Skip to main content
PMC home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2016 Feb 29.
Published in final edited form as: Cancer Epidemiol Biomarkers Prev. 2007 Apr;16(4):775–782. doi: 10.1158/1055-9965.EPI-06-0168

The Epidemiology of Arm and Hand Swelling in Premenopausal Breast Cancer Survivors

Electra D Paskett 1,2, Michelle J Naughton 3, Thomas P McCoy 4, L Douglas Case 4, Jill M Abbott 1
PMCID: PMC4771019  NIHMSID: NIHMS694019  PMID: 17416770

Abstract

Background

Breast cancer survivors suffer from lymphe-dema of the arm and/or hand. Accurate estimates of the incidence and prevalence of lymphedema are lacking, as are the effects of this condition on overall quality of life.

Methods

Six hundred twenty-two breast cancer survivors (age, ≤45 years at diagnosis) were followed with semiannual questionnaires for 36 months after surgery to determine the incidence of lymphedema, prevalence of persistent swelling, factors associated with each, and quality of life.

Results

Of those contacted and eligible for the study, 93% agreed to participate. Fifty-four percent reported arm or hand swelling by 36 months after surgery, with 32% reporting persistent swelling. Swelling was reported to occur in the upper arm (43%), the hand only (34%), and both arm and hand (22%). Factors associated with an increased risk of developing swelling included having a greater number of lymph nodes removed [hazards ratio (HR), 1.02; P < 0.01], receiving chemotherapy (HR, 1.76; P = 0.02), being obese (HR, 1.51 versus normal weight; P = 0.01), and being married (HR, 1.36; P = 0.05). Factors associated with persistent swelling were having more lymph nodes removed (odds ratio, 1.03; P = 0.01) and being obese (odds ratio, 2.24 versus normal weight; P < 0.01). Women reporting swelling had significantly lower quality of life as measuredly the functional assessment of cancer therapy-breast total score and the SF-12 physical and mental health subscales (P < 0.01 for each).

Conclusions

Lymphedema occurs among a substantial proportion of young breast cancer survivors. Weight management may be a potential intervention for those at greatest risk of lymphedema to maintain optimal health-related quality of life among survivors.

Introduction

Breast cancer is the most common type of cancer and the second leading cause of cancer mortality among women in the United States (1). It ranks second among cancer deaths in all women (1) and first in cancer deaths among women ages 20 to 59 years (2). Although advancements in cancer treatment and emphasis on early detection through mammography screening have allowed more cancer patients to become survivors, there has been little change in the number of new cases of invasive breast cancer in women younger than age 40 years (3). Survivors face psychological, physical, and emotional challenges, all of which affect quality of life (4).

Lymphedema is a common complication of cancer therapy and is characterized by an accumulation of lymphatic fluid in the interstitial tissue that causes swelling, most often in the arms or legs. Lymphedema can occur anywhere lymph nodes have been surgically removed or lymph flow has been disturbed (5). An unwanted consequence of cancer treatment (4), lymphedema is especially concerning to patients who think they have been cured of their cancer (6).

Lymphedema following treatment for breast cancer has received attention in multiple studies. The overall incidence of arm lymphedema can range from 8% to 56% 2 years following surgery, depending on the extent of axillary surgery and the use of radiotherapy (7–15). Most women with lymphedema develop it within the first 12 to 14 months following treatment (16, 17).

Lymphedema can cause limitations in range of motion, pain, weakness, or stiffness in the affected arm (18, 19). It also results in psychological problems, including anxiety, depression, sexual dysfunction, social avoidance, and exacerbation of existing psychiatric illness (20). The effect of arm swelling on appearance has been suggested to be greater than the effect of coping with the initial diagnosis and treatment of breast cancer as the swollen arm or hand is a constant reminder of breast cancer, is a subject of curiosity to others, and may suggest a recurrence to the survivor (6). Generally, quality of life is compromised for breast cancer patients with lymphedema (5, 21–25).

Consistency among studies about prevalence and incidence rates, risk factors, and prevention and treatment for lymphedema among breast cancer survivors is lacking. Many reasons for this gap have been proposed. Lymphedema continues to be under diagnosed and is not defined or measured in a standardized manner (26–28), thus making estimates of incidence difficult to obtain. Few studies are designed to follow newly diagnosed women in a longitudinal manner to capture the incidence of this condition and determine the prevalence of the condition over time. Cross-sectional study designs, most commonly used, only provide a snap shot of the prevalence of lymphedema at a single point in time, not in a longitudinal fashion following diagnosis.

Although the etiologic factors for lymphedema have not been studied extensively, some studies have identified several common factors associated with the development of this condition. Extent of axillary dissection, radiation therapy, obesity at diagnosis, older age, postoperative fluid formation, and infection in the arm have been reported as related factors (10, 29–31).

Although breast cancer affects women of all ages, young women with breast cancer (i.e., those under age 50 years) tend to have more aggressive breast tumors (32, 33), which necessitates treatments that may be more toxic than those offered to older women (34–36). Although breast cancer incidence and mortality continue to decline among women younger than 50 years (37), these toxic treatments may cause significant side effects that may last a long time. Furthermore, very little has been reported on lymphedema in this patient population that receives more intensive treatment and may suffer from the associated effects of this side effect for a longer time period, especially during the most productive years of life.

This prospective study is one of the first in the United States to establish reliable estimates of and factors associated with the incidence and prevalence of arm swelling, to explore which patient characteristics are associated with the incidence and persistence of lymphedema, as well as to document the effect of swelling on quality of life among young breast cancer survivors. Thus, this study provides data not found in previous studies that have used cross-sectional designs.

Materials and Methods

Procedures and Participants

Data for this study were taken from participants recruited to the Menstrual Cycle Maintenance and Quality of Life After Breast Cancer Treatment Study, a prospective, observational study of patients ages 18 to 45 years (38). The objectives of this study are to document and identify determinants of menstrual cycle maintenance after breast cancer treatment, to examine survivor’s quality of life longitudinally, to track reproductive events among those attempting pregnancy, and ultimately to investigate the effect of subsequent pregnancy on survival. Recruitment to this study occurred from January 1998 to December 2005. This article includes 3 years of prospective data from the first 627 women who were recruited to this study through July of 2002 to address secondary goals related to lymphedema. Follow-up of participants continues.

Patients were recruited from clinical centers at the Memorial Sloan-Kettering Cancer Center in New York City, New York (449 women); M. D. Anderson Cancer Center in Houston, Texas (92 women); Presbyterian Hospital in Dallas, Texas (37 women); and the Wake Forest University Baptist Medical Center in Winston-Salem, North Carolina (49 women). Women were identified at these clinical centers using tumor/surgical registries or physician referrals. Inclusion criteria included female patients ages 18 to 45 years at diagnosis with a stage I, II, or III invasive breast cancer within the previous 8 months. All patients were required to have regular menstrual cycles at the time of diagnosis. Thus, patients who had a previous hysterectomy, even with intact ovaries, were ineligible for this protocol. Patients were excluded if they had a prior or concurrent history of any cancer, excluding basal or squamous cell skin carcinoma and stage 0 cervical cancer. This study was approved by the Institutional Review Board of each hospital as well as the U.S. Department of Defense Human Subjects Committee.

