Skip to main content
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2015 Nov 6.
Published in final edited form as: JAMA Oncol. 2015 Oct 1;1(7):931–941. doi: 10.1001/jamaoncol.2015.2666

Acute and Short-Term Toxicities of Conventionally Fractionated Versus Hypofractionated Whole Breast Irradiation in a Prospective, Randomized Trial

Simona F Shaitelman 1, Pamela J Schlembach 2, Isidora Arzu 3, Matthew Ballo 4, Elizabeth S Bloom 5, Daniel Buchholz 6, Gregory M Chronowski 7, Tomas Dvorak 8, Emily Grade 9, Karen E Hoffman 10, Patrick Kelly 11, Michelle Ludwig 12, George H Perkins 13, Valerie Reed 14, Shalin Shah 15, Michael C Stauder 16, Eric A Strom 17, Welela Tereffe 18, Wendy A Woodward 19, Joe Ensor 20, Donald Baumann 21, Alastair M Thompson 22, Diana Amaya 23, Tanisha Davis 24, William Guerra 25, Lois Hamblin 26, Gabriel Hortobagyi 27, Kelly K Hunt 28, Thomas A Buchholz 29, Benjamin D Smith 30
PMCID: PMC4635441  NIHMSID: NIHMS732775  PMID: 26247543

Abstract

IMPORTANCE

The most appropriate dose-fractionation for whole breast irradiation (WBI) remains uncertain.

OBJECTIVE

To assess acute and six-month toxicity and quality of life (QoL) with conventionally fractionated WBI (CF-WBI) versus hypofractionated WBI (HF-WBI).

DESIGN

Unblinded randomized trial of CF-WBI (n=149; 50 Gy/25 fractions + boost [10–14 Gy/5–7 fractions]) versus HF-WBI (n=138; 42.56 Gy/16 fractions + boost [10–12.5 Gy/4–5 fractions]).

SETTING

Community-based and academic cancer centers.

PARTICIPANTS

287 women age ≥ 40 years with stage 0–II breast cancer treated with breast-conserving surgery for whom whole breast irradiation without addition of a third field was recommended. 76% (n=217) were overweight or obese. Patients were enrolled from February 2011 through February 2014.

INTERVENTION(S) FOR CLINICAL TRIALS

CF-WBI versus HF-WBI.

MAIN OUTCOME MEASURES

Physician-reported acute and six-month toxicities using NCICTCv4.0 and patient-reported QoL using the FACT-B version 4. All analyses were intention-to-treat, with outcomes compared using chi-square, Cochran-Armitage test, and ordinal logistic regression. Patients were followed for a minimum of 6 months.

RESULTS

Treatment arms were well-matched for baseline characteristics including FACT-B total score (P=0.46) and individual QoL items such as lack of energy (P=0.86) and trouble meeting family needs (P=0.54). Maximal physician-reported acute dermatitis (P<0.001), pruritus (P<0.001), breast pain (P=0.001), hyperpigmentation (P=0.002), and fatigue (P=0.02) during radiation were lower in patients randomized to HF-WBI. Overall grade ≥2 acute toxicity was less with HF-WBI vs. CF-WBI (47% vs. 78%; P<0.001). Six months after radiation, physicians reported less fatigue in patients randomized to HF-WBI (P=0.01), and patients randomized to HF-WBI reported less lack of energy (P<0.001) and less trouble meeting family needs (P=0.01). Multivariable regression confirmed the superiority of HF-WBI in terms of patient-reported lack of energy (OR 0.39, 95% CI 0.24–0.63) and trouble meeting family needs (OR 0.34, 95% CI 0.16–0.75).

CONCLUSIONS AND RELEVANCE

HF-WBI appears to yield less acute toxicity than CF-WBI, as well as less fatigue and trouble meeting family needs six months after completing radiation. These findings should be communicated to patients as part of shared decision-making.

TRIAL REGISTRATION

NCT01266642 (https://clinicaltrials.gov/ct2/show/NCT01266642)

INTRODUCTION

To date, four randomized trials including over 7,000 women have compared conventionally fractionated whole breast irradiation (CF-WBI) to hypofractionated whole breast irradiation (HF-WBI).[13] With 10-year follow-up, these studies have shown equivalent rates of overall survival and local control between the two treatment regimens. Additionally, the United Kingdom START A and B trials reported less moderate or marked breast induration, telangiectasia, breast edema, and breast shrinkage in women randomized to HF-WBI.[1] Nevertheless, adoption of HF-WBI in the United States has been tepid, with only one-third of patients for whom HF-WBI is endorsed by the American Society for Radiation Oncology (ASTRO) actually receiving this treatment.[47]

The reasons underlying slow adoption of HF-WBI in the United States are likely multifactorial and reflect both scientific as well as pragmatic concerns.[8] Key ongoing obstacles to adoption of HF-WBI in the United States include the lingering concern that HF-WBI may actually increase toxicity due to higher dose per fraction and questions regarding the applicability of the published trials to practices that routinely use a tumor bed boost and to patients with larger body mass index (BMI) and central axis separation.[8, 9]

We sought to address these obstacles to adoption of HF-WBI by incorporating detailed toxicity and quality of life assessment into a randomized trial of HF-WBI versus CF-WBI, both followed by a tumor bed boost, and inclusive of all patients regardless of BMI or separation. Herein, we report physician-reported acute and six-month toxicities and patient-reported QoL by treatment arm.

PATIENTS AND METHODS

Methods

Enrollment

Patients were enrolled from 2011 to 2014 at The University of Texas MD Anderson Cancer Center (including both the Main Campus located in the Texas Medical Center and four surrounding MD Anderson regional centers); Orlando Health (formerly MD Anderson Orlando – Orlando, FL); and Banner MD Anderson in Gilbert, AZ. Women eligible for enrollment were age ≥ 40 years with pathologically-confirmed female carcinoma in situ (DCIS) or invasive breast cancer, stage Tis-T2, N0-N1a, M0, treated with breast conserving surgery with final negative margins (defined as no tumor on ink), with the physician-declared intent to deliver WBI without addition of a third field to cover the regional lymph nodes. Exclusion criteria included concomitant active treatment for another malignancy, history of prior breast cancer, bilateral breast cancer, prior overlapping radiation, pregnancy, or lack of fluency in English or Spanish.

