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. Author manuscript; available in PMC: 2017 Dec 29.
Published in final edited form as: JAMA. 2014 Sep 3;312(9):902–914. doi: 10.1001/jama.2014.10707

Use of and Mortality After Bilateral Mastectomy Compared With Other Surgical Treatments for Breast Cancer in California, 1998–2011

Allison W Kurian 1, Daphne Y Lichtensztajn 1, Theresa H M Keegan 1, David O Nelson 1, Christina A Clarke 1, Scarlett L Gomez 1
PMCID: PMC5747359  NIHMSID: NIHMS927867  PMID: 25182099

Abstract

IMPORTANCE

Bilateral mastectomy is increasingly used to treat unilateral breast cancer. Because it may have medical and psychosocial complications, a better understanding of its use and outcomes is essential to optimizing cancer care.

OBJECTIVE

To compare use of and mortality after bilateral mastectomy, breast-conserving therapy with radiation, and unilateral mastectomy.

DESIGN, SETTING, AND PARTICIPANTS

Observational cohort study within the population-based California Cancer Registry; participants were women diagnosed with stages 0–III unilateral breast cancer in California from 1998 through 2011, with median follow-up of 89.1 months.

MAIN OUTCOMES AND MEASURES

Factors associated with surgery use (from polytomous logistic regression); overall and breast cancer–specific mortality (from propensity score weighting and Cox proportional hazards analysis).

RESULTS

Among 189 734 patients, the rate of bilateral mastectomy increased from 2.0% (95% CI, 1.7%–2.2%) in 1998 to 12.3% (95% CI, 11.8%–12.9%) in 2011, an annual increase of 14.3% (95% CI, 13.1%–15.5%); among women younger than 40 years, the rate increased from 3.6% (95% CI, 2.3%–5.0%) in 1998 to 33% (95% CI, 29.8%–36.5%) in 2011. Bilateral mastectomy was more often used by non-Hispanic white women, those with private insurance, and those who received care at a National Cancer Institute (NCI)–designated cancer center (8.6% [95% CI, 8.1%–9.2%] among NCI cancer center patients vs 6.0% [95% CI, 5.9%–6.1%] among non-NCI cancer center patients; odds ratio [OR], 1.13 [95% CI, 1.04–1.22]); in contrast, unilateral mastectomy was more often used by racial/ethnic minorities (Filipina, 52.8% [95% CI, 51.6%–54.0%]; OR, 2.00 [95% CI, 1.90–2.11] and Hispanic, 45.6% [95% CI, 45.0%–46.2%]; OR, 1.16 [95% CI, 1.13–1.20] vs non-Hispanic white, 35.2% [95% CI, 34.9%–35.5%]) and those with public/Medicaid insurance (48.4% [95% CI, 47.8%–48.9%]; OR, 1.08 [95% CI, 1.05–1.11] vs private insurance, 36.6% [95% CI, 36.3%–36.8%]). Compared with breast-conserving surgery with radiation (10-year mortality, 16.8% [95% CI, 16.6%–17.1%]), unilateral mastectomy was associated with higher all-cause mortality (hazard ratio [HR], 1.35 [95% CI, 1.32–1.39]; 10-year mortality, 20.1% [95% CI, 19.9%–20.4%]). There was no significant mortality difference compared with bilateral mastectomy (HR, 1.02 [95% CI, 0.94–1.11]; 10-year mortality, 18.8% [95% CI, 18.6%–19.0%]). Propensity analysis showed similar results.

CONCLUSIONS AND RELEVANCE

Use of bilateral mastectomy increased significantly throughout California from 1998 through 2011 and was not associated with lower mortality than that achieved with breast-conserving surgery plus radiation. Unilateral mastectomy was associated with higher mortality than were the other 2 surgical options.

Randomized trials have demonstrated similar survival for patients with early-stage breast cancer treated with breast-conserving surgery and radiation or with mastectomy.1,2 However, older data show increasing use of mastectomy, and particularly bilateral mastectomy, among US patients with breast cancer.3–5 Bilateral mastectomy represents both treatment (for the affected breast) and prevention (for the contralateral breast), with the uncommon exception of patients having bilateral tumors. The causes of the increasing use of bilateral mastectomy are unknown; one possibility is the dissemination of sensitive diagnostic tests such as breast magnetic resonance imaging and genetic testing of BRCA1 (unigene cluster number Hs.194143) and BRCA2 (unigene cluster number Hs.34012).4,6 Although it may be cited as a justification for bilateral mastectomy, evidence for a survival benefit appears limited to rare patient subgroups, including women with BRCA1/2 mutations or strong family history of cancer.7–9

Because bilateral mastectomy is an elective procedure for unilateral breast cancer and may have detrimental effects in terms of complications and associated costs10,11 as well as body image and sexual function,12,13 a better understanding of its use and outcomes is crucial to improving cancer care. Because patients’ preferences drive its use, patients are unlikely to accept randomization to a less extensive surgical procedure in a clinical trial; thus, observational studies offer a feasible alternative to address an important clinical question. To minimize selection bias, we designed a population-based study of the use and outcomes of bilateral mastectomy compared with other surgical treatments, using the California Cancer Registry (CCR, part of the National Cancer Institute [NCI] Surveillance, Epidemiology and End Results [SEER] program), which comprises about 99% of all breast cancer cases statewide.

Methods

Case Ascertainment and Data Collection

The study population consisted of all female California residents newly diagnosed with a first primary breast cancer (International Classification of Diseases–Oncology, 3rd edition, morphology codes C50.0–50.9), of American Joint Commission on Cancer stages 0–III, from January 1, 1998, through December 31, 2011. Approval for human subjects research was obtained from the Cancer Prevention Institute of California institutional review board. We obtained CCR data routinely abstracted from medical records on age at diagnosis, race/ethnicity (from patients’ medical records and registry categorization; assessed because prior research indicates that the use of and survival after surgical procedures vary by race/ethnicity, and because we aimed to evaluate these associations in a population-based context), marital status, stage, tumor grade, tumor size, histology, lymph node involvement, metastasis, and biomarkers.14 Tumors with histologic morphology codes 8500–8508 and 8521–8523 were coded as ductal and those with codes 8520 and 8524–8525 as lobular. We also obtained CCR information on initial treatment (surgery, chemotherapy, and radiation therapy), primary health insurance, census block group of residence at diagnosis, and vital status (determined by CCR through hospital follow-up and database linkages, including the Social Security Administration) as of December 31, 2010, and, for the deceased, the underlying cause of death.

Tumor Biomarker Information

Estrogen-receptor and progesterone-receptor status were each categorized as positive (≥5% nuclear staining), negative, borderline, not tested, not recorded, or unknown. Tumors were considered estrogen receptor–/progesterone receptor–positive if they were estrogen receptor–positive, progester-one receptor–positive, or both, and as estrogen receptor–/progesterone receptor–negative if both were negative. Given that CCR did not systematically collect v-erb-b2 avian erythroblastic leukemia viral oncogene homologue 2 (ERBB2, also known as HER-2/neu, unigene cluster number Hs.446352) testing results before 2006, ERBB2 data are not included.