Data Collection and Instruments

Patients completed questionnaires at baseline and at 6-month intervals thereafter. All follow-up data collection was conducted by mail through the study coordinating center at the Wake Forest University School of Medicine. Descriptions of the questionnaires pertinent to the incidence, prevalence, quality of life and development of lymphedema, and used in the current analyses are listed below. In brief, these questionnaires provided information about patient demographics, their cancer diagnosis and treatment, patient risk factors for disease and/or lymphedema, and life quality.

Demographics

Age, race/ethnicity, marital status, educational background, income, and employment and insurance status were collected from self-report.

Medical and reproductive history

Information was collected about comorbid conditions, family history, and reproductive history, including parity, pelvic surgery, and menstrual cycling.

Medical chart review

An extensive medical chart review was done on all patients by clinic staff at 1 year after recruitment. Information was obtained on the date and technique of breast cancer diagnosis, tumor size, location, grade, hormone receptor status, number of nodes examined, number of positive lymph nodes, type of definitive cancer surgery, and reconstructive surgery, if any. Chemotherapy information (dates, drugs, and dosages in milligrams) was gathered from medical oncology office records. Likewise, dose per treatment, treatment area, and total dosage and duration of treatment were recorded for women receiving radiation therapy. Hormonal therapies, such as tamoxifen, were recorded with dates, routes of administration, and dosages.

Arm and hand swelling form

Patients were asked if they had experienced any swelling in their arm or hand since their surgery (at baseline) or in the last 6 months (at each follow-up assessment), location of swelling, and severity. Patients were also asked to assess the effect of swelling on daily life functions, such as wearing clothing, the completion of routine personal, home, and work tasks, exercise, and general use of the affected hand/arm(s). In addition, participants indicated whether they had sought treatment for the condition, and if yes, what type of treatment they received (31). These questions have been successfully used in previous studies and research protocols (4). Other methods to measure arm volume (i.e., volume by perometry, water displacement, or arm circumference measurements) were not feasible given data collection by mail. Previous work, however, has indicated moderate correlation between objective measurements of swelling and self-report of swelling (39).

Personal habits questionnaire

Information about women’s smoking and alcohol use, height in inches, weight in pounds, weight change, and exercise habits were collected. Body mass index (BMI) was calculated from height and weight measurements (weight/height2, as kg/m2) and then categorized (referred to as weight status) as normal/underweight (BMI, <25 kg/m2), overweight (BMI, 25–29.9 kg/m2), or obese (BMI, ≥30 kg/m2).

Functional assessment of cancer therapy-breast

The functional assessment of cancer therapy-breast (FACT-B) is a multidimensional, cancer-specific quality of life measure. This scale assesses physical well-being, social/family well-being, relationship with doctor, emotional well-being, functional well-being, and concerns specific to breast cancer patients. Scores can be calculated for each of the six subscales, as well as a total score composed of all six subscales. Higher scores on this measure indicate better levels of functioning (40).

SF-12 health status questionnaire

The SF-12 is a 12-item short form of the SF-36 Health Status Questionnaire, a generic health-related quality of life instrument (41, 42). The SF-12 is composed of two components, a physical health and a mental health subscale. These subscales are scored with a mean of 50 and a SD of 10. Higher scores on these subscales indicate higher levels of functioning.

Follow-up questionnaires

Participants completed updates of their medical and reproductive history every 6 months, including their general medical status, cancer recurrences, reproductive events, surgical procedures, and any current or newly initiated drugs and/or therapy. Patients also completed the FACT-B, SF-12, follow-up Arm and Hand Swelling, and Personal Habits forms at 6-month intervals. Updates of participant demographics, primarily changes in marital status, education, income, employment, and insurance status were collected every 12 months.

Analytic Methods

Of the 849 women contacted about the study, 672 were eligible to participate. Of these eligible women, 627 (93%) agreed to participate. The 45 women who refused participation in the study were similar in age to those who participated (median age, 40.1 versus 39.8 years, respectively; P = 0.82, Wilcoxon rank-sum) but different in race (77% White versus 89% White, respectively; P = 0.04, Fisher’s exact). Five of the 627 participants completed no follow-up surveys after surgery and were excluded from all data analyses. Time was calculated from surgery until the date of the survey and divided into 6-month intervals for descriptive purposes. Prevalence of swelling during these intervals was calculated by dividing the number of participants who indicated that they had experienced swelling by the number of participants who filled out a survey during that time. Time to first swelling occurrence was calculated as the time from surgery until the first occurrence of swelling. Because participants were asked if they had experienced swelling since surgery (baseline survey) or in the last 6 months (follow-up surveys), we used the midpoint of the interval for the event time when swelling was noted.

The Kaplan-Meier method (43) was used to estimate time to swelling, and Cox proportional hazards regression was used to determine which covariates were significantly associated with this outcome (44). Age (in years), race (White versus other), marital status (married versus single), education (high school graduate or less, some college, and college graduate), weight status (normal/underweight, overweight, and obese), current smoking status (smoker and nonsmoker), weekly exercise (none, walking, mild, moderate, and strenuous), having a child <8 years of age, employment status (full-time, part-time, homemaker, and other), reconstructive surgery, lumpectomy, mastectomy, nodal dissection [none, sentinel node dissection (SND) only and axillary node dissection (AND)], number of lymph nodes removed, number of positive lymph nodes, antibiotic use at baseline, radiation therapy, chemotherapy, and tamoxifen use were included as covariates in the model. All covariates were considered fixed except for receiving tamoxifen, which was treated as a time varying covariate.

To account for missing visits, the probability of swelling at the missing visit was determined using participants with complete data whose patterns matched that of the participant with missing data. Then, 1,000 samples were taken from the original population, with the time to first swelling for a particular participant sampled with probability p (45). The Kaplan-Meier and Cox proportional hazards analyses were then run on each sample, and estimates across all the analyses for the results were pooled. For time to swelling, the estimates were simply the means of the monthly Kaplan-Meier estimates. For the Cox proportional hazards models, the HR was estimated as the exponential of the average β for a particular covariate, the 95% confidence interval was obtained as the exponential of the average β ± 1.96 times the square root of the average variance of the β, and the P value was calculated based on Wald tests (the average β divided by the square root of the average variance).

To assess which demographic and clinical factors were associated with self-reported swelling over time, a longitudinal logistic regression model was fit using the Generalized Estimating Equations method to account for the multiple observations per person (46, 47). An autoregressive covariance structure was used to model the correlation of the repeated measurements over time. Time was considered in this model by flooring the time since surgery to the nearest month and modeled as continuous. Persistent swelling was defined as the report of two or more swelling episodes within the first 3 years after surgery. A multivariable logistic regression model was used to determine which demographic and medical factors were associated with persistent swelling by 3 years after surgery. The effect of missing swelling data was examined by looking at patterns of missing data and calculating weights from observed proportions of persistent swelling from complete case data. Weighted imputation for missing data was done using resampling as described above for time to first swelling occurrence. Logistic regression for persistent swelling was analyzed for each sample, and mean estimates were calculated.

