Over 100,000 women undergo reduction mammaplasty each year.1 Symptomatic relief is the primary motivating factor for many of these women.2,3 It is these subjective factors, such as symptoms of back and neck pain, headaches, shoulder grooving, and upper extremity numbness, that drive the health burden of macromastia and motivate women to seek reduction mammaplasty,4–6 as opposed to quantitative factors, such as body mass index or breast cup size. These same symptoms have also been shown to improve after reduction mammaplasty,7–9 highlighting their importance as outcome metrics. Thus, it is necessary to use research tools that are capable of appropriately capturing these constructs from the patient perspective when evaluating the outcomes of patients presenting for surgical relief of macromastia and the impact of intervention on their symptoms.
Breast surgery–specific patient-reported outcome instruments do just this and are frequently used in patients seeking reduction mammaplasty. The BREAST-Q Reduction module, one of the most widely used patient-reported outcome instruments specific to reduction mammaplasty, allows researchers and clinicians to capture reproducible data regarding the impact of macromastia on symptoms and quality of life, and to track change over time.10,11 However, unlike objective outcomes in surgical research, the interpretation of patient-reported outcome results presents a unique challenge.
Patient-reported outcome instruments, including the BREAST-Q, generate a numeric score. This score is given meaning when compared over time or between intervention groups. However, the clinical relevance of these findings without such comparisons is not always readily apparent. Thus, a current limitation to the BREAST-Q Reduction module is a lack of normative scores for breast-related satisfaction and well-being of women in the general population; such normative scores could be used to provide clinical context for both preoperative and postoperative data points.
The primary aim of this study was to generate and describe population norms for the BREAST-Q Reduction module. The secondary aim was to compare Army of Women population norms to previously published BREAST-Q Reduction scores, to bring greater clinical context and understanding to previously determined findings describing women presenting for and undergoing reduction mammaplasty.
PATIENTS AND METHODS
Participants were recruited through the Army of Women, an online community started in 2008 by the Dr. Susan Love Research Foundation, with the goal of connecting breast cancer researchers to women with and without breast cancer. To recruit patients using the Army of Women, researchers must have funding, institutional review board approval from the home institution, and be accepted by the Army of Women Scientific Advisory Committee. After institutional review board exemption was granted from Dartmouth College, and after acceptance by the Army of Women, an electronic recruitment e-mail (e-blast) was circulated to Army of Women members. Interested women self-selected to participate if they met the following inclusion criteria: age 18 years or older, no personal history of breast cancer or breast surgery, and the ability to complete a questionnaire online in English.
The e-blast was sent to 121,688 Army of Women members. Those participants who were interested and self-screened themselves as eligible followed a link to electronically complete the BREAST-Q, which was administered using Qualtrics (Provo, Utah), an online, Web-based software for questionnaire administration. Participant recruitment was part of a larger study generating normative values for the three BREAST-Q modules (i.e., Reduction, Augmentation, and Reconstruction). Participants did not know which BREAST-Q module was being completed. In addition to completing a preoperative BREAST-Q module, data collection included demographic questions as well as bra cup size, height, and weight. A recruitment algorithm was written into Qualtrics that automatically rerouted participants to the next BREAST-Q module after 1200 participants had completed one of the modules, starting with Reduction, followed by Reconstruction and then Augmentation. Normative data for the latter two will be reported in other articles.
The BREAST-Q is a rigorously developed, well-validated, patient-reported outcome instrument designed for all types of breast surgery.11,12 Used in research with over 22,000 women having different types of breast surgery, the BREAST-Q is one of the most widely used breast surgery–specific patient-reported outcome instruments.11–17 The BREAST-Q, first published in 2009, was developed following internationally accepted guidelines for patient-reported outcome development.4,18 Development of the conceptual framework and set of scales included a literature review, 48 primary patient interviews, 46 cognitive debriefing interviews, and expert opinion from a panel of plastic surgeons and other health care professionals. The BREAST-Q was then tested in a sample of 2715 patients, 908 presurgery patients, and 1807 postsurgery patients, with a response rate of 72 percent.