Randomization

Patients were randomly allocated to treatment with either HF-WBI (42.56Gy in 16 fractions WBI) or CF-WBI (50Gy in 25 fractions WBI). The tumor bed boost if final margins were negative by ≥2mm or if there was a negative re-excision was 10Gy in 4 fractions or 12.5Gy in 5 fractions for HF-WBI and CF-WBI, respectively, and 12.5Gy in 5 fractions or 14Gy in 7 fractions if final margins were <2mm for HF-WBI and CF-WBI, respectively. The Pocock-Simon randomization method of dynamic allocation[10] was used to balance the arms of the study for post-operative physician-reported cosmetic assessment (excellent/good vs. fair/poor), bra cup size (D or higher vs. C or lower), receipt of chemotherapy (yes/no), margin status (< 2 mm vs ≥ 2 mm), and treatment location (Houston-area facilities vs. Banner MD Anderson vs. Orlando Health).

Radiation treatment

Patients were treated with megavoltage tangential portals and forward- or inverse-planned segmental fields to improve dose homogeneity. Dose was prescribed to a calculation point in the breast, within 2 cm of the chestwall-lung interface. Patient positioning in the supine or prone position was at physician discretion. Radiation oncologists were instructed to minimize the volume of tissue receiving greater than 108% of the prescription dose. Coverage of the undissected low axilla (levels I and II) was permitted if clinically indicated. The boost was delivered with either electrons or photons and could be omitted if the tumor bed volume precluded safe delivery of the boost.

Patient assessments

Patient-reported QoL was determined using the Functional Assessment of Cancer Therapy for Patients with Breast Cancer (FACT-B) version 4 in either English or Spanish.[1113] The FACT-B was administered prior to initiation of radiation and six months after completing radiation. The developer’s guidelines were used for scoring the FACT-B, including handling of missing data.[14]

Physician assessments

The treating physician assessed toxicities using the National Cancer Institute Common Toxicity Criteria v4.0 (NCICTCv4.0). All patients underwent weekly toxicity assessments during radiation and were scheduled for assessment six months after completing radiation. Additional toxicity evaluations were at the discretion of the treating physician and/or prompted by patient need. Acute toxicities were defined as toxicities occurring during radiation or within 42 days of completion of radiation; the maximal grade of each acute toxicity is reported herein. Six-month toxicities were defined as toxicities documented at the six-month follow up visit. All toxicities were recorded by the treating physician using templates specifying common radiation-related toxicities and their definitions according to NCICTCv4.0.

Statistical methods

The primary outcome of this study is the proportion of patients with an adverse patient-reported cosmetic outcome, determined using the validated Breast Cancer Treatment Outcomes Scale (BCTOS), three years after completion of treatment. This outcome will be reported when all patients have completed a minimum of three years follow up. The trial was designed to enroll 288 evaluable patients, which yields 90% power with a 1-sided significance level of 0.10 to test the hypothesis that the probability of an adverse cosmetic outcome with HF-WBI is no more than 10% worse than the probability of an adverse cosmetic outcome with CF-WBI, assuming a prevalence of adverse cosmetic outcome of 35% with HF-WBI and 40% with CF-WBI and a drop-out rate of 5%. Prespecified secondary outcomes, which are reported herein, include differences by randomization arm in physician-reported acute and six-month toxicities and patient-reported QoL. These secondary outcomes were considered hypothesis-generating and were thus not adjusted for multiplicity.

Differences in baseline patient, tumor, and treatment characteristics by randomization arm were assessed using the chi-square test or the exact calculation of the Fisher exact test as appropriate. Race/ethnicity was determined via patient report and categorized by applying standard definitions in use by the U.S. Census Bureau. Differences by randomization arm in physician-reported acute and six month toxicities were assessed using the Cochran-Armitage test for trend or chi-square test as appropriate. Exploratory, post hoc subset analyses explored whether these toxicities differed for patients in the highest quartile of body mass index or central axis separation. Differences by randomization arm in FACT-B total score and component scores were assessed using the t-test at baseline and at the six month assessment. Difference by randomization arm between FACT-B total and component scores at six months relative to baseline was also assessed via the t-test. Given a borderline association between physical well-being and randomization arm, differences in outcome by randomization arm for each of the seven items contributing to physical well-being were assessed using the Cochran-Armitage test for trend. As statistically significant associations with randomization arm were noted for Question 1 (Q1) (“I have a lack of energy”) and Question 3 (Q3) (“Because of my physical condition, I have trouble meeting the needs of my family”), ordinal logistic regression models for Q1 and Q3 were created using proc genmod in SAS, using a multinomial distribution and cumlogit link function. We selected the following candidate variables a priori for potential inclusion in these models based on their clinical relevance: randomization arm, age, race, body mass index, estrogen receptor status (negative, positive, not tested), tumor behavior (invasive vs. in situ), chemotherapy receipt (none, neoadjuvant, or adjuvant), central axis separation, volume of breast tissue receiving 90% of prescription dose (V90), volume of breast tissue receiving 105% of prescription dose (V105), maximum point dose (Dmax), tumor bed volume, and percent of dose delivered with 18 MV photons. Continuous variables were divided into quartiles as we did not have any a priori hypotheses regarding specific thresholds or cutpoints for these variables. Candidate variables were included in the final models if associated with the outcome at p<0.20 in bivariate analysis. Patients with missing outcome data were excluded from the relevant model. There were no missing covariable values. Sensitivity analyses tested whether type of FACT-B administration (electronic vs. paper) was predictive of outcome for each model.

This study was approved by the University of Texas MD Anderson Cancer Center Institutional Review Board and was independently monitored by the Institution’s Data Safety and Monitoring Board. Written informed consent was obtained from each subject. All analyses were intention-to-treat with two-sided α=0.05 and were performed using SAS v9.2 (Cary, NC).