Neighborhood Socioeconomic Information

For each case, we assigned a previously developed measure of neighborhood socioeconomic status (SES). For cases diagnosed in 1998–2005, we used a measure of neighborhood-level SES quintiles based on distribution across California, incorporating block group-level data from the 2000 Census on income, education, housing costs, and occupation.15 For cases diagnosed in 2006–2010, we used data from the American Community Survey of the US Census to derive a similar index.

Hospital-Level Information

The CCR records the facility reporting each case. Using the aforementioned index, we determined the SES distribution of all cases for each facility and identified facilities that were NCI–designated cancer centers.

Statistical Analysis

We used polytomous logistic regression to model surgery use. Survival time was measured in days from diagnosis to death. Women who died from other causes were censored at time of death for the analysis of breast cancer–specific mortality. Women alive at the time of last follow-up or December 31, 2010, were censored then. We used Cox proportional hazards to model the association of various factors with overall and breast cancer–specific mortality. The proportional hazards assumption was confirmed by testing the correlation of Schoenfeld residuals with time. For both models (surgery use and mortality), covariates included age, race/ethnicity, tumor size, grade, histology, nodal and estrogen receptor/progesterone receptor status, receipt of adjuvant chemotherapy and radiation, neighbor hood SES quintile, marital and insurance status, the SES composition of patients at the reporting hospital, care at an NCI-designated cancer center, and diagnosis year. Stage was included as a stratifying variable in the Cox regression, allowing baseline hazards to vary by stage. Multicol-linearity in the models was assessed using the variance inflation factor. We did not test for a priori interactions but did conduct stratified analyses by age and stage. Missing data were coded as unknown and retained as a separate category for analyses.

We used SAS version 9.3 for all analyses except those of surgical use trends, for which we used Joinpoint (Joinpoint Regression Program version 4.0.4 [Statistical Research and Applications Branch, NCI]). This program uses Monte Carlo Permutation tests to model data and identify up to 3 points (“joinpoints”) at which there was a statistically significant change in linear trend.16 Results of joinpoint analysis were used to inform grouping of diagnosis years in logistic regression analysis.

Propensity score analyses defined surgery type as the patient attribute for which scores were calculated.17 We used generalized boosting models, a nonparametric machine-learning classifier, in the R package twang, setting the search limit to 15 000 trees.18 All independent variables in Table 1 and Table 2 were used to calculate per-patient scores, except 3 variables highly correlated with others (radiation therapy with surgery type; chemotherapy and adjuvant treatment with administration of chemotherapy before or after the surgical procedure).

Table 1.

Patient and Tumor Characteristics According to Surgery Type: Bilateral Mastectomy, Breast-Conserving Surgery With Radiation, and Unilateral Mastectomy, Stages 0–III Breast Cancer, 1998–2011, California

