Sage Journals: Discover world-class research

Abstract

Introduction

Surgery is an essential component of breast cancer treatment. Surgical complications may impact receipt of adjuvant therapy and long-term outcomes. Differences in insurance coverage and access to care by patient age in the general U.S. population may affect breast cancer diagnosis and surgery and thus age comparisons in research. We compared postoperative outcomes following breast cancer surgery between age groups in the U.S. Military Health System, which provides beneficiaries access to comprehensive care across the lifespan.

Methods

We identified women aged ≥18 years with stage I–III breast cancer diagnosed from 2001 to 2014 undergoing surgery without reconstruction in the MilCanEpi database. Multivariable Poisson regression estimated the adjusted risk ratios (ARRs) with 95% confidence intervals (CIs) in association with age at diagnosis (18-39, 40-49, 50-64, and ≥65) for 30-day general and breast complications (surgical site infection, seroma, hematoma, or lymphedema), reoperation, and hospital readmission while controlling for potential confounders.

Results

The study included 7835 women who were 18-39 (9.2%), 40-49 (23.6%), 50-64 (42.7%), and ≥65 (24.5%). The overall risk of general or breast complications did not differ significantly by age when controlled for demographic, tumor, and treatment variables. However, women aged 40-49 had a statistically increased adjusted risk of seroma (ARR = 1.50; 95% CI = 1.03-2.18) compared to women aged 50-64. No significant age-related differences were observed for reoperation or hospital readmission after adjustment.

Conclusion

In the Military Health System, the overall risk of 30-day postoperative complications and hospital readmissions were not statistically different by age after adjustment for clinical and demographic factors. The findings support that surgical decision-making continue to prioritize tumor characteristics, comorbidity burden, and other clinical factors rather than age alone when assessing perioperative risk.

Keywords

breast cancer mastectomy breast-conserving surgery complications age

Introduction

Breast cancer is the most commonly diagnosed cancer among women in the general U.S. population and within the Military Health System (MHS).^1-3 Age at diagnosis is a known factor influencing breast cancer presentation, treatment, and outcomes.^4-7 Younger premenopausal women are more likely to present with aggressive tumor subtypes, such as triple-negative or HER2-positive disease, and often receive more intensive treatment, including neoadjuvant chemotherapy and bilateral mastectomy.^4,8-10 In contrast, older postmenopausal women are more likely to present with estrogen-receptor positive disease, have less aggressive subtypes, and may have lower rates of surgery and adjuvant therapy due to concerns about comorbidity, frailty, or competing mortality risks.^11-14 These patterns contribute to age-related disparities in breast cancer outcomes, including lower breast cancer-specific survival among women aged ≥75 years, even when controlling for tumor subtype and stage.^10,15-17

Surgical treatment—either breast-conserving therapy (BCT) or mastectomy—remains a cornerstone of curative-intent management for patients of all ages with nonmetastatic disease.¹⁸ However, short-term postoperative complications can delay adjuvant therapies, prolong recovery, and adversely affect both quality of life and long-term outcomes.^19-21 Little is known about how age affects short-term surgical outcomes, particularly postoperative complications. Prior studies have reported conflicting findings, with some showing no significant differences by age, while others have observed elevated medical complication risks in older patients, especially following mastectomy.^22-25 Younger patients may also be at increased risk of postoperative morbidity and reoperation due to more extensive surgical procedures or additional interventions.^5,20

In the general U.S. population, access to cancer screening, diagnosis, and treatment services may vary between age groups based on insurance coverage and financial barriers.^26-29 Research in a universal care system can minimize many of the socioeconomic barriers that complicate care and research in the general U.S. population and help inform clinical decision-making and age-appropriate perioperative care.^30-32 The MHS serves 9.6 million Department of War (DoW) beneficiaries, including active-duty uniformed service members, retired military service members, activated National Guard, other DoW employees, and their family members.³² Insurance coverage and access to care is provided to beneficiaries of all ages with low to no out-of-pocket costs.³¹ Therefore, the MHS provides a unique setting to examine these associations due to its universal insurance coverage and relatively standardized access to care. This study aimed to examine the association between age at diagnosis and 30-day postoperative outcomes including general and breast-specific complications and hospital readmissions among women undergoing surgery without immediate reconstruction for stage I–III breast cancer in the MHS.

Materials and Methods

Data Sources

This study used the MilCanEpi database which contains information on patients diagnosed or treated for cancer in the MHS from the DoW cancer registry linked to administrative data and medical encounters in the MHS data repository employing similar methods as Eaglehouse et al.^33,34 The study was reviewed and informed consent was waived by the Uniformed Services University of the Health Sciences Institutional Review Board, Bethesda, Maryland (FWA 00001628) on 19 July 2019 (Reference #914142) and renewed on 4 March 2025 (Reference #981045). The study was conducted in accordance with the Helsinki Declaration of 1975, as revised in 2024. The Reporting of studies Conducted using Observational Routinely-collected health Data (RECORD) checklist was used in the creation of this report.³⁵

Study Population

The study included women aged ≥18 who were diagnosed with a single primary invasive breast cancer (ICD-O-3 primary site code C500-506, C508, C509 and ICD-9-CM diagnosis codes 174.x) between January 1, 2001 and December 31, 2014 and received surgery as primary treatment. The included data years corresponded with the nationwide expansion of the ACS-NSQIP and the most recent linked data available at the time of analyses.^33,36 Women were eligible if they were diagnosed with American Joint Commission on Cancer (AJCC) stages I-III breast cancer and had surgical records in the medical encounter data in MilCanEpi. Patients with stage IV tumors excluded because surgery is not typically delivered as curative treatment. Using methods similar to Eaglehouse et al.,³⁴ breast cancer surgery was defined as any excisional procedure (see Appendix Table A1) within 6 months of the cancer diagnosis. Patients with reconstruction procedures at the time of diagnosis or during follow-up for outcomes were excluded to limit possible effects of reconstruction (eg, approach, timing with surgery) on the measured outcomes.^37,38 To reduce unmeasured confounding, patients with surgery recorded only in the cancer registry portion of MilCanEpi were excluded due to incomplete information on study variables.

Study Variables

Patient information included age at diagnosis, race as documented in the data (Asian or Pacific Islander, Black, Native American or Alaska Native, White, multiple races, other race, or unknown), ethnicity (Hispanic, Latinx, or Spanish origin), marital status (married, single, separated, widowed, or divorced), active-duty status at diagnosis (yes or no), sponsor service branch (Air Force, Army, Navy or Marine Corps, or other DoW), U.S. geographic region (Northeast, South, West, or Overseas), and Elixhauser comorbidities modified for those with cancer (0, 1-2, 3-4, or 5 or more).^39,40 Comorbidities in the Elixhauser index were captured if there was at least 1 inpatient or 3 outpatient records with a diagnosis code prior to the cancer diagnosis date. Information on recent history of myocardial infarction (MI) within 6 months prior to surgery and chronic heart failure (CHF) within 30 days prior to surgery, as defined in the NSQIP, were also captured.^36,41 Patients with recent history of MI or CHF were subsequently excluded due to possible association with the study outcomes.

