Accepted Manuscript
Disparities in Access to Care and Outcomes in Patients with Adrenocortical Carcinoma
Abdulrahman Y. Hammad, MD, Tina W.F. Yen, MD MS, Azadeh A. Carr, MD, Douglas B. Evans, MD, Tracy S. Wang, MD MPH
PII:
S0022-4804(17)30098-7
DOI:
10.1016/j.jss.2017.02.046
Reference:
YJSRE 14171
To appear in:
Journal of Surgical Research
Received Date: 19 January 2017
Revised Date: 4 February 2017
Accepted Date: 23 February 2017
JSR Journal of
Surgical Research
0
Official Publication al tho Association for Academic Burgiry
Full- Fast and Sutrait Marctipa:
Please cite this article as: Hammad AY, Yen TWF, Carr AA, Evans DB, Wang TS, Disparities in Access to Care and Outcomes in Patients with Adrenocortical Carcinoma, Journal of Surgical Research (2017), doi: 10.1016/j.jss.2017.02.046.
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Disparities in access to care in ACC patients
Revised 2/2/2017
Disparities in Access to Care and Outcomes in Patients with Adrenocortical Carcinoma
Abdulrahman Y. Hammad MD, Tina W F Yen MD MS, Azadeh A. Carr, MD, Douglas B. Evans, MD Tracy S Wang MD MPH
Division of Surgical Oncology, Department of Surgery, Medical College of Wisconsin, Milwaukee, WI, USA
Presented at the Society of Asian Academic Surgeons Inaugural meeting, September 24, 2016, Stanford University, Palo Alto, CA.
Short Title: Disparities in access to care in ACC patients.
Disclosure: No relevant financial disclosures
Funding: None
Keywords: Adrenocortical Carcinoma, Disparities in Care, Surgical Resection, Resection Margins, National Cancer Database, Proportional Hazard Models.
Corresponding Author:
Tracy S Wang MD MPH Division of Surgical Oncology Department of Surgery Medical College of Wisconsin 9200 West Wisconsin Ave Milwaukee, WI 53226, USA Phone: 414-805-5755 Fax: 414-805-5771 tswang@mcw.edu
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Disparities in access to care in ACC patients
Abstract
Background: Surgical resection remains the mainstay of treatment for patients with adrenocortical carcinoma (ACC). The aim of the current study is to examine disparities in access to surgical resection and identify factors associated with overall survival following surgical resection.
Methods: The National Cancer Database (NCDB) was queried for patients with ACC (2004-2013). Patient characteristics and disease details were abstracted. Logistic regression analysis was performed to examine the factors associated with surgical resection, and a multivariate Cox proportional hazards model was utilized to identify predictors of survival in the surgical cohort.
Results: Surgical resection was performed in 2007/2946 (68%) ACC patients. On multivariate logistic regression analysis controlling for clinicodemographic factors, surgery was less likely to be performed in patients ≥56 years, males, African-Americans, patients with government insurance, or those treated at community cancer centers (p<0.05). On a multivariate Cox proportional hazards model adjusting for clinicodemographic and treatment variables, older age (≥56 years) and presence of comorbidities were associated with worse overall survival.
Conclusion: These findings suggest that there are demographic and socioeconomic disparities in access to surgical resection for ACC. However, after adjusting for patient and clinical characteristics, only patient age and presence of comorbidities were predictors of worse survival in patients undergoing surgery for ACC. More data are needed to determine the factors driving these disparities.
