metricas
covid
Buscar en
Annals of Hepatology
Toda la web
Inicio Annals of Hepatology Insurance status impacts treatment for hepatocellular carcinoma
Journal Information
Vol. 18. Issue 3.
Pages 461-465 (May - June 2019)
Share
Share
Download PDF
More article options
Visits
1250
Vol. 18. Issue 3.
Pages 461-465 (May - June 2019)
Original article
Open Access
Insurance status impacts treatment for hepatocellular carcinoma
Visits
1250
Lindsay A. Sobotkaa, Alice Hintonb, Lanla F. Contehc,
Corresponding author
Lanla.Conteh@osumc.edu

Corresponding author at: 410W. 10th Street, Columbus, OH 43210, United States.
a Department of Internal Medicine, The Ohio State University, Wexner Medical Center, Columbus, Ohio, United States
b Division of Biostatistics, College of Public Health, The Ohio State University, Columbus, Ohio, United States
c Department of Medicine, Section of Gastroenterology, Hepatology and Nutrition, The Ohio State Wexner Medical Center, Columbus, Ohio, United States
This item has received

Under a Creative Commons license
Article information
Abstract
Full Text
Bibliography
Download PDF
Statistics
Tables (3)
Table 1. Demographic and clinical parameters in patients with hepatocellular carcinoma by primary payer.
Table 2. Multivariable logistic regressions comparing outcomes of hepatocellular carcinoma by payer.
Table 3. Multinomial logistic regression to evaluate disparities in treatment for hepatocellular carcinoma based on payer.a,b
Show moreShow less
Additional material (4)
Abstract
Introduction and aim

Previous studies have identified treatment disparities in the treatment of hepatocellular carcinoma (HCC) based on insurance status and provider. Recent studies have shown more Americans have healthcare insurance; therefore we aim to determine if treatment disparities based on insurance providers continue to exist.

Materials and methods

A retrospective database analysis using the NIS was performed between 2010 and 2013 including adult patients with a primary diagnosis of HCC determined by ICD-9 codes. Multivariable logistic regressions were performed to analyze differences in treatment, mortality, features of decompensation, and metastatic disease based on the patient's primary payer.

Results

This study included 62,368 patients. Medicare represented 44% of the total patients followed by private insurance (27%), Medicaid (19%), and other payers (10%). Patients with Medicare, Medicaid, and other payer were less likely to undergo liver transplantation [(OR 0.63, 95% CI 0.47–0.84), (OR 0.23, 95% CI 0.15–0.33), (OR 0.26, 95% CI 0.15–0.45)] and surgical resection [(OR 0.74, 95% CI 0.63–0.87), (OR 0.40, 95% CI 0.32–0.51), (OR 0.42, 95% CI 0.32–0.54)] than patients with private insurance. Medicaid patients were less likely to undergo ablation then patients with private insurance (OR 0.52, 95% CI 0.40–0.68). Patients with other forms of insurance were less likely to undergo transarterial chemoembolization (TACE) compared to private insurance (OR 0.64, 95% CI 0.43–0.96).

Conclusion

Insurance status impacts treatment for HCC. Patients with private insurance are more likely to undergo curative therapies of liver transplantation and surgical resection compared to patients with government funded insurance.

Keywords:
Medicaid
Medicare
Private insurance
Liver transplantation
Disparities
Full Text
1Introduction

The incidence of hepatocellular carcinoma (HCC) has exponentially increased over the last decade with greater than 25,000 patients diagnosed in 2014 [1,2]. Unlike many other malignancies, the mortality rate is also increasing at an average of 2% a year and the 5 year survival rate remains less than 20% [2]. HCC is quickly becoming one of the leading causes of cancer related mortality in the United States despite advancements in treatment with liver transplantation, surgical resection, ablation, and transarterial chemoembolization (TACE) [3–5].

With the growing attention to the need for available and affordable healthcare in the United States, more citizens had some form of insurance in 2014 compared to 2010, according to a recent government census. The uninsured rate dropped from 16% to 10%; however this represents 33 million American citizens still without healthcare insurance [6]. Despite more Americans having insurance, disparities in treatment based on insurance payer continue to exist and HCC is not an exception. Previous studies on hepatocellular carcinoma (HCC) showed that patients with Medicaid, Medicare, or no insurance were less likely to undergo surgery for early stage HCC compared to patients with private insurance. In the instances where surgery was completed, a higher rate of complications was noted in patients who did not have private insurance [7].