Cancer information included diagnosis date, AJCC tumor stage (I, II, or III), AJCC tumor grade (G1-4, or Gx), tumor histology (ductal carcinoma, lobular carcinoma, other), tumor laterality (right or left), tumor location (quadrant, nipple or center, overlapping, other), estrogen (ER) and progesterone receptor (PR) status, HER2 status (available 2010-2014), and regional lymph node involvement. Information on cancer surgery included its date, type (partial or breast-conserving mastectomy; or total or radical mastectomy), surgery admission type (inpatient or outpatient), length of stay (LOS) for inpatient surgery admissions, care setting (military or civilian), and final surgical margin (positive or negative). The cancer diagnosis and surgery dates were used to determine time-to-surgery in days.⁴² Date(s) of other treatment(s) were extracted from the data to determine whether each patient received neoadjuvant chemotherapy or radiation therapy.

Outcomes

The primary study outcomes included 30-day complications, reoperations, and hospital readmissions.³⁴ General complications included stroke, myocardial infarction (MI), hemorrhage, blood transfusion, pneumonia, deep vein thrombosis (DVT), pulmonary embolism (PE), other thrombosis, systemic inflammatory response syndrome (SIRS), severe sepsis, septic shock, urinary tract infection (UTI), and death.^{19,36,38,43-45} Breast complications included surgical site infection (SSI), lymphedema, seroma, and hematoma.^19,44,46-51 Medical encounter records with a relevant ICD-9 diagnosis code occurring within 30 days of surgery were used to indicate complications (see Appendix Table A2).^{19,48,49,52-58} Reoperation included procedures for partial or total mastectomy occurring between 7 and 30 days after the initial surgery.⁵⁹ Hospital readmission included inpatient encounters with any diagnosis other than breast reoperation occurring within 30 days of the initial cancer surgery.^41,60

Statistical Analysis

First, we examined patients’ characteristics by age at diagnosis, grouped as 18-39, 40-49, 50-64, and ≥65 years using Chi-square tests. The age groups were selected to include women classified as adolescent and young adults (aged 18-39); premenopausal women (aged 40-49), postmenopausal women (aged 50-64), and older women with Medicare eligibility (aged ≥65). We compared the median (interquartile range; IQR) time-to-surgery and median (IQR) LOS for inpatient surgery admission across age groups using non-parametric tests. Then, we reported the frequency of complications, reoperation, and readmissions among age groups and used modified Poisson regression with log link and robust standard errors to estimate rate ratios (RRs) with 95% confidence intervals (CIs) of 30-day outcomes in association with age at diagnosis. Poisson regression was selected because it allows for robust risk estimates for rare (<10%) and non-rare (>10%) events in dynamic cohorts while controlling for potential confounders.^61-63 Adjusted rate ratios (ARRs) with 95% CIs were estimated from multivariable models including patient demographic, tumor, and treatment characteristics. Analyses were conducted in SAS 9.4 (SAS Inc., Cary, NC).

Results

The study included 7835 women with a breast cancer diagnosis who received surgery (Figure 1). The average age of women at diagnosis was 56.2 (±12.8) years with 9.2% of women aged 18-39, 23.6% aged 40-49, 42.7% aged 50-64, and 24.5% aged ≥65. A higher proportion of younger women (age 18-39 or 40-49) were non-Hispanic Black race-ethnicity, married, or lived outside the continental United States at time of breast cancer diagnosis relative to women aged 50 or older (Table 1). There was an increasing level of comorbidity with increasing age categories, with women aged ≥65 at diagnosis having the highest frequency of 3-4 comorbidities (23.2%) or ≥5 comorbidities (22.3%) compared to the other age groups. Regarding cancer diagnosis, younger women tended to be diagnosed during earlier years of the data, had a higher frequency of stage II or stage III tumors at diagnosis, had a higher percentage of ductal carcinoma and lower frequency of lobular carcinoma, had higher grade (AJCC G3 or G4), and had a higher frequency of estrogen and progesterone receptor negative tumors relative to older women (Table 2).

Figure 1.

Selection of patients with stage I-III breast cancer who received surgery without immediate reconstruction as primary treatment in the U.S. Military Health System, 2001-2014

Table 1.

Characteristics of Patients Receiving Primary Surgical Treatment Without Immediate Reconstruction for Stage I-III Invasive Breast Cancer in the U.S. Military Health System, 2001-2014, by Age at Diagnosis

Age at diagnosis	18-39 (n = 722)	40-49 (n = 1847)	50-64 (n = 3343)	≥65 (n = 1923)	P
Characteristic	N (%)	N (%)	N (%)	N (%)	P
Race-ethnicity					<.001
Non-Hispanic White	372 (51.5)	1079 (58.4)	2077 (62.1)	1370 (71.2)
Non-Hispanic Black	173 (24.0)	385 (20.8)	480 (14.4)	208 (10.8)
Asian or Pacific Islander	76 (10.5)	192 (10.4)	430 (12.9)	188 (9.8)
Non-Hispanic other race	19 (2.6)	41 (2.2)	76 (2.3)	35 (1.8)
Hispanic or Latina	69 (9.6)	122 (6.6)	213 (6.4)	93 (4.8)
Unknown	13 (1.8)	28 (1.5)	67 (2.0)	29 (1.5)
Marital status					<.001
Married	620 (85.9)	1637 (88.6)	2799 (83.7)	1220 (63.4)
Single	50 (6.9)	66 (3.6)	81 (2.4)	21 (1.1)
Sep., divorc., widow	41 (5.7)	120 (6.5)	422 (12.6)	664 (34.5)
Unknown	11 (1.5)	24 (1.3)	41 (1.2)	18 (0.9)
Active duty at diagnosis					<.001
No	562 (77.8)	1669 (90.4)	3288 (98.4)	---^a
Yes	160 (22.2)	178 (9.6)	55 (1.7)	---
Sponsor service branch					<.001
Army	267 (37.0)	594 (32.2)	1125 (33.7)	666 (34.6)
Navy/Marine corps	167 (23.1)	470 (25.5)	834 (25.0)	439 (22.8)
Air Force	186 (25.8)	513 (27.8)	949 (28.4)	632 (32.9)
Other DoW/unknown	102 (14.1)	270 (14.6)	435 (13.0)	186 (9.7)
Region at diagnosis					<.001
Northeast U.S.	183 (25.4)	533 (28.9)	841 (25.2)	514 (26.7)
Southern U.S.	226 (31.3)	636 (34.4)	1254 (37.5)	653 (34.0)
Western U.S.	250 (34.6)	583 (31.6)	1188 (35.5)	719 (37.4)
Outside continental U.S.	63 (8.7)	95 (5.1)	60 (1.8)	37 (1.9)
Elixhauser comorbidity count					<.001
0	426 (59.0)	856 (46.4)	930 (27.8)	226 (11.8)
1	158 (21.9)	441 (23.9)	814 (24.4)	430 (22.4)
2	76 (10.5)	267 (14.5)	599 (17.9)	391 (20.3)
3-4	49 (6.8)	214 (11.6)	657 (19.7)	447 (23.2)
5 or more	13 (1.8)	69 (3.7)	343 (10.3)	429 (22.3)

^aActive-duty status not shown for women ≥65 due to small sample (n < 11) with “yes” value.