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Disparities in access to care in ACC patients
Introduction
Adrenal cortical carcinoma (ACC) is a rare abdominal neoplasm, with an estimated annual worldwide incidence of 0.7-2.0cases/ million.(1,2) The disease has a bimodal age distribution and is seen more frequently in females, with a reported female/male ratio of 1.5:1.(3-5) However, there are no reported differences in survival based on patients’ gender or ethnicity.(4,6,7) The prognosis of this aggressive neoplasm remains poor, as 50%-70% of patients present with advanced disease.(5,8) Surgical resection with negative margins is considered the optimal treatment for ACC, if no distant or locoregional spread has occurred, although the role of lymphadenectomy remains unclear.(5,9) Positive resection margins and/or positive lymph nodes are associated with disease recurrence and poorer long-term outcomes.(6,7, 10, 11) In patients that are considered to be at high risk for recurrent disease, adjuvant therapy with mitotane may provide additional survival benefit.(12)
Previous studies have shown that age, sex, race/ethnicity, socioeconomic status or the urbanicity of residence all play a role in cancer patients’ access to care and long-term outcomes.(13-17) For example, socioeconomic status was found to be associated with delay in health-care, tumor staging and treatment modalities in esophageal cancer.(18) In hepatocellular carcinoma, significant survival differences exist based on racial and ethnic disparities despite the receipt of comparable treatments.(19)
The current study hypothesized that similar disparities in access to care and outcomes exist among patients with ACC. Utilizing the National Cancer Database, this study examines these potential demographic and socioeconomic disparities in access to surgery and identifies which factors are associated with overall survival in patients with ACC.
Methods
The National Cancer Database (NCDB), a national registry resulting from a joint project between the Commission on Cancer of the American College of Surgeons (COC) and the American Cancer
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Disparities in access to care in ACC patients Society, was established to analyze and track patients with malignant neoplastic diseases, their treatments, and their outcomes in the United States. Since 1998, all COC-accredited cancer programs are required to submit annual reports to the NCDB. Currently, the database contains approximately 70% of all newly diagnosed cancer cases nationwide.(20) After Institutional Review Board exemption was granted, the de- identified NCDB-Participant User File (PUF) was queried for ACC cases diagnosed between 2004 & 2013 with follow-up through 2015.
Utilizing the International Classification of Disease, third revision (ICD-3), all adult patients (age ≥18 years) were identified utilizing site Code (C74.0, C74.9), combined with histologic subtype codes (8010, 8140, & 8370) for ACC. Demographic characteristics were collected for the identified cohort and included age (years), sex, race (Caucasian, African American, or Others), insurance status (private, Medicare/other government, Medicaid, or other [unknown/ no insurance]), annual income (<38,000-63,000, >$63,000/year), and county of residence (metropolitan, urban and rural), per the NCDB coding dictionary.(21) Age was treated as a dichotomous variable, with a threshold of 56 years, based on the mean and median age of the examined cohort.(22) Clinical variables collected included patient comorbidities, as measured by the Charlson Comorbidity Index (CCI), tumor size, grade, stage, and facility type (academic cancer program, community cancer program, other). Patients who underwent surgical resection were identified using Facility Oncology Registry Data System [FORDS] codes, and surgery-related outcomes including surgical margin and lymph node status, 30-day readmission rates, 30-and 90-day mortality rates, and receipt of adjuvant therapies (chemotherapy or radiotherapy) were collected and analyzed.
Univariate and multivariate logistic regression analyses were performed to examine the factors associated with the receipt of surgical resection of the tumor. Factors analyzed included Clinicodemographics (age, sex, race, comorbidity), socioeconomic (insurance status, income level, county category), treating facility, and tumor characteristics (size, grade, and stage,). Univariate and multivariate Cox proportional hazards model was utilized to identify predictors of overall survival (OS) in the surgical
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cohort. OS was calculated from the time of diagnosis till the time of death by the means of Kaplan-Meier estimates and compared using the log-rank test. Odds ratio (OR) and 95% confidence intervals (CI) were reported for the logistic regression analysis, while hazards ratio (HR) and 95%CI were reported for Cox proportional hazards model. For the survival analyses, the above factors plus treatment factors (surgical resection, chemotherapy, and radiation therapy) were included in the model. Variables with p<0.1 on the univariate analysis were included in the multivariate analysis for both the logistic regression analysis and Cox proportional hazards model. Alpha was established at 0.05 for all tests and all p<0.05 was considered significant. Statistical analysis was performed using STATA version 12.0 (StataCorp LP, College Station, Texas).