Variable Bilateral Mastectomy Breast-Conserving Surgery With Radiation Unilateral Mastectomy Total
No. Row % (95% CI) No. Row % (95% CI) No. Row % (95% CI)
All patients 11 692 6.2 (6.1–6.3) 104 420 55.0 (54.8–55.3) 73 622 38.8 (38.6–39.0) 189 734
Race/ethnicity
 Non-Hispanic white 8758 6.9 (6.8–7.1) 73 310 57.9 (57.6–58.2) 44 557 35.2 (34.9–35.5) 126 625
 Non-Hispanic black 416 4.2 (3.8–4.6) 5483 55.1 (54.1–56.0) 4057 40.7 (39.8–41.7) 9956
 Hispanic 1450 5.0 (4.8–5.3) 14 279 49.4 (48.8–50.0) 13 172 45.6 (45.0–46.2) 28 901
 Chinese 172 3.3 (2.8–3.7) 2520 47.9 (46.5–49.2) 2570 48.8 (47.5–50.2) 5262
 Japanese 100 4.2 (3.4–5.0) 1317 54.7 (52.7–56.7) 989 41.1 (39.1–43.1) 2406
 Filipina 268 4.0 (3.5–4.4) 2922 43.2 (42.0–44.4) 3574 52.8 (51.6–54.0) 6764
 Other Asian/Pacific Islander 440 5.3 (4.8–5.8) 3765 45.4 (44.4–46.5) 4079 49.2 (48.2–50.3) 8284
 Non-Hispanic American Indian/other/unknown 88 5.7 (4.6–6.9) 824 53.6 (51.2–56.1) 624 40.6 (38.2–43.1) 1536
Age at diagnosis, y
 <40 1586 15.7 (15.0–16.4) 4092 40.4 (39.5–41.4) 4448 43.9 (43.0–44.9) 10 126
 40–49 3898 10.3 (10.0–10.6) 19 175 50.8 (50.3–51.4) 14 636 38.8 (38.3–39.3) 37 709
 50–64 4549 6.1 (6.0–6.3) 43 709 58.9 (58.6–59.3) 25 922 34.9 (34.6–35.3) 74 180
 ≥65 1659 2.4 (2.3–2.6) 37 444 55.3 (54.9–55.7) 28 616 42.3 (41.9–42.6) 67 719
Marital status
 Not married 3698 5.1 (4.9–5.3) 38 936 53.6 (53.3–54.0) 29 954 41.3 (40.9–41.6) 72 588
 Married 7753 6.9 (6.7–7.0) 63 433 56.1 (55.8–56.4) 41 884 37.0 (36.8–37.3) 113 070
 Unknown 241 5.9 (5.2–6.6) 2051 50.3 (48.8–51.9) 1784 43.8 (42.2–45.3) 4076
Neighborhood SES quintilea
 1 (lowest) 795 3.9 (3.7–4.2) 9339 46.2 (45.5–46.8) 10 101 49.9 (49.2–50.6) 20 235
 2 1480 4.8 (4.6–5.0) 15 621 50.6 (50.1–51.2) 13 752 44.6 (44.0–45.1) 30 853
 3 2164 5.6 (5.4–5.8) 20 904 54.0 (53.5–54.5) 15 665 40.4 (40.0–40.9) 38 733
 4 2899 6.3 (6.1–6.6) 26 008 56.9 (56.5–57.4) 16 790 36.7 (36.3–37.2) 45 697
 5 4354 8.0 (7.8–8.3) 32 548 60.0 (59.6–60.4) 17 314 31.9 (31.5–32.3) 54 216
Insurance status
 Private 9477 7.7 (7.6–7.9) 68 395 55.7 (55.4–56.0) 44 894 36.6 (36.3–36.8) 122 766
 Medicare 782 3.2 (3.0–3.4) 13 722 56.3 (55.7–56.9) 9876 40.5 (39.9–41.1) 24 380
 Military 99 6.1 (4.9–7.2) 835 51.3 (48.8–53.7) 695 42.7 (40.3–45.1) 1629
 Not insured or self-pay 80 5.4 (4.2–6.5) 693 46.5 (43.9–49.0) 718 48.2 (45.6–50.7) 1491
 Public or Medicaid 1072 3.3 (3.1–3.5) 15 762 48.3 (47.8–48.9) 15 768 48.4 (47.8–48.9) 32 602
 Unknown 182 2.7 (2.3–3.0) 5013 73.0 (72.0–74.1) 1671 24.3 (23.3–25.4) 6866
American Joint Committee on Cancer stage
 0 1779 7.6 (7.3–8.0) 14 697 63.0 (62.3–63.6) 6864 29.4 (28.8–30.0) 23 340
 I 4376 5.0 (4.9–5.2) 57 946 66.8 (66.5–67.1) 24 436 28.2 (27.9–28.5) 86 758
 II 4641 6.7 (6.5–6.8) 29 397 42.2 (41.8–42.5) 35 669 51.2 (50.8–51.5) 69 707
 III 896 9.0 (8.5–9.6) 2380 24.0 (23.1–24.8) 6653 67.0 (66.1–67.9) 9929
Tumor size, cm
 <1 2366 5.8 (5.6–6.0) 28 022 68.9 (68.4–69.3) 10 310 25.3 (24.9–25.8) 40 698
 1–1.9 3933 5.3 (5.2–5.5) 46 936 63.5 (63.2–63.8) 23 047 31.2 (30.8–31.5) 73 916
 2–2.9 2786 6.6 (6.3–6.8) 20 044 47.3 (46.9–47.8) 19 507 46.1 (45.6–46.6) 42 337
 3–3.9 1419 7.4 (7.0–7.8) 6395 33.3 (32.6–33.9) 11 400 59.3 (58.6–60.0) 19 214
 4–5 1188 8.8 (8.3–9.2) 3023 22.3 (21.6–23.0) 9358 69.0 (68.2–69.7) 13 569
Grade
 I 1962 4.9 (4.7–5.1) 26 134 65.7 (65.2–66.1) 11 694 29.4 (28.9–29.8) 39 790
 II 4610 6.0 (5.8–6.2) 42 862 55.9 (55.5–56.2) 29 219 38.1 (37.8–38.4) 76 691
 III 4421 7.0 (6.8–7.2) 30 525 48.4 (48.0–48.8) 28 159 44.6 (44.2–45.0) 63 105
 Unknown 699 6.9 (6.4–7.4) 4899 48.3 (47.3–49.2) 4550 44.8 (43.9–45.8) 10 148
Histology
 Ductal 9706 6.0 (5.9–6.1) 90 011 55.5 (55.3–55.8) 62 336 38.5 (38.2–38.7) 162 053
 Lobular or lobular component 1290 9.6 (9.1–10.1) 6070 45.0 (44.1–45.8) 6134 45.5 (44.6–46.3) 13 494
 Other 696 4.9 (4.6–5.3) 8339 58.8 (58.0–59.6) 5152 36.3 (35.5–37.1) 14 187
ER/PR status
 Negative (ER- and PR-negative) 1974 6.9 (6.6–7.2) 13 914 48.4 (47.8–49.0) 12 870 44.8 (44.2–45.3) 28 758
 Positive (ER- or PR-positive) 8536 6.2 (6.0–6.3) 79 457 57.5 (57.2–57.8) 50 213 36.3 (36.1–36.6) 138 206
 Unknown or borderline 1182 5.2 (4.9–5.5) 11 049 48.5 (47.9–49.2) 10 539 46.3 (45.6–46.9) 22 770
Lymph node involvement
 Negative 7824 5.7 (5.6–5.8) 84 655 61.7 (61.5–62.0) 44 667 32.6 (32.3–32.8) 137 146
 Positive 3868 7.4 (7.1–7.6) 19 765 37.6 (37.2–38.0) 28 955 55.1 (54.6–55.5) 52 588
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Abbreviations: ER, estrogen receptor; PR, progesterone receptor; SES, socioeconomic status.

a

Distribution based on statewide quintiles.

Table 2.

Diagnosis and Treatment Characteristics According to Surgery Type: Bilateral Mastectomy, Breast-Conserving Surgery With Radiation, and Unilateral Mastectomy, Stages 0–III Breast Cancer, 1998–2011, California