Table 2.

Breast Cancer Diagnosis and Treatment Information for Patients Receiving Primary Surgical Treatment Without Immediate Reconstruction for Stage I-III Invasive Breast Cancer in the U.S. Military Health System, 2001-2014, by Age at Diagnosis

Age at diagnosis (years)	18-39 (n = 722)	40-49 (n = 1847)	50-64 (n = 3343)	≥65 (n = 1923)	P
Characteristic	N (%)	N (%)	N (%)	N (%)	P
Cancer diagnosis year					.012
2001-2004	272 (37.7)	613 (33.2)	1062 (31.8)	639 (33.2)
2005-2009	271 (37.5)	723 (39.1)	1265 (37.8)	705 (36.7)
2010-2014	179 (24.8)	511 (27.7)	1016 (30.4)	579 (30.1)
Tumor stage					<.001
I	246 (34.1)	829 (44.9)	1860 (55.6)	1197 (62.3)
II	330 (45.7)	756 (40.9)	1172 (35.1)	573 (29.8)
III	146 (20.2)	262 (14.2)	311 (9.3)	153 (8.0)
Tumor histology					<.001
Ductal carcinoma	598 (82.8)	1503 (81.4)	2602 (77.8)	1420 (73.8)
Lobular carcinoma	20 (2.8)	105 (5.7)	273 (8.2)	191 (9.9)
Ductal + lobular carcinoma	41 (5.7)	109 (5.9)	234 (7.0)	156 (8.1)
Other carcinoma	39 (5.4)	101 (5.5)	162 (4.9)	102 (5.3)
Other (non-carcinoma)	24 (3.3)	29 (1.6)	72 (2.2)	54 (2.8)
Tumor grade					<.001
1	68 (9.4)	370 (20.0)	802 (24.0)	558 (29.0)
2	217 (30.1)	669 (36.2)	1267 (37.9)	775 (40.3)
3 or 4	372 (51.5)	662 (35.8)	954 (28.5)	409 (21.3)
Unknown	65 (9.0)	146 (7.9)	320 (9.6)	181 (9.4)
Tumor laterality					.78
Left	363 (50.3)	947 (51.3)	1721 (51.5)	964 (50.1)
Right	359 (49.7)	900 (48.7)	1622 (48.5)	959 (49.9)
Tumor location (quadrant)					.003
Upper outer	272 (37.7)	708 (38.3)	1238 (37.0)	673 (35.0)
Upper inner	81 (11.2)	206 (11.2)	385 (11.5)	226 (11.8)
Lower outer	59 (8.2)	136 (7.4)	249 (7.5)	135 (7.0)
Lower inner	31 (4.3)	122 (6.6)	225 (6.7)	134 (7.0)
Nipple/center	21 (2.9)	73 (4.0)	135 (4.0)	118 (6.1)
Overlapping	174 (24.1)	388 (21.0)	743 (22.2)	457 (23.8)
Axilla/NOS/unknown	84 (11.6)	214 (11.6)	368 (11.0)	180 (9.4)
Hormone receptor status					<.001
ER+/PR+	349 (48.3)	1138 (61.6)	2045 (61.2)	1262 (65.6)
ER+/PR-	66 (9.1)	139 (7.5)	369 (11.0)	232 (12.1)
ER-/PR+	18 (2.5)	38 (2.1)	25 (0.8)	22 (1.1)
ER-/PR-	219 (30.3)	405 (21.9)	626 (18.7)	247 (12.8)
Unknown	70 (9.7)	127 (6.9)	278 (8.3)	160 (8.3)
HER2 status ^a					<.001
Positive	55 (7.6)	113 (6.1)	204 (6.1)	88 (4.6)
Negative	118 (16.3)	375 (20.3)	751 (22.5)	452 (23.5)
Unknown	18 (2.5)	50 (2.7)	98 (2.9)	61 (3.2)
Unavailable^a	531 (73.6)	1309 (70.9)	2290 (68.5)	1322 (68.8)
Time between diagnosis and surgery (days)					<.001
Median (interquartile range)	24 (11-41)	26 (14-41)	28 (17-42)	30 (19-43)
Neoadjuvant treatment					<.001
No	198 (27.4)	534 (28.9)	1074 (32.1)	850 (44.2)
Yes	524 (72.6)	1313 (71.1)	2269 (67.9)	1073 (55.8)
Care setting of surgery					.010
Military (direct)	614 (85.0)	1556 (84.2)	2876 (86.0)	1691 (87.9)
Civilian (private sector)	108 (15.0)	291 (15.8)	467 (14.0)	232 (12.1)
Surgery admission duration					<.001
Inpatient (≥24 h stay)	121 (16.8)	237 (12.8)	434 (13.0)	320 (16.6)
Outpatient (<24 h stay)	601 (83.2)	1610 (87.2)	2909 (87.0)	1603 (83.4)
Surgery type					<.001
Partial mastectomy (ie, breast conserving, lumpectomy)	423 (58.6)	1254 (67.9)	2266 (67.8)	1167 (60.7)
Total or radical mastectomy	299 (41.4)	593 (32.1)	1077 (32.2)	756 (39.3)
Final surgical margin					<.001
Negative	586 (81.2)	1530 (82.8)	2890 (86.5)	1684 (87.6)
Positive	101 (14.0)	241 (13.1)	352 (10.5)	178 (9.3)
Unknown	35 (4.9)	76 (4.1)	101 (3.0)	61 (3.2)
Lymph node surgery at time of breast surgery ^b					<.001
None	358 (49.6)	813 (44.0)	1329 (39.8)	799 (41.6)
Sentinel lymph node biopsy (SLNB)	200 (27.8)	687 (37.2)	1418 (42.4)	771 (40.1)
Axillary lymphadenectomy (ALND)	164 (22.7)	347 (18.8)	596 (17.8)	353 (18.4)
Regional lymph node positive					<.001
No	343 (47.5)	1078 (58.4)	2225 (66.6)	1294 (67.3)
Yes	342 (47.4)	693 (37.5)	970 (29.0)	456 (23.7)
Unknown	37 (5.1)	76 (4.1)	148 (4.4)	173 (9.0)

Abbreviations: Estrogen Receptor (ER), Progesterone Receptor (PR).