Results
Patient and Tumor Characteristics
A total of 2,946 ACC patients were identified for the period of 2004-2013 (Table I). The median age at diagnosis of the entire cohort was 56 (interquartile range [IQR], 45-67 years). Overall, the majority of patients were female (59%), Caucasian (86%), covered by private insurance (52%), and were treated equally at community cancer programs (43%) and/or at academic cancer programs (41%). Approximately 75% of the examined cohort had tumors ≥5cm (median size 10.2 cm [IQR: 7.0-14.5]).
Surgical Resection
Surgical resection was performed in 68% (2,007/2,946; Table II). This included resection (70%); resection with contiguous organs (18%); debulking (2%); surgery not-otherwise specified (4%); and others (131; 7%). Negative resection margins (RO resection) were achieved in 66%; negative lymph nodes were reported in 17%. The 30-day readmission rate was 5%, while 30-day and 90-day mortality rates were 2% and 6%, respectively. On univariate analysis (Table I), patients in the surgical cohort were more likely to be younger, male, white, have fewer comorbidities and have private insurance. Additionally, patients in the surgical group were more likely to have been treated at academic cancer center but less
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Disparities in access to care in ACC patients
likely to receive chemotherapy. On multivariate logistic regression analysis adjusting for all clinicopathologic and treatment variables except county of residence (Table III), predictors of not receiving surgical resection were older age, male sex, being African-American and having government (Medicare/other government or Medicaid) insurance.
Prognostic Factors of Survival
On univariate Cox proportional hazards model, older age (≥56 years), greater number of comorbidities (CCI: 1; CCI≥2) and government insurance were the only patient characteristics associated with worse overall survival (Table IV). On multivariate Cox proportional hazards model, after adjusting for all tumor characteristics and treatment factors, only age and the number of comorbidities remained predictors of worse overall survival. There was a trend towards patients with government insurance having worse survival (p=0.06).
Discussion
In patients diagnosed with ACC, surgery remains the only potentially curative option. Studies suggest that disparities in surgical care and outcomes exist in the United States; patients’ age, sex, and ethnicity are reported to affect surgical decision, as well as operative and post-operative outcomes in cancer patients. (23-26) Similarly, socioeconomic status has been reported as an independent predictor of surgical mortality and post-operative outcomes.(14, 15, 17) Careful selection of the most suitable candidates for surgical resection results in better long-term outcomes. The current study aimed to explore these potential disparities in patients presenting with ACC who undergo surgery (versus those that do not), and to examine the impact of sociodemographic factors on overall survival in the surgical cohort.
Consistent with previous studies, in the current study, older age was a negative predictor of survival supporting the incorporation of patient age into the staging of ACC.(22, 27, 28) Asare et al. suggested that the incorporation of age into the staging system may provide a better prediction of overall survival and therefore guide treatment recommendation options.(22) However, a recent multi-institutional study
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Disparities in access to care in ACC patients showed that older age (≥65 years) does not impact overall survival or recurrence-free survival.(29) Due to the different age cut-offs used in these studies, further analyses are still required to determine the appropriate age cut-off that might impact survival. Consistent with prior studies, the current study confirms that females are more likely to be diagnosed with the disease but that female gender is not a negative predictor of survival. (3, 27, 28)
In a recent systematic review by Haider et al. that included 89 studies published between 1990 and 2011 examining a multitude of general surgery patients, insurance status was found to influence access to surgery and long-term outcomes.(16) Uninsured and publicly insured patients were found to have higher morbidity and mortality rates compared to privately insured patients. Interestingly, the results of the current study confirm the impact of the type of insurance on treatment, but not on mortality in patients with ACC, as the results show that patients with non-private insurance were less likely to receive surgical resection of their tumor. The explanation for these findings is likely multifactorial as factors such as patient age, sex, race, socioeconomic status, and comorbidities may influence one’s insurance status, which may then affect access to care and likelihood of undergoing surgery. Why the type of insurance was not a predictor of overall survival is unclear, but may be partially related to the poor prognosis of patients with of ACC in general.
