Identifying factors influencing delays in breast cancer treatment in Kentucky following the 2014 Medicaid expansion

Abstract

Background and Objectives:

A previous analysis of breast cancer care after the 2014 Medicaid expansion in Kentucky demonstrated delays in treatment despite a 12% increase in insurance coverage. This study sought to identify factors associated with treatment delays to better focus efforts for improved breast cancer care.

Methods:

The Kentucky Cancer Registry was queried for adult women diagnosed with invasive breast cancer between 2010 and 2016 who underwent up-front surgery. Demographic, tumor, and treatment characteristics were assessed to identify factors independently associated with treatment delays.

Results:

Among 6225 patients, treatment after Medicaid expansion (odds ratio [OR] = 2.18, 95% confidence interval [CI] = 1.874–2.535, P < .001), urban residence (OR = 1.362, 95% CI = 1.163–1.594, P < .001), treatment at an academic center (OR = 1.988, 95% CI = 1.610–2.455, P < .001), and breast reconstruction (OR = 3.748, 95% CI = 2.780–5.053, P < .001) were associated with delay from diagnosis to surgery. Delay in postoperative chemotherapy was associated with older age (OR = 1.155,95% CI = 1.002–1.332, P = .0469), low education level (OR = 1.324, 95% CI = 1.164–1.506, P < .001), hormone receptor positivity (OR = 1.375, 95% CI = 1.187–1.593, P < .001), and mastectomy (OR = 1.312, 95% CI = 1.138–1.513, P < .001). Delay in postoperative radiation was associated with younger age (OR = 1.376, 95% CI = 1.370–1.382, P < .001), urban residence (OR = 1.741, 95% CI = 1.732–1.751, P < .001), treatment after Medicaid expansion (OR = 2.007, 95% CI = 1.994–2.021, P < .001), early stage disease (OR = 5.661, 95% CI = 5.640–5.682, P < .001), and mastectomy (OR = 1.884, 95% CI = 1.870–1.898, P < .001).

Conclusions:

Patient, tumor, and socioeconomic factors influence the timing of breast cancer treatment. Improving timeliness of treatment will likely require improvements in outreach, education, and healthcare infrastructure.

1 |. INTRODUCTION

After diagnosis of breast cancer, patients are now waiting longer for definitive surgical treatment. In an analysis of the National Cancer Database (NCDB), Leiderbach, et al¹ found that wait times increased significantly from 2003 to 2011 by 6, 9, and 8 days for patients undergoing lumpectomy and mastectomy with or without reconstruction respectively (P < .001). Bleichert, et al² reported that the time interval from the first surgical visit to definitive surgery in Medicare patients increased from 21 days in 1992 to 32 days in 2005. These “delays” were attributed to several demographic and preoperative evaluation factors.

Several entities have defined timeliness of breast cancer treatment as part of their quality improvement efforts. The National Comprehensive Cancer Network (NCCN) and the American Society of Clinical Oncology support adjuvant hormonal therapy for hormone receptor-positive tumors within 1 year of diagnosis, chemotherapy for hormone receptor-negative cancer within 4 months of diagnosis, and radiation after lumpectomy within 1 year of diagnosis as time-dependent quality measures.^3,4 However, no such standard was recommended for the time from breast cancer diagnosis to definitive surgery.⁴ The National Consortium of Breast Centers, through its quality initiative, the National Quality Measures for Breast Centers (NQMBC), has recommended timeliness of care between diagnosis and surgical treatment as a measure of quality but has not established a specific benchmark.⁵

A previous analysis of breast cancer care after the 2014 Medicaid expansion in Kentucky (as part of the Patient Protection and Affordable Care Act (ACA) enacted by the United States government in March 2010), demonstrated several positive effects including increases in early stage at presentation, increased the use of breast conserving therapy (BCT), and higher rates of radiotherapy after BCT. Despite a 12% increase in insurance coverage, the expansion resulted in delays from diagnosis to treatment (38.7 +/− 47.9 days before vs 49.4 +/− 54.8 days after the expansion, P < .001).⁶ The reason for these delays, however, remains unclear. This study sought to identify factors associated with delays in treatment, which can inform healthcare entities and local governments on how to better focus efforts for improved timeliness of breast cancer care.