Variable Bilateral Mastectomy Breast-Conserving Surgery With Radiation Unilateral Mastectomy Total
No. Row % (95% CI) No. Row % (95% CI) No. Row % (95% CI)
Year of cancer diagnosis
 1998 249 2.0 (1.7–2.2) 6453 51.7 (50.8–52.5) 5790 46.3 (45.5–47.2) 12 492
 1999 298 2.4 (2.1–2.6) 6566 52.3 (51.4–53.1) 5702 45.4 (44.5–46.2) 12 566
 2000 400 3.0 (2.7–3.3) 7226 54.1 (53.3–54.9) 5730 42.9 (42.1–43.7) 13 356
 2001 483 3.5 (3.2–3.9) 7286 53.5 (52.7–54.4) 5842 42.9 (42.1–43.8) 13 611
 2002 509 3.8 (3.5–4.1) 7341 54.6 (53.8–55.5) 5591 41.6 (40.8–42.4) 13 441
 2003 605 4.6 (4.3–5.0) 7310 56.1 (55.3–57.0) 5107 39.2 (38.4–40.1) 13 022
 2004 704 5.3 (4.9–5.7) 7468 56.2 (55.4–57.1) 5111 38.5 (37.7–39.3) 13 283
 2005 642 4.7 (4.3–5.0) 8117 59.3 (58.5–60.2) 4920 36.0 (35.2–36.8) 13 679
 2006 821 6.1 (5.7–6.5) 7746 57.5 (56.7–58.3) 4905 36.4 (35.6–37.2) 13 472
 2007 1017 7.2 (6.8–7.7) 8053 57.3 (56.5–58.1) 4979 35.4 (34.6–36.2) 14 049
 2008 1209 8.5 (8.0–9.0) 7852 55.3 (54.4–56.1) 5148 36.2 (35.4–37.0) 14 209
 2009 1437 10.3 (9.8–10.8) 7541 54.0 (53.2–54.8) 4987 35.7 (34.9–36.5) 13 965
 2010 1550 10.9 (10.4–11.4) 7687 53.9 (53.1–54.7) 5021 35.2 (34.4–36.0) 14 258
 2011 1768 12.3 (11.8–12.9) 7774 54.2 (53.4–55.1) 4789 33.4 (32.6–34.2) 14 331
Received care at an NCI- designated cancer center
 No 10 860 6.0 (5.9–6.1) 98 658 54.8 (54.6–55.0) 70 559 39.2 (39.0–39.4) 180 077
 Yes 832 8.6 (8.1–9.2) 5762 59.7 (58.7–60.6) 3063 31.7 (30.8–32.6) 9657
Patient SES quintile distribution of reporting hospitala
 >50% of patients in quintiles 1 (lowest)-2 1587 4.7 (4.5–4.9) 15 773 46.9 (46.3–47.4) 16 286 48.4 (47.9–48.9) 33 646
 >50% of patients in quintiles 4–5 7044 7.2 (7.1–7.4) 57 514 59.1 (58.8–59.4) 32 701 33.6 (33.3–33.9) 97 259
 Mixed SES distribution 3061 5.2 (5.0–5.4) 31 133 52.9 (52.5–53.3) 24 635 41.9 (41.5–42.3) 58 829
Radiation therapy
 No 9869 13.8 (13.5–14.0) 0 NA 61 811 86.2 (86.0–86.5) 71 680
 Yes 1823 1.5 (1.5–1.6) 104 420 88.5 (88.3–88.6) 11 811 10.0 (9.8–10.2) 118 054
Chemotherapy
 No 6392 5.2 (5.1–5.4) 71 382 58.5 (58.2–58.8) 44 296 36.3 (36.0–36.6) 122 070
 Yes 5300 7.8 (7.6–8.0) 33 038 48.8 (48.4–49.2) 29 326 43.3 (43.0–43.7) 67 664
Chemotherapy timing
 After surgery 3753 6.5 (6.3–6.7) 29 123 50.7 (50.3–51.1) 24 583 42.8 (42.4–43.2) 57 459
 Before surgery 1490 17.9 (17.1–18.7) 2874 34.5 (33.5–35.5) 3963 47.6 (46.5–48.7) 8327
 No chemotherapy 6392 5.2 (5.1–5.4) 71 382 58.5 (58.2–58.8) 44 296 36.3 (36.0–36.6) 122 070
 Unknown 57 3.0 (2.3–3.8) 1041 55.4 (53.2–57.7) 780 41.5 (39.3–43.8) 1878
Adjuvant treatment, chemotherapy, and/or radiation therapy
 No 6143 5.1 (5.0–5.3) 71 382 59.8 (59.5–60.1) 41 892 35.1 (34.8–35.4) 119 417
 Yes 5549 7.9 (7.7–8.1) 33 038 47.0 (46.6–47.4) 31 730 45.1 (44.8–45.5) 70 317
Breast reconstructive surgery
 No 6428 3.7 (3.6–3.8) 104 229 59.8 (59.6–60.1) 63 529 36.5 (36.2–36.7) 174 186
 Yes 5264 33.9 (33.1–34.6) 191 1.2 (1.1–1.4) 10 093 64.9 (64.2–65.7) 15 548
Vital status
 Dead 903 2.8 (2.6–3.0) 13 571 42.5 (41.9–43.0) 17 489 54.7 (54.2–55.3) 31 963
 Alive 10 789 6.8 (6.7–7.0) 90 849 57.6 (57.3–57.8) 56 133 35.6 (35.3–35.8) 157 771
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Abbreviations: NA, not available; NCI, National Cancer Institute; SES, socioeconomic status.

a

Distribution based on statewide quintiles.

We used graphical analysis to assess the postbalance maximum standardized effect difference for each variable17 and calculated weights for the average treatment effect (average outcome for the whole population after one surgery vs another); and average treatment effect for those treated (average out come for those treated after one surgery vs another). The svykm and svylogrank functions from the survey package19 were used to calculate weighted Kaplan-Meier curves and P values; the svycoxph function was used for weighted Cox proportional hazard models, with outcome regressed on treatment and stratified by stage. Weighted CIs for mortality rates were calculated by the survfit function in the R survival package.

Results

Patient Characteristics

A total of 291 117 stages 0–III breast cancer cases were diagnosed and reported to CCR from January 1, 1998, through December 31, 2011. Cases were excluded if missing essential data for categorization or if ineligible for breast-conserving surgery with radiation according to practice guide lines,20 as follows: diagnosed by death certificate or autopsy only (n = 33); tumor larger than 5 cm or unknown, microscopic or diffuse tumor, Paget disease of breast or mammographic diagnosis only, or inflammatory carcinoma (n = 41 853); no pathology report confirmation (n = 283); unknown lymph node involvement (n = 1771); surgery other than bilateral mastectomy, breast-conserving surgery with radiation, or unilateral mastectomy (n = 52 343); and diagnosis of bilateral tumors or a second primary breast tumor within 60 days (n = 5100), resulting in 189 734 women included in analyses of surgery use. Mortality analyses excluded women diagnosed after 2010 because of incomplete mortality data for 2011 (n = 14 331), those having zero or invalid survival time (n = 11), and those having unknown cause of death (n = 475). Mortality analyses included 174 917 women; median follow-up time was 89.1 months (inter quartile range, 54.8–129.9 months).

The proportions of all patients who underwent each surgery were 6.2% (95% CI, 6.1%–6.3%) for bilateral mastectomy, 55.0% (95%, 54.8%–55.3%) for breast-conserving surgery with radiation; and 38.8% (95% CI, 38.6%–39.0%) for unilateral mastectomy (Table 1 and eTable in the Supplement). Among all patients, the rate of bilateral mastectomy increased from 2.0% (95% CI, 1.7%–2.2%) in 1998 to 12.3% (95% CI, 11.8%–12.9%) in 2011, an annual increase of 14.3% (95% CI, 13.1%–15.5%)(Table 2 and eTable). The increase in bilateral mastectomy rate was greatest among women younger than 40 years: the rate increased from 3.6% (95% CI, 2.3%–5.0%) in 1998 to 33.0% (95% CI, 29.8%–36.5%) in 2011, increasing by 17.6% (95% CI, 14.9%–20.4%) annually. Use of unilateral mastectomy declined in all age groups (Figure 1).

Figure 1.

Figure 1

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Joinpoint Analysis Showing Time Trends in Use of Bilateral Mastectomy, Breast-Conserving Surgery With Radiation, and Unilateral Mastectomy, According to Patient Age in Years at Breast Cancer Diagnosis

Data points indicate observed data.

Multiple Regression Analysis of Characteristics Associated With Surgical Type

Factors associated with having undergone bilateral mastectomy (vs breast-conserving surgery with radiation) included age younger than 50 years, non-Hispanic white race/ethnicity, larger tumor size, nodal involvement, lobular histology, higher grade or estrogen receptor–/progesterone receptor–negative status, care at a hospital predominantly serving patients with lower SES or at an NCI-designated cancer center, having higher neighborhood SES, and recent diagnosis. Factors inversely associated with having undergone bilateral mastectomy (vs breast-conserving surgery with radiation) included age 65 years or older, minority race/ethnicity, receipt of adjuvant therapy, married status, and insurance type other than private (Table 3).