Longitudinal mixed models were fit to explore how swelling, demographic, and medical characteristics affected women’s quality of life as measured by the SF-12 and FACT-B. An autoregressive covariance structure was used to model the correlation of the repeated measurements over time. In addition to the covariates described above for the survival analysis, the Generalized Estimating Equations and quality of life mixed models also included linear and quadratic terms for months past surgery. For these models, all covariates were considered to be fixed in the analyses except for: weight status, antibiotic use, current smoking status, exercise, and tamoxifen use. Tamoxifen was modeled a lag1 time-varying covariate. All the analyses were conducted using SAS version 8.2 (SAS Institute, Inc., Cary, NC).

Results

Characteristics of the Participants

The baseline demographic, medical, and psychosocial characteristics of the 622 participants with both baseline and postsurgery follow-up are presented in Table 1. The median age of the women when diagnosed with breast cancer was 39 years (range, 20–45 years). The majority of the participants were non-Hispanic White (89%) and were married or had a live-in partner (75%). Most (62%) women had children, and 36% currently had children <8 years. Two thirds (66%) had a 4-year college degree or higher. Thirty-eight percent of the women had an annual household income between $50,000 and $100,000, and one third had a household income above $100,000 annually. Less than half (43%) of the participants had a past smoking history when enrolled in the study; eight percent reported current smoking at baseline. Weekly level of exercise varied, with 82% of the women exercising weekly at some level but only 31% reporting any strenuous exercise. Thirty-four percent of the women were overweight or obese, as classified by their weight status (BMI, ≥25 kg/m2). The mean (±SD) scores for FACT-B, SF-12M, and SF-12P at baseline were 105.5 (19.2), 43.0 (8.2), and 44.2 (8.9), respectively.

Table 1.

Demographic, medical, and psychosocial characteristics of sample (N= 622)

Characteristic n (%)
Age at diagnosis, mean [SD (range)], y 38.5 [4.9 (20–45)]
Race/ethnicity
  White 555 (89)
  African-American 28 (4)
  Hispanic 23 (4)
  Asian/Pacific Islander 16 (3)
Marital status
  Single/separated/widowed 156 (25)
  Married/marriage-like 466 (75)
Education
  High school graduate or less 54(9)
  Some college 158 (25)
  College graduate (4y) or above 409 (66)
Annual family income ($)
  <50K/y 177 (29)
  50–100K/y 232 (38)
  >100K/y 201 (33)
Employment status
  Full-time 339 (55)
  Part-time 86 (14)
  Full-time homemaker 107 (17)
  Other 90 (14)
Insurance
  None 4(1)
  HMO only 155 (29)
  Group only 298 (56)
  Medicaid only 8 (2)
  VA/military only 3 (1)
  Other 48 (9)
  Multiple types 15 (3)
No. children
  0 234(38)
  1 117 (19)
  2 182 (29)
  3+ 89 (14)
Children <8 years of age 225 (36)
Weight status
  Underweight/normal (BMI, <25 kg/m2) 408 (66)
  Overweight (BMI, 25–29.9 kg/m2) 118 (19)
  Obese (BMI, ≥30 kg/m2) 96 (15)
Smoking status
  Never 354(57)
  Former 268 (43)
  Current 48 (8)
Weekly exercise
  None 113 (18)
  Walking only 86 (14)
  Mild 73 (12)
  Moderate 158 (25)
  Strenuous 191 (31)
Type of surgery
  Lumpectomy only 320 (51)
  Mastectomy 296 (48)
Type of node dissection
  Sentinel (SND) only 26 (4)
  Axillary (AND) 580 (93)
  Neither 14(2)
No. nodes removed, median [SD (range)] 15.0 [9.3 (0–51)]
No. positive nodes
  0 350 (56)
  1–3 172 (28)
  4–9 59 (9)
  10+ 41 (7)
Antibiotics for infection 19 (3)
Chemotherapy (yes) 545 (88)
Tamoxifen (yes) 343 (55)
Radiation therapy (yes) 435 (70)
Quality of life measures, mean [SD (range)]
  FACT-B 105.5 [19.2 (44–146)]
  SF-12M 43.0 [8.2 (14–61)]
  SF-12P 44.2 [8.9 (20–65)]
Open in a new tab

NOTE: N = 622, at the baseline survey unless otherwise specified.

Abbreviations: HMO, Health Maintenance Organization; VA, Veterans Affairs.

Over half (51%) of the women had a lumpectomy only, and 48% had a mastectomy. Sixty percent of the participants having mastectomies underwent immediate reconstructive surgery. Ninety-three percent of all women had AND, 4% had SND only, and 2% had neither. Seventy-one percent of the women had 10 or more nodes removed (median of 15 nodes removed), and 44% had one or more positive nodes. Eighty-eight percent of the women received chemotherapy, 70% received radiation therapy, and 55% received tamoxifen sometime after their diagnosis of breast cancer.

Follow-up Surveys

The 622 participants with postsurgery follow-up completed up to seven follow-up surveys over the course of the first 3 years after survey. Of the 622 participants, 296 (48%) had complete data for all visits. More than three fourths (n = 482; 77%) of the women had >50% data for all visits over the follow-up period. The effect of missing data was examined by comparing analyses with complete-case data to analyses using imputation as described in the analytic methods. Prevalence and correlates of outcomes were similar and results presented are based on the analyses with resampling, where applicable.

Swelling

Twenty percent of the women reported having arm/hand swelling during the first 6 months following surgery, 36% by 1 year, and over half (54%) by the 3rd year following surgery. Figure 1 shows the Kaplan-Meier estimate of ever reporting arm/hand swelling over the first 3 years following surgery. The median time to swelling was ~26 months after surgery. Prevalence of swelling varied from 23% to 29% for any 6-month window following surgery. Women reported swelling in the upper arm only more frequently (43%) than in the hand only (34%) or in both the arm and hand (22%). Seventy percent of the cases of swelling were reported as being mild, 25% were moderate, and 5% reported severe swelling. Forty-three percent of the swelling cases were accompanied by pain in the affected hand and/or arm.

Figure 1.

Figure 1

Open in a new tab

Swelling incidence over first 3 y following surgery (N = 622).

Table 2 summarizes the results of the Cox proportional hazards model assessing which factors were associated with ever swelling. Number of nodes removed was the most significant factor (P = 0.003), with the hazard increasing by 2.2% for each additional node removed (~24% increase for 10 nodes). Additionally, the hazard of swelling was increased by 76% for women who received chemotherapy (P = 0.02), by 51% for those who were obese at diagnosis (relative to normal weight; P = 0.01), and by 36% for those who were married (P = 0.05).

Table 2.