There are four preoperative BREAST-Q Reduction scales: Satisfaction with Breasts (n = 11 items), Psychosocial Well-being (n = 9 items), Sexual Well-being (n = 5 items), and Physical Well-being (n = 14 items). Questions assess breast satisfaction, including satisfaction with macromastia symptoms, and quality of life and well-being as related to macromastia and reduction mammaplasty. For all BREAST-Q scales, items are summed and transformed on a scale from 0 (worst) to 100 (best) using the Q-Score program (New York, N.Y.). In the BREAST-Q development sample (n = 1950), Reduction scales had Cronbach alpha scores between 0.83 and 0.95, mean item total correlations from 0.46 to 0.83, and test-retest reliability with intraclass correlation coefficients between 0.73 and 0.94. In addition, the BREAST-Q has demonstrated validity and the ability to detect clinically meaningful change.14
Descriptive statistics were computed, including the mean, standard deviation, and 95 percent confidence interval for continuous variables, and percentages were listed for categorical variables. Backward-selection linear multivariate regression was used to determine variables associated with BREAST-Q scores. Variables were categorized to form dichotomous variables as follows: body mass index greater than or equal to 30 kg/m2 versus body mass index less than 30 kg/m2, age 40 years or older versus age younger than 40 years, bra size greater than or equal to D versus less than D, white non-Hispanic versus other ethnicity, college degree or higher versus less than college degree education, full-time versus other than full-time employment, income greater than or equal to $40,000 versus less than $40,000 per year, and married versus other marital status. Binomial variables with a probability of less than 0.2 were rejected and removed from the model, and the model was rerun with only the significant variables (p < 0.05). Statistically significant difference was determined by use of 95 percent confidence intervals in which there was a difference in the results if the confidence intervals of the measures did not cross. Data analysis was performed using Stata/SE 11.0 (StataCorp., College Station, Texas).
A separate analysis compared the normative scores to published and unpublished BREAST-Q Reduction scores using 95 percent confidence intervals. To identify published scores, we searched PubMed in January of 2016 with “BREAST-Q” or “BREASTQ” as key terms, and then screened title and abstracts to identify publications using the Reduction module. A 2013 prospective study by Coriddi et al. was selected, as it had the greatest number of participants and most complete prospective data set from available studies. Coriddi et al. reported data for all of the Reduction scales in 38 preoperative patients and 38 patients at 6 weeks postoperatively.10 Mean age was 36 ± 13 years and mean body mass index was 32 ± 6 kg/m2. The pedicle was superomedial in 33 percent and inferior in 67 percent of patients. Skin incision was Wise pattern in 76 percent and vertical incision in 24 percent of patients. Given the small sample size in available published data, the authors also used an unpublished preoperative BREAST-Q Reduction data set of 279 patients presenting for breast reduction at Dartmouth–Hitchcock Medical Center. This data set was collected as part of routine clinical care and was granted institutional review board exemption from Dartmouth’s Committee for the Protection of Human Subjects (Study 000280776). Mean age was 45 ± 14 years and mean body mass index was 31 ± 7 kg/m2. Surgical incision and pedicle information were not available, as this is a preoperative cohort. From the selected studies, we extracted the following information: study design, sample size, and BREAST-Q scores. We contacted the authors as needed to obtain missing data. The sample size, mean BREAST-Q score, and standard deviation were used to calculate a 95 percent confidence interval for each publication.
There were 121,688 Army of Women members at the time of e-blast. Three months after the e-blast, a second e-blast was circulated to complete recruitment for the remaining 409 participants needed to reach the minimum 3600 participants for all three BREAST-Q modules. Across all three modules, a total of 4326 women self-selected as eligible participants meeting the study inclusion criteria, 3618 women completed BREAST-Q preoperative modules, and 142 women who were not included attempted to participate after the final module had reached capacity, before the Army of Women closed the study. The overall response rate across all three modules was 86.5 percent. In total, 1206 women completed the BREAST-Q Reduction module preoperative questionnaire.