Table 3.

Multiple Regression Odds Ratios for Associations With Receipt of Bilateral Mastectomy or Unilateral Mastectomy vs Breast-Conserving Surgery With Radiation as the Reference Groupa

Variable Odds Ratio (95% CI)
Bilateral Mastectomy vs Breast-Conserving Surgery With Radiation Unilateral Mastectomy vs Breast-Conserving Surgery With Radiation
Race/ethnicity
 Non-Hispanic white 1 [Reference] 1 [Reference]
 Chinese 0.41 (0.35–0.48) 1.95 (1.84–2.08)
 Filipina 0.61 (0.54–0.70) 2.00 (1.90–2.11)
 Hispanic 0.63 (0.59–0.67) 1.16 (1.13–1.20)
 Japanese 0.63 (0.51–0.77) 1.40 (1.28–1.53)
 Non-Hispanic American Indian/other/unknown 0.76 (0.61–0.96) 1.23 (1.10–1.38)
 Non-Hispanic black 0.53 (0.47–0.59) 0.89 (0.85–0.94)
 Other Asian/Pacific Islander 0.64 (0.58–0.71) 1.88 (1.79–1.97)
Age at diagnosis, y
 <40 3.81 (3.55–4.08) 1.31 (1.25–1.38)
 40–49 2.00 (1.91–2.10) 1.15 (1.12–1.18)
 50–64 1 [Reference] 1 [Reference]
 ≥65 0.45 (0.42–0.48) 1.34 (1.30–1.38)
Tumor size
 Per centimeter 1.36 (1.34–1.39) 1.61 (1.60–1.63)
Lymph node involvement
 Negative 1 [Reference] 1 [Reference]
 Positive 1.66 (1.58–1.75) 2.16 (2.10–2.22)
Histology
 Ductal 1 [Reference] 1 [Reference]
 Lobular or with lobular component 2.19 (2.05–2.35) 1.36 (1.31–1.42)
 Other 0.89 (0.82–0.97) 0.96 (0.92–1.00)
Grade
 I 1 [Reference] 1 [Reference]
 II 1.17 (1.11–1.24) 1.18 (1.15–1.22)
 III 1.30 (1.22–1.38) 1.24 (1.20–1.28)
 Unknown 1.67 (1.52–1.84) 1.45 (1.38–1.52)
ER/PR status
 Positive 1 [Reference] 1 [Reference]
 Negative 1.12 (1.05–1.19) 1.17 (1.13–1.21)
 Unknown or borderline 1.53 (1.43–1.64) 1.53 (1.48–1.58)
Adjuvant treatment, chemotherapy, and/or radiation
 No 1 [Reference] 1 [Reference]
 Yes 0.91 (0.86–0.95) 0.86 (0.84–0.89)
Neighborhood SES quintileb,c
 1 (lowest) 1 [Reference] 1 [Reference]
 2 1.10 (1.00–1.21) 0.91 (0.88–0.95)
 3 1.18 (1.08–1.29) 0.85 (0.82–0.89)
 4 1.22 (1.11–1.33) 0.80 (0.76–0.83)
 5 1.41 (1.29–1.55) 0.73 (0.70–0.76)
Marital status
 Not married 1 [Reference] 1 [Reference]
 Married 0.95 (0.91–0.99) 1.07 (1.05–1.10)
 Unknown 1.06 (0.92–1.22) 1.37 (1.28–1.47)
Insurance status
 Private 1 [Reference] 1 [Reference]
 Medicare 0.97 (0.88–1.06) 0.97 (0.93–1.00)
 Military 0.84 (0.68–1.04) 1.08 (0.97–1.21)
 Not insured or self-pay 0.78 (0.61–0.99) 1.08 (0.96–1.21)
 Public or Medicaid 0.66 (0.61–0.71) 1.08 (1.05–1.11)
 Unknown 0.26 (0.22–0.31) 0.37 (0.35–0.40)
Patient SES distribution of reporting hospitalb
 >50% of patients in quintiles 1–2 1.12 (1.05–1.20) 1.49 (1.44–1.53)
 >50% of patients in quintiles 4–5 1 [Reference] 1 [Reference]
 Mixed distribution 1.05 (1.00–1.10) 1.32 (1.28–1.35)
Received care at an NCI- designated cancer center
 No 1 [Reference] 1 [Reference]
 Yes 1.13 (1.04–1.22) 0.81 (0.77–0.85)
Year of cancer diagnosis
 1998–2004 1 [Reference] 1 [Reference]
 2005–2011 2.73 (2.61–2.86) 0.84 (0.82–0.86)
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Abbreviations: ER, estrogen receptor; NCI, National Cancer Institute; PR, progesterone receptor; SES, socioeconomic status.

a

Odds ratios based on polytomous logistic regression modeling. Model covariates were age, race/ethnicity, tumor size, grade, ER/PR status, nodal status, histology, receipt of adjuvant treatments including chemotherapy and radiation, neighborhood SES quintile, marital status, insurance status, SES composition of patients at the reporting hospital, care at an NCI-designated cancer center, and year of diagnosis.

b

Distribution based on statewide quintiles.

c

P value for trend of SES was <.001 for both bilateral mastectomy and unilateral mastectomy compared with breast-conserving surgery with radiation.

Characteristics associated with having undergone unilateral mastectomy (vs breast-conserving surgery plus radiation) included diagnosis at age other than 50 to 64 years, Asian, Hispanic, and American Indian race/ethnicity (with notable associations for Filipina and Hispanic women vs non-Hispanic white women), larger tumor size, nodal involvement, lobular histology, higher grade, estrogen receptor–/progesterone receptor–negative status, married status, public/Medicaid insurance, or care at a hospital predominantly serving patients of lower SES (Table 3). Factors inversely associated with having unilateral mastectomy (vs breast-conserving surgery with radiation) included black race, receipt of adjuvant therapy, care at an NCI-designated cancer center, higher neighborhood SES, and recent diagnosis.

Multiple Regression Analysis of Mortality After Surgery

Compared with breast-conserving surgery with radiation, bilateral mastectomy was not associated with a mortality difference (hazard ratio [HR], 1.02 [95% CI, 0.94–1.11]), whereas unilateral mastectomy was associated with higher mortality (HR, 1.35[95% CI, 1.32–1.39]) (Table 4). Other factors associated with overall mortality included age 65 years or older or younger than 40 years, black race, larger tumor size, nodal involvement, higher grade, estrogen receptor–/progesterone receptor–negative status, lower neighborhood SES, unmarried status, having Medicare or public/Medicaid insurance, and receiving care at a hospital predominantly serving patients of lower SES. Higher mortality was associated with unilateral mastectomy in all age groups. Similar mortality between bilateral mastectomy and breast-conserving surgery with radiation was observed in all age groups except women 65 years or older, whose survival was slightly better after breast-conserving surgery with radiation. Findings were similar for breast cancer–specific mortality (Table 5). Compared with unilateral mastectomy, bilateral mastectomy was associated with lower overall mortality (HR, 0.75 [95% CI, 0.70–0.82]) and breast cancer–specific mortality (HR, 0.85 [95% CI, 0.76–0.94]).