Association between patient characteristics and time to first swelling (results from weighted resampling, Cox regression analysis; N= 622)

Characteristic HR (95% CI) P
Non-White vs White 1.30 (0.89–1.88) 0.17
Married vs single 1.36 (1.00–1.85) 0.05
Education 0.56
  Some college vs
high school graduate and below		 1.08 (0.68–1.73) 0.74
  College graduate vs
high school graduate and below		 0.93 (0.60–1.46) 0.76
Weight status 0.04
  Overweight vs normal/underweight* 1.24(0.92–1.69) 0.16
  Obese vs normal/underweight† 1.51 (1.09–2.09) 0.01
Age at diagnosis, y 1.00 (0.97–1.03) 1.00
Current smoker (Y/N) 0.84(0.51–1.40) 0.51
Weekly exercise 0.12
  Walking vs none 1.14(0.73–1.77) 0.56
  Mild vs none 1.49 (0.97–2.30) 0.07
  Moderate vs none 1.18 (0.80–1.72) 0.40
  Strenuous vs none 1.06 (0.73–1.55) 0.76
Children <8 y old 0.86 (0.64–1.14) 0.29
Employment 0.53
  Part-time vs full-time 0.84(0.58–1.23) 0.38
  Full-time homemaker vs full-time 0.91 (0.63–1.31) 0.61
  Other vs full-time 1.06 (0.76–1.48) 0.74
Reconstructive surgery (Y/N) 0.78 (0.55–1.09) 0.15
Lumpectomy (Y/N) 0.96 (0.69–1.34) 0.81
Mastectomy (Y/N) 1.36 (0.92–2.03) 0.13
Node dissection 0.56
  None vs AND 1.05 (0.38–2.91) 0.93
  SND only vs AND 0.68 (0.33–1.41) 0.30
No. nodes removed 1.02 (1.01–1.04) <0.01
No. nodes positive 0.99 (0.96–1.01) 0.28
Antibiotic use at baseline (Y/N) 1.66 (0.90–3.03) 0.10
Radiation therapy (Y/N) 1.23 (0.86–1.77) 0.26
Chemotherapy (Y/N) 1.76 (1.10–2.82) 0.02
Tamoxifen (Y/N) 0.81 (0.62–1.05) 0.11
Open in a new tab

Abbreviations: 95% CI, 95% confidence interval; Y/N, yes/no.

*

BMI, 25–29.9 versus <25 kg/m2.

†

BMI, ≥30 versus <25 kg/m2.

Table 3 presents the results of the longitudinal analysis of factors associated with the prevalence of swelling during the first 3 years following breast cancer surgery. Non-white race, [odds ratio (OR), 1.69; P = 0.04], a greater number of nodes removed (OR, 1.04; P < 0.01), tamoxifen use (OR, 1.45; P = 0.02), and needing antibiotics for arm or hand infection (OR, 2.41; P < 0.01) were factors significantly related to the prevalence of arm and/or hand swelling over time.

Table 3.

Factors associated with swelling that occurred during the 1st 3 y (results from the Generalized Estimating Equations modeling; N = 622)

Characteristic OR (95% CI) P
Months past surgery
  Linear 1.06 (1.02–1.10) <0.01
  Quadratic 0.998 (0.997–0.999) <0.01
Non-White vs White 1.69 (1.03–2.75) 0.04
Married vs single 1.38 (0.95–2.01) 0.09
Education 0.17
  Some college vs
high school graduate and below		 1.20 (0.66–2.18) 0.55
  College graduate vs
high school graduate and below		 0.83 (0.47–1.47) 0.53
Weight status 0.07
  Overweight vs normal/underweight* 1.35 (0.98–1.87) 0.07
  Obese vs normal/underweight† 1.54(1.02–2.32) 0.04
Age at diagnosis, y 1.00 (0.96–1.03) 0.83
Current smoker (Y/N) 0.82 (0.51–1.33) 0.42
Weekly exercise 0.64
  Walking vs none 1.12 (0.85–1.48) 0.43
  Mild vs none 1.29 (0.90–1.84) 0.17
  Moderate vs none 0.97 (0.67–1.41) 0.88
  Strenuous vs none 1.04(0.73–1.48) 0.83
Children <8 y old 0.79 (0.55–1.13) 0.19
Employment 0.99
  Part-time vs full-time 1.05 (0.63–1.75) 0.86
  Full-time homemaker vs full-time 1.00 (0.64–1.57) 0.99
  Other vs full-time 0.98 (0.63–1.51) 0.91
Reconstructive surgery (Y/N) 0.68 (0.44–1.04) 0.08
Lumpectomy (Y/N) 0.76 (0.49–1.17) 0.21
Mastectomy (Y/N) 1.36 (0.82–2.25) 0.23
Node dissection 0.31
  None vs AND 0.88 (0.31–2.54) 0.82
  SND only vs AND 0.57 (0.26–1.25) 0.16
No. nodes removed 1.04(1.02–1.06) <0.01
No. nodes positive 0.97 (0.94–1.01) 0.12
Antibiotic use (Y/N) 2.41 (1.66–3.48) <0.01
Radiation therapy (Y/N) 1.48 (0.95–2.32) 0.09
Chemotherapy (Y/N) 1.58 (0.91–2.76) 0.10
Tamoxifen (Y/N) 1.45 (1.06–1.99) 0.02
Open in a new tab
*

BMI, 25–29.9 versus <25 kg/m2.

†

BMI, ≥30 versus <25 kg/m2.

Logistic regression was used to examine the simultaneous effects of demographic and clinical factors on persistent swelling during this 3-year period (Table 4). Approximately 32% of the women experienced persistent swelling (i.e., two or more episodes of arm and/or hand swelling) during the first 3 years after surgery. Only two variables were found to be significantly related to persistent swelling: the number of nodes removed and weight status. For each additional lymph node removed, the odds of persistent swelling increased by 3% (OR, 1.03; P = 0.01). For women with baseline weight status in the obese range (i.e., >30 kg/m2) compared with normal/ underweight weight status (<25 kg/m2), the odds of persistent swelling were 2.24 times higher (P < 0.01).

Table 4.

Factors associated with persistent swelling during the first 3 y (results from logistic regression using weighted resampling; N = 622)

Characteristic OR (95% CI) P
Non-White vs White 1.52 (0.82–2.80) 0.18
Married vs single 1.41 (0.88–2.26) 0.15
Education 0.22
  Some college vs
high school graduate and below		 1.20 (0.57–2.51) 0.64
  College graduate vs
high school graduate and below		 0.81 (0.40–1.65) 0.56
Weight status 0.01
  Overweight vs normal/underweight* 1.58 (0.97–2.56) 0.07
  Obese vs normal/underweight† 2.24(1.33–3.78) <0.01
Age at diagnosis, y 0.99 (0.95–1.03) 0.75
Current smoker (Y/N) 0.73 (0.35–1.55) 0.42
Weekly exercise 0.28
  Walking vs none 0.77 (0.39–1.54) 0.46
  Mild vs none 1.62 (0.82–3.21) 0.17
  Moderate vs none 1.34 (0.74–2.42) 0.33
  Strenuous vs none 1.17 (0.66–2.08) 0.59
Children <8 y old 0.76 (0.48–1.20) 0.24
Employment 0.79
  Part-time vs full-time 1.17 (0.65–2.09) 0.60
  Full-time homemaker vs full-time 1.14 (0.64–2.04) 0.66
  Other vs full-time 1.16 (0.67–1.99) 0.60
Reconstructive surgery (Y/N) 0.78 (0.45–1.35) 0.37
Lumpectomy (Y/N) 1.01 (0.58–1.74) 0.98
Mastectomy (Y/N) 1.22 (0.63–2.35) 0.55
Node dissection 0.45
  None vs AND 0.96 (0.21–4.44) 0.96
  SND only vs AND 0.51 (0.15–1.66) 0.26
No. nodes removed 1.03 (1.01–1.06) 0.01
No. nodes positive 0.98 (0.94–1.03) 0.44
Antibiotic use at baseline (Y/N) 1.37 (0.47–4.03) 0.56
Radiation therapy (Y/N) 1.26 (0.70–2.24) 0.44
Chemotherapy (Y/N) 1.80 (0.94–3.46) 0.08
Tamoxifen (Y/N) 1.27 (0.86–1.87) 0.23
Open in a new tab

NOTE: Persistent swelling was defined as the report of two or more swelling episodes within the first 3 y after surgery.