The limitations of this study include those inherent to a retrospective review of a large hospital- based cancer database, particularly potential discrepant coding for extent of surgery and missing information regarding certain tumor characteristics, particularly disease stage and grade. Finally, mitotane is coded in the NCDB as chemotherapy, which does not allow for the examination of its particular impact on survival. Yet, the database allows the examination of disparities in access to surgical resection and factors associated with overall survival in a large cohort of ACC patients. The results seen are largely consistent with the current literature and highlight some important points that can be further investigated.
Conclusion
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These findings demonstrate that in patients with ACC, significant disparities exist in access to surgery as patients who are older (≥56 years), male, African-American, have non-private insurance, and are treated at community cancer centers are less likely to undergo surgery. In addition, among those that undergo surgery, patients who are older and have more comorbidities have worse overall survival. Additional efforts to examine the etiology and address these disparities are needed.
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Disparities in access to care in ACC patients
| Variables (n) | Total (n=2,946) | Surgical Cohort (n=2,007) | Non-Surgical Cohort (n=939) | p-value |
|---|---|---|---|---|
| Clinicodemographic | ||||
| Age, median (IQR) | 56 (45-67) | 55 (44-66) | 60 (48-71) | |
| Mean±SD | 55.8±15.1 | 54.2±15.1 | 59.1±16.2 | <0.001 |
| <56 years | 1,358 (46) | 1,055 (53) | 372 (40) | <0.001 |
| ≥56 years | 1,588 (54) | 952 (47) | 567 (60) | |
| Gender | ||||
| Female | 1,749 (59) | 784 (36) | 413 (44) | 0.011 |
| Male | 1,197 (41) | 1,223 (61) | 526 (56) | |
| Race | ||||
| Caucasian | 2,529 (86) | 1,748 (87) | 781 (83) | 0.013 |
| African American | 281 (9) | 171 (9) | 110 (12) | |
| Others | 136 (5) | 88 (4) | 48 (5) | |
| Charlson Comorbidity Index | ||||
| 0 | 2,196 (74) | 1,535 (76) | 661 (70) | 0.001 |
| 1 | 553 (19) | 356 (18) | 197 (21) | |
| ≥2 | 197 (7) | 116 (6) | 81 (9) | |
| Socioeconomic | ||||
| Insurance | ||||
| Private | 1,523 (52) | 1,134 (56) | 389 (41) | |
| Government | ||||
| Medicare | 919 (31) | 553 (28) | 366 (39) | <0.001 |
| Medicaid | 196 (7) | 119 (6) | 77 (8) | |
| Other government | 44 (1) | 31 (2) | 13 (1) | |
| Unknown/no insurance | 264 (9) | 170 (8) | 94 (10) | |
| Income/ year | ||||
| <38k | 498 (17) | 321 (16) | 177 (19) | |
| ACCEP 38k-63k | 1,445 (49) | 1,006 (50) | 439 (47) | 0.023 |
| >63k | 930 (32) | 639 (32) | 291 (31) | |
| Unknown | 73 (2) | 41 (2) | 32 (4) | |