^aHER2 status was not a required reporting item in the cancer registry prior to 2010 so it is unavailable for >95% of cancers diagnosed prior to 2010 in the data.

^bCode for most extensive lymph node surgery in the ±7 days of the primary surgery (partial or total mastectomy); ALND considered most extensive, followed by SLNB, and CFNA.

The median time between cancer diagnosis and surgery in the study cohort was 28 (IQR 16-42) days. The median time-to-surgery increased from 24 days among women aged 18-39 to 30 days among women aged ≥65 (Table 2; Kruskal-Wallis P < .001). For treatment, younger women were more likely to receive neoadjuvant chemotherapy prior to surgery and less likely to receive lymph node surgery at time of primary breast surgery relative to older women (Table 2). A higher percentage of women aged 40-49 or 50-64 receive partial mastectomy relative to the youngest (18-39) and oldest (≥65) age groups. Younger women had a higher frequency of positive surgical margin (ie, residual disease) and positive regional lymph nodes relative to the older age groups with increasing trends over the increasing age groups. For women with inpatient surgical admissions (n = 1112), the median LOS was 2 (1-2) days for women aged 18-39 and aged ≥65, and 1 (1-2) day for women aged 40-49 and 50-64, respectively (data not shown in table; Kruskal-Wallis P = .007).

Overall, 2.0% of the study patients had a general surgical complication and 6.7% had a breast complication. By age, the frequency of general complications differed significantly across age groups (Chi-square P < .05; Figure 2) and the frequency of breast complications was not statistically different (Chi-square P = .29; Figure 2). While older women (≥65) had higher unadjusted rates of general complications (RR = 1.77; 95% CI = 1.25-2.50) relative to women diagnosed at age 50-64, these differences were not statistically significant after multivariable adjustment for demographic, tumor, and treatment variables and time to surgery (Table 3). The overall risk of any breast complication did not differ significantly by age. However, women aged 40-49 had a statistically significant increased adjusted risk of seroma (ARR = 1.50; 95% CI = 1.03-2.18) compared to women aged 50-64 when complications were evaluated separately.

Figure 2.

Percentage of women with 30-day postoperative complications after receiving surgery for stage I-III breast cancer in the U.S. Military Health System, 2001-2014, by age at diagnosis. Notes. General complications include death, hemorrhage, blood transfusion, myocardial infarction, stroke, urinary tract infection, pneumonia, deep vein thrombosis, pulmonary embolism, other thrombosis, systemic inflammatory response syndrome, severe sepsis, or septic shock; Breast complications include surgical site infection, hematoma, seroma, lymphedema, or upper limb nerve injury; Reoperation is a second surgical procedure (lumpectomy or mastectomy) at least 7 days after the first surgery date and within 30 days of the index surgery; and hospital readmission is any inpatient encounter within 30 days after the initial surgery for any cause, excluding admission related to reoperation. There were n = 0 deaths and n = 0 blood transfusions occurring during the 30-day follow-up

Table 3.

Poisson Regression Estimated Adjusted Risk Ratios (ARRs) and 95% Confidence Intervals (CIs) for 30-Day Postoperative Outcomes in Association With Age at Diagnosis Among Women With Stage I-III Breast Cancer Receiving Surgical Treatment Without Immediate Reconstruction^a in the U.S. Military Health System, 2001-2014

Age at diagnosis	Age 18-39			Age 40-49			Age 50-64		Age ≥65
Outcome	N (%)	RR (95%CI)	ARR^b,c (95% CI)	N (%)	RR (95%CI)	ARR^b,c (95% CI)	N (%)	RR/ARR (95% CI)	N (%)	RR (95%CI)	ARR^b,c (95% CI)
General complication^d	12 (1.7)	0.91 (0.49, 1.68)	0.83 (0.43, 1.60)	21 (1.1)	0.62 (0.38, 1.02)	0.63 (0.38, 1.05)	61 (1.8)	1.00 (reference)	62 (3.2)	1.77 (1.25, 2.50)	1.19 (0.76, 1.86)
Breast complication^e	50 (6.9)	1.15 (0.85, 1.54)	1.13 (0.82, 1.55)	128 (6.9)	1.15 (0.93, 1.42)	1.19 (0.95, 1.48)	202 (6.0)	1.00 (reference)	141 (7.3)	1.21 (0.99, 1.49)	1.01 (0.78, 1.30)
Surgical site infection (SSI)	10 (1.4)	0.58 (0.30, 1.11)	0.54 (0.28, 1.07)	44 (2.4)	1.00 (0.69, 1.43)	1.02 (0.70, 1.48)	80 (2.4)	1.00 (reference)	60 (3.1)	1.31 (0.94, 1.81)	1.11 (0.73, 1.70)
Hematoma	13 (1.8)	1.40 (0.76, 2.59)	1.33 (0.71, 2.49)	20 (1.1)	0.84 (0.50, 1.43)	0.85 (0.50, 1.45)	43 (1.3)	1.00 (reference)	35 (1.8)	1.42 (0.91, 2.20)	1.00 (0.57, 1.74)
Seroma	18 (2.5)	1.32 (0.79, 2.22)	1.28 (0.73, 2.24)	51 (2.8)	1.47 (1.02, 2.11)	1.50 (1.03, 2.18)	63 (1.9)	1.00 (reference)	47 (2.4)	1.30 (0.89, 1.88)	1.29 (0.83, 2.00)
Lymphedema	15 (2.1)	1.83 (1.02, 3.30)	1.68 (0.94, 3.01)	22 (1.2)	1.05 (0.62, 1.77)	1.01 (0.60, 1.70)	38 (1.1)	1.00 (reference)	15 (0.8)	0.69 (0.38, 1.24)	0.70 (0.41, 1.20)
Reoperation^f	124 (17.2)	1.04 (0.87, 1.24)	0.98 (0.82, 1.16)	344 (18.6)	1.13 (1.00, 1.27)	1.02 (0.90, 1.15)	553 (16.5)	1.00 (reference)	259 (13.5)	0.81 (0.71, 0.93)	0.96 (0.82, 1.12)
Hospital readmission^g	50 (6.9)	1.23 (0.91, 1.66)	1.13 (0.82, 1.55)	104 (5.6)	1.00 (0.79, 1.26)	0.98 (0.78, 1.24)	188 (5.6)	1.00 (reference)	123 (6.4)	1.38 (0.91, 1.42)	1.04 (0.80, 1.36)

^aImmediate reconstruction considered any reconstruction procedure occurring on the date of the initial surgery through 30 days post-op.