*

BMI, 25–29.9 versus <25 kg/m2.

†

BMI, ≥30 versus <25 kg/m2.

Quality of Life

Table 5 shows the results for the longitudinal mixed modeling exploring the relationships between arm and/or hand swelling and quality of life, adjusted for demographic and clinical factors. Women with no swelling had significantly higher (better) SF-12M, SF-12P, and FACT-B scores than women reporting swelling (P value <0.01 for each subscale).

Table 5.

Adjusted effects of swelling on quality of life: SF-12M, SF-12P, and FACT-B (results from longitudinal mixed modeling; N = 622)

Scale Estimate SE (95% confidence
limits)		 P
SF-12M 1.67 0.39 (0.91,2.43) <0.01
  Mean scores at 3 y
   Not swelling 44.8 0.73
   Swelling 43.1 0.78
SF-12P 1.29 0.37 (0.56,2.03) <0.01
  Mean scores at 3 y
   Not swelling 49.8 0.84
   Swelling 48.6 0.88
FACT-B 2.19 0.67 (0.87,3.51) <0.01
  Mean scores at 3 y
   Not swelling 113.8 2.03
   Swelling 111.7 2.08
Open in a new tab

NOTE: Models adjusted for months past surgery (linear and quadratic term), age at diagnosis (in years), race (White versus other), marital status (married versus single), education (high school graduate or less, some college, college graduate), weight status category (time varying), current smoking status (time varying), weekly exercise category (time varying), having a child <8 y of age, employment status (full-time, part-time, homemaker, and other), reconstructive surgery, lumpectomy, mastectomy, nodal dissection (none, SND only, and AND), number of nodes removed, number of positive nodes, antibiotic use (time varying), radiation therapy, chemotherapy, and tamoxifen use (lag1 time varying).

Discussion

Lymphedema is an often debilitating consequence of breast cancer treatment (5, 9, 48–51). The goal of this study was to determine prospectively the incidence and prevalence of lymphedema in young breast cancer survivors, to assess which factors were associated with reporting lymphedema (ever and persistently), and to assess the effect of lymphedema on quality of life. To date, this is the first study in the United States to address these issues among young breast cancer survivors.

Lymphedema Incidence

Swelling may occur at any point following axillary node dissection or radiation therapy, beginning immediately after or even delayed by several years. Our findings revealed a high cumulative incidence of swelling among young breast cancer survivors, with more than half (54%) reporting ever swelling by 36 months after surgery. Few studies have assessed the cumulative incidence of swelling in a prospective study design; however, other cross-sectional studies have reported swelling rates of 8% to 39% at 18 months to 20 years after treatment, respectively (10, 11). Previous studies have not been limited to young (≤45 years of age) breast cancer survivors, as was true in the present study. In addition, the present study used a prospective design with assessment of swelling every 6 months, which enabled estimation of both the incidence and the prevalence of swelling.

Using various multivariable regression models, several factors were shown to contribute significantly to swelling during the 3-year study period in this study. Number of nodes removed and obesity were significantly associated (or borderline associated) with time to first swelling, swelling over time, and persistent swelling. The finding that young breast cancer survivors had a greater risk of swelling as more nodes were removed during surgery is consistent with other studies. A German study by Engel et al. (7) found that the odds of swelling among women who had between 10 and 20 nodes removed were 2.6 times the odds of swelling among women who did not have axillary surgery, and the effect was even more pronounced for women who had >20 nodes removed. Similar findings have been reported by others (52, 53). Our study found an OR of 1.04, revealing that for every node removed, the odds of swelling increased by 4%. If 10 nodes were removed, the odds of swelling among young breast cancer survivors would increase to 48%, and if 20 nodes were removed, the odds of swelling would increase to 119%. Although this is somewhat lower than that reported in a study of similar design (7), it is comparable and similar in magnitude. Additionally, it is medically plausible that the removal of more nodes contributes to higher risk of swelling given that there is greater disruption of lymph flow as more nodes are removed. Other studies, however, have not found a significant effect for the number of lymph nodes removed on the incidence of lymphedema (8, 54), and reasons for this difference are unclear.

The relationship between weight status (i.e., BMI category) and swelling is particularly significant because weight status was associated with swelling in all models. This finding is corroborated in other studies (8, 52, 55) and has many implications. Overweight and obesity can be easily identified in breast cancer patients and, with some effort, it can be modified after treatment to reduce a woman’s risk of swelling. There is overwhelming evidence that overweight and obesity contribute significantly to other health problems, not only among cancer survivors but also among all Americans (56, 57). One recent study by Denmark-Wahnefried et al. (58) reported that a majority (70%) of breast cancer survivors are overweight or obese, putting most survivors at greater risk for cancer recurrence, cardiovascular disease, diabetes, and overall poorer quality of life (59–63). Given these indications, oncologists should strongly encourage their breast cancer patients to engage in and routinely practice weight control strategies to minimize their risk for swelling, cancer recurrence, and development of other chronic diseases.

Other demographic and medical characteristics that significantly affected the onset of lymphedema or persistent swelling were marital status, chemotherapy, race, tamoxifen use, and antibiotic use at baseline. The risk of swelling among married women was 1.36 times higher than the risk of swelling for unmarried women, although a prior study by Engel et al. (7) suggested no relationship between swelling and relationship status. It is not known why relationship status would be related to risk of swelling. If married women had higher BMIs or had more nodes removed, they might be more likely to experience higher incidence of swelling; however, those relationships were not found in this study. Higher rates of swelling could be related to the types of activities, in which married women engage (e.g., more routine household chores, care of children, etc.) compared with other women.

Women receiving chemotherapy, taking tamoxifen, and receiving antibiotics at baseline were also more likely to report swelling over time. The risk of swelling was increased by 76% for women receiving chemotherapy, which contradicts findings from several other studies that found no association between receipt of chemotherapy and swelling, even after accounting for axillary node dissection (8, 27, 52, 54). Perhaps, the more aggressive treatment offered to younger breast cancer survivors was related to the increased risk of postoperative swelling in this population.

The odds of reporting swelling were greater in non-White women compared with White women (OR, 1.69), and this finding is supported by others (52). In addition, the women in our study who took tamoxifen were more likely to report swelling (OR, 1.45) than those who did not take tamoxifen, whereas a previous study reported no association with tamoxifen use (54). Clearly, this finding warrants further study as this relationship was based on self-report of swelling. Similarly, women receiving antibiotics also reported more swelling (OR, 2.41). Using antibiotic use as a proxy for arm infection, Petrek et al. (64) also reported a significant relationship between arm infection and arm swelling.

Several factors in our study did not have a significant effect on the incidence of lymphedema, including education, type of surgery, having reconstructive surgery, having radiation, the number of positive nodes, age at diagnosis, smoking, and exercise frequency. In some cases, other findings support ours (7, 8, 52–54), whereas in other cases, they show a different trend (9, 27, 55, 65, 66). For example, there was no relationship between receiving radiation and swelling among women in our study; however, others have reported receipt of radiation as part of breast cancer treatment to be a risk factor for arm swelling (9, 65, 66). These differences may, in fact, be the result of the populations studied and the type of study design. The present study focuses solely on young breast cancer survivors in a prospective design.