Table 4.

Multiple Regression Hazard Ratios for Associations of Patient and Clinical Characteristics With Overall Mortality, Stages 0–III Breast Cancer, 1998–2010, Californiaa

Variable Deceased Patients Total Patients HR (95% CI)
Surgical procedure
 Bilateral mastectomy 635 9907 1.02 (0.94–1.11)
 Breast-conserving surgery with radiation 9949 96 462 1 [Reference]
 Unilateral mastectomy 13 699 68 548 1.35 (1.32–1.39)
Race/ethnicity
 Chinese 383 4787 0.70 (0.63–0.78)
 Filipina 529 6150 0.69 (0.63–0.75)
 Hispanic 2982 26 035 0.81 (0.77–0.84)
 Japanese 244 2263 0.70 (0.62–0.80)
 Non-Hispanic American Indian/other/unknown 150 1378 0.85 (0.72–1.00)
 Non-Hispanic black 1701 9112 1.12 (1.06–1.17)
 Non-Hispanic white 17 782 117 853 1 [Reference]
 Other Asian/Pacific Islander 512 7339 0.67 (0.61–0.73)
Age at diagnosis, y
 <40 1124 9341 1.11 (1.04–1.19)
 40–49 2503 34 878 0.82 (0.78–0.86)
 50–64 5621 68 104 1 [Reference]
 ≥65 15 035 62 594 2.65 (2.56–2.75)
Tumor size
 Per centimeter NA NA 1.23 (1.21–1.25)
Lymph node involvement
 Negative 14 327 126 165 1 [Reference]
 Positive 9956 48 752 1.46 (1.40–1.51)
Histology
 Ductal 20 561 149 278 1 [Reference]
 Lobular or with lobular component 1961 12 403 0.89 (0.84–0.93)
 Other 1761 13 236 0.92 (0.87–0.96)
Grade
 I 3825 36 593 1 [Reference]
 II 8919 70 377 1.15 (1.11–1.20)
 III 9828 58 247 1.49 (1.43–1.55)
 Unknown 1711 9700 1.23 (1.16–1.30)
ER/PR status
 Negative 4992 26 685 1.48 (1.43–1.53)
 Positive 15 375 125 955 1 [Reference]
 Unknown or borderline 3916 22 277 1.11 (1.07–1.15)
Adjuvant treatment, chemotherapy, and/or radiation
 No 15 336 109 699 1 [Reference]
 Yes 8947 65 218 0.78 (0.76–0.81)
Neighborhood SES quintileb,c
 1 (lowest) 3308 18 484 1 [Reference]
 2 4758 28 329 0.97 (0.92–1.01)
 3 5394 35 740 0.90 (0.86–0.94)
 4 5564 42 120 0.85 (0.81–0.89)
 5 5259 50 244 0.73 (0.70–0.77)
Marital status
 Married 11 432 104 647 1 [Reference]
 Not married 12 438 67 098 1.36 (1.33–1.40)
 Unknown 413 3172 1.18 (1.07–1.30)
Insurance status
 Medicare 5229 22 445 1.22 (1.18–1.26)
 Military 158 1487 1.12 (0.96–1.31)
 Not insured or self-pay 187 1408 1.10 (0.95–1.27)
 Private 11 957 113 347 1 [Reference]
 Public or Medicaid 5892 29 746 1.25 (1.21–1.29)
 Unknown 860 6484 0.92 (0.86–0.99)
Patient SES distribution of reporting hospitalb
 >50% of patients in quintiles 4–5 10 471 89 573 1 [Reference]
 >50% of patients in quintiles 1–2 5555 31 015 1.12 (1.08–1.16)
 Mixed distribution 8257 54 329 1.07 (1.04–1.11)
Received care at an NCI-designated cancer center
 No 23 494 166 025 1 [Reference]
 Yes 789 8892 0.82 (0.76–0.88)
Year of cancer diagnosis
 Per year NA NA 0.87 (0.87–0.88)
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Abbreviations: ER, estrogen receptor; HR, hazard ratio; NA, not applicable; NCI, National Cancer Institute; PR, progesterone receptor; SES, socioeconomic status.

a

Mortality analyses excluded women diagnosed after 2010 because of incomplete mortality data for 2011. Model covariates included age, race/ethnicity, tumor size, grade, and ER/PR status, nodal status, histology, receipt of adjuvant treatments including chemotherapy and radiation, neighborhood SES quintile, marital status, insurance status, SES composition of patients at the reporting hospital, care at an NCI-designated cancer center, and year of diagnosis. Models were stratified by American Joint Committee on Cancer stage.

b

Distribution based on statewide quintiles.

c

P value for trend of SES was <.001.

Table 5.

Multiple Regression Hazard Ratios for Associations of Patient and Clinical Characteristics With Breast Cancer–Specific Mortality, Stages 0–III Breast Cancer, 1998–2010, Californiaa