| County category | ||||
| Metro | 2,334 (79) | 1,586 (79) | 784 (80) | |
| Urban | 431 (15) | 304 (15) | 127 (13) | 0.177 |
| Rural | 59 (2) | 43 (2) | 16 (2) | |
| Unknown | 122 (4) | 74 (4) | 48 (5) | |
| Tumor Characteristics | ||||
| Size/ cm | ||||
| <5cm | 357 (12) | 256 (13) | 101 (11) | <0.001 |
| ≥5cm | 2,220 (75) | 1,629 (81) | 591 (63) | |
| Unknown | 369 (13) | 122 (6) | 247 (26) |
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| Grade | ||||
| Well differentiated | 73 (5) | 62 (3) | 11 (1) | |
| Moderately differentiated | 104 (4) | 96 (5) | 8 (1) | <0.001 |
| Poorly differentiated | 344 (11) | 228 (11) | 116 (12) | |
| Anaplastic | 122 (4) | 103 (5) | 19 (2) | |
| Unknown | 2,303 (78) | 1,518 (76) | 785 (84) | |
| Stage | ||||
| Stage 1 | 67 (2) | 63 (3) | 4 (0) | |
| Stage 2 | 314 (11) | 304 (15) | 10 (1) | <0.001 |
| Stage 3 | 167 (6) | 159 (8) | T 8 (1) | |
| Stage 4 | 526 (18) | 224 (11) | 302 (32) | |
| Unknown | 1,872 (63) | 1,257 (63) | 615 (66) | |
| Treatments | ACCEPTED MARS C. | |||
| Surgery | ||||
| No | 939 (32) | - | - | |
| Yes | 2,007 (68) | |||
| Chemotherapy | 1,767 (60) | |||
| None | 1,067 (36) | 1,280 (64) | 487 (52) | <0.001 |
| Yes | 112 (4) | 646 (32) | 421 (44) | |
| Unknown | 81 (4) | 31 (3) | ||
| Radiotherapy | ||||
| None | 2,520 (86) | 1,705 (85) | 815 (87) | 0.247 |
| Yes | 389 (13) | 273 (14) | 116 (12) | |
| Unknown | 37 (1) | 29 (1) | 8 (1) | |
| Treating facility | ||||
| Academic Cancer program | 1,201 (41) | 874 (43) | 327 (35) | <0.001 |
| Community Cancer program | 1,275 (43) | 776 (39) | 499 (53) | |
| Other | 470 (16) | 357 (18) | 113 (12) |
| Variables (n) | Total (%) (n=2,007) |
|---|---|
| Surgery | |
| Resection | 1,408 (70) |
| Resection with contiguous organ | 355 (18) |
| Debulking | 31 (1) |
| Surgery, NOS | 213 (11) |
| Surgical margins | |
| R0 | 1,321 (66) |
| R1/R2 | 15 PT 372 (18) |
| Unknown | 314 (16) |
| Lymph node status | |
| Negative | 333 (17) |
| Positive | 126 (6) |
| Unknown | 1,548 (77) |
| 30-Day readmission | |
| No | 1,816 (91) |
| Yes | 105 (5) |
| Unknown | 86 (4) |
| 30-Day mortality | MANUS |
| No | 1,716 (86) |
| Yes | 49 (2) |
| Unknown | 242 (12) |
| 90-Day mortality | |
| No | 1,637 (83) |
| Yes | 120 (6) |
| ACCEPTED Unknown | 250 (12) |
| Variables | Univariate | Multivariate | ||
|---|---|---|---|---|
| OR (95% CI) | p value | OR (95% CI) | p value | |
| Clinicodemographics | C | |||
| Age | <0.001 | 0.001 | ||
| <56 years | Ref | Ref | ||
| ≥56 years | 0.59 (0.50-0.69) | 0.67 (0.53-0.84) | ||
| Gender | 0.011 | 0.023 | ||
| Female | Ref | Ref | ||
| Male | 0.81 (0.69-0.95) | 0.81 (0.67-0.97) | ||
| Race | 0.013 | 0.012 | ||
| Caucasian | Ref | Ref | ||