Lymphedema Prevalence

Persistent swelling has been less studied. Our findings provide an estimate of repeated or continuous swelling up to 3 years after surgery. Within 6 months of surgery, ~20% of young breast cancer survivors reported swelling. By 36 months, 54% of the participants had swelled and 32% (59% of those with any swelling) had persistent swelling. These findings are similar to those reported by Engel et al., (7) where 38% of the participants experienced continuous swelling 5 years from surgery. Factors related to persistent swelling were similar to those related to incident swelling.

Lymphedema and Quality of Life

Young breast cancer survivors who reported swelling experienced a poorer quality of life compared with women who did not report swelling, as evidenced by scores on the FACT-B and the mental and physical scales of the SF-12. The results of numerous other studies confirm these findings with more heterogeneous populations, thus suggesting that, in this respect, the effect of lymphedema on quality of life is not different for young breast cancer survivors compared with older breast cancer survivors (7, 9–11, 52, 67, 68).

Research as has also shown that as arm problems (i.e., swelling and limited movement) are treated and subside, quality of life significantly improves (7). This suggests that prompt diagnosis and treatment of lymphedema can help maintain quality of life among survivors.

Strengths and Limitations

Because of the large sample size and prospective design, our study provides prospective estimates of lymphedema incidence and prevalence and the effect of lymphedema on quality of life among young breast cancer survivors. To date, relatively few studies have prospectively determined lymphedema incidence or examined persistent swelling; however, our estimates of both incidence and prevalence of swelling are consistent with previous estimates from cross-sectional studies. Thus, our study extends what is known about the prevalence of lymphedema and its effect as a chronic health condition.

Several limitations should be noted, however. Young breast cancer survivors in this study were mostly White, affluent, and well-educated women who may be healthier (e.g., only 8% self-reported smoking) than the average young breast cancer survivor. Therefore, caution should be used when generalizing these results to a more representative population. Second, women in this study were recruited through tumor registries and physician practices. Consequently, those who chose to participate may be different than those who chose not to participate. Third, the sample for this study included only those women who were 45 years of age or younger at diagnosis; therefore, caution should again be used when generalizing these results to older populations. Finally, lymphedema was measured through self-report and was not validated by physical measurement. Other studies (39) have reported moderate correlation between objective measurements indicating swelling and self-report of swelling (c-statistic, 0.919; ref. 39), thus self-report is fairly accurate.

Conclusions

In general, our findings further support results of previous studies examining lymphedema incidence and its effect on quality of life and extend what is known about lymphedema prevalence and incidence using a prospective design with a large sample size. Lymphedema is clearly a chronic condition, which negatively affects breast cancer survivors’ quality of life. These issues underlie the importance of awareness, prevention, early diagnosis, and treatment of lymphedema. Understanding those factors that increase the odds of lymphedema incidence and persistent swelling will allow clinicians, researchers, and educators to more accurately identify those at greatest risk (i.e., those with axillary node dissection and who are obese) and to develop programs and practices that best meet the needs of breast cancer survivors. For example, a weight management program that promotes weight loss or prevention of weight gain postoperatively may reduce the incidence of lymphedema among those at greater risk. Similarly, providing lymphedema prevention education to those younger women who undergo more extensive axillary node dissection and/or chemotherapy may reduce the risk of prevalent swelling or the severity if swelling does develop. In so doing, cancer survivors of all ages will ultimately enjoy better quality of life.

Acknowledgments

Grant support: U.S. Army Medical Research and Materiel Command grants DAMD17-96-1-6292 and DAMD17-01-1-0447.

Footnotes

Presented in part at both an oral paper session and a poster session at the Era of Hope Department of Defense Breast Cancer Research Program Meeting, June 11, 2005, Philadelphia, PA and at Congress of Epidemiology 2001, Toronto, Ontario, Canada.