For the Reduction sample, the mean age was 55 ± 13 years, mean body mass index 27 ± 6 kg/m2, and bra cup size of at least a D was present in 40 percent of women (n = 481). The majority of participants were of white ethnicity [n = 1093 (91 percent)], 84 percent had a college education or greater (n = 1009), 43 percent were employed full-time (n = 511), 44 percent had an annual gross household income of $100,000 or greater (n = 505), and 69 percent were married (n = 828). A chronic health condition was reported in 50 percent (n = 596), with commonly cited conditions as follows: hypothyroidism, diabetes, hypertension, hyperlipidemia, asthma, gastroesophageal reflux disease, inflammatory bowel disease, irritable bowel syndrome, arthritis, psoriasis, and headaches. Full demographic values of the women who completed the Reduction module are listed in Table 1.
The normative scores are shown in Table 2 and ranged from 55 to 76, with standard deviations ranging from 11 to 19. The Sexual Well-being scale was completed by 85 percent (n = 1024), the lowest completion rate. Of note, the instructions specify not to complete the Sexual Well-being scale if the participant was uncomfortable with the content or felt items were not applicable.
For the four BREAST-Q scales, the linear multivariate regression models generated between three and five demographic variables associated with Reduction scores. Figure 1 demonstrates these significant variables with 95 percent confidence intervals. Common across the four BREAST-Q Reduction scales was the association of lower BREAST-Q scores for respondents with a body mass index of 30 kg/m2 or more and bra cup size of D or greater compared with the corresponding reference groups (all values in the regression models for these two variables were p < 0.001).
The normative scale scores generated in this study were compared to previously published (Coriddi et al.) and unpublished (Dartmouth) BREAST-Q data in patients presenting for and undergoing reduction mammaplasty. Figure 2 shows the results of the preoperative studies and the postoperative prospective study in comparison with the normative results. The two separate preoperative means were not significantly different from each other, and both were significantly lower than the norm across all four scales. Postoperative means were significantly higher than the norm across all four scales.
Relief of symptoms (e.g., neck, back, shoulder, and arm pain; headaches; rashes; itching; and bra strap grooving) is the primary motivators for most women pursuing reduction mammaplasty.5,6 Generic patient-reported outcome instruments have demonstrated that these women with symptomatic macromastia who undergo reduction mammaplasty report significant improvements in pain and quality of life, often to a level that is better than that of the general population.6,19 Furthermore, researchers have failed to explain these improvements in quality of life and symptoms using objective measures, such as body mass index, bra cup size, and quantity of resected breast tissue.19–21 However, despite these well-established findings in the literature, stating that it is subjective rather than objective measures that matter most for patients, third-party payers have yet to respond. Third-party payers often require the inevitable failure of lengthy nonoperative treatment attempts, size requirements of the initial bra cup size, and/or predetermined quantities of breast tissue resected, continuing to rely on quantitative data to drive reimbursements for a procedure that is best evaluated in qualitative outcomes.
Patient-reported outcome instruments represent a potential bridge to this discrepancy. Furthermore, disease-specific patient-reported outcome instruments, as opposed to generic instruments such as the 36-Item Short-Form Health Survey or the EuroQol instrument, which are used to assess general changes in patient-reported outcomes across multiple disease processes, have the potential to provide reproducible data, specific to a given disease process and capable of capturing change over time.22 The BREAST-Q Reduction module provides such data for patients presenting for and undergoing reduction mammaplasty.11 However, a key limitation of the current disease-specific patient-reported outcome instruments for macromastia and reduction mammaplasty, and specifically the BREAST-Q Reduction module, is the lack of normative data. Whereas generic patient-reported outcome instruments, such as the 36-Item Short-Form Health Survey, are scaled to a normative population, before this analysis, it was not known what a normative BREAST-Q Reduction score was.
In this study, we successfully generated population norms for the Reduction module of the BREAST-Q. Normative BREAST-Q scores will help to demonstrate the health burden associated with macromastia and the impact of surgical intervention. Within the normative scores, larger body mass index and bra cup sizes were associated with lower BREAST-Q scores compared with reference groups with smaller body mass indices and bra cup sizes. This finding suggests that even women not seeking reduction mammaplasty but with higher body mass indices and/or bra cup sizes may have lower associated well-being or quality of life with regard to their breasts.