| African American | 0.69 (0.53-0.89) | 0.68 (0.50-0.93) | ||
| Others | 0.81 (0.57-1.17) | 0.67 (0.44-1.02) | ||
| Charlson comorbidity index | <0.001 | 0.067 | ||
| 0 | Ref | Ref | ||
| 1 | 0.77 (0.63-0.94) | 0.81 (0.64-1.02) | ||
| ≥2 | 0.61 (0.45-0.83) | 0.73 (0.52-1.03) | ||
| Socioeconomic | ||||
| Insurance | <0.001 | 0.002 | ||
| Private | Ref | Ref | ||
| Medicaid | 0.53 (0.38-0.82) | 0.57 (0.40-0.82) | ||
| Medicare + other government | 0.52 (0.44-0.62) | 0.66 (0.53-0.83) | ||
| Unknown/no insurance (n=264) | 0.62 (0.47-1.81) | 0.71 (0.51-0.98) | ||
| Income/ year | 0.024 | 0.233 | ||
| <38k | Ref | Ref | ||
| 38k-63k | 1.26 (1.01-1.56) | 1.14 (0.88-1.47) | ||
| >63k | 1.21 (0.96-1.52) | 1.00 (0.76-1.31) | ||
| Unknown (n=73) | 0.70 (0.42-1.16) | 0.72 (0.41-1.26) | ||
| County category | 0.182 | |||
| Metro | Ref | |||
| Urban | 1.12 (0.90-1.41) | - | ||
| Rural | 1.26 (0.70-2.26) | - | ||
| Unknown (n=122) | 0.72 (0.50-1.05) | - | ||
| Tumor Characteristics | ||||
| Size/ cm, | <0.001 | <0.001 | ||
| <5cm | Ref | Ref | ||
| ≥5cm | 1.08 (0.84-1.39) | 1.00 (0.76-1.32) | ||
| Unknown (n=369) | 0.19 (0.14-0.26) | 0.22 (0.16-0.32) | ||
| Grade | <0.001 | <0.001 | ||
| Well differentiated | Ref | Ref | ||
| Moderately differentiated | 2.13 (0.81 -5.60) | 1.12 (0.40-3.16) | ||
| Poorly differentiated | 0.34 (0.17-0.68) | 0.27 (0.12-0.56) | ||
| Anaplastic | 0.96 (0.43-2.20) | 0.47 (0.19-1.14) | ||
| Unknown (n=2,303) | 0.34 (0.17-0.65) | 0.21 (0.10-0.43) | ||
| Stage | <0.001 | <0.001 | ||
| Stage 1 | Ref | Ref | ||
| Stage 2 | 1.93 (0.59-6.34) | 1.65 (0.47-5.54) | ||
| Stage 3 | 1.26 (0.37-4.33) | 1.02 (0.28-3.58) | ||
| Stage 4 | 0.04 (0.01-0.13) | 0.04 (0.01-0.12) | ||
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| Unknown (n=1,872) | 0.12 (0.04-0.35) | 0.13 (0.04-0.36) | |
|---|---|---|---|
| Treatment | |||
| Treating facility | <0.001 | <0.001 | |
| Academic Cancer program | Ref | Ref | |
| Community Cancer program | 0.58 (0.49-0.68) | 0.55 (0.45-0.68) | |
| Other (n=470) | 1.18 (0.92-1.51) | 0.92 (0.68-1.26) | |
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| Variables | Univariate | Multivariate | ||
|---|---|---|---|---|
| HR (95% CI) | p value | HR (95% CI) | p value | |
| Clinicodemographics | ||||
| Age | <0.001 | 0.005 | ||
| <56 years | Ref | Ref | ||
| ≥56 years | 1.37 (1.21-1.56) | 1.25 (1.06-1.46) | ||
| Gender | 0.839 | |||
| Female | Ref | - | ||
| Male | 0.98 (0.86-1.12) | - | ||
| Race | ||||
| Caucasian | Ref | 0.690 | - | |
| African American | 0.91 (0.72-1.16) | - | ||
| Others | 1.06 (0.78-1.45) | - | ||
| Charlson comorbidity index | <0.001 | <0.001 | ||
| 0 | Ref | Ref | ||
| 1 | 1.39 (1.19-1.64) | 1.39 (1.17-1.65) | ||
| ≥2 | 1.54 (1.21-1.98) | 1.61 (1.24-2.09) | ||