2 |. METHODS

2.1 |. Patient cohort and data acquisition

The Kentucky Cancer Registry, the Kentucky state-designated population-based central cancer registry, was queried for all women at least 20 years of age diagnosed with breast cancer between 2010 and 2016 who underwent up-front surgery for their breast cancer. Demographic information, including age, race, region of residence, and socioeconomic information (including the degree of poverty, education level, and insurance status) were included in the data analysis. Patients with age younger than 65 years old were considered as younger age group. Education ascertainment and degree of poverty were extracted from the 2008 to 2012 American Community Survey (ACS) data and were categorized into either four quartile-based groups or two median-based groups according to high school graduation rate and percentage of individuals below the poverty line at the county level. First course treatment data, including information about timing and type of surgery, radiation therapy, and chemotherapy; receipt of breast reconstruction; type of surgery; and era of treatment (before or after Medicaid expansion) were all evaluated. Other clinic information, such as tumor size, grade, stage at diagnosis, number of nodes examined, number of nodes positive, hormone receptor positivity, and human epidermal growth factor receptor 2 (HER2) status were also included in data analysis.

2.2 |. Evaluation of delays in breast cancer treatment

Delays in breast cancer treatment were evaluated with respect to surgery, chemotherapy, and radiation therapy. Delay in surgery was defined as more than 30 days from diagnosis to surgery in women who underwent up-front surgery. Delay in chemotherapy was defined as more than 60 days from surgery to initiation of chemotherapy. Delay in radiation therapy was defined as more than 90 days from surgery to initiation of radiation. Regarding delays in radiation therapy, patients receiving chemotherapy after surgery were excluded. Patients were stratified according to whether or not they experienced delays and compared with demographic, tumor, and treatment characteristics to identify factors associated with delays in breast cancer treatment.

2.3 |. Statistical analysis

Descriptive analysis, including χ² tests and two sample t tests, were used to examine associations between the delay status and categorical and continuous variables, respectively. Multiple logistic regression analyses were performed to assess for demographic and clinical factors independently associated with delays in surgery, postoperative chemotherapy, and radiation. All analyses were performed using SAS statistical software, version 9.4 (SAS Institute). All statistical tests were two-sided, and P < .05 was utilized as the threshold for statistical significance.

3 |. RESULTS

Among 6225 patients included in this analysis, 2227 patients experienced a delay from diagnosis to surgery (35.78%), 1255 patients experienced a delay from surgery to postoperative chemotherapy (20.16%), and 3223 patients experienced a delay from surgery to postoperative radiation (93.86%). A descriptive analysis of the patient cohort is presented in Table 1.

TABLE 1.

Study cohort characteristics

	Study cohort (n = 6225)
Age (years)
<50	1664
50–64	2965
65–74	1306
75+	290
Ethnicity
Caucasian	5675
African-American	486
Other/unknown	64
Year of treatment
2010–2013	3782
2014–2016	2443
Area of residence
Metro	3483
Nonmetro	2742
Appalachian status
Appalachia	1748
Non-Appalachia	4477
Education
Very Low	1810
Low	1618
Moderate	1994
High	803
Poverty
Low	1478
Moderate	1445
High	1538
Very High	1764
Insurance Status
Not Insured	122
Private	3502
Medicare	1826
Medicaid	661
Other public	86
Unknown	28
Treatment at academic hospital
No	5356
Yes	869
Tumor size
<3.0 cm	4523
3.0–5.9 cm	1588
≥6.0 cm	114
Nodes examined
0	298
1–11	4401
12+	1465
Unknown	61
Nodes positive
0	3142
1–11	2531
12+	216
Unknown	336
Tumor grade
Well-differentiated	598
Moderately differentiated	2377
Poorly differentiated	3123
Undifferentiated	17
Unknown	110
Hormone receptor positive
Negative	1758
Positive	4389
Unknown	78
HER2 positive
Negative	2852
Positive	841
Borderline	923
Unknown	1609
Stage
0	38
I	2042
II	2927
III	1047
IV	108
Unknown	63
Type of surgery
Lumpectomy	2608
Mastectomy	3613
NOS	4
Reconstruction (Y)
No	5208
Yes	1017

Abbreviation: HER2, human epidermal growth factor receptor 2; NOS, not otherwise specified.

On univariate analysis, multiple socioeconomic, tumor, and treatment-related factors were associated with delays in surgery, postoperative chemotherapy, and radiation. Those comparisons are detailed in Tables 2A–C.