^bPoisson models for ‘general complication’, ‘breast complication’, ‘reoperation’, and ‘hospital readmission’ adjusted for race-ethnicity, marital status, active-duty military status, service branch, geographic region, modified Elixhauser comorbidities, cancer diagnosis year, tumor stage, tumor histology, tumor grade, tumor location, lymph node surgery (sentinel node biopsy or axillary node dissection), lymph node positivity, estrogen and progesterone hormone receptor status, HER2 status (positive, negative, unknown, or unavailable), time-to-surgery, neoadjuvant chemotherapy or radiation, surgery extent (partial or total mastectomy), surgery admission duration (inpatient or outpatient), surgery care setting (military or civilian), and other health insurance.

^cPoisson models for specific breast complications of ‘surgical site infection’, ‘hematoma’, ‘seroma’, and ‘lymphedema’ adjusted for race-ethnicity, geographic region, comorbidities, tumor stage, tumor histology, tumor location, surgery care setting, surgery type, surgery admission duration, surgery extent, lymph node surgery, lymph node positivity, time-to-surgery, neoadjuvant treatment, and other health insurance.

^dGeneral complications: death, hemorrhage, blood transfusion, myocardial infarction (MI), stroke, urinary tract infection (UTI), pneumonia, deep vein thrombosis (DVT), pulmonary embolism (PE), other thrombosis, systemic inflammatory response syndrome (SIRS), severe sepsis, or septic shock. There were n = 0 deaths and n = 0 blood transfusions occurring during the 30-day follow-up.

^eBreast complications: surgical site infection (SSI), hematoma, seroma, lymphedema, or upper limb nerve injury.

^fSecond surgical procedure (lumpectomy or mastectomy) at least 7 days after the first surgery date and within 30 days of the index surgery.

^gInpatient encounter within 30 days after the initial surgery for any cause, excluding encounter related to reoperation.

Bold text indicates statistical significance at the alpha=0.05 level.

The overall rate of reoperation within 30 days of the initial surgery was 16.3%. Women aged 40-49 had the highest rate (18.6%) and women aged 65+ had the lowest rate (13.5%) (Chi-square P < .001; Figure 2). In univariable Poisson regression, women ≥65 had a lower risk of reoperation (RR = 0.81, 95% CI = 0.71, 93) relative to women aged 50-64, but the association was attenuated and not statistically significant when adjusted for the patient, tumor, and treatment factors (Table 3). There were no statistical differences in reoperation between women aged 18-39 or 40-49 relative to women aged 50-64. The overall rate of 30-day hospital readmission was 5.9% and the rate did not differ across the age groups (Chi-square P = .41; Figure 2). No significant age differences in readmission were noted in the regression analysis (Table 3).

In subsequent analysis stratified by surgery extent (partial or total and radical mastectomy), there were no statistically significant differences in the outcomes by age at diagnosis in models adjusted for potential confounders (see Appendix Table A3). However, the number of events was small (n < 11) among several age groups by surgery type which may affect estimate reliability and limit the ability to detect statistically meaningful differences.

Discussion

In the Military Health System, where women have insurance coverage and access to health services regardless of age, we noted some variation in short-term surgical outcomes by age at diagnosis among women with non-metastatic breast cancer who underwent surgery without immediate reconstruction. However, there were no overall statistically significant differences in 30-day postoperative outcomes by age group in the MHS population when adjusted for patient, tumor, and treatment factors. This is important as health systems strive to achieve optimal surgical outcomes for all patients regardless of clinical presentation of the disease.

Consistent with the epidemiology of breast cancer in the United States, younger women aged 18-39 or 40-49 had a higher frequency of diagnoses with pathologically unfavorable tumors (eg, regional stage, high grade, hormone receptor negative) relative to women aged 50-64 or ≥65 in the study population of DoW beneficiaries with breast cancer.^4,6 This finding further highlights the need to understand how tumors among young women may differ biologically from tumors in older, postmenopausal women and how this may influence response to treatment. Notably, despite this more aggressive disease profile and higher rates of neoadjuvant therapy, younger women in the present study did not experience increased short-term complication rates, reinforcing the safety and feasibility of timely surgical management in this population. These findings are especially relevant for preserving access to adjuvant therapy and supporting return to duty among active-duty servicewomen.^21,64 However, the current study did not include women receiving immediate reconstruction. Thus, the distribution of tumor characteristics and its implications for surgical management and outcomes may differ when these patients are otherwise included.

Our analysis found that general surgical complications were more common among older women (≥65) compared to other age groups, consistent with prior studies suggesting increased susceptibility to medical complications such as infections, thromboembolic events, or cardiovascular issues in older surgical patients.^19,22 A population-based cohort study on breast cancer surgical outcomes found that medical complications were more common in women over 70 compared to those aged 50-69, while major surgical complications did not differ significantly by age group.²² However, older women had a higher incidence of complications such as infections and cardiovascular issues following more extensive surgery (mastectomy).²² In our study, after adjusting for comorbidities and other clinical factors, the association between age and general complications was no longer statistically significant. Breast-specific complications—including surgical site infection, hematoma, and lymphedema—occurred at similar rates across age groups, further supporting the idea that biological age alone may not be a sufficient indicator of risk for short-term postoperative morbidity in breast cancer surgery. These findings are supported by a study by Wolde et al. that found age was not a risk factor for developing post-operative complications after breast cancer surgery.²⁵ Type of surgery was the most important risk factor, as well as increased BMI.²⁵ Although women aged ≥65 had the highest comorbidity burden in our study, age was not independently associated with increased risk of complications after adjusting for comorbidity and other clinical variables. This reinforces the importance of assessing perioperative risk using individualized comorbidity measures rather than relying on age alone as a proxy for surgical risk.

One incidental finding was the increased risk of seroma among women aged 40-49 compared to those aged 50-64. Seroma formation is common after mastectomy, with some studies reporting rates over 50%.^65,66 Surgical approach and technique, lymph node dissection, increased body weight, and tumor size may play a role in seroma development.^65,66 However, seroma presence does not necessarily indicate a complication unless persistent or infected and many resolve without intervention. In our study, the overall frequency was low (<3%) relative to other studies and the absolute difference between age groups was small. We do not know from the data whether this represents an overall low occurrence or whether only those cases which required intervention were documented. Thus, the clinical relevance of the finding is unclear and may require further investigation into whether seromas are related to biological (eg, age) or clinical factors (eg, drain placement, surgical approach) in this population.