| Socioeconomic | ||||
| Insurance | <0.001 | 0.057 | ||
| Private | Ref | Ref | ||
| Medicaid | 1.34 (1.04-1.74) | 1.30 (0.99-1.70) | ||
| Medicare + other government | 1.40 (1.21-1.61) | 1.22 (1.04-1.42) | ||
| Unknown/no insurance (n=264) | 1.10 (0.87-1.40) | 0.98 (0.76-1.27) | ||
| Income/ year | 0.193 | |||
| <38k | Ref | - | ||
| 38k-63k | 0.95 (0.79-1.14) | - | ||
| >63k | 0.88 (0.73-1.07) | - | ||
| Unknown (n=41) | 1.36 (0.88-2.09) | |||
| County category | 0.962 | |||
| Metro | Ref | - | ||
| Urban | 1.02 (0.86-1.22) | - | ||
| Rural | 1.03 (0.67-1.58) | - | ||
| Unknown (n=74) | 1.07 (0.77-1.49) | - | ||
| Tumor Characteristics | ||||
| Size/ cm | 0.013 | 0.319 | ||
| <5cm | Ref | Ref | ||
| ≥5cm | 1.35 (1.10-1.66) | 1.18 (0.94-1.48) | ||
| Unknown (n=122) | 1.40 (1.02-1.91) | 1.17 (0.82-1.65) | ||
| Grade | <0.001 | 0.001 | ||
| Well differentiated | Ref | Ref | ||
| Moderately differentiated | 1.38 (0.77-2.45) | 1.42 (0.77-2.64) | ||
| Poorly differentiated | 3.29 (2.01-5.39) | 2.89 (1.68-4.97) | ||
| Anaplastic | 2.73 (1.60-4.65) | 2.63 (1.47-4.69) | ||
| Unknown (n=1,518) | 2.21 (1.38-3.53) | 2.24 (1.34-3.74) | ||
| Stage | <0.001 | <0.001 | ||
| Stage 1 | Ref | Ref | ||
| Stage 2 | 1.50 (0.75-3.01) | 1.44 (0.67-3.05) | ||
| Stage 3 | 2.69 (1.33-5.42) | 2.38 (1.11-5.08) | ||
| Stage 4 | 4.81 (2.43-9.54) | 3.18 (1.51-6.70) | ||
| Unknown (n=1,257) | 2.31 (1.19-4.47) | 2.11 (1.03-4.30) | ||
ACCEPTED MANUSCRIPT
Disparities in access to care in ACC patients
| Surgical margins | Ref <0.001 | |||
|---|---|---|---|---|
| R0 | Ref | <0.001 | ||
| R1/R2 | 2.25 (1.92-2.63) | 1.92 (1.61-2.27) | ||
| Unknown (n=314) | 1.69 (1.39-2.07) | 1.76 (1.42-2.17) | ||
| Lymph node status | ||||
| Negative | Ref | <0.001 | Ref | 0.003 |
| Positive | 2.40 (1.83-3.14) | 1.65 (1.23-2.21) | ||
| Unknown (n=1,548) | 1.02 (0.85-1.21) | 1.14 (0.94-1.38) | ||
| Treatments | ||||
| Surgery | <0.001 | <0.001 | ||
| Resection | Ref | Ref | ||
| Resection with contiguous organ | 1.39 (1.18-1. 36) | 1.32 (1.11-1.57) | ||
| Debulking | 3.78 (2.53-5.65) | 2.41 (1.54-3.76) | ||
| Surgery, NOS (n=96) | 0.92 (0.74-1.15) | 0.83 (0.65-1.06) | ||
| Chemotherapy | <0.001 | 0.154 | ||
| None | Ref | Ref | ||
| Yes | 1.26 (1.10-1.45) | 1.10 (0.94-1.28) | ||
| Unknown (n=81) | 0.57 (0.38-0.86) | 0.73 (0.46-1.15) | ||
| Radiotherapy | 0.018 | 0.074 | ||
| None | Ref | Ref | ||
| Yes | 1.11 (0.92-1.34) | 0.86 (0.70-1.07) | ||
| Unknown (n=29) | 0.31 (0.13-0.75) | 0.39 (0.15-1.02) | ||
| Treating facility | 0.359 | |||
| Academic Cancer program | Ref | - | ||
| Community Cancer program | 1.03 (0.90-1.19) | - | ||
| Other (n=357) | 0.90 (0.75-1.08) | - | ||
HR: Hazards ratio; CI: confidence interval; NOS: not-otherwise specified.