References

  • 1.American Cancer Society. Cancer facts and figures. Atlanta: American Cancer Society, Inc; 2006. [Google Scholar]
  • 2.Jemal A, Murray T, Ward E, et al. Cancer statistics, 2005. CA Cancer J Clin. 2005;55:10–30. doi: 10.3322/canjclin.55.1.10. [DOI] [PubMed] [Google Scholar]
  • 3.American Cancer Society. Breast cancer facts and figures 2005–2006. Atlanta: American Cancer Society, Inc; 2005. [Google Scholar]
  • 4.Paskett ED, Stark NN. Lymphedema: knowledge, treatment, and impact among breast cancer survivors. Breast J. 1999;5:341. doi: 10.1046/j.1524-4741.2000.99072.x. [DOI] [PubMed] [Google Scholar]
  • 5.Guralnik JM, LaCroix AZ, Abbott RD, et al. Maintaining mobility in late life: demographic characteristics and chronic conditions. Am J Epidemiol. 1993;137:845–857. doi: 10.1093/oxfordjournals.aje.a116746. [DOI] [PubMed] [Google Scholar]
  • 6.Petrek JA, Pressman PI, Smith RA. Lymphedema: current issues in research and management. CA Cancer J Clin. 2000;50:292–307. doi: 10.3322/canjclin.50.5.292. [DOI] [PubMed] [Google Scholar]
  • 7.Engel J, Kerr J, Schlesinger-Raab A, Sauer H, Holzel D. Axilla surgery severely affects quality of life: results of a 5-year prospective study in breast cancer patients. Breast Cancer Res Treat. 2003;79:47–57. doi: 10.1023/a:1023330206021. [DOI] [PubMed] [Google Scholar]
  • 8.Ozaslan C, Kuru B. Lymphedema after treatment of breast cancer. Am J Surg. 2004;187:69–72. doi: 10.1016/j.amjsurg.2002.12.003. [DOI] [PubMed] [Google Scholar]
  • 9.Kwan W, Jackson J, Weir LM, Dingee C, McGregor G, Olivotto IA. Chronic arm morbidity after curative breast cancer treatment: prevalence and impact on quality of life. J Clin Oncol. 2002;20:4242–4248. doi: 10.1200/JCO.2002.09.018. [DOI] [PubMed] [Google Scholar]
  • 10.Velanovich V, Szymanski W. Quality of life of breast cancer patients with lymphedema. Am J Surg. 1999;177:184–188. doi: 10.1016/s0002-9610(99)00008-2. [DOI] [PubMed] [Google Scholar]
  • 11.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. doi: 10.1002/cncr.11531. [DOI] [PubMed] [Google Scholar]
  • 12.Petrek JA, Heelan MC. Incidence of breast carcinoma-related lymphedema. Cancer. 1998;83:1776–1781. doi: 10.1002/(sici)1097-0142(19981215)83:12b+<2776::aid-cncr25>3.0.co;2-v. [DOI] [PubMed] [Google Scholar]
  • 13.Swedborg I, Wallgren A. The effect of pre- and post-mastectomy radiotherapy on the degrees of edema, shoulder-joint mobility, and gripping force. Cancer. 1981;47:877–881. doi: 10.1002/1097-0142(19810301)47:5<877::aid-cncr2820470511>3.0.co;2-3. [DOI] [PubMed] [Google Scholar]
  • 14.Kissin MW, Quero Della Rovere G, Easton D, Westbury G. Risk of lymphedema following the treatment of breast cancer. Br J Surg. 1986;73:580–584. doi: 10.1002/bjs.1800730723. [DOI] [PubMed] [Google Scholar]
  • 15.Gerber L, Lampert M, Wood C, et al. Comparison of pain, motion, and edema after modified radical mastectomy vs. local excision with axillary dissection and radiation. Breast Cancer Res Treat. 1992;21:139–145. doi: 10.1007/BF01836960. [DOI] [PubMed] [Google Scholar]
  • 16.Werner RS, McCormick B, Petrek J, et al. Arm edema in conservatively managed breast cancer: obesity is a major predictive factor. Radiology. 1991;180:177–184. doi: 10.1148/radiology.180.1.2052688. [DOI] [PubMed] [Google Scholar]
  • 17.Guedes Neto HI. Arm edema after treatment for breast cancer. Lymphology. 1997;30:35–36. [PubMed] [Google Scholar]
  • 18.Sneeuw KC, Aaronson NK, Yarnold JR, et al. Cosmetic and functional outcomes of breast conserving treatment for early stage breast cancer: relationship with psychosocial functioning. Radiother Oncol. 1992;25:160–166. doi: 10.1016/0167-8140(92)90262-s. [DOI] [PubMed] [Google Scholar]
  • 19.Maunsell E, Brisson J, Deschenes L. Arm problems and psychological distress after surgery for breast cancer. Can J Surg. 1993;36:315–320. [PubMed] [Google Scholar]
  • 20.Passik S, Newman M, Brennan M, Holland J. Psychiatric consultation for women undergoing rehabilitation for upper-extremity lymphedema following breast cancer treatment. J Pain Symptom Manage. 1993;8:226–233. doi: 10.1016/0885-3924(93)90132-f. [DOI] [PubMed] [Google Scholar]
  • 21.Parker SL, Tong T, Bolden S, Wingo PA. Cancer statistics, 1997. CA Cancer J Clin. 1997;47:5–27. doi: 10.3322/canjclin.47.1.5. [DOI] [PubMed] [Google Scholar]
  • 22.Balducci L, Schapira DV, Cox CE, Greenberg HM, Lyman GH. Breast cancer of the older woman: an annotated review. J Am Geriatr Soc. 1991;39:1113–1123. doi: 10.1111/j.1532-5415.1991.tb02879.x. [DOI] [PubMed] [Google Scholar]
  • 23.Yancik R, Ries LG, Yates JW. Breast cancer in aging women: a population-based study of contrasts in stage, surgery, and survival. Cancer. 1989;63:976–981. doi: 10.1002/1097-0142(19890301)63:5<976::aid-cncr2820630532>3.0.co;2-a. [DOI] [PubMed] [Google Scholar]
  • 24.Kessler LG. The relationship between age and the incidence of breast cancer: population and screening program data. Cancer. 1992;69:1896–1903. doi: 10.1002/1097-0142(19920401)69:7+<1896::aid-cncr2820691704>3.0.co;2-1. [DOI] [PubMed] [Google Scholar]
  • 25.Anderson RT, James MK, Miller ME, Worley AS, Longino CF., Jr The timing of change: patterns in transitions in functional status among elderly persons. J Gerontol B Psychol Sci Soc Sci. 1998;53:S17–S27. doi: 10.1093/geronb/53b.1.s17. [DOI] [PubMed] [Google Scholar]
  • 26.Hull MM. Lymphedema in women treated for breast cancer. Semin Oncol Nurs. 2000;16:226–237. doi: 10.1053/sonc.2000.8117. [DOI] [PubMed] [Google Scholar]
  • 27.Geller BM, Vacek PM, O’Brien P, Secker-Walker RH. Factors associated with arm swelling after breast cancer surgery. J Womens Health. 2003;12:921–930. doi: 10.1089/154099903770948159. [DOI] [PubMed] [Google Scholar]
  • 28.Warmuth M, Bowen G, Prosnitz L, Chu L, Broadwater G, Peterson B. Complications of axillary lymph node dissection for carcinoma of the breast: a report based on a patient survey. Cancer. 1998;83:1362–1368. doi: 10.1002/(sici)1097-0142(19981001)83:7<1362::aid-cncr13>3.0.co;2-2. [DOI] [PubMed] [Google Scholar]
  • 29.Paskett ED, Naughton M, Robertson J, Petrek J. Lymphedema in young breast cancer survivors. Proc Am Assoc Cancer Res. 2001;42:740. [Google Scholar]
  • 30.Lin PP, Allison DC, Wainstock J, et al. Impact of axillary lymph node dissection on the therapy of breast cancer patients. J Clin Oncol. 1993;11:1536–1544. doi: 10.1200/JCO.1993.11.8.1536. [DOI] [PubMed] [Google Scholar]
  • 31.Bartelin H, Garavaglia G, Johansson KA, et al. Quality assurance in conservative treatment of early breast cancer: report on a consensus meeting of the EORTC Radiotherapy and Breast Cancer Cooperative groups and the EUSOMA (European Society of Mastology) Radiother Oncol. 1991;22:323–326. doi: 10.1016/0167-8140(91)90172-d. [DOI] [PubMed] [Google Scholar]
  • 32.Kroman N, Jensen MB, Wohlfahrt J, Mouridsen HT, Andersen PK, Melbye M. Factors influencing the effect of age on prognosis in breast cancer: population based study. Br Med J. 2000;320:474–478. doi: 10.1136/bmj.320.7233.474. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Talley LI, Grizzle WE, Waterbor JW, Brown D, Weiss H, Frost AR. Hormone receptors and proliferation in breast carcinomas of equivalent histologic grades in pre- and postmenopausal women. Int J Cancer. 2002;98:118–127. doi: 10.1002/ijc.10171. [DOI] [PubMed] [Google Scholar]