RESULTS

Patients

A total of 432 patients were assessed for eligibility for enrollment, of whom 300 patients were registered for protocol treatment and 287 were randomized and evaluable (Figure 1). Of 149 patients randomized to CF-WBI, all (100%) received the allocated WBI and boost doses. Of 138 patients randomized to HF-WBI, 137 (99%) received a hypofractionated schedule of WBI (n=134, 42.56 Gy/16 fractions; n=2, 42.4 Gy/16 fractions; n=1, 42.52 Gy/16 fractions) and 136 (99%) received the allocated boost dose. One (1%) patient randomized to HF-WBI received conventional fractionation (46 Gy in 23 fractions followed by a 14 Gy in 7 fraction boost). Median number of elapsed days over which radiation was delivered was 36 days for CF-WBI (interquartile range [IQR] 35–36) and 22 days for HF-WBI (IQR 22–23). Half of the treatment plans (143) involved a Dmax of 107% of prescription dose or higher.

Figure 1. Consort diagram.

Figure 1

Abbreviations: CF (conventional fractionation), HF (hypofractionation), WBI (whole breast irradiation)

In total, 25% (n=72) of patients were not non-Hispanic white, 28% (n=80) were overweight, and 48% (n=137) were obese, as defined by body mass index.[15] Median age was 60 years (IQR 54–66). Baseline patient, tumor and treatment characteristics were well matched (Table 1 and see eTable 1 in the supplement). Of those patients who received systemic therapy, type of therapy was similar between treatment arms.

Table 1.

Baseline patient, tumor, and treatment characteristics

CF-WBI (n=149) HF-WBI (n=138) P*
N % N %
Patient characteristics
Age at diagnosis (years) 0.55
  40–49 13 9 19 14
  50–59 55 37 46 33
  60–69 59 40 51 37
  70 and older 22 15 22 16
Race 0.68
  White Non-Hispanic 116 78 99 72
  Hispanic 16 11 20 15
  Black Non-Hispanic 15 10 17 12
  Asian Non-Hispanic 2 1 2 1
Menopausal Status 0.23
  Premenopausal 9 6 13 9
  Perimenopausal 8 5 3 2
  Postmenopausal 132 89 122 88
Bra Cup Size 0.53
  A 13 9 7 5
  B 31 21 34 25
  C 50 34 46 33
  D 40 27 35 25
  DD 12 8 16 12
  DDD 2 1 0 0
  EE 1 1 0 0
BMI Quartile (kg/cm2) 0.08
  <24.48 35 24 37 27
  24.48 – <29.18 38 26 35 25
  29.18 – <33.64 30 20 40 29
  >33.64 46 31 26 19
Physician-Assessed Cosmesis 0.16
  Excellent-Good 135 91 131 95
  Fair-Poor 14 10 7 5

Tumor characteristics
Tumor Behavior 0.07
  Invasive 110 74 114 83
  DCIS 39 26 24 17
Tumor Grade 0.46
  1 40 27 34 25
  2 70 47 73 53
  3 39 26 30 22
  Unclassified 0 0 1 1
Margin Status 0.67
  negative, ≥ 2 mm 133 89 121 88
  negative, < 2 mm 16 11 17 12
Quadrant 0.28
  Central 16 11 27 20
  Lower Inner 9 6 7 5
  Lower Outer 22 15 17 12
  Upper Inner 22 15 15 11
  Upper Outer 80 54 72 52
Estrogen Receptor Status 0.39
  Positive 130 87 118 86
  Negative 18 12 16 12
  Not tested 1 1 4 3
Progesterone Receptor Status 0.42
  Positive 112 75 102 74
  Negative 36 24 32 23
  Not tested 1 1 4 3
Her2-neu Status 0.43
  Positive 12 8 11 8
  Negative 102 69 103 75
  Not tested 35 24 24 17
Pathologic Stage among patients with invasive cancer without neoadjuvant therapy (n=196)
  pT1mic-pT1a 16 17 12 12 0.44
  pT1b 24 26 23 23
  pT1c 43 46 48 47
  pT2 11 12 19 19
  pN0 79 84 89 87 0.02
  pN1mic 14 15 6 6
  pN1a 1 1 7 7
Clinical and Pathologic Stage among patients with invasive cancer with neoadjuvant therapy (n=28)
  cT1c 2 12 2 17 0.76
  cT2 14 88 10 84
  cN0 13 81 11 92 0.44
  cN1a 3 19 1 8
  pT0 7 44 5 42 0.68
  pTis 1 6 2 17
  pT1a 2 13 0 0
  pT1b 0 0 0 0
  pT1c 4 25 3 25
  pT2 2 13 2 17
  pN0 16 100 12 100 .

Treatment characteristics
Chemotherapy 0.67
  None 106 71 96 70
  Neoadjuvant 16 11 12 9
  Adjuvant 27 18 30 22
Treatment Location 0.16
  Houston-area 141 95 132 96
  Banner MD Anderson 4 3 0 0
  Orlando Health 4 3 6 4

Abbreviations: CF (conventionally fractionated), DCIS (ductal carcinoma in situ), HF (hypofractionated), WBI (whole breast irradiation)

*

Fisher’s exact test used for race, estrogen receptor status, progesterone receptor status, and bra cup size. Chi-square test used for all other comparisons.

This patient’s cancer was diagnosed on core biopsy but grade could not be assigned. There was no residual disease in the lumpectomy specimen.

Staging information is only presented for patients with invasive breast cancer. A total of 63 patients had DCIS. Because DCIS typically does not undergo pathologic staging of the axillary nodes, patients with DCIS are not included in the comparison of stage by randomization arm. Additionally, staging is different for patients treated with upfront surgery compared to those treated with neoadjuvant chemotherapy, which is the reason that these two groups of patients are separated in the table.