TABLE 2A.

Comparison of patients who did and did not experience delays from diagnosis to surgery

	Delay from diagnosis to surgery (n = 2227)	No delay from diagnosis to surgery (n = 3998)	P
Age (years)			.0143
<50	642	1022
50 to 64	1045	1920
65 to 74	452	854
75+	88	202
Age (years)			.0607
<65	1687	2942
65+	540	1056
Ethnicity			<.0001
Caucasian	1990	3685
African-American	219	267
Other/Unknown	18	46
Year of treatment			<.0001
2010 to 2013	1115	2667
2014 to 2016	1112	1331
Area of residence			<.0001
Metro	1406	2077
Nonmetro	821	1921
Appalachian status			<.0001
Appalachia	541	1207
Non-Appalachia	1686	2791
Education level			<.0001
Low	1090	2338
High	1137	1660
Poverty			<.0001
Low	574	904
Moderate	608	837
High	510	1028
Very high	535	1229
Insurance status			.0979
Not Insured	42	80
Private	1269	2233
Medicare	636	1190
Medicaid	227	434
Other public	43	43
Unknown	10	18
Treatment at academic center			<.0001
No	1773	3583
Yes	454	415
Tumor size			.0025
<3.0 cm	1671	2852
3.0 to 5.9 cm	526	1062
≥6.0 cm	30	84
Nodes examined			.0185
0	84	214
1 to 11	1613	2788
12+	511	954
Unknown	19	42
Nodes positive			.0101
0	1115	2027
1 to 11	934	1597
12+	84	132
Unknown	94	242
Tumor grade			.0011
Well-differentiated	223	375
Moderately differentiated	920	1457
Poorly differentiated	1039	2084
Undifferentiated	5	12
Unknown	40	70
Hormone receptor positive			<.0001
Negative	537	1221
Positive	1669	2720
Unknown	21	57
HER2 status			.1011
Negative	1020	1832
Positive	306	535
Borderline	357	566
Unknown	544	1065
Stage			.0095
0	11	27
I	739	1303
II	1057	1870
III	376	671
IV	20	88
Unknown	24	39
Type of surgery			<.0001
Lumpectomy	815	1793
Mastectomy	1411	2202
NOS	1	3
Reconstruction (Y)			<.0001
No	1614	3594
Yes	613	404

Abbreviation: HER2, human epidermal growth factor receptor 2; NOS, not otherwise specified.

TABLE 2C.

Comparison of patients who did and did not experience delays from surgery to radiation

	Delay from surgery to radiation (n = 3223)	No delay from surgery to radiation (n = 211)	P
Age, y			.0026
<50	824	43
50 to 64	1632	102
65 to 74	646	48
75+	121	18
Age, y			.014
<65	2456	145
65+	767	2456
Ethnicity			.5114
Caucasian	2920	192
African-American	271	16
Other/unknown	32	3
Year of treatment			.0001
2010 to 2013	1855	150
2014 to 2016	1368	61
Area of residence			<.0001
Metro	1897	95
Nonmetro	1326	116
Appalachian Status			.0197
Appalachia	820	69
Non-Appalachia	2403	143
Education level			.0002
Low	1660	137
High	1563	74
Poverty			.0006
Low	849	34
Moderate	780	49
High	772	51
Very high	822	77
Insurance status			.0108
Not insured	59	5
Private	1908	99
Medicare	873	76
Medicaid	331	24
Other public	40	5
Unknown	12	2
Treatment at academic hospital			.1422
No	2771	189
Yes	452	22
Tumor size			<.0001
<3.0 cm	2324	166
3.0 to 5.9 cm	858	34
≥6.0 cm	41	11
Nodes examined			<.0001
0	101	18
1 to 11	2255	159
12+	848	27
Unknown	19	7
Nodes positive			<.0001
0	1473	127
1 to 11	1485	53
12+	150	8
Unknown	115	23
Tumor grade			<.0001
Well-differentiated	314	30
Moderately differentiated	1257	82
Poorly differentiated	1607	84
Undifferentiated	6	0
Unknown	39	15
Hormone receptor positive			.0719
Negative	872	49
Positive	2321	157
Unknown	30	5
HER2 positive			.5215
Negative	1577	94
Positive	372	30
Borderline	475	34
Unknown	799	53
Stage			<.0001
0	8	6
I	1011	102
II	1388	63
III	773	20
IV	20	15
Unknown	23	5
Type of surgery			.0093
Lumpectomy	2098	159
Mastectomy	1122	52
NOS	3	0
Reconstruction (Y)			.0479
No	2964	202
Yes	259	9

Abbreviation: HER2, human epidermal growth factor receptor 2; NOS, not otherwise specified.