With the increasing incidence and worsening mortality in HCC, it becomes crucial to reevaluate disparities in treatment for HCC based on insurance provider given of the effects on HCC on healthcare costs, morbidity, and mortality.

We hypothesized that patients with Medicaid, Medicare, and other forms of insurance, including self-pay, no charge, Workers Compensation, CHAMPUS, CHAMPVA, Title V, and other government programs will be less likely to receive curative treatment for HCC than patients with private insurance.

2Materials and methods

Data source: A retrospective database analysis using the Nationwide Inpatient Sample (NIS) was performed between 2010 and 2013. The NIS is part of the Healthcare Cost and Utilization Project (HCUP). This database represents information from over 7 million hospital discharges annually from hospitals across the United States and therefore is one of the largest, publically available databases. Information obtained from this database includes primary and secondary diagnoses, procedures, and demographic information [8]. This information is de-identified to protect the privacy of the patients, the physician involved in care, and the hospital in which care was received; therefore this study is exempt from review by The Ohio State University Institutional Review Board (IRB).

Sample study: Patients were identified using the International Classification of Disease, Ninth Revision, Clinical Modification (ICD-9) code for HCC (155.0). Patients were excluded from this study if they were under the age of 18 or if they had cancer in the liver that was non-hepatic in origin. Patients were evaluated based on their insurance provider, which was defined as Medicaid, Medicare, private insurance and other which includes self-pay, no charge, Workers Compensation, CHAMPUS, CHAMPVA, Title V, and other government programs.

Outcomes of interest: The primary outcome of interest included evaluation of treatment disparities based on insurance provider. Treatment for HCC included liver transplantation, surgical resection, ablation, TACE, and noninvasive which includes patients that did not receive treatment or treatment was not coded. Secondary outcomes of interest included difference in features of liver decompensation, metastatic disease and inpatient mortality. Features of liver decompensation were defined as the presence of ascites, coagulopathy, esophageal varices, portal hypertension gastropathy, encephalopathy, edema, hepatorenal syndrome, and spontaneous bacterial peritonitis. In our analysis, feature of liver decompensation and metastatic disease were represented as categorical variables in Table 1 and dichotomous variables in Table 2 for the multivariable analysis.

Table 1.

Demographic and clinical parameters in patients with hepatocellular carcinoma by primary payer.