Rates of reoperation for cancer and hospital readmission did not differ significantly by age after multivariable adjustment, echoing findings from prior large-scale studies.^49,50,58,59 The slightly higher unadjusted reoperation rate in women aged 40-49 and lower rate in women ≥65 in the present study is consistent with other national-level cohort data and may be explained by differences in tumor biology, margin status, and surgical approach rather than age alone as evidenced in the adjusted estimates.^50,51 In a prior study of women in the MHS, Eaglehouse et al. found that age was not significantly related to rates of re-excision for women undergoing breast conserving surgery when other factors such as tumor location, size, and regional lymph node involvement were considered.⁵⁹ Similarly, the absence of age-related differences in hospital readmission in the current study supports the overall safety of breast cancer surgery across all adult age groups in a universally insured population. Collectively, these findings support a nuanced understanding of postoperative care needs across the age spectrum and suggest that short-term recovery is not necessarily compromised by younger age despite the more aggressive disease phenotype.

This study offers several strengths, including the use of a large, population-based cohort within the Military Health System, which ensures relatively uniform access to care and comprehensive capture of clinical data and thus reduces the possible effects of access to care on research results. However, certain limitations must be acknowledged. First, for any studies based on medical claims data, the use of administrative data to capture outcomes using ICD and CPT codes may under- or overestimate true event rates despite the use of validated definitions. Likewise, administrative data is subject to coding errors, although it is reviewed for completeness and accuracy to ensure proper billing and payment. However, such errors may not substantially differ by age, thus having minimal effect on our results. Second, the administrative data does not include clinical details which could be used to determine the severity of complications, whether intervention was needed to resolve a complication, or reason for reoperation (eg, obtain clean margins, drain placement, abscess removal). Thus, we cannot exclude possible differences by age in the severity of complications, and thus need for medical intervention, nor reoperations specific to achieving negative surgical margins vs management of a complication. The database also does not include clinical details of the surgery, such as type of anesthesia used, time in the operating room, surgeon specialty, etc. which may affect the outcome of surgery. Thus, we cannot account for any potential differences in these unmeasured confounders by age nor their impacts on the results. Third, the study period spanned from 2001 to 2014 which may not fully reflect changes in breast cancer surgery and perioperative management that have evolved over the past years, such as expansion of oncoplastic techniques and minimally invasive platforms and selective node surgery omission. While our analysis provides insights on potential differences in outcomes by age, the results should be interpreted in the context of standard surgical practice during the time period of the data (ie, 2001-2014) and the generalizability to women undergoing breast cancer surgery in the present may be limited. Also, HER2 status was mostly unavailable prior to 2010, as it was not a required item in cancer registries during this time. Thus, we were unable to fully account for differences in tumor biology (eg, triple negative breast cancer) by age and adjust for its possible effects in the regression models. Next, while the 30-day follow-up period captured immediate complications after surgery and is consistent with the ACS-NSQIP reporting window, it may not capture all complications related to surgery. Thus, we cannot exclude the possibility of any age-related differences in complications occurring beyond 30-days, nor the possibility of differences in complications after adjuvant therapy for these women undergoing breast cancer surgery. Finally, women eligible for care in the MHS may differ from those in the general population in underlying health conditions or behaviors and the study excluded women with immediate reconstruction. These factors may limit generalizability of the study results.

Conclusions

In the Military Health System, the overall risk of 30-day general and breast-specific complications, reoperations, and readmissions among younger and older women undergoing breast cancer surgery without immediate reconstruction did not differ significantly from middle-aged women with breast cancer after adjustment for clinical and demographic factors. The results in this universal health system suggest that age may play a limited role in short-term surgical outcomes for breast cancer. Surgical decision-making should continue to prioritize tumor characteristics, comorbidity burden, and other clinical factors rather than age alone when assessing perioperative risk. Nevertheless, future research is needed to evaluate whether there are differences in complication rates of cancer treatment over longer intervals (eg, months, years after surgery) by age and to assess for any differential impacts of complications on quality-of-life. Also, as surgical treatment of breast cancer continues to evolve, studies which consider breast reconstruction and different approaches to lymph node management and their use and outcomes by age will be needed.

Supplemental Material

Supplemental Material - Age at Breast Cancer Diagnosis and Short-Term Postoperative Outcomes for Women Treated in a Universal Health System

Supplemental Material for Age at Breast Cancer Diagnosis and Short-Term Postoperative Outcomes for Women Treated in a Universal Health System by Gabrielle Falco, Sarah Darmon, Matthew Nealeigh, Robert W. Krell, Craig D. Shriver, Kangmin Zhu, and Yvonne L. Eaglehouse in Cancer Control

Footnotes

Acknowledgement

The authors thank the Joint Pathology Center (JPC) for providing the Department of War (DoW) cancer registry data and the Defense Health Agency (DHA) for providing the Military Health System (MHS) data repository (MDR) data. The authors thank ICF International, the Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc. (HJF, Inc.), and the Uniformed Services University of the Health Sciences (USUHS) for data linkage and hosting.

ORCID iD

Yvonne L. Eaglehouse

Ethical Considerations

This retrospective cohort study used data from the Military Cancer Epidemiology (MilCanEpi) database. The MilCanEpi database was approved for access for research by the Uniformed Services University of the Health Sciences Institutional Review Board, Bethesda, Maryland (FWA 00001628) on 19 July 2019 (Reference #914142) and renewed on 4 March 2025 (Reference #981045).

Consent to Participate

The database study was reviewed by the Uniformed Services University of the Health Sciences Institutional Review Board (FWA 00001628; Reference #914142 and #981045) and it was determined that the requirement for informed consent was waived.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Murtha Cancer Center Research Program (MCCRP) of the Department of Surgery, Uniformed Services University of the Health Sciences (USUHS) under the auspices of the Henry M. Jackson Foundation for the Advancement of Military Medicine (HJF, Inc.), grant numbers HHU0001-16-2-0014 and HU0001-18-2-0032. The funding agency had no role in the study design; in the collection, analysis, and interpretation of data; or in the writing of the report.

Declaration of Conflicting Interests

The authors declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: YE, SD, and KZ were employees of the Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., a 501(c)(3) non-profit organization at the time the work was performed. The authors have no other potential conflicts of interest to declare.

Data Availability Statement

The data that support the findings of this study are not publicly available due to the restrictions in the access and use of the MilCanEpi data specified in the data sharing agreements and regulatory approvals. The Department of War cancer registry data and data dictionary may be requested from the Joint Pathology Center and online at https://jpc.capmed.mil/. The Military Health System Data Repository (MDR) data and data dictionary may be requested from the Defense Health Agency and online at .