On multivariable analysis, listed in Table 3, treatment after the 2014 Medicaid expansion (odds ratio [OR] = 2.18, 95% confidence interval [CI] = 1.874–2.535, P < .001), residence in an urban area (OR = 1.362, 95% CI = 1.163–1.594, P < .001), treatment at an academic center (OR = 1.988, 95% CI = 1.610–2.455, P < .001), and breast reconstruction (OR = 3.748, 95% CI = 2.780–5.053, P < .001) were associated with delays from the time of diagnosis to surgery. Borderline HER2 status and poorly differentiated tumor grade were also associated with delay from diagnosis to surgery (Table 3).

TABLE 3.

Stepwise logistic regression results for associations between covariates and three different outcome variables

	Model 1		Model 2		Model 3
Variable Lista	OR	95% CI	OR	95% CI	OR	95% CI
Age group, y
<65	...b		1.155	(1.002–1.332)	1.376	(1.370–1.382)
65+	...		Ref		Ref
Ethnicity
African-American	1.243	(0.951, 1.624)	...		...
Other	0.386	(0.152, 0.931)	...		...
Caucasian	Ref		...		...
Year of treatment
2014 to 2016	2.180	(1.874–2.535)	...		2.007	(1.994–2.021)
2010 to 2013	Ref		...		Ref
Area of residence
Metro	1.362	(1.610–2.455)	...		1.741	(1.732–1.751)
Nonmetro	Ref		...		Ref
Education level
Low	...		1.324	(1.164–1.506)	...
High	...		Ref		...
Insurance status
Private	...		...		2.559	(2.546–2.572)
Medicare	...		...		1.935	(1.923–1.947)
Medicaid	...		...		2.022	(1.999–2.045)
Other public	...		...		1.029	(1.005–1.053)
Unknown	...		...		0.897	(0.864–0.931)
Not Insured	...		...		Ref
Treatment at academic hospital
Yes	1.988	(1.610–2.455)	...		...
No	Ref		...		...
Nodes examined
0	...		2.501	(0.781–8.013)	0.559	(0.550–0.568)
1 to 11	...		0.769	(0.644–0.919)	0.507	(0.505–0.509)
Unknown	...		1.017	(0.467–2.217)	0.193	(0.188–0.198)
12+	...		Ref		Ref
Nodes positive
0	...		1.883	(1.258–2.819)	...
1 to 11	...		1.448	(0.990–2.118)	...
Unknown	...		0.796	(0.243–2.614)	...
12+	...		Ref		...
Tumor grade
Moderately differentiated	0.953	(0.734–1.238)		1.551	(1.542–1.560)
Poorly differentiated	0.706	(0.544–0.916)	...		2.045	(2.034–2.057)
Undifferentiated	1.359	(0.232–7.950)	...		10.664	(8.715–13.049)
Unknown	0.976	(0.509–1.873)	...		0.361	(0.355–0.368)
Well-differentiated	Ref				Ref
Hormone receptor status
Positive	...		1.366	(1.179, 1.582)	...
Unknown	...		1.289	(0.738, 2.252)	...
Negative	...		Ref		...
HER2 status
Negative	1.103	(0.862–1.411)	...		...
Borderline	1.366	(1.022–1.827)	...		...
Unknown	0.949	(0.724–1.244)	...		...
Positive	Ref		...		...
Stage group
Early stage	...		...		5.661	(5.640–5.682)
Unknown	...		...		10.186	(9.872–10.511)
Late stage	...		...		Ref
Type of surgery
Mastectomy	0.909	(0.762–1.084)	1.312	(1.138–1.513)	1.884	(1.870–1.898)
NOS	<0.001	(<0.001, >999.999)	1.429	(0.147, 13.889)	8.409	(6.999–10.102)
Lumpectomy	Ref		Ref		Ref
Reconstruction
Yes	3.748	(2.780–5.053)	0.829	(0.686–1.002)	0.758	(0.745–0.770)
No	Ref		Ref		Ref

Abbreviations: CI, confidence interval; HER2, human epidermal growth factor receptor 2; NOS, not otherwise specified; OR, odds ratio.