Our comparison of normative BREAST-Q scores with previously collected data highlights the extent to which preoperative scores were below normative values, quantifying the health burden associated with macromastia. In addition, postoperative scores were significantly higher than the norm, demonstrating the success of reduction mammaplasty. Of note, the normative BREAST-Q scores in women with a large body mass index or breast cup size, although lower than a reference group of women with a small body mass index or breast cup size, were significantly higher than the preoperative scores in women presenting for reduction mammaplasty. This finding suggests that a large body mass index or bra cup size does not alone explain the full health burden of disease associated with macromastia.
The strengths of this study are as follows. This is the first study to generate normative values for the BREAST-Q, one of the most widely used patient-reported outcome instruments in breast surgery. Furthermore, the sample size is large, with over 1200 participants. Lastly, given the standard scoring system of the BREAST-Q, the normative data presented here can be seamlessly integrated into ongoing and future clinical care and research, providing a normative reference point for BREAST-Q score interpretation.
The limitations of this study include our sample characteristics and method of selection. Our sample population is predominantly white, educated, and wealthy, and although this is comparable to both the Reduction data presented from Dartmouth and the overall current use of the BREAST-Q,17 the Army of Women,23 and a common issue faced in large-scale health outcomes research,24 it is not representative of the U.S. population at large. In addition, women self-selected themselves to be participants in the study, without a clinician or researcher confirming eligibility. Although the inclusion criteria were straightforward and did not rely on significant medical knowledge, it is possible that they were misinterpreted. It is also possible that women actively pursuing or planning for (but who had not yet undergone) reduction mammaplasty were included in the analysis. The data collected for this study were collected as part of a larger study evaluating normative scores across all three preoperative BREAST-Q modules. There were slight variances in demographic values and preoperative BREAST-Q scores among the three samples (variance likely explained by differences in each module’s question content). Each module was completed by 1200 participants in full before the algorithm moving to the next module. This algorithm may have introduced more bias than if participants were assigned randomly to a module and all three modules were completed simultaneously.
There were also limitations in our comparison to the literature. The postoperative outcomes described here were at 6 weeks, a relatively short follow-up period. It is possible that if this type of cohort completed the BREAST-Q months to several years postoperatively, the scores might return to population norms, and here we are merely presenting an exaggerated effect immediately following surgery. In addition, despite the study by Coriddi et al. being the largest prospective study published to date, there were only 38 preoperative and 38 postoperative patients, with only some overlap in individuals between these two groups, further limiting these data.
The normative values described here provide researchers and clinicians with a novel method of interpreting BREAST-Q Reduction data. Our hope is that this new normative clinical framework will inform future research working to better understand the health burden of macromastia and evaluate the outcomes of reduction mammaplasty. In addition, we hope that these normative data could be used to better frame the discussion of appropriate surgical indications for mammaplasty, as determined by surgeons and third-party payers, with the goal of better aligning the findings in the literature with payment behaviors. Future directions could include establishing normative data for populations with increased diversity.
The normative data generated in this analysis provide an essential yet previously unavailable clinically relevant reference point for the interpretation of the BREAST-Q Reduction module. We provide context to better delineate the health burden associated with macromastia, such as confirming that bra cup size and large body mass index negatively impact health-related quality of life, yet not at the level of patients presenting for reduction mammaplasty. These data also confirm that women presenting for reduction mammaplasty have a quality of life significantly below that of the norm, and that this significantly improves to above the norm with surgical intervention. These normative values may be used to drive future research and clinical care regarding the health burden of macromastia, including appropriate indications for surgical intervention from the perspectives of both the clinician and a third-party payer, and to evaluate outcomes after reduction mammaplasty.
Funding for the study was provided from a discretionary account of Dr. Kerrigan’s held by The Dartmouth Institute.
2. Atterhem H, Holmner S, Janson PEReduction mammaplasty: Symptoms, complications, and late results. A retrospective study on 242 patients. Scand J Plast Reconstr Surg Hand Surg. 1998;32:281–286.
3. Singh KA, Losken AAdditional benefits of reduction mammaplasty: A systematic review of the literature. Plast Reconstr Surg. 2012;129:562–570.
4. Netscher DT, Meade RA, Goodman CM, Brehm BJ, Friedman JD, Thornby JPhysical and psychosocial symptoms among 88 volunteer subjects compared with patients seeking plastic surgery procedures to the breast. Plast Reconstr Surg. 2000;105:2366–2373.