ER positive: ≥ 1% of cells stained for estrogen receptor; PR positive: ≥ 1% of cells stained for progesterone receptor; Her2-neuNeu positive: 3+ by immunohistochemistry or gene amplification by fluorescence in situ hybridization

Acute toxicity

Overall rates of any physician-assessed grade ≥ 2 and any grade ≥ 3 acute toxicity were lower with HF-WBI compared to CF-WBI (47% vs. 78%, P<.001 and 0% vs. 5%, P=0.007, respectively) (Table 2). Examining specific acute toxicities, patients treated with HF-WBI vs. CF-WBI had lower rates of physician-assessed grade fatigue (Ptrend=0.02; grade≥2: 9% vs. 17%), pruritus (Ptrend<0.001; grade≥1: 54% vs. 81%), breast pain (Ptrend=0.001; grade≥1: 55% vs. 74%), dermatitis (Ptrend<0.001; grade≥2: 36% vs. 69%), and hyperpigmentation (Ptrend=0.002; grade≥2: 9% vs. 20%). In an exploratory subset analysis, there was no difference in acute grade ≥ 2 or grade ≥ 3 toxicity for patients in the highest quartile of body mass index (P=0.22 for grade ≥ 2 and P=0.55 for grade ≥ 3) or for patients in the highest quartile of central axis separation (P=0.17 for grade ≥ 2 and P=0.24 for grade ≥ 3).

Table 2.

Physician-Reported Maximal Acute Toxicities (NCI CTCAE v4.0)

CF-WBI (n=149) HF-WBI (n=138) P*
N % N %
Any Grade ≥ 2 Acute Toxicity <0.001
 None 33 22 73 53
 Any 116 78 65 47
Any Grade ≥ 3 Acute Toxicity 0.001
 None 141 95 138 100
 Any 8 5 0 0
Fatigue
 0 23 15 29 21 0.02
 1 101 68 97 70
 2 20 13 12 9
 3 5 3 0 0
Pruritus <0.001
 0 29 20 63 46
 1 110 74 69 50
 2 10 7 6 4
Breast Pain 0.001
 0 39 26 62 45
 1 97 65 69 50
 2 13 9 7 5
Shoulder Arthralgia 0.46
 0 124 83 120 87
 1 24 16 16 12
 2 0 0 2 1
 3 1 1 0 0
Dermatitis <0.001
 0 1 1 8 6
 1 45 30 80 58
 2 101 68 50 36
 3 2 1 0 0
Hyperpigmentation 0.002
 0 45 30 60 44
 1 74 50 66 48
 2 30 20 12 9
Breast Edema 0.10
 0 94 63 98 71
 1 51 34 39 28
 2 4 3 1 1
 3 0 0 0 0
Wound Complications, Non-Infectious 0.61
 0 147 99 137 99
 1 2 1 1 1
Skin Ulceration 0.19
 0 142 95 136 99
 1 5 3 1 1
 2 2 1 1 1
Seroma 0.19
 0 127 85 109 79
 1 21 14 28 20
 2 1 1 1 1
Breast Infection 0.46
 0 145 97 136 99
 2 4 3 2 1
Wound Infection 0.96
 0 148 99 137 99
 2 1 1 1 1
Soft Tissue Necrosis of the Chest Wall/Thorax .
 0 149 100 138 100
Upper Extremity Edema 0.51
 0 141 95 134 97
 1 8 5 3 2
 2 0 0 1 1
All others 0.20
 0 133 89 128 93
 1 12 8 9 7
 2 4 3 1 1

Abbreviations: CF (conventionally fractionated), HF (hypofractionated), NCI CTCAE (National Cancer Institute Common Toxicity Criteria Adverse Events), WBI (whole breast irradiation)

*

Cochran-Armitage test for trend used for all P-values except chi-square used for any grade ≥ 2 toxicity and Fisher’s exact test used for any grade ≥ 3 toxicity.

Acute toxicities were recorded on a weekly basis during radiation using a structured template which specified these toxicities and their definitions. Any subsequent toxicity occurring within 42 days of treatment completion was also included in this analysis of acute toxicity.

Six-month toxicity

A total of 271 of 287 patients (94%) were evaluated for physician-assessed six-month toxicity, 142 (95%) randomized to CF-WBI and 129 (94%) randomized to HF-WBI. Patients randomized to HF-WBI experienced less physician-rated grade ≥2 fatigue compared to CF-WBI (Ptrend=0.01; grade≥2: 0% vs. 6%). All other six-month toxicities were comparable between the two treatment arms (Table 3). In an exploratory subset analysis, there was no difference in six-month grade ≥ 2 or grade ≥ 3 toxicity for patients in the highest quartile of body mass index (P=0.86 for grade ≥ 2 and P=1.00 for grade ≥ 3) or for patients in the highest quartile of central axis separation (P=0.62 for grade ≥ 2 and P=1.00 for grade ≥ 3).

Table 3.

Physician-Assessed Maximal Toxicities at Six Months (NCI CTCAE v4.0)

CF-WBI (n=142) HF-WBI (n=129) P*
N % N %
Combined
 Any grade 2 or higher 0.81
  None 96 68 89 69
  Any 46 32 40 31
 Any grade 3 or higher 0.18
  None 140 99 129 100
  Any 2 1 0 0

Constitutional
 Fatigue 0.01
  0 89 63 94 73
  1 44 31 35 27
  2 9 6 0 0

Dermatology/Skin
 Hyperpigmentation 0.65
  0 49 35 54 42
  1 82 58 60 47
  2 11 8 15 12
 Skin Induration 0.43
  0 121 85 104 81
  1 19 13 24 19
  2 2 1 1 1
 Dermatitis 0.73
  0 121 85 111 86
  1 20 14 18 14
  2 1 1 0 0
 Telangiectasia 0.60
  0 138 97 126 98
  1 3 2 3 2
  2 1 1 0 0
 Skin Ulceration
  0 142 100 129 100 .
 Wound Complications, Non-Infectious
  0 142 100 129 100 .

Infection
 Breast Infection 0.83
  0 141 99 128 99
  2 0 0 1 1
  3 1 1 0 0
 Wound Infection
  0 142 100 129 100 .