^aVariables were found significant in stepwise logistic regression models. Model 1 models patients experience delays from diagnosis to surgery. Model 2 models patients experience delays from surgery to chemotherapy. Model 3 models patients experience delays from surgery to radiation.

^bVariable is not significant in stepwise logistic regression.

Delay in postoperative chemotherapy (>60 days from surgery to chemotherapy) was associated with older age (OR = 1.155, 95% CI = 1.002–1.332, P = .0469), low education level (OR = 1.324, 95% CI = 1.164–1.506, P < .001), hormone receptor positivity (OR = 1.375, 95% CI = 1.187–1.593, P < .001), and undergoing mastectomy rather than lumpectomy (OR = 1.312, 95% CI = 1.138–1.513, P < .001). Number of lymph nodes examined and number of positive nodes also were associated with delays from surgery to chemotherapy (Table 3).

Finally, delay in postoperative radiation (>90 days from surgery to radiation) was associated with younger age (OR = 1.376, 95% CI = 1.370–1.382, P < .001), residence in an urban area (OR = 1.741, 95% CI = 1.732–1.751, P < .001), treatment after Medicaid expansion (OR = 2.007, 95% CI = 1.994–2.021, P < .001), early stage disease (OR = 5.661, 95% CI = 5.640–5.682, P < .001), and undergoing mastectomy rather than lumpectomy (OR = 1.884, 95% CI = 1.870–1.898, P < .001). Insurance coverage, higher tumor grade, and examination of a greater number of lymph nodes were also all associated with delays from surgery to radiation (Table 3). Interestingly, reconstruction was associated with a lower likelihood of delay from surgery to radiation (OR = 0.758, 95% CI = 0.745–0.770, P < .001).

4 |. DISCUSSION

Multiple studies have demonstrated increased delays from diagnosis to breast cancer treatment in the past 20 years. Defining the optimal time to breast cancer care has been difficult though. Common wisdom based on the early detection paradigm would suggest that shorter intervals from diagnosis to treatment translate into better outcomes. Unfortunately, there is no accepted benchmark or standard for what this time should be.⁷ Studies have chosen different and specific thresholds in an attempt to identify which may become deleterious for the patient; most suggest that longer delays probably have a gradual effect on outcomes.

One should be cautious when evaluating different studies as they use different definitions, endpoints, and timeframes.⁸ Smaller single-institution studies usually lack the follow-up and patient volumes necessary to detect differences in outcomes.^7,9 Larger studies from national databases show that longer delays may have an effect. A study from the Korean Central Cancer Registry showed that delays of more than 12 weeks (vs <4 weeks) to curative surgery were associated with increased mortality in breast cancer patients (hazard ratio [HR] 1.91, 95% CI, 1.06–3.49). Polverini, et al,¹⁰ in a study using NCBD data, found that patients with stage I and II breast cancer with greater than 12 weeks of treatment delays, had worse overall survival (OS) than those treated in less than 4 weeks (stage I HR 1.19,95% CI,1.11–1.28, stage II HR 1.16, 95% CI, 1.08–1.25). Bleichert et al³ evaluated two larger cohorts from the Surveillance, Epidemiology and End Results (SEER)-Medicare and NCDB and noted that OS decreased for each 30-day interval of delay (SEER: HR 1.09; 95% CI, 1.06–1.13; P < .01, NCDB: HR 1.10;955 CI, 1.07–1.13; P <.01). Despite suggestions from the same author that acceptable time from diagnosis to surgery is less than 90 days, we chose a 30-day timeframe based on his initial work showing a small but definitive disadvantage at more than 30 days.⁸

Healthcare policy has occupied center stage in voters’ minds during the past decade. The Patient Protection and Affordable Care Act (ACA), enacted by the United States government in March 2010, allowed for several provisions that states could enact to increase insurance coverage. Some states, including Kentucky, chose to expand Medicaid coverage for those uninsured. A study of states expanding Medicaid before the ACA suggested, among other benefits, a significant decrease in delays to care of 2.9% (21.3% relative reduction, P = .002).¹¹ Our previous study evaluating the effect of the Medicaid expansion on breast cancer care showed that despite some positive effects, patients experienced increased delays from diagnosis to surgical treatment. Our present study confirms delays to surgery and radiotherapy, but no delays between surgery and chemotherapy.⁶ This is in contrast to the effect of the 2005 Medicaid disenrollment in Tennessee, which resulted in the later stage of disease at diagnosis of breast cancer and decreased delays to treatment.¹² As studies continue to evaluate the complex interactions between healthcare reform and cancer care,¹³ we have attempted to understand other factors related to treatment delays.