  • 34.Shapiro CL, Recht A. Late effects of adjuvant therapy for breast cancer. J Natl Cancer Inst Monogr. 1994;16:101–112. [PubMed] [Google Scholar]
  • 35.Quivey J, Luce JM, Stewart SL, Johnston M, Banks PJ, Bloom JR. Proceedings of the American Society of Clinical Oncology. Baltimore (MD): Waverly Press; 1998. Younger women with breast cancer: patterns of care in 5 San Francisco Bay Area Counties. [Google Scholar]
  • 36.Osteen RT, Cady B, Friedman M, et al. Patterns of care for younger women with breast cancer. J Natl Cancer Inst Monogr. 1994;16:43–46. [PubMed] [Google Scholar]
  • 37.SEER Cancer statistics review, 1975-2002. Bethesda (MD: National Cancer Institute; 2005. [Google Scholar]
  • 38.Petrek JA, Naughton MJ, Case LD, et al. Incidence, time course, and determinants of menstrual bleeding after breast cancer treatment: a prospective study. J Clin Oncol. 2006;24:1045–1051. doi: 10.1200/JCO.2005.03.3969. [DOI] [PubMed] [Google Scholar]
  • 39.Armer JM, Radina ME, Porock D, Culbertson SD. Predicting breast cancer-related lymphedema using self-reported symptoms. Nurs Res. 2003;52:370–379. doi: 10.1097/00006199-200311000-00004. [DOI] [PubMed] [Google Scholar]
  • 40.Brady M, Cella D, Mo F. Reliability and validity of the functional assessment of cancer therapy-breast (FACT-B) quality of life instrument. J Clin Oncol. 1997;15:974–986. doi: 10.1200/JCO.1997.15.3.974. [DOI] [PubMed] [Google Scholar]
  • 41.Ware J, Kosinski M, Keller SD. A 12-item short-form health survey: construction of scales and preliminary tests of reliability and validity. Med Care. 1996;34:220–233. doi: 10.1097/00005650-199603000-00003. [DOI] [PubMed] [Google Scholar]
  • 42.Gandek B, Ware J, Aaronson NK, et al. Cross-validation of item selection and scoring for the SF-12 Health Survey in nine countries: results from the IQOLA Project, International Quality of Life Assessment. J Clin Epidemiol. 1998;51:1171–1178. doi: 10.1016/s0895-4356(98)00109-7. [DOI] [PubMed] [Google Scholar]
  • 43.Kaplan EL, Meier P. Nonparametric estimation from incomplete observations. J Am Stat Assoc. 1958;53:457–481. [Google Scholar]
  • 44.Cox DR. Regression models and life tables. J R Stat Soc Ser B. 1972;34:187–220. [Google Scholar]
  • 45.Good PI. Resampling methods. 2nd. New York: Springer; 2005. [Google Scholar]
  • 46.Liang KY, Zeger SL. Longitudinal data analysis using general linear models. Biometrika. 1986;73:13–22. [Google Scholar]
  • 47.Zeger SL, Liang KY. Longitudinal data analysis for discrete and continuous outcomes. Biometrics. 1986;42:121–130. [PubMed] [Google Scholar]
  • 48.Tobin MB, Lacy HJ, Meyer L, Mortimer PS. The psychological morbidity of breast cancer related arm swelling. Cancer. 1993;72:3248–3252. doi: 10.1002/1097-0142(19931201)72:11<3248::aid-cncr2820721119>3.0.co;2-z. [DOI] [PubMed] [Google Scholar]
  • 49.Woo B, Dibble SL, Piper BF, Keating SB, Weiss MC. Differences in fatigue by treatment methods in women with breast cancer. Oncol Nurs Forum. 1998;25:915–920. [PubMed] [Google Scholar]
  • 50.Witte MH, Wutte CL, Mortimer PS, Jamal S. Lymphedema in the developing and developed world: contrasts and prospects. Lymphology. 1988;21:242–243. [PubMed] [Google Scholar]
  • 51.Kosorok MR, Omenn GS, Diehr P, Koepsell TD, Patrick DL. Restricted activity days among older adults. Am J Public Health. 1992;82:1263–1267. doi: 10.2105/ajph.82.9.1263. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 52.Beaulac SM, McNair LA, Scott TE, La Morte WW, Kavanah MT. Lymphedema and quality of life in survivors of early-stage breast cancer. Arch Surg. 2002;137:1253–1257. doi: 10.1001/archsurg.137.11.1253. [DOI] [PubMed] [Google Scholar]
  • 53.Goffman TE, Laronga C, Wilson L, Elkins D. Lymphedema of the arm and breast in irradiated breast cancer patients: risks in an era of dramatically changing axillary surgery. Breast J. 2004;10:405–411. doi: 10.1111/j.1075-122X.2004.21411.x. [DOI] [PubMed] [Google Scholar]
  • 54.Hinrichs CS, Watroba NL, Rezaishiraz H, et al. Lymphedema secondary to postmastectomy radiation: incidence and risk factors. Ann Surg Oncol. 2004;11:573–580. doi: 10.1245/ASO.2004.04.017. [DOI] [PubMed] [Google Scholar]
  • 55.Johansson K, Ohlsson K, Ingvar C, Albertsson M, Ekdahl C. Factors associated with the development of arm lymphedema following breast cancer treatment: a match pair case-control study. Lymphology. 2002;35:59–71. [PubMed] [Google Scholar]
  • 56.Hu FB. Overweight and obesity in women: health risks and consequences. J Womens Health. 2003;12:163–172. doi: 10.1089/154099903321576565. [DOI] [PubMed] [Google Scholar]
  • 57.Aronne LJ. Classification of obesity and assessment of obesity-related health risks. Obes Res. 2002;10:105S–115S. doi: 10.1038/oby.2002.203. [DOI] [PubMed] [Google Scholar]
  • 58.Denmark-Wahnefried W, Aziz NM, Rowland JH, Pinto BM. Riding the crest of the teachable moment: promoting long-term health after the diagnosis of cancer. J Clin Oncol. 2005;23:5814–5830. doi: 10.1200/JCO.2005.01.230. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 59.Brown JK, Byers T, Doyle C, et al. Nutrition and physical activity during and after cancer treatment: an American Cancer Society guide for informed choices. CA Cancer J Clin. 2003;53:268–291. doi: 10.3322/canjclin.53.5.268. [DOI] [PubMed] [Google Scholar]
  • 60.Rock CL, Denmark-Wahnefried W. Nutrition and survival after the diagnosis of breast cancer: a review of the evidence. J Clin Oncol. 2002;20:3302–3316. doi: 10.1200/JCO.2002.03.008. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 61.Chlebowski RT, Aiello E, McTiernan A. Weight loss in breast cancer patient management. J Clin Oncol. 2002;20:1128–1143. doi: 10.1200/JCO.2002.20.4.1128. [DOI] [PubMed] [Google Scholar]
  • 62.Nuver J, Smit AJ, Postma A, Sleijfer DT, Gietema JA. The metabolic syndrome in long-term cancer survivors: an important target for secondary measures. Cancer Treat Rev. 2002;28:195–214. doi: 10.1016/s0305-7372(02)00038-5. [DOI] [PubMed] [Google Scholar]
  • 63.Argiles JM, Lopez-Soriano FJ. Insulin and cancer. Int J Oncol. 2001;18:683–687. [PubMed] [Google Scholar]
  • 64.Petrek JA, Senie RT, Peters M, Rosen PP. Lymphedema in a cohort of breast carcinoma survivors 20 years after diagnosis. Cancer. 2001;92:1368–1377. doi: 10.1002/1097-0142(20010915)92:6<1368::aid-cncr1459>3.0.co;2-9. [DOI] [PubMed] [Google Scholar]
  • 65.Schijven MP, Vingerhoets AJJM, Rutten HJT, et al. Comparison of morbidity between axillary lymph node dissection and sentinel node biopsy. Eur J Surg Oncol. 2003;29:341–350. doi: 10.1053/ejso.2002.1385. [DOI] [PubMed] [Google Scholar]
  • 66.Deo SVS, Ray S, Rath GK, et al. Prevalence and risk factors for development of lymphedema following breast cancer treatment. Indian J Cancer. 2004;41:8–12. [PubMed] [Google Scholar]
  • 67.Pereira de Godoy JM, Braile DM, de Fatima Godoy M, Longo O., Jr Quality of life and peripheral lymphedema. Lymphology. 2002;35:72–75. [PubMed] [Google Scholar]
  • 68.Pain SJ, Vowler SL, Purushotham AD. Is physical function a more appropriate measure than volume excess in the assessment of breast cancer-related lymphoedema (BCRL)? Eur J Cancer. 2003;39:2168–2172. doi: 10.1016/s0959-8049(02)00770-0. [DOI] [PubMed] [Google Scholar]

RESOURCES