Lymphatics
 Upper Extremity Edema 0.92
  0 140 99 127 98
  1 2 1 2 2
 Breast Edema 0.78
  0 114 80 97 75
  1 21 15 30 23
  2 7 5 2 2

Musculoskeletal/Soft Tissue
 Fibrosis - Superficial Soft Tissue 0.89
  0 111 78 100 78
  1 30 21 28 22
  2 1 1 1 1
 Fibrosis - Deep Connective Tissue 0.26
  0 121 85 104 81
  1 21 15 24 19
  2 0 0 1 1
 Seroma 0.80
  0 127 89 114 88
  1 14 10 13 10
  2 0 0 2 2
 Soft Tissue Necrosis of the Chest Wall/Thorax
  0 142 100 129 100

Pain
 Breast Pain 0.89
  0 99 70 92 71
  1 41 29 32 25
  2 2 1 5 34
 Other Pain 0.49
  0 132 93 123 95
  1 9 6 5 4
  2 1 1 1 1

Pulmonary
 Cough 0.14
  0 141 99 125 97
  1 1 1 4 3
 Dyspnea 0.14
  0 142 100 127 98
  1 0 0 2 2
 Pneumonitis
  0 142 100 129 100

Sexual/Reproductive Function
 Nipple/Areolar 0.93
  0 117 82 106 82
  1 21 15 19 15
  2 4 3 4 3
 Breast Atrophy 0.72
  0 93 66 82 64
  1 33 23 31 24
  2 16 11 16 12

Other
 All others combined 0.30
  0 136 96 126 98
  1 5 4 3 2
  2 1 1 0 0

Abbreviations: CF (conventionally fractionated), HF (hypofractionated), NCI CTCAE (National Cancer Institute Common Toxicity Criteria Adverse Events), WBI (whole breast irradiation)

*

P-value from Cochran-Armitage test for trend, with the exception of any grade 2 or higher and any grade 2 or higher, where P-value is from chi-square test.

These toxicities were recorded by the treating physician using a structured template which specified these toxicities and their definitions

Patient-reported quality of life

Prior to initiation of radiation, 286 of 287 patients (99.7%) completed the FACT-B, 148 (99%) randomized to CF-WBI and 138 (100%) randomized to HF-WBI. The randomization arms were well-matched for all components of the FACT-B, including total score (P=0.46), physical well-being (P=0.63), functional well-being (P=0.63), and breast cancer-specific concerns (P=0.86).

At the six-month follow up visit, 266 of 287 patients (93%) completed the FACT-B, 128 (93%) randomized to HF-WBI and 138 (93%) randomized to CF-WBI. At six months, there was no difference by randomization arm in FACT-B total score (P=0.20), functional well-being (P=0.10), or breast cancer-specific concerns (P=0.82). There was a trend toward improved physical well-being in patients randomized to HF-WBI vs. CF-WBI at the six month follow up visit (mean score 25.5 vs. 24.7, P=0.06), although this trend was not significant when comparing the difference at six months relative to baseline (P=0.46) (Table 4).

Table 4.

Mean Baseline and 6 Month FACT-B Scores by Randomization Arm

CF-WBI HF-WBI P*
N Mean (95% CI) N Mean (95% CI)
Baseline
Physical Well-Being 149 24.5 (23.9–25.1) 138 24.7 (24.1–25.4) 0.63
Functional Well-Being 148 22.2 (21.4–23.0) 138 22.5 (21.6–23.4) 0.63
Emotional Well-Being 148 20.4 (20.0–20.9) 138 20.5 (19.9–21.0) 0.92
Social Well-Being 149 24.4 (23.6–25.1) 138 25.1 (24.3–25.9) 0.16
FACT-G Total Score 148 91.6 (89.7–93.4) 138 92.8 (90.9–94.8) 0.35
Breast Cancer Concerns 149 27.2 (26.4–27.9) 138 27.3 (26.4–28.2) 0.86
FACT-B Total Score 148 118.8 (116.4–121.1) 138 120.1 (117.5–122.6) 0.46
Six months
Physical Well-Being 140 24.7 (24.1–25.3) 128 25.5 (24.9–26.1) 0.06
Functional Well-Being 140 23.2 (22.5–24.0) 128 24.1 (23.4–24.9) 0.10
Emotional Well-Being 140 21.1 (20.6–21.6) 128 21.3 (20.8–21.8) 0.60
Social Well-Being 140 24.6 (23.9–25.4) 128 24.8 (24.0–25.6) 0.74
FACT-G Total Score 138 93.6 (91.8–95.5) 128 95.7 (93.9–97.6) 0.12
Breast Cancer Concerns 141 28.6 (27.8–29.4) 128 28.7 (27.9–29.5) 0.82
FACT-B Total Score 138 122.3 (119.9–124.7) 128 124.5 (122.1–126.9) 0.20
Difference between 6 month and baseline outcomes
Physical well-being 140 0.28 (−0.40–0.95) 128 0.62 (0.04–1.19) 0.46
Functional Well-Being 139 1.01 (0.26–1.76) 128 1.5 (0.69–2.32) 0.38
Emotional Well-Being 139 0.67 (0.06–1.29) 128 0.93 (0.23–1.63) 0.58
Social Well-Being 140 0.23 (−0.35–0.81) 128 −0.31 (−1.24–0.61) 0.32
FACT-G Total Score 137 2.29 (0.58–4.00) 128 2.74 (0.91–4.56) 0.73
Breast Cancer Concerns 141 1.50 (0.71–2.28) 128 1.54 (0.62–2.46) 0.94
FACT-B Total Score 137 3.85 (1.74–5.96) 128 4.27 (2.01–6.53) 0.79

Abbreviations: CF (conventionally fractionated), HF (hypofractionated), WBI (whole breast irradiation)

*

P-value from t-test.

In analyzing responses to the seven items contributing to physical well-being, there was no difference in any item prior to radiation (P≥0.22; see eTable 2 in the supplement). At the six month follow up, outcomes for Q1 (lack of energy) and Q3 (trouble meeting family needs) favored patients randomized to HF-WBI (P<0.001 and P=0.01, respectively). There was no difference by randomization arm at six months for the other items contributing to physical well-being. Ordinal logistic regression models confirmed the superiority of HF-WBI compared to CF-WBI on Q1 (lack of energy) (OR 0.39, 95% CI 0.24–0.63; P<0.001) and Q3 (trouble meeting family needs) (OR 0.34, 95% CI 0.16–0.75; P=0.007) (see eTable 3 in the supplement).

