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. 2018 Aug 16;5(1):51–57. doi: 10.1001/jamaoncol.2018.2956

Table 1. Clinical Charateristics of Patients With Breast Cancer (BC) or Ovarian Cancer (OV) and In-Laboratory Controlsa.

Charateristic Patients, No. (%)
With BC (n = 9639) With OV (n = 2051) Controls (n = 3988)
Race/ethnicity
White 7208 (74.8) 1718 (83.8) 2765 (69.3)
African American 985 (10.2) 80 (3.9) 323 (8.1)
Hispanic 874 (9.1) 161 (7.8) 561 (14.1)
Asian 572 (5.9) 92 (4.5) 339 (8.5)
Age at diagnosis, y
Mean (SD) 48.7 (11.5) 55.7 (14.1) 39.7 (14.7)b
≤45 3960 (41.1) 445 (21.7) 2671 (67.0)
46-60 3876 (40.2) 768 (37.4) 951 (23.8)
>60 1518 (15.7) 751 (36.6) 332 (8.3)
Not providedc 285 (3.0) 87 (4.2) 34 (0.9)
Sex
Male 123 (1.3) 0 1315 (33.0)
Female 9516 (98.7) 2051 (100.0) 2673 (67.0)
BC histology
IDC 6829 (70.8) NA NA
ILC 493 (5.1) NA NA
IDC and ILC 141 (1.5) NA NA
Not providedc 2176 (22.6) NA NA
Bilateral BC
Yes 1321 (13.7) NA NA
Not providedc 8318 (86.3) NA NA
BC subtypes (receptor status)
ER+, PR+, and HER2 (HR+) 2476 (25.7) NA NA
ER, PR, and HER2+ (HR) 278 (2.9) NA NA
ER+, PR+, and HER2+ (TPBC) 539 (5.6) NA NA
ER, PR, and HER2 (TNBC) 1154 (12.0) NA NA
Additional cancer primary
Colorectal cancer 166 (1.7) 35 (1.7) NA
Uterine cancer 378 (3.9) 145 (7.1) NA
Others 97 (1.0) 28 (1.4) NA
None 8998 (93.3) 1843 (89.8) NA
1st- or 2nd-Degree relative with any cancer
Yes 8152 (84.6) 1670 (81.4) NA
No 282 (2.9) 72 (3.5) NA
Not providedc 1205 (12.5) 309 (15.1) NA
1st- or 2nd-Degree relative with BC
Yes 5404 (56.1) 787 (38.4) NA
No 3030 (31.4) 955 (46.6) NA
Not providedc 1205 (12.5) 309 (15.1) NA
1st- or 2nd-Degree relative with OV
Yes 981 (10.2) 245 (11.9) NA
No 7453 (77.3) 1497 (73.0) NA
Not providedc 1205 (12.5) 309 (15.1) NA

Abbreviations: ER, estrogen receptor; HER2, human epidermal growth factor receptor 2; HR, hormone receptor; IDC, invasive ductal carcinoma; ILC, invasive lobular carcinoma; PR, progesterone receptor; NA, not applicable; TNBC, triple-negative BC; TPBC, triple-positive BC; +, positive for the receptor; −, negative for the receptor.

a

Inferred ethnicity using principal component analysis to identify population substructure based on exome-sequencing data.

b

Age at testing for controls.

c

Incomplete or unavailable clinical information.