  Medicare (N=27,401)Medicaid (N=11,640)Private (N=16,896)Other (N=6431) 
  n  n  n  n  p-Value 
Age (years)<0.001 
≤64  6185  22.57%  10,760  92.44%  13,903  82.28%  5625  87.46%   
65–79  15,908  58.06%  730  6.27%  2531  14.98%  703  10.93%   
80  5308  19.37%  151  1.29%  462  2.73%  103  1.61%   
Gender<0.001 
Male  18,592  67.87%  9198  79.13%  12,757  75.50%  5174  80.46%   
Female  8803  32.13%  2426  20.87%  4139  24.50%  1257  19.54%   
Race<0.001 
Caucasian  15,765  57.53%  4155  35.69%  9497  56.21%  2844  44.22%   
African-American  3471  12.67%  2707  23.26%  2236  13.24%  1267  19.71%   
Hispanic  3645  13.30%  2206  18.95%  2020  11.95%  1118  17.39%   
Other/unknown  4520  16.49%  2573  22.10%  3143  18.60%  1202  18.69%   
Geographic region<0.001 
Northeast  6758  24.66%  2920  25.09%  3990  23.62%  843  13.11%   
Midwest  5149  18.79%  1733  14.89%  3071  18.17%  1277  19.86%   
South  9611  35.08%  3789  32.55%  6118  36.21%  3067  47.69%   
West  5883  21.47%  3198  27.48%  3717  22.00%  1244  19.34%   
Discharge year0.975 
2010  6604  24.10%  2952  25.36%  4534  26.84%  1649  25.64%   
2011  7047  25.72%  2938  25.24%  4232  25.05%  1613  25.07%   
2012  6715  24.51%  2845  24.44%  4035  23.88%  1595  24.80%   
2013  7035  25.67%  2905  24.96%  4095  24.24%  1575  24.49%   
Hepatitis C  3845  14.03%  2650  22.76%  3180  18.82%  1080  16.79%  <0.001 
Hepatitis B  857  3.13%  960  8.25%  1161  6.87%  436  6.78%  <0.001 
Alcohol  3523  12.86%  2645  22.72%  2406  14.24%  1436  22.33%  <0.001 
NASH  9336  34.07%  4221  36.26%  6159  36.45%  2124  33.02%  0.045 
Primary Sclerosing Cholangitis  244  0.89%  83  0.71%  201  1.19%  54  0.84%  0.251 
Primary Biliary Cirrhosis  101  0.37%  11  0.09%  57  0.34%  ≤10  0.08%  0.086 
Autoimmune  84  0.31%  25  0.22%  55  0.33%  21  0.32%  0.882 
Other  12,871  46.97%  3584  30.79%  6799  40.24%  2366  36.79%  <0.001 
Liver decompensation features<0.001 
Zero  16,255  59.32%  5799  49.82%  9942  58.84%  3245  50.45%   
One  7376  26.92%  3681  31.63%  4579  27.10%  1958  30.44%   
Two  3051  11.13%  1704  14.64%  1966  11.64%  925  14.38%   
Three or greater  719  2.62%  456  3.91%  409  2.42%  304  4.73%   
Metastasis0.001 
None  23,112  84.35%  9358  80.39%  14,266  84.44%  5297  82.36%   
Single site  3339  12.18%  1720  14.78%  2064  12.21%  853  13.26%   
Two or more site  950  3.47%  562  4.83%  566  3.35%  282  4.38%   
Elixhauser comorbidity score<0.001 
<3  11,133  40.63%  5961  51.21%  9884  58.50%  3594  55.89%   
≥3  16,268  59.37%  5679  48.79%  7012  41.50%  2837  44.11%   
Treatment options<0.001 
Transplant  643  2.35%  209  1.79%  997  5.90%  125  1.95%   
Resection  3528  12.88%  789  6.78%  2692  15.93%  472  7.34%   
Ablation  1873  6.84%  507  4.36%  1151  6.81%  250  3.88%   
TACE  2037  7.44%  970  8.33%  1487  8.80%  449  6.98%   
Noninvasive  19,319  70.51%  9165  78.73%  10,569  62.55%  5135  79.85%   
In Hospital Mortality  2210  8.07%  1190  10.23%  1816  10.76%  877  13.67%  <0.001 
Table 2.

Multivariable logistic regressions comparing outcomes of hepatocellular carcinoma by payer.

Outcome  Payer  Adjusted odds ratio  95% confidence interval 
Metastatic hepatocellular carcinomaaPrivate Insurance  Reference   
Medicaid  1.29  1.11, 1.49 
Medicare  1.08  0.94, 1.24 
Other  1.13  0.95, 1.36 
Liver decompensationbPrivate Insurance  Reference   
Medicaid  1.23  1.07, 1.41 
Medicare  1.15  1.02, 1.29 
Other  1.25  1.07, 1.46 
Inpatient mortalitycPrivate Insurance  Reference   
Medicaid  0.80  0.65, 0.97 
Medicare  0.56  0.46, 0.69 
Other  1.11  0.90, 1.36 
a

Model is adjusted for age, gender, race, geographic region, hepatitis C, alcohol, NASH, liver decompensation features, and Elixhauser comorbidity score.

b

Model is adjusted for age, gender, race, geographic region, hepatitis C, alcohol, NASH, primary biliary cirrhosis, metastasis, and Elixhauser comorbidity score.

c

Model is adjusted for age, gender, race, geographic region hepatitis C, hepatitis B, alcohol, NASH, liver decompensation features, metastasis, and treatment.

Covariates: Multiple factors were evaluated to determine associations with insurance provider including age, gender and race. Additional data obtained for each patient included geographic location of the hospital and risk factors for HCC defined as Hepatitis C, Hepatitis B, alcohol use disorder, non-alcohol fatty liver disease, primary sclerosing cholangitis, primary biliary cirrhosis (now primary biliary cholangitis), autoimmune hepatitis, or other. Comorbidities were also evaluated using the Elixhauser comorbidity scale which was modified to exclude liver disease [9]. These variables were determined through the appropriate ICD-9 codes.

