  • 13
    Ersek M, Ferrell BR, Dow KH, Melancon CH. Quality of life in women with ovarian cancer. West J Nurs Res. 1997; 19: 334-350.
  • 14
    Wood WC, Budman DR, Korzun AH, et al. Dose and dose intensity of adjuvant chemotherapy for stage II, node-positive breast carcinoma. N Engl J Med. 1994; 330: 1253-1259.
  • 15
    Budman D, Berry DA, Cirrincione CT, et al. Dose and dose intensity as determinants of outcome in the adjuvant treatment of breast cancer. J Natl Cancer Inst. 1998; 90: 1205-1211.
  • 16
    Paskett ED, Herndon JE 2nd, Day JM, et al; Cancer and Leukemia Group B. Applying a conceptual model for examining health-related quality of life in long-term breast cancer survivors: CALGB study 79804. Psychooncology. 2008; 17: 1108-1120.
  • 17
    Ware JE, Snow KK, Kosinski M, Gandek B. SF-36 Health Survey Manual and Interpretation Guide. Boston, Mass: New England Medical Center, The Health Institute; 1993.
  • 18
    Stewart AL, Ware J. Measure of Functioning and Well-Being: The Medical Outcomes Study Approach. Durham, NC: Duke University Press; 1992.
  • 19
    Radloff LS. The CES-D scale: a self-report depression scale for research in the general population. Appl Psychol Meas. 1977; 1: 385-401.
  • 20
    Kash KM, Jacobsen PB, Holland JC, Osborne MP, Miller DG. Measuring breast cancer anxiety. Presented at the 42nd Annual Meeting of the Academy of Psychosomatic Medicine, Palm Springs, California, November 16-19, 1995.
  • 21
    Lerman C, Trock B, Rimer B. Psychological side effects of breast cancer screening. Health Psychol. 1991; 10: 259-267.
  • 22
    Spielberger CD, Gorsuch RL, Lushene RD. Manual for the State-Trait Anxiety Inventory. Palo Alto, Calif: Consulting Psychologists Press; 1970.
  • 23
    Taylor JA. A personality scale of manifest anxiety. J Abnorm Psychol. 1953; 48: 285-290.
  • 24
    Sherbourne CD, Stewart AL. The MOS social support survey. Soc Sci Med. 1991; 32: 705-714.
  • 25
    Anderson D, Bilodeau B, Deshaies G, et al. French-Canadian validation of the MOS social support survey. Can J Cardiol. 2005; 21: 867-873.
  • 26
    Wilcox S, Aragaki A, Mouton CP, et al. The effects of widowhood on physical and mental health, health behaviors, and health outcomes: the Women's Health Initiative. Health Psychol. 2003; 22: 513-522.
  • 27
    Holland JC, Kash KM, Passik S, et al. A brief spiritual beliefs inventory for use in quality of life research in life-threatening illnesses. Psychooncology. 1998; 7: 460-469.
  • 28
    Holland JC, Herndon J, Kornblith AB, et al. A sociodemographic data collection model for cooperative clinical trials [abstract]. Proc Am Soc Clin Oncol. 1992; 11: 157. Abstract 445.
  • 29
    Greenberg DB, Kornblith AB, Herndon JE, et al. Quality of life of adult leukemia survivors treated on clinical trials of the Cancer and Leukemia Group B from 1971-1988: predictors for later psychological distress. Cancer. 1997; 80: 1936-1944.
  • 30
    George LK, Fillenbaum G. OARS methodology: a decade of experience in geriatric assessment. J Am Geriatrics Soc. 1985; 33: 607-615.
  • 31
    Paskett E. Lymphedema: knowledge, treatment and impact among breast cancer survivors. Breast J. 1999; 6: 373-378.
  • 32
    Crooks V, Waller S, Smith T, Hahn TJ. The use of the Karnofsky performance scale in determining outcomes and risk in geriatric outpatients. J Gerontol. 1991; 46: M139-M44.
  • 33
    Cohen J. Statistical Power Analysis for the Behavioral Sciences, 2nd ed. New York, NY: Academic Press; 1988.
  • 34
    Jonckhere AR. A distribution-free k-sample test against ordered alternatives. Biometrika. 1954; 41: 133-145.
  • 35
    Paskett E, Tatum C, Rushing J, et al. Randomized trial of an intervention to improve mammography utilization among a triracial rural population of women. J Natl Cancer Inst. 2006; 98: 1226-1237.
  • 36
    Broeckel JA, Jacobsen PB, Balducci L, et al. Quality of life after adjuvant chemotherapy for breast cancer. Breast Cancer Res Treat. 2000; 62: 141-150.
  • 37
    Buijs C, Rodenhuis S, Seynaeve CM, et al. Prospective study of long-term impact of adjuvant high-dose and conventional-dose chemotherapy on health-related quality of life. J Clin Oncol. 2007; 25: 5403-5409.
  • 38
    Connor-Spady BL, Cumming C, Nabholtz JM, et al. A longitudinal prospective study of health-related quality of life in breast cancer patients following high-dose chemotherapy with autologous blood stem cell transplantation. Bone Marrow Transplant. 2005; 36: 251-259.
  • 39
    Peppercorn J, Herndon J, Kornblith AB, et al. Quality of life among patients with stage II and III breast carcinoma randomized to receive high-dose chemotherapy with autologous bone marrow support or intermediate-dose chemotherapy: results from Cancer and Leukemia Group B 9066. Cancer. 2005; 104: 1580-1589.
  • 40
    Fehlauer F, Tribius S, Mehnert A, Rades D. Health-related quality of life in long term breast cancer survivors treated with breast conserving therapy: impact of age at therapy. Breast Cancer Res Treat. 2005; 92: 217-222.
  • 41
    Peuckmann V, Ekholm O, Rasmussen NK, et al. Health-related quality of life in long-term breast cancer survivors: nationwide survey in Denmark. Breast Cancer Res Treat. 2007; 104: 39-46.
  • 42
    Cimprich B, Ronis DL, Martinez-Ramos G. Age at diagnosis and quality of life in breast cancer survivors. Cancer Pract. 2002; 10: 85-93.
  • 43
    Robb C, Haley WE, Balducci L, et al. Impact of breast cancer survivorship on quality of life in older women. Crit Rev Oncol Hematol. 2007; 62: 84-91.
  • 44
    Meeske K, Smith AW, Alfano CM, et al. Fatigue in breast cancer survivors 2 to 5 years post diagnosis: a HEAL Study report. Qual Life Res. 2007; 16: 947-960.
  • 45
    Bower JE, Ganz PA, Desmond KA, et al. Fatigue in long-term breast carcinoma survivors: a longitudinal investigation. Cancer. 2006; 106: 751-758.
  • 46
    Ganz PA. Quality of life across the continuum of breast cancer care. Breast J. 2000; 6: 324-330.
  • 47
    Nieboer P, Buijs C, Rodenhuis S, et al. Fatigue and relating factors in high-risk breast cancer patients treated with adjuvant standard or high-dose chemotherapy: a longitudinal study. J Clin Oncol. 2005; 23: 8296-8304.
  • 48
    Burckhardt CS, Jones KD. Effects of chronic widespread pain on the health status and quality of life of women after breast cancer surgery [serial online]. Health Qual Life Outcomes. 2005; 3: 30.
  • 49
    Schultz PN, Klein MJ, Beck ML, et al. Breast cancer: relationship between menopausal symptoms, physiologic health effects of cancer treatment and physical constraints on quality of life in long-term survivors. J Clin Nurs. 2005; 14: 204-211.