DISCUSSION

These randomized trial data demonstrate that HF-WBI followed by a tumor bed boost, in comparison to CF-WBI followed by a tumor bed boost, resulted in lower rates of physician-assessed acute toxicities during radiation and less physician-reported fatigue six months after radiation. Patient-reported outcomes reinforced this finding, with patients randomized to HF-WBI noting less lack of energy and less trouble meeting family needs six months after radiation. No measured side effects or QoL parameters were worse with HF-WBI compared to CF-WBI.

Defining the standard of care for WBI

Our study findings speak directly to the ongoing discussion seeking to define the most appropriate standard of care for dose-fractionation in WBI. In 2011, ASTRO published an evidence-based guideline on fractionation for WBI. The guideline concluded that the evidence suggests the equivalence of HF-WBI to CF-WBI for certain patient groups, notably those with pT1-2 N0 disease, age 50 years and older, not treated with chemotherapy, and where the radiation dose inhomogeneity could be limited to within ± 7% in the central axis.[16] Notably, however, the ASTRO guideline stopped short of endorsing HF-WBI as a preferred treatment strategy for such patients. Subsequently, in 2013, the ASTRO Choosing Wisely Campaign issued a stronger statement, noting “Don’t initiate whole breast radiotherapy as a part of breast conservation therapy in women age ≥50 with early stage invasive breast cancer without considering shorter treatment schedules”.

Nevertheless, evidence suggests that there has been limited adoption of HF-WBI in the United States, in contrast to other healthcare systems. A recent observational cohort study from 14 commercial health care plans in the United States reported that only 34.5% of appropriate candidates for HF-WBI received this treatment in 2013, similar to the rate seen in a study examining practice patterns in Michigan between 2011 and 2013.[4, 6] In contrast, practice patterns in the United Kingdom and Canada have demonstrated much broader uptake of HF-WBI.[1719] Limited adoption of HF-WBI in the United States has been attributed in part to concerns regarding the applicability of the available evidence to practice patterns in the United States, where use of a tumor bed boost is much more common and where higher prevalence of obesity may result in fewer patients meeting the dose homogeneity or central axis separation criteria applied in the randomized literature.[8, 9] Within this context, results from our trial provide strong reassurance that HF-WBI with a sequential tumor bed can be safely administered with regard to acute and short-term toxicity in a patient population where three-quarters of patients were overweight or obese and half had a D-max of 107% or higher.

Radiotherapy and fatigue

Our study findings also improve the understanding of the relevance of fatigue during and after breast radiation. Previously reported data indicate that the severity and frequency of patient-reported fatigue increase during the course of radiotherapy, peaking during the last week of treatment and impacting over three-quarters of patients.[20, 21] A recent study of 250 breast cancer patients treated with standard fractionation breast radiotherapy in Norway found that the volume of the breast receiving 40 Gy or more was a significant predictor of increased fatigue during radiotherapy, whereas the volume of the breast receiving 5 Gy was not.[22] Finally, a chart review of 161 breast cancer patients treated with CF-WBI, HF-WBI, and accelerated partial breast radiation from the Cancer Institute of New Jersey found mean fatigue was less with HF-WBI compared to CF-WBI at the first week, midway, and 4 weeks after completion of radiation therapy.[23]

Notably, this study is the first to prospectively measure and report lack of energy before initiation of radiation and six months after radiation within the context of a randomized trial. Our novel finding of a differential effect between the treatment arms on lack of energy supports that hypothesis that HF-WBI confers a substantive benefit to patients, beyond the abbreviated time to complete therapy. We hypothesize that less fatigue in the HF-WBI arm translated into less trouble meeting family needs. Strikingly, in a multivariable analysis, the negative impact of CF-WBI on both energy and ability to meet family needs was comparable or greater in magnitude to the effect of adjuvant chemotherapy on these endpoints. Further, we found that dosimetric parameters were not predictive of these patient-reported outcomes, suggesting these complications are truly driven by the selected dose-fractionation scheme and not the volume of tissue treated or relative hotspots.

The biologic mechanism underlying radiation-related fatigue is unclear. Fatigue during and acutely following CF-WBI has previously been found to be linked to higher levels of neutrophils, red blood cells, hemoglobin and D-dimer, as well as to depression and mood disturbance prior to initiation of radiation.[24][2528] During radiation, a greater decrease in platelets, albumin, and red blood cells has been seen in those patients who develop fatigue. Receipt of WBI has also been associated with alterations in amino acid homeostasis among patients experiencing fatigue, with increased urinary excretion. [27]

Limitations

This study had limitations. First, patients were not routinely assessed within one to three weeks of concluding radiation, and thus acute toxicities may have been underascertained if they did not manifest until after completion of radiation. Second, all of the analyses reported herein were secondary and were considered hypothesis-generating. Third, it was not practical to blind patients and physicians to treatment arm within the context of this trial. Fourth, long-term toxicity data from the trial are still pending. Fifth, the dose-fractionation schema used for the standard fractionation arm of the study was 50Gy in 25 fractions; 45–50 Gy in 1.8 Gy per fraction is also a commonly used method to deliver CF-WBI, and any differences in associated acute and short-term outcome remain uncertain in their comparison with HF-WBI.

Conclusion

In this randomized trial, HF-WBI resulted in substantially less acute and short-term toxicity compared to CF-WBI. These findings should be communicated to patients as part of shared decision-making regarding election of radiotherapy regimen and are relevant to the ongoing discussion regarding the most appropriate standard of care for WBI dose-fractionation.

Supplementary Material

Suppl 1
Suppl 2

Acknowledgments

Funding: This work was supported by a Career Development Award from the Conquer Cancer Foundation of the American Society of Clinical Oncology (BDS), the Breast Cancer Research Foundation, the Cancer Prevention and Research Institute of Texas (RP140020), The Center for Radiation Oncology Research at The University of Texas MD Anderson, a philanthropic gift from Ann and Clarence Cazalot, and the National Cancer Institute at the National Institutes of Health funding of the Biostatistics Resource Group (P30CA016672).

Footnotes

Author Contributions: Dr. Smith had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Dr. Smith and Dr. Ensor conducted the data analysis.