With respect to delays from time of diagnosis to surgical intervention, our study found it to be correlated more strongly with women receiving care at an academic institution, living in an urban area, and undergoing breast reconstruction. This is supported by the work by Leiderbach et al,¹ who found that facility factors had the strongest association with time delays on NCDB data analysis. Academic institutions were approximately 1.5 times [OR = 1.54, 95% CI, 1.47–1.60] more likely to have a more than 30-day delay compared with community facilities. The increased use of magnetic resonance imaging (MRI), although not evaluated in this database, has also been noted to be a significant factor of delays to surgery,⁷ and to increased mastectomy rates.¹⁴ More patients requiring mastectomy are receiving breast reconstruction in the last decade.¹⁵ It is unsurprising that patients undergoing breast reconstruction are at greater risk of delay as there is an inherent increased complexity in the coordination of care for these individuals. Simple mastectomy or lumpectomy is typically performed by a single surgeon and requires less operating room time compared to reconstructive operations that might be performed by multiple surgeons. Jabo et al¹⁶ evaluated a registry of over 56 000 patients from California with stage 0-III breast cancer and found that when immediate breast reconstruction was performed, there was an average of 49 days from date of diagnosis to surgery vs 35 days in women who did not elect for immediate reconstruction.¹⁶

Optimal timing from surgery to chemotherapy has also been difficult to establish. Some studies demonstrate a detriment related to chemotherapy delays in terms of OS, disease-free survival, and disease-specific survival for all patient as well as for some specific subtypes, while others do not.⁸ Gagliato et al¹⁷ found that initiation of chemotherapy more than 62 days was associated with significant increase in the risk of death compared with those treated within 30 days (HR = 1.19, 95% CI = 1.02–1.38). Survival was mostly compromised on patients with triple negative (TNBC) tumors and HER2 positive tumors (HR = 1.54, 95% CI = 1.09–2.18 and HR = 3.09, 95% CI = 1.49–6.39, respectively). In a larger study from the California Registry, delays to chemotherapy were found to have adverse outcomes not after 60 days but at more than 90 days (HR = 1.34, 95% CI = 1.12–1.57) and again in patients with TNBC (HR = 1.53, 95% CI = 1.17–2.00).¹⁸ Delays to surgery appear to be associated with delays from surgery to chemotherapy. Leiderbach et al¹ found that patients with wait times more than 30 days to first surgery were 36% (OR = 1.36, 95% CI, 1.30–1.43) more likely to have a delay more than 60 days from definitive surgery to adjuvant chemotherapy. In addition, postoperative complications delay chemotherapy initiation. Patients having postoperative complications after breast reconstruction are at higher risk of delay to chemotherapy than those who do not (56 vs 45 days, P = .017).¹⁹ A 60-day timeframe was chosen for our study since it was found to be the most commonly cited maximum acceptable time interval from surgery to chemotherapy.^1,7,17

The effect of delays from surgery to radiation therapy have also been difficult to establish. The only time-dependent quality measure for radiotherapy is radiation after lumpectomy within 1 year of diagnosis.⁴ This assumes that a patient will receive chemotherapy before radiation therapy. For those patients not needing chemotherapy, the effect of radiation therapy delays has been studied with varying results. A large SEER-Medicare study of more than 18 000 women treated with BCS and radiation without chemotherapy found that one-third of patients had intervals to radiotherapy of more than 6 weeks and this delay was associated with an increase in local recurrence (HR = 1.19, 95% CI = 1.01–1.39, P = .004).²⁰ Patients likely to experience delays were node-positive, low income, non-White, and regions of the US with higher rates of BCS. Another SEER-Medicare series of 13 907 patients treated with BCS and radiotherapy without chemotherapy found that delays more than 12 weeks had worse disease-specific (HR = 3.81, 95% CI = 2.98–4.87, P < .0001) and OS (HR = 1.91, 95% CI = 1.63–2.23, P < .0001). No benefit from earlier initiation of radiotherapy was seen.²¹ The 90-day interval found in this last study was chosen in for our study as a time interval from radiation to surgery. These studies, like ours, found multiple patient-related factors associated with delays. Our study also highlights the effect of the Medicaid expansion on delays to radiation therapy but unfortunately does not offer a clear explanation for this.