Disclaimer

The contents of this abstract are the sole responsibility of the authors and do not necessarily reflect the views, assertions, opinions, or policies of the Uniformed Services University of the Health Sciences, the Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., the Department of War, or the Departments of the Army, Navy, or Air Force. Mention of trade names, commercial products, or organizations does not imply endorsement by the U.S. government.

Supplemental Material

Supplemental material for this article is available online.

Appendix

References

Siegel

Kratzer

Giaquinto

Sung

Jemal

. Cancer statistics, 2025. CA Cancer J Clin. 2025;75(1):10-45.

Bytnar

McGlynn

Nealeigh

Shriver

Zhu

. Cancer incidence in the US military: an updated analysis. Cancer. 2024;130(1):96-106.

Hamlin

Gabor

. Breast cancer incidence and risk factors among active duty members of the armed forces compared to the civilian population. Preprints Lancet. 2025. doi:10.2139/ssrn.5327045

Azim

Jr Partridge

. Biology of breast cancer in young women. Breast Cancer Res. 2014;16(4):427.

Freedman

Partridge

. Management of breast cancer in very young women. Breast. 2013;22(Suppl 2):S176-S179.

Klauber-DeMore

. Tumor biology of breast cancer in young women. Breast Dis. 2005;23:9-15.

Dietz

Partridge

Gemignani

Javid

Kuerer

. Breast cancer management updates: young and older, pregnant, or male. Ann Surg Oncol. 2015;22(10):3219-3224.

Zimmer

Zhu

Steeg

, et al. Analysis of breast cancer in young women in the Department of Defense (DoD) database. Breast Cancer Res Treat. 2018;168(2):501-511.

Humlevik

ROC

Svanøe

Aas

, et al. Distinct clinicopathological features and treatment differences in breast cancer patients of young age. Sci Rep. 2025;15(1):5655.

10.

Kim

Freedman

Partridge

. The impact of young age at diagnosis (age <40 years) on prognosis varies by breast cancer subtype: a U.S. SEER database analysis. Breast. 2022;61:77-83.

11.

Akinoso-Imran

O'Rorke

Kee

Jordao

Walls

Bannon

. Surgical under-treatment of older adult patients with cancer: a systematic review and meta-analysis. J Geriatr Oncol. 2022;13(4):398-409.

12.

Field

Bosco

Prout

, et al. Age, comorbidity, and breast cancer severity: impact on receipt of definitive local therapy and rate of recurrence among older women with early-stage breast cancer. J Am Coll Surg. 2011;213(6):757-765.

13.

LeMasters

Madhavan

Sambamoorthi

Hazard-Jenkins

Kelly

Long

. Receipt of guideline-concordant care among older women with stage I-III breast cancer: a population-based study. J Natl Compr Cancer Netw. 2018;16(6):703-710.

14.

Jones

Courneya

Mackey

, et al. Cardiopulmonary function and age-related decline across the breast cancer survivorship continuum. J Clin Oncol. 2012;30(20):2530-2537.

15.

Beadle

McCarthy

Baade

. Effect of age at diagnosis of breast cancer on the patterns and risk of mortality from all causes: a population-based study in Australia. Asia Pac J Clin Oncol. 2013;9(2):129-138.

16.

Freedman

Keating

Lin

, et al. Breast cancer-specific survival by age: worse outcomes for the oldest patients. Cancer. 2018;124(10):2184-2191.

17.

Gnerlich

Deshpande

Jeffe

Sweet

White

Margenthaler

. Elevated breast cancer mortality in women younger than age 40 years compared with older women is attributed to poorer survival in early-stage disease. J Am Coll Surg. 2009;208(3):341-347.

18.

Gradishar

Moran

Abraham

, et al. Breast cancer, version 3.2024, NCCN clinical practice guidelines in oncology. J Natl Compr Cancer Netw. 2024;22(5):331-357.

19.

Al-Hilli

Wilkerson

. Breast surgery: management of postoperative complications following operations for breast cancer. Surg Clin North Am. 2021;101(5):845-863.

20.

Tevis

Steiman

Neuman

Greenberg

Wilke

. Postoperative complications in combined gynecologic, plastic, and breast surgery: an analysis from National Surgical Quality Improvement Program. Breast J. 2019;25(6):1111-1116.

21.

Islam

Dahlui

Majid

, et al. Factors associated with return to work of breast cancer survivors: a systematic review. BMC Public Health. 2014;14(Suppl 3):S8.

22.

de Boniface

Szulkin

Johansson

ALV

. Medical and surgical postoperative complications after breast conservation versus mastectomy in older women with breast cancer: Swedish population-based register study of 34 139 women. Br J Surg. 2023;110(3):344-352.

23.

Dillon

Thomas

Rosenberger

, et al. Mortality in older patients with breast cancer undergoing breast surgery: how low is “low risk”. Ann Surg Oncol. 2021;28(10):5758-5767.

24.

de Glas

Kiderlen

Bastiaannet

, et al. Postoperative complications and survival of elderly breast cancer patients: a focus study analysis. Breast Cancer Res Treat. 2013;138(2):561-569.

25.

Ten Wolde

Kuiper

de Wilt

JHW

Strobbe

LJA

. Postoperative complications after breast cancer surgery are not related to age. Ann Surg Oncol. 2017;24(7):1861-1867.

26.

Barnett

Berchick

. Current Population Reports: Health Insurance Coverage in the United States, 2016. U.S. Census Bureau, editor. Washington, D.C.: U.S. Government Printing Office; 2017:44.

27.

Abdelsattar

Hendren

Wong

. The impact of health insurance on cancer care in disadvantaged communities. Cancer. 2017;123(7):1219-1227.

28.

Guy

Jr Yabroff

Ekwueme

, et al. Healthcare expenditure burden among non-elderly cancer survivors, 2008-2012. Am J Prev Med. 2015;49(6 Suppl 5):S489-S497.

29.

Hsu

Wang

Habif

Jr Ma

Johnson

. Breast cancer stage variation and survival in association with insurance status and sociodemographic factors in us women 18 to 64 years old. Cancer. 2017;123(16):3125-3131.

30.

Liggett

Norris

Rush

Sicignano

Oxner

. The military health system: minimizing disparities in breast cancer treatment. Mil Med. 2023;188(Supplement_6):494-502.

31.

Defense Health Agency . Evaluation of the TRICARE Program: Fiscal Year 2022 Report to Congress. Falls Church, VA: Defense Health Agency; 2022.

32.

Adirim

. A military health system for the twenty-first century. Health Aff (Millwood). 2019;38(8):1268-1273.

33.

Eaglehouse

Shriver

Lin

, et al. MilCanEpi: increased capability for cancer care research in the Department of Defense. JCO Clin Cancer Inform. 2023;7(7):e2300035.

34.