5. Kerrigan CL, Collins ED, Striplin D, et alThe health burden of breast hypertrophy. Plast Reconstr Surg. 2001;108:1591–1599.
6. Gonzalez MA, Glickman LT, Aladegbami B, Simpson RLQuality of life after breast reduction surgery: A 10-year retrospective analysis using the Breast Q questionnaire. Does breast size matter? Ann Plast Surg. 2012;69:361–363.
7. Glatt BS, Sarwer DB, O’Hara DE, Hamori C, Bucky LP, LaRossa DA retrospective study of changes in physical symptoms and body image after reduction mammaplasty. Plast Reconstr Surg. 1999;103:76–82; discussion 83.
8. Rogliani M, Gentile P, Labardi L, Donfrancesco A, Cervelli VImprovement of physical and psychological symptoms after breast reduction. J Plast Reconstr Aesthet Surg. 2009;62:1647–1649.
9. Blomqvist L, Eriksson A, Brandberg YReduction mammaplasty provides long-term improvement in health status and quality of life. Plast Reconstr Surg. 2000;106:991–997.
10. Coriddi M, Nadeau M, Taghizadeh M, Taylor AAnalysis of satisfaction and well-being following breast reduction using a validated survey instrument: The BREAST-Q. Plast Reconstr Surg. 2013;132:285–290.
11. Pusic AL, Klassen AF, Scott AM, Klok JA, Cordeiro PG, Cano SJDevelopment of a new patient-reported outcome measure for breast surgery: The BREAST-Q. Plast Reconstr Surg. 2009;124:345–353.
12. Pusic AL, Reavey PL, Klassen AF, Scott A, McCarthy C, Cano SJMeasuring patient outcomes in breast augmentation: Introducing the BREAST-Q Augmentation module. Clin Plast Surg. 2009;36:23–32, v.
13. Cano S, Klassen AF, Scott A, Thoma A, Feeny D, Pusic AHealth outcome and economic measurement in breast cancer surgery: Challenges and opportunities. Expert Rev Pharmacoecon Outcomes Res. 2010;10:583–594.
14. Cano SJ, Klassen AF, Scott AM, Cordeiro PG, Pusic ALThe BREAST-Q: Further validation in independent clinical samples. Plast Reconstr Surg. 2012;129:293–302.
15. Pusic AL, Klassen AF, Cano SJUse of the BREAST-Q in clinical outcomes research. Plast Reconstr Surg. 2012;129:166e–167e; author reply 167e.
16. Cano SJ, Klassen AF, Scott AM, Pusic ALA closer look at the BREAST-Q(©). Clin Plast Surg. 2013;40:287–296.
17. Cohen WA, Mundy LR, Ballard TN, et alThe BREAST-Q in surgical research: A review of the literature 2009-2015. J Plast Reconstr Aesthet Surg. 2016;69:149–162.
18. Aaronson N, Alonso J, Burnam A, et alAssessing health status and quality-of-life instruments: Attributes and review criteria. Qual Life Res. 2002;11:193–205.
19. Collins ED, Kerrigan CL, Kim M, et alThe effectiveness of surgical and nonsurgical interventions in relieving the symptoms of macromastia. Plast Reconstr Surg. 2002;109:1556–1566.
20. Spector JA, Karp NSReduction mammaplasty: A significant improvement at any size. Plast Reconstr Surg. 2007;120:845–850.
21. Spector JA, Singh SP, Karp NSOutcomes after breast reduction: Does size really matter? Ann Plast Surg. 2008;60:505–509.
22. Klassen AF, Stotland MA, Skarsgard ED, Pusic ALClinical research in pediatric plastic surgery and systematic review of quality-of-life questionnaires. Clin Plast Surg. 2008;35:251–267.
23. Bright EE, Petrie KJ, Partridge AH, Stanton ALBarriers to and facilitative processes of endocrine therapy adherence among women with breast cancer. Breast Cancer Res Treat. 2016;158:243–251.
24. Stanton AL, Morra ME, Diefenbach MA, et alResponding to a significant recruitment challenge within three nationwide psychoeducational trials for cancer patients. J Cancer Surviv. 2013;7:392–403.