The results of this study demonstrate that a variety of patient, tumor, and socioeconomic factors influence timing of treatment in the care of breast cancer. Delays to surgery are likely related to access to care and treatment options, while delays to chemotherapy are related to patient characteristics (age and comorbidities) and tumor biology. This study should be interpreted in light of several limitations. The Kentucky cancer registry lacks the granularity of data to determine referral patterns, access to care or the use and frequency of second opinions. Our investigation looked at over 6000 patients from the Kentucky breast cancer registry that is an excellent investigation of breast cancer trends in one state. However, factors that affect women in Kentucky may vary across state lines and abroad. Understanding what factors are delaying treatment may need to be adjusted between different hospital settings.

5 |. CONCLUSIONS

A variety of patient, tumor, and socioeconomic factors influence the timing of treatment in the care of breast cancer. Improving timeliness of treatment will likely require improvements in outreach, education, and healthcare infrastructure. As multidisciplinary teams work to optimize operations, systemic therapy regimens, and radiation therapy, they should also consider elements that improve accessibility and efficiency of care delivery as well as patient awareness of the totality of breast cancer care.

TABLE 2B.

Comparison of patients who did and did not experience delays from surgery to chemotherapy

	Delay from surgery to chemotherapy (n = 1255)	No delay from surgery to chemotherapy (n = 4970)	P
Age, y			.0012
<50	291	1373
50 to 64	611	2354
65 to 74	276	1030
75+	77	213
Age, y			.0238
<65	902	3727
65+	353	1243
Ethnicity			.7718
Caucasian	1149	4526
African-American	96	390
Other/unknown	10	54
Year of treatment			.128
2010 to 2013	786	2996
2014 to 2016	469	1974
Area of residence			<.0001
Metro	637	2846
Nonmetro	618	2124
Appalachian status			.0001
Appalachia	407	1341
Non-Appalachia	848	3629
Education level			<.0001
Low	768	2660
High	487	2310
Poverty			<.0001
Low	249	1229
Moderate	266	1179
High	323	1215
Very high	417	1347
Insurance status			<.0001
Not insured	28	94
Private	570	2932
Medicare	437	1389
Medicaid	194	467
Other public	21	65
Unknown	5	23
Treatment at academic hospital			.1957
No	1094	4262
Yes	161	709
Tumor size			.3371
<3.0 cm	913	3610
3.0 to 5.9 cm	313	1275
≥6.0 cm	29	85
Nodes examined			.0025
0	80	218
1 to 11	841	3560
12+	322	1143
Unknown	12	49
Nodes positive			.0662
0	636	2506
1 to 11	497	2034
12+	37	179
Unknown	85	251
Tumor grade			.0027
Well-differentiated	150	448
Moderately differentiated	496	1881
Poorly differentiated	579	2544
Undifferentiated	3	14
Unknown	27	83
Hormone receptor positive			.0005
Negative	299	1459
Positive	938	3451
Unknown	18	60
HER2 positive			.3306
Negative	565	2287
Positive	155	686
Borderline	199	724
Unknown	336	1273
Stage			.0257
0	13	25
I	433	1609
II	555	2372
III	209	929
IV	29	79
Unknown	16	47
Type of surgery			.0021
Lumpectomy	471	2137
Mastectomy	783	2830
NOS	1	3
Reconstruction (Y)			.1989
No	1065	4143
Yes	190	827

Abbreviation: HER2, human epidermal growth factor receptor 2; NOS, not otherwise specified.

DATA AVAILABILITY STATEMENT

The data that support the findings of this study are available from the Kentucky Cancer Registry. Restrictions apply to the availability of these data, which were used as part of a collaboration with the Kentucky Cancer Registry as part of this study. Data are available from the Kentucky Cancer Registry with appropriate permissions.