Statistical analysis: Associations between payer and each of the factors of interest were evaluated using chi square tests. Multivariable logistic regression models were fit for the presence of metastatic HCC, liver decompensation, and mortality and a multinomial logistic regression model was fit for treatment modality received where noninvasive treatment was the reference outcome. Terms in each of the models were determined through backward selection where hepatitis C, hepatitis B, alcohol, nonalcoholic fatty liver disease, primary sclerosing cholangitis, primary biliary cirrhosis, autoimmune, liver decompensation, metastasis, Elixhauser comorbidity score, and treatment modality were eligible for inclusion, where appropriate. Further, age, gender, race, and geographic location of the hospital were fixed in all models. In all models, private insurance was treated as the reference payer category.

All analyses were performed using weighted data employing appropriate survey procedures to produce national estimates. Data was analyzed using SAS 9.4 (SAS Institute Inc. Cary, NC).

3Result3.1Patient demographics

There was a total of 62,368 patients with HCC included in the study. The major identifiable insurance provider was Medicare, representing 44% (27,401) of the total patients, followed by private insurance (27%, 16,896), Medicaid (19%, 11,640), and other forms of payment (10%, 6431) (Table 1).

3.2Inpatient treatment for HCC

There were notable disparities in the treatment of HCC with significant differences based on the primary payer in the univariate analysis (p value <0.001). Patients with private insurance had higher rates of treatment compared to patients with Medicare, Medicaid, and other forms of payment. On multivariable analysis, patients with Medicare, Medicaid, and other forms of insurance were less likely to undergo liver transplant than patients with private insurance [(OR 0.63, 95% CI 0.47–0.84), (OR 0.23, 95% CI 0.15–0.33), (OR 0.26, 95% CI 0.15–0.45), respectively]. Patients with Medicare, Medicaid, and other forms of payment were also less likely to undergo resection than patients with private insurance [(OR 0.74, 95% CI 0.63–0.87), (OR 0.40, 95% CI 0.32–0.51), (OR 0.42, 95% 0.32–0.54), respectively]. Medicaid patients were less likely to undergo ablation as treatment for HCC compared to patients with private insurance (OR 0.52, 95% CI 0.40–0.68). Patients with other forms of insurance were less likely to undergo TACE compared to patients with private insurance (OR 0.64, 95% CI 0.43–0.96) (Table 2). These models were adjusted for age, gender, race, geographic region, hepatitis C, hepatitis B, alcohol, NASH, liver decompensation and Elixhauser comorbidity score.

3.3Liver severity, comorbidities, and risk for metastatic HCC

On univariate analysis, features of liver decompensation were significantly different between insurance providers (p value <0.001) (Table 1). Multivariable analysis demonstrated that patients with Medicaid, Medicare, or other forms of payment were more likely to present with liver decompensation than patients with private insurance [(OR 1.23, 95% CI 1.07–1.41), (OR 1.15, 95% CI 1.02–1.29), (OR 1.25, 95% CI 1.07–1.46), respectively] (Table 3) after adjusting for age, gender, race, geographic region, hepatitis C, alcohol, NASH, liver decompensation and Elixhauser comorbidity score.

Table 3.

Multinomial logistic regression to evaluate disparities in treatment for hepatocellular carcinoma based on payer.a,b

Intervention  Payer  Odds ratio  Confidence interval 
Liver transplantPrivate  Reference   
Medicare  0.63  0.47, 0.84 
Medicaid  0.23  0.15, 0.33 
Other  0.26  0.15, 0.45 
ResectionPrivate  Reference   
Medicare  0.74  0.63, 0.87 
Medicaid  0.40  0.32, 0.51 
Other  0.42  0.32, 0.54 
AblationPrivate  Reference   
Medicare  1.17  0.93, 1.48 
Medicaid  0.52  0.40, 0.68 
Other  0.52  0.37, 0.74 
TACEPrivate  Reference   
Medicare  0.99  0.81, 1.20 
Medicaid  0.76  0.53, 1.09 
Other  0.64  0.43, 0.96 
a

Noninvasive treatment is treated as the reference category.

b

Model adjusts for age, gender, race, geographic region, hepatitis C, hepatitis B, alcohol, NASH, liver decompensation features, and Elixhauser comorbidity score.

There was also a significant difference in the Elixhauser comorbidity score between payers (p value <0.001). Medicare patients were more likely to have a greater number of Elixhauser comorbidities with 59.37% of patients presenting with 3 or more comorbidities (Table 1).