Eaglehouse

Darmon

Nealeigh

Koehlmoos

Shriver

Zhu

. Short-term outcomes of breast cancer surgery by race-ethnicity in the Military Health System. Ann Surg Oncol. 2025;32:7693.

35.

Benchimol

Smeeth

Guttmann

, et al. The reporting of studies conducted using observational routinely-collected health data (RECORD) statement. PLoS Med. 2015;12(10):e1001885.

36.

American College of Surgeons . National Surgical Quality Improvement Program. Chicago, IL: American College of Surgeons; 2024. https://www.facs.org/quality-programs/data-and-registries/acs-nsqip/

37.

Miller

Steiner

Barrett

Fingar

Elixhauser

. Breast Reconstruction Surgery for Mastectomy in Hospital Inpatient and Ambulatory Settings, 2009–2014. Healthcare cost and utilization project (HCUP) statistical briefs. Statistical Brief #228. Rockville (MD): Agency for Healthcare Research and Quality (US); 2017:1-20.

38.

Parrish

Markov

Michael Johnson

Fox

. Hospital length of stay and hospital readmission after immediate breast reconstruction in the United States: implications for quality measurement. J Plast Reconstr Aesthetic Surg. 2022;75(1):439-488.

39.

Elixhauser

Steiner

Harris

Coffey

. Comorbidity measures for use with administrative data. Med Care. 1998;36(1):8-27.

40.

Mehta

Sura

Adhikari

, et al. Adapting the Elixhauser comorbidity index for cancer patients. Cancer. 2018;124(9):2018-2025.

41.

American College of Surgeons . User Guide for the Participant Use Data File. Chicago, IL: American College of Surgeons; 2007:1-40.

42.

Eaglehouse

Park

Georg

, et al. Consolidation of cancer registry and administrative claims data on cancer diagnosis and treatment in the US Military Health System. JCO Clin Cancer Inform. 2020;4:906-917.

43.

Navi

Zhang

Kaiser

, et al. Cancer and the risk of perioperative arterial ischemic events. Eur Heart J Qual Care Clin Outcomes. 2023;10(4):345-356.

44.

Olsen

Nickel

Fox

, et al. Incidence of surgical site infection following mastectomy with and without immediate reconstruction using private insurer claims data. Infect Control Hosp Epidemiol. 2015;36(8):907-914.

45.

Knoedler

Kauke-Navarro

Knoedler

, et al. Racial disparities in surgical outcomes after mastectomy in 223 000 female breast cancer patients: a retrospective cohort study. Int J Surg. 2024;110(2):684-699.

46.

Polverini

Nelson

Marcinkowski

, et al. Time to treatment: measuring quality breast cancer care. Ann Surg Oncol. 2016;23(10):3392-3402.

47.

Kaufman

Shockney

Rabinowitz

, et al. National quality measures for breast centers (NQMBC): a robust quality tool: breast center quality measures. Ann Surg Oncol. 2010;17(2):377-385.

48.

Montagna

Barrio

. Managing the morbidity: individualizing risk assessment, diagnosis, and treatment options for upper extremity lymphedema. Surg Oncol Clin N Am. 2023;32(4):705-724.

49.

. Breast cancer-related lymphedema: symptoms, diagnosis, risk reduction, and management. World J Clin Oncol. 2014;5(3):241-247.

50.

Jatoi

. Reducing reoperation rates after breast-conserving surgery. Lancet Oncol. 2013;14:5-6.

51.

Morrow

Abrahamse

Hofer

, et al. Trends in reoperation after initial lumpectomy for breast cancer: addressing overtreatment in surgical management. JAMA Oncol. 2017;3(10):1352-1357.

52.

Metcalfe

Neudam

Forde

, et al. Case definitions for acute myocardial infarction in administrative databases and their impact on in-hospital mortality rates. Health Serv Res. 2013;48(1):290-318.

53.

Goldstein

. Accuracy of ICD-9-CM coding for the identification of patients with acute ischemic stroke. Stroke. 1998;29(8):1602-1604.

54.

Olsen

Ball

Nickel

Wallace

Fraser

. Validation of ICD-9-CM diagnosis codes for surgical site infection and noninfectious wound complications after mastectomy. Infect Control Hosp Epidemiol. 2017;38(3):334-339.

55.

Fang

Fan

Sung

, et al. Validity of using inpatient and outpatient administrative codes to identify acute venous thromboembolism: the CVRN VTE study. Med Care. 2017;55(12):e137-e143.

56.

Heijboer

RRO

Lubberts

van Dijk

PAD

, et al. The validity of using ICD-9 codes for identifying venous thromboembolism following below knee surgery. Orthopaedic J Harvard Med School. 2016;17(June):18-23.

57.

Jolley

Sawka

Yergens

Quan

Jetté

Doig

. Validity of administrative data in recording sepsis: a systematic review. Crit Care. 2015;19(1):139.

58.

Higgins

Deshpande

Zilberberg

, et al. Assessment of the accuracy of using ICD-9 diagnosis codes to identify pneumonia etiology in patients hospitalized with pneumonia. JAMA Netw Open. 2020;3(7):e207750.

59.

Eaglehouse

Georg

Jatoi

Shriver

Zhu

. Factors related to re-excision procedures following primary breast-conserving surgery for women with breast cancer in the U.S. Military Health System. J Surg Oncol. 2019;121(2):200-209.

60.

Habermann

Thomsen

Milbrandt

Nassr

Larson

. Risk factors for 30-day unplanned readmission and major perioperative complications after spine fusion surgery in adults: a review of the national surgical quality improvement program database. Spine. 2016;41(19):1523-1534.

61.

McNutt

Xue

Hafner

. Estimating the relative risk in cohort studies and clinical trials of common outcomes. Am J Epidemiol. 2003;157(10):940-943.

62.

Chen

Qian

Shi

Franklin

. Comparing performance between log-binomial and robust poisson regression models for estimating risk ratios under model misspecification. BMC Med Res Methodol. 2018;18(1):63.

63.

Gallis

Turner

. Relative measures of association for binary outcomes: challenges and recommendations for the global health researcher. Ann Glob Health. 2019;85(1):137.

64.

Sun

Shigaki

Armer

. Return to work among breast cancer survivors: a literature review. Support Care Cancer. 2017;25(3):709-718.

65.

Awad

Chan

. Encapsulated chronic recurrent seroma following modified radical mastectomy: surgical resection and reconstruction by muscle-sparing latissimus dorsi flap—A case report and review of literature. Ann Breast Surg. 2020;4:10. doi:10.21037/abs-19-71a

66.

Srivastava

Basu

Shukla

. Seroma formation after breast cancer surgery: what we have learned in the last two decades. J Breast Cancer. 2012;15(4):373-380.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.12 MB

0.00 MB