Variable Deceased Patients Total Patients HR (95% CI)
Surgical procedure
 Bilateral mastectomy 392 9907 1.09 (0.98–1.21)
 Breast-conserving surgery with radiation 3620 96 462 1 [Reference]
 Unilateral mastectomy 6115 68 548 1.29 (1.23–1.35)
Race/ethnicity
 Chinese 210 4787 0.85 (0.74–0.97)
 Filipina 315 6150 0.83 (0.74–0.94)
 Hispanic 1703 26 035 0.90 (0.85–0.95)
 Japanese 80 2263 0.70 (0.56–0.88)
 Non-Hispanic American Indian/other/unknown 73 1378 1.06 (0.84–1.34)
 Non-Hispanic black 896 9112 1.22 (1.14–1.32)
 Non-Hispanic white 6529 117 853 1 [Reference]
 Other Asian/Pacific Islander 321 7339 0.81 (0.72–0.90)
Age at diagnosis, y
 <40 1027 9341 1.32 (1.22–1.41)
 40–49 1995 34 878 0.97 (0.92–1.03)
 50–64 3311 68 104 1 [Reference]
 ≥65 3794 62 594 1.43 (1.35–1.51)
Tumor size
 Per centimeter NA NA 1.33 (1.30–1.36)
Lymph node involvement
 Negative 3905 126 165 1 [Reference]
 Positive 6222 48 752 1.96 (1.85–2.07)
Histology
 Ductal 8915 149 278 1 [Reference]
 Lobular or with lobular component 684 12 403 0.98 (0.90–1.07)
 Other 528 13 236 0.78 (0.71–0.85)
Grade
 I 634 36 593 1 [Reference]
 II 3071 70 377 1.87 (1.71–2.04)
 III 5953 58 247 3.12 (2.86–3.41)
 Unknown 469 9700 1.82 (1.60–2.06)
ER/PR status
 Negative 3295 26 685 1.80 (1.71–1.88)
 Positive 5622 125 955 1 [Reference]
 Unknown or borderline 1210 22 277 1.12 (1.05–1.20)
Adjuvant treatment, chemotherapy, and/or radiation
 No 3742 109 699 1 [Reference]
 Yes 6385 65 218 1.10 (1.05–1.16)
Neighborhood SES quintileb,c
 1 (lowest) 1506 18 484 1 [Reference]
 2 2007 28 329 0.99 (0.93–1.06)
 3 2181 35 740 0.93 (0.87–1.00)
 4 2257 42 120 0.89 (0.83–0.96)
 5 2176 50 244 0.80 (0.74–0.86)
Marital status
 Married 5559 104 647 1 [Reference]
 Not married 4393 67 098 1.13 (1.08–1.18)
 Unknown 175 3172 1.08 (0.93–1.26)
Insurance status
 Medicare 1362 22 445 1.23 (1.15–1.31)
 Military 84 1487 1.07 (0.86–1.33)
 Not insured or self-pay 120 1408 1.09 (0.91–1.31)
 Private 5831 113 347 1 [Reference]
 Public or Medicaid 2368 29 746 1.30 (1.23–1.37)
 Unknown 362 6484 0.80 (0.72–0.89)
Patient SES distribution of reporting hospitalb
 >50% of patients in quintiles 4–5 4316 89 573 1 [Reference]
 >50% of patients in quintiles 1–2 2456 31 015 1.12 (1.05–1.18)
 Mixed distribution 3355 54 329 1.07 (1.02–1.12)
Received care at an NCI-designated cancer center
 No 9731 166 025 1 [Reference]
 Yes 396 8892 0.87 (0.78–0.96)
Year of cancer diagnosis
 Per year Not applicable Not applicable 0.87 (0.87–0.88)
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Abbreviations: HR, hazard ratio; NA, not applicable; NCI, National Cancer Institute; SES, socioeconomic status.

a

Mortality analyses excluded women diagnosed after 2010 because of incomplete mortality data for 2011. Model covariates included age, race/ethnicity, tumor size, grade, and ER/PR status, nodal status, histology, receipt of adjuvant treatments including chemotherapy and radiation, neighborhood SES quintile, marital status, insurance status, SES composition of patients at the reporting hospital, care at an NCI-designated cancer center, and year of diagnosis. Models were stratified by American Joint Committee on Cancer stage.

b

Distribution based on statewide quintiles.

c

P value for trend of SES was <.001.

Propensity Analysis of Marginal Mortality After Surgery

Figure 2A shows estimated mortality among all patients if surgical procedure were randomly assigned (analysis of average treatment effect). The estimated 10-year mortality rates were 18.8% (95% CI, 18.6%–19.0%) for bilateral mastectomy, 16.8% (95% CI, 16.6%–17.1%) for breast-conserving surgery with radiation, and 20.1% (95%CI, 19.9%–20.4%) for unilateral mastectomy. Figure 2B–D shows estimated mortality from another surgical procedure among patients who had a specific surgical procedure (analysis of average treatment effect for those treated). For patients receiving breast-conserving surgery with radiation, bilateral mastectomy would have resulted in marginally higher mortality, on average, and unilateral mastectomy in higher mortality. For patients receiving unilateral mastectomy, bilateral mastectomy would have resulted in unchanged mortality and breast-conserving surgery with radiation in lower mortality. For patients receiving bilateral mastectomy, breast-conserving surgery with radiation would have resulted in unchanged mortality and unilateral mastectomy in higher mortality. Proportional hazards regression models showed similar results (Table 6).

Figure 2.

Figure 2

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Propensity-Weighted Kaplan-Meier Plots of Estimated Mortality Among All Patients if Surgical Procedure Had Been Randomly Assigned and of Estimated Mortality if a Different Surgical Procedure Had Been Performed Among Patients Who Had Undergone a Specific Surgical Procedure

A, Estimated mortality among all patients if surgical procedure were randomly assigned (analysis of average treatment effect). B–D, Estimated mortality from another surgical procedure among patients who had a specific surgical procedure (analysis of average treatment effect for those treated). B, For patients receiving breast-conserving surgery with radiation, bilateral mastectomy would have resulted in marginally higher mortality, on average, and unilateral mastectomy in higher mortality. C, For patients receiving unilateral mastectomy, bilateral mastectomy would have resulted in unchanged mortality and breast-conserving surgery with radiation in lower mortality. D, For patients receiving bilateral mastectomy, breast-conserving surgery with radiation would have resulted in unchanged mortality and unilateral mastectomy in higher mortality.

Table 6.

Propensity Score Analysis of Overall Mortality, Showing Average Effect of an Alternative Surgical Procedure on Patients Treated With a Specific Surgical Procedure (Average Treatment Effect of Those Treated)

Surgical Treatment and Alternatives Hazard Ratio for Mortality (95% CI)
Bilateral mastectomy
 vs unilateral mastectomy 1.23 (1.13–1.33)
 vs breast-conserving surgery with radiation 0.94 (0.86–1.02)
Breast-conserving surgery with radiation
 vs bilateral mastectomy 1.13 (1.00–1.28)
 vs unilateral mastectomy 1.27 (1.23–1.31)
Unilateral mastectomy
 vs bilateral mastectomy 0.93 (0.83–1.04)
 vs breast-conserving surgery with radiation 0.81 (0.78–0.84)
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Discussion

This observational study comprising 189 734 women with unilateral early-stage breast cancer compared 3 surgical treatments and found a substantial increase in the rate of bilateral mastectomy throughout California from 1998 through 2011. To our knowledge, this is the first side-by-side comparison of all 3 common surgical treatments for early-stage breast cancer. Previous SEER studies have compared 2 treatments at a time: some reported a survival advantage with bilateral vs unilateral mastectomy21,22 and others reported improved survival after breast-conserving surgery with radiation compared with unilateral mastectomy.23,24 By comparing all 3 surgical options for a patient with early-stage breast cancer, we found no mortality benefit associated with bilateral mastectomy compared with breast-conserving surgery, and higher mortality associated uniquely with unilateral mastectomy.