Presentation of Findings: The findings of this study, in part, were presented at the ASTRO 56th Annual Meeting, San Francisco, CA, September 2014.

No individuals listed received compensation. Written permission was granted from all individuals listed in the acknowledgements section.

All information included in this manuscript is original and has not been previously published.

Conflict of Interest Disclosures: SFS: Grant from Elekta; Consultation for MD Anderson Physicians’ Network; BDS: Grant from Varian Medical Systems. MCS: Consultation for MD Anderson Physicians’ Network; None of this funding was used to support the research contained herein. DB: Honorarium from Genomic Health Advisory Panel. GNH: served as a Scientific/Advisory Committee member for Antigen Express, Bayer Healthcare Pharmaceuticals, Galena Biopharma, Metastat, Novartis Pharmaceuticals Corp., Oncimmune, Pfizer, Inc., and Rockpointe and served as consultant to AstraZeneca Pharmaceuticals, Celgene, Genentech Inc., Peregrine Pharmaceuticals, Inc (none of the disclosure from GNH are relevant to the current manuscript).

Role of the Funder/Sponsor: None of the funding organizations had a role in the design or conduct of the study; collection, management, analysis, and interpretation of the data; or preparation, review, or approval of the manuscript, or decision to submit for publication.

Additional Contributions: Protocol Development: The authors would like to thank the Patient-Reported Outcomes, Survey & Population Research Shared Resource of The University of Texas MD Anderson Cancer Center for assistance in developing this protocol.

Editorial Assistance: Stephanie Deming, BA, Department of Scientific Publications, The University of Texas MD Anderson Cancer Center, for assistance in editing this manuscript.

Data Collection: The MD Anderson Cancer Research Support Center led by Susie Bullock, RN.

Contributor Information

Simona F. Shaitelman, Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center

Pamela J. Schlembach, Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center

Isidora Arzu, Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center

Matthew Ballo, Department of Radiation Oncology, The University of Tennessee Health Science Center

Elizabeth S. Bloom, Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center

Daniel Buchholz, Department of Radiation Oncology, UF Health Cancer Center, Orlando Health

Gregory M. Chronowski, Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center

Tomas Dvorak, Department of Radiation Oncology, UF Health Cancer Center, Orlando Health

Emily Grade, Department of Radiation Oncology, Banner MD Anderson Cancer Center

Karen E. Hoffman, Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center

Patrick Kelly, Department of Radiation Oncology, UF Health Cancer Center, Orlando Health

Michelle Ludwig, Department of Radiation Oncology, Baylor College of Medicine

George H. Perkins, Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center.

Valerie Reed, Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center

Shalin Shah, Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center

Michael C. Stauder, Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center

Eric A. Strom, Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center

Welela Tereffe, Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center

Wendy A. Woodward, Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center

Joe Ensor, Houston Methodist Research Institute, The Methodist Hospital

Donald Baumann, Department of Plastic Surgery, The University of Texas MD Anderson Cancer Center

Alastair M. Thompson, Department of Surgical Oncology, The University of Texas MD Anderson Cancer Center

Diana Amaya, Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center

Tanisha Davis, Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center

William Guerra, Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center

Lois Hamblin, Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center

Gabriel Hortobagyi, Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center

Kelly K. Hunt, Department of Surgical Oncology, The University of Texas MD Anderson Cancer Center