For the surgical treatment of early-stage breast cancer, available randomized trial data are limited to those showing no survival difference between unilateral mastectomy and breast-conserving surgery.1,2 There is no randomized trial evidence to inform whether bilateral mastectomy improves survival, and it is unlikely that such a trial will ever be performed. Thus, conclusions about surgical treatments must rely on observational studies that compare the effectiveness of different procedures in practice21,22,25,26; however, a recent meta-analysis judged the existing data inadequate to enable conclusions about the effect of bilateral mastectomy on survival.27 Patient selection attributable to unmeasured factors probably explains much of the higher mortality that we observed with unilateral mastectomy relative to the other 2 surgical procedures. In prior SEER-based studies, both we24 and Agarwal et al23 reported worse survival associated with unilateral mastectomy vs breast-conserving surgery with radiation, results that persisted after propensity analysis. We agree with previous suggestions that patients with tumor features suggesting poor prognosis, such as lymphovascular invasion or extranodal extension, which SEER does not record and for which we cannot control, are more likely to undergo unilateral mastectomy than breast conservation and also to experience worse survival.23,24 The current study offers another potential explanation, namely confounding related to sociodemographic differences between women who underwent bilateral mastectomy and women who underwent unilateral mastectomy.

Women who underwent bilateral mastectomy were more likely to be non-Hispanic white and privately insured, to live in high SES neighborhoods, and to be treated in NCI-designated cancer centers. By contrast, women who underwent unilateral mastectomy were more likely to be Asian, Hispanic, or non-Hispanic American Indian/other/unknown; to have public/Medicaid insurance, and to be treated in hospitals serving patients of lower SES; they were less likely to live in high SES neighborhoods or to be treated in NCI-designated cancer centers. Cancer registry data lack details about comorbidities and specific regimens of endocrine, radiation, and chemotherapy. However, prior studies enriched for clinical data, including our own within the Kaiser Permanente Northern California health care system, reported treatment-limiting comorbidities (for example, diabetes and myocardial infarction) and reduced treatment intensity among the same racial/ethnicminority, low SES patients who most frequently under went unilateral mastectomy in our current study.28–30 In addition to signifying unmeasured poor prognostic factors,21,22 unilateral mastectomy might correlate with subtle disparities in effective access (for example, diabetic neuropathy that limits chemotherapy dosing; lack of transportation to the postsurgical radiation treatments required for breast conservation) that we could not identify using registry data and that may mediate higher mortality. By contrast, patterns of bilateral mastectomy use suggest that affluent non-Hispanic white women, women of high SES, or both seek more aggressive preventive care, consistent with reported associations between greater use of expensive diagnostic tests (such as breast MRI and genetic testing) and bilateral mastectomy within this patient subgroup.4,31

The increase in bilateral mastectomy use despite the absence of supporting evidence has puzzled clinicians and health policy makers. Proposed explanations include the increasing use of highly sensitive breast magnetic resonance imaging, with increases in anxiety-producing recall and biopsy rates that may drive patients to undergo preventive surgery,6,31,32 and the dissemination of genetic testing, which facilitates identification of high-risk patients who benefit from bilateral mastectomy.7,8,33 Although fear of cancer recurrence may prompt the decision for bilateral mastectomy, such fear usually exceeds the estimated risk.34,35 Other studies found recurrence fears less influential than aesthetic considerations, notably those that arise with new reconstruction approaches that achieve cosmetic symmetry through bilateral tissue flap placement.6,36 Because cosmesis may be inferior if both breasts are not reconstructed simultaneously, these new approaches encourage use of immediate bilateral mastectomy. We found that bilateral mastectomy use over time increased most among patients younger than 40 years at diagnosis, which may be attributable to their relatively high probability of carrying genetic mutations (an evidence-based indication for bilateral mastectomy)37 or to the greater likelihood that they have young children and may therefore seek maximal intervention in hope of extending their lives (an emotional rather than evidence-based decision).34,35,38 Although some studies reported patient satisfaction after bilateral mastectomy,39 others observed deleterious effects on body image, sexual function, and quality of life12; moreover, repeat operations and complications (including flap failure, necrosis, and infection) are substantially more common with bilateral mastectomy than with other surgical procedures.10,11

In a time of increasing concern about overtreatment,40 the risk-benefit ratio of bilateral mastectomy warrants careful consideration and raises the larger question of how physicians and society should respond to a patient’s preference for a morbid, costly intervention of dubious effectiveness.

Our study used a population-based statewide data set, multiple regression analysis, and propensity scores. However, given its observational design, it cannot prove causation and may be subject to selection bias and uncontrolled confounding. As discussed above, unmeasured patient selection factors related to cancer prognosis and access to care may explain the higher mortality observed with unilateral mastectomy. Other limitations include the lack of SEER data on diagnostic testing (eg, magnetic resonance imaging, genetic testing for BRCA1/2 and other inherited mutations, tumor analysis for ERBB2 amplification, and broader genomic profiling), details of systemic treatments, family cancer history, and comorbidities. Additional information gaps include patient preferences and physician recommendations, which influence surgical decisions.38 Future research with more comprehensive data sets that integrate detailed clinical, treatment, and patient-reported information will be essential to advance understanding of breast surgery use and to enhance the quality of cancer care.

Conclusions

Among all women diagnosed with early-stage breast cancer in California, the percentage undergoing bilateral mastectomy increased substantially between 1998 and 2011, despite a lack of evidence supporting this approach. Bilateral mastectomy was not associated with lower mortality than breast-conserving surgery plus radiation, but unilateral mastectomy was associated with higher mortality than the other options. These results may inform decision-making about the surgical treatment of breast cancer.

Supplementary Material

Suppl Data

Acknowledgments

Funding/Support: This study was supported by the Jan Weimer Junior Faculty Chair in Breast Oncology, the Suzanne Pride Bryan Fund for Breast Cancer Research at Stanford Cancer Institute, and the NCI SEER program under contract HHSN261201000140C awarded to the Cancer Prevention Institute of California (CPIC). The collection of cancer incidence data was supported by the California Department of Health Services as part of the statewide cancer reporting program mandated by California Health and Safety Code Section 103885; the NCI SEER program under contracts HHSN261201000140C awarded to CPIC, HHSN261201000035C to the University of Southern California, and HHSN261201000034C to the Public Health Institute; and the CDC National Program of Cancer Registries, under agreement 1U58 DP000807-01 awarded to the Public Health Institute.

Footnotes

Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Dr Clarke and Dr Gomez reported receiving grants from Genentech outside the submitted work. No other authors reported disclosures.

Role of the Funders/Sponsors: None of the funders/sponsors had any role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication.

Disclaimer: The ideas and opinions expressed herein are those of the authors, and endorsement by the University or State of California, the California Department of Health Services, the NCI, or the CDC or their contractors and subcontractors is not intended and should not be inferred.

Author Contributions: Drs Kurian and Gomez had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Kurian, Clarke, Gomez.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Kurian, Nelson, Clarke, Gomez.

Critical revision of the manuscript for important intellectual content: Kurian, Lichtensztajn, Keegan, Nelson, Clarke, Gomez.

Statistical analysis: Lichtensztajn, Nelson.

Obtained funding: Kurian, Gomez.

Administrative, technical, or material support: Clarke, Gomez.

Study supervision: Kurian, Clarke, Gomez.

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