Thomas A. Buchholz, Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center

Benjamin D. Smith, Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center

References

  • 1.Haviland JS, Owen JR, Dewar JA, et al. The UK Standardisation of Breast Radiotherapy (START) trials of radiotherapy hypofractionation for treatment of early breast cancer: 10-year follow-up results of two randomised controlled trials. Lancet Oncol. 2013;14(11):1086–94. doi: 10.1016/S1470-2045(13)70386-3. [DOI] [PubMed] [Google Scholar]
  • 2.Whelan TJ, Pignol JP, Levine MN, et al. Long-term results of hypofractionated radiation therapy for breast cancer. N Engl J Med. 362(6):513–20. doi: 10.1056/NEJMoa0906260. [DOI] [PubMed] [Google Scholar]
  • 3.Owen JR, Ashton A, Bliss JM, et al. Effect of radiotherapy fraction size on tumour control in patients with early-stage breast cancer after local tumour excision: long-term results of a randomised trial. Lancet Oncol. 2006;7(6):467–71. doi: 10.1016/S1470-2045(06)70699-4. [DOI] [PubMed] [Google Scholar]
  • 4.Bekelman JE, Sylwestrzak G, Barron J, et al. Uptake and Costs of Hypofractionated vs Conventional Whole Breast Irradiation After Breast Conserving Surgery in the United States, 2008–2013. JAMA. 2014 doi: 10.1001/jama.2014.16616. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Jagsi R, Falchook AD, Hendrix LH, et al. Adoption of hypofractionated radiation therapy for breast cancer after publication of randomized trials. Int J Radiat Oncol Biol Phys. 2014;90(5):1001–9. doi: 10.1016/j.ijrobp.2014.09.032. [DOI] [PubMed] [Google Scholar]
  • 6.Jagsi R, Griffith KA, Heimburger D, et al. Choosing wisely? Patterns and correlates of the use of hypofractionated whole-breast radiation therapy in the state of michigan. Int J Radiat Oncol Biol Phys. 2014;90(5):1010–6. doi: 10.1016/j.ijrobp.2014.09.027. [DOI] [PubMed] [Google Scholar]
  • 7.Wang EH, Mougalian SS, Soulos PR, et al. Adoption of Hypofractionated Whole-Breast Irradiation for Early-Stage Breast Cancer: A National Cancer Data Base Analysis. Int J Radiat Oncol Biol Phys. 2014 doi: 10.1016/j.ijrobp.2014.06.038. [DOI] [PubMed] [Google Scholar]
  • 8.Mowery YM, Blitzblau RC. Whole-breast radiation therapy: the long and short of it. Int J Radiat Oncol Biol Phys. 2014;90(5):990–2. doi: 10.1016/j.ijrobp.2014.10.028. [DOI] [PubMed] [Google Scholar]
  • 9.Goffman TE, Glatstein E. Hypofractionation redux? J Clin Oncol. 2004;22(4):589–91. doi: 10.1200/JCO.2004.07.174. [DOI] [PubMed] [Google Scholar]
  • 10.Pocock SJ, Simon R. Sequential treatment assignment with balancing for prognostic factors in the controlled clinical trial. Biometrics. 1975;31:103–115. [PubMed] [Google Scholar]
  • 11.Webster K, Cella D, Yost K. The Functional Assessment of Chronic Illness Therapy (FACIT) Measurement System: properties, applications, and interpretation. Health Qual Life Outcomes. 2003;1:79. doi: 10.1186/1477-7525-1-79. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Fallowfield LJ, Leaity SK, Howell A, et al. Assessment of quality of life in women undergoing hormonal therapy for breast cancer: validation of an endocrine symptom subscale for the FACT-B. Breast Cancer Res Treat. 1999;55(2):189–99. doi: 10.1023/a:1006263818115. [DOI] [PubMed] [Google Scholar]
  • 13.Brady MJ, Cella DF, Mo F, et al. Reliability and validity of the Functional Assessment of Cancer Therapy-Breast quality-of-life instrument. J Clin Oncol. 1997;15(3):974–86. doi: 10.1200/JCO.1997.15.3.974. [DOI] [PubMed] [Google Scholar]
  • 14.Fairclough DL, Cella DF. Functional Assessment of Cancer Therapy (FACT-G): non-response to individual questions. Qual Life Res. 1996;5(3):321–9. doi: 10.1007/BF00433916. [DOI] [PubMed] [Google Scholar]
  • 15.Clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults: executive summary. Expert Panel on the Identification, Evaluation, and Treatment of Overweight in Adults. Am J Clin Nutr. 1998;68(4):899–917. doi: 10.1093/ajcn/68.4.899. [DOI] [PubMed] [Google Scholar]
  • 16.Smith BD, Bentzen SM, Correa CR, et al. Fractionation for whole breast irradiation: an American Society for Radiation Oncology (ASTRO) evidence-based guideline. Int J Radiat Oncol Biol Phys. 2011;81(1):59–68. doi: 10.1016/j.ijrobp.2010.04.042. [DOI] [PubMed] [Google Scholar]
  • 17.National Collaborating Centre for Cancer. Early and Locally Advanced Breast Cancer: Diagnosis and Treatment. Cardiff (UK): 2009. [PubMed] [Google Scholar]
  • 18.Ashworth A, Kong W, Whelan T, et al. A population-based study of the fractionation of postlumpectomy breast radiation therapy. Int J Radiat Oncol Biol Phys. 2013;86(1):51–7. doi: 10.1016/j.ijrobp.2012.12.015. [DOI] [PubMed] [Google Scholar]
  • 19.Berrang TS, Truong PT, Tyldesley S, et al. A population-based study of the fractionation of postlumpectomy breast radiation therapy. In regard to Ashworth et al. Int J Radiat Oncol Biol Phys. 2013;87(4):632–3. doi: 10.1016/j.ijrobp.2013.07.013. [DOI] [PubMed] [Google Scholar]
  • 20.Hickok JT, Roscoe JA, Morrow GR, et al. Frequency, severity, clinical course, and correlates of fatigue in 372 patients during 5 weeks of radiotherapy for cancer. Cancer. 2005;104(8):1772–8. doi: 10.1002/cncr.21364. [DOI] [PubMed] [Google Scholar]
  • 21.Reidunsdatter RJ, Albrektsen G, Hjermstad MJ, et al. One-year course of fatigue after post-operative radiotherapy in Norwegian breast cancer patients--comparison to general population. Acta Oncol. 2013;52(2):239–48. doi: 10.3109/0284186X.2012.742563. [DOI] [PubMed] [Google Scholar]
  • 22.Reidunsdatter RJ, Rannestad T, Frengen J, et al. Early effects of contemporary breast radiation on health-related quality of life - predictors of radiotherapy-related fatigue. Acta Oncol. 2011;50(8):1175–82. doi: 10.3109/0284186X.2011.604345. [DOI] [PubMed] [Google Scholar]
  • 23.Taunk NK, Haffty BG, Chen S, et al. Comparison of radiation-induced fatigue across 3 different radiotherapeutic methods for early stage breast cancer. Cancer. 2011;117(18):4116–24. doi: 10.1002/cncr.26013. [DOI] [PubMed] [Google Scholar]
  • 24.Wratten C, Kilmurray J, Nash S, et al. Fatigue during breast radiotherapy and its relationship to biological factors. Int J Radiat Oncol Biol Phys. 2004;59(1):160–7. doi: 10.1016/j.ijrobp.2003.10.008. [DOI] [PubMed] [Google Scholar]
  • 25.Noal S, Levy C, Hardouin A, et al. One-year longitudinal study of fatigue, cognitive functions, and quality of life after adjuvant radiotherapy for breast cancer. Int J Radiat Oncol Biol Phys. 2011;81(3):795–803. doi: 10.1016/j.ijrobp.2010.06.037. [DOI] [PubMed] [Google Scholar]
  • 26.Magnan MA, Mood DW. The effects of health state, hemoglobin, global symptom distress, mood disturbance, and treatment site on fatigue onset, duration, and distress in patients receiving radiation therapy. Oncol Nurs Forum. 2003;30(2):E33–9. doi: 10.1188/03.ONF.E33-E39. [DOI] [PubMed] [Google Scholar]
  • 27.Hugh Dunstan R, Sparkes DL, Macdonald MM, et al. Altered amino acid homeostasis and the development of fatigue by breast cancer radiotherapy patients: A pilot study. Clin Biochem. 2011;44(2–3):208–15. doi: 10.1016/j.clinbiochem.2010.10.002. [DOI] [PubMed] [Google Scholar]
  • 28.Geinitz H, Zimmermann FB, Thamm R, et al. Fatigue in patients with adjuvant radiation therapy for breast cancer: long-term follow-up. J Cancer Res Clin Oncol. 2004;130(6):327–33. doi: 10.1007/s00432-003-0540-9. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Suppl 1
Suppl 2

RESOURCES