The majority of patients presented with no evidence of metastasis, however there was a significant difference in the number of metastasized sites between payers on univariate analysis (p value 0.001) (Table 1). On multivariable analysis, patients with Medicaid were more likely to have metastatic HCC than patients with private insurance (OR 1.29, 95% CI 1.11–1.49) (Table 3) after adjusting for age, gender, race, geographic region, hepatitis C, alcohol, NASH, liver decompensation feature and Elixhauser comorbidity score.

3.4Inpatient mortality

Inpatient mortality was significantly different between payers on univariate analysis (p value <0.001) (Table 1). After adjusting for confounders, patients with Medicare and Medicaid were less likely to have inpatient mortality compared to patients with private insurance [(OR 0.56, 95% CI 0.46–0.69), (OR 0.80, 95% CI 0.65–0.97), respectively] (Table 3) after adjusting for age, gender, race, geographic region, hepatitis C, hepatitis B, alcohol, NASH, liver decompensation, metastasis and treatment.

4Discussion

This study shows that treatment disparities in patients with HCC continue to exist. The most notable of these are the disparities in the definitive curative therapies with liver transplantation and surgical resection based on insurance provider. However, disparities also exist in rates of ablation and TACE [7]. These disparities are likely influenced by higher rates of metastatic disease at time of diagnosis, decompensated liver disease, and other comorbidities in patients with government funded insurance, which have also been noted in previous studies [10–13]. These patients are less likely to undergo routine screening tests for liver cancer and have less opportunities to follow-up with a specialist. Despite recent changes in health care to promote treatment equity despite insurance provider, disparities in treatment continue to exist. It is crucial to recognize these disparities as treatment has a significant impact on patient outcomes and health care utilization in the United States.

Patients with Medicaid, Medicare, and other forms of non-private insurance are more likely to present with decompensated liver disease and other comorbidities than patients with private insurance. This is likely influenced by many factors, including availability to care and treatment, such as curative treatment for hepatitis C. Patients with Medicaid are also more likely to present with metastatic disease compared to patients with private insurance. Foremost, patients with these insurance providers are less likely to undergo routine screening exams for HCC. Previous studies have shown that only 38% of the eligible Medicaid patients underwent some form of imaging for HCC screening in a 15 month time frame [14]. Patients with Medicaid also have difficulty accessing providers, specifically specialists that are more likely to recommend screening exams for HCC. One study showed that only 21% of Medicaid patients with cirrhosis actually followed up with a gastroenterologist. When they followed up with a gastroenterologist they were more likely to undergo routine screening exams [14].

This study showed that patients with Medicaid, Medicare, and other forms of non-private insurance are less likely to undergo treatment for HCC than patients with private insurance. Part of this disparity may be related to increased rates of decompensated disease, metastatic disease, and other comorbidities in patients with government funded insurances which was seen in this study; however the cost of intervention likely factors into this disparity as well. It is suspected that the financial burden of HCC on the United States is greater than $450 million, which is an average of about $32,000 per patient considering that patients undergoing liver transplantation and surgical resection incur more costs than TACE and ablation [15]. This study shows that patients with private insurance were more likely to undergo the most expensive interventions, specifically transplant and resection compared to interventions like TACE and ablation which are significantly less expensive. This is further supported by patients with “other” insurance or payer which includes self-pay or charity cases being less likely to undergo any intervention for HCC. Given the financial burden of this disease, its complications, and impact on society, it is crucial to pick the best intervention at the lowest possible cost, recognizing that the best treatment for a specific patient may be more costly than other forms of treatment.

Patients with Medicaid, Medicare, and other forms of payment suffer worse clinical outcomes, specifically, quality of life and mortality than patients with private insurance. The 5-year survival rate of HCC is less than 20%; however, if patients undergo curative treatment, their disease-free survival and life expectancy exponentially increases. Several studies have shown that patients undergoing transplantation for HCC had a disease-free survival of greater than 75% at 5 years [16]. Patients with government funded insurance who receive less curative interventions would therefore be expected to have higher mortality rates overall. Interestingly, this study shows that Medicaid and Medicare patients actually have decreased mortality rates, however, it should be noted that this only reflects inpatient mortality. Patients with private insurance are more likely to undergo surgical intervention for HCC and therefore may have higher inpatient mortality rated as a result of complications. In addition, patients with government funded insurance may actually be pursuing comfort measures at home after hospital discharge.

Quality of life is also affected in patients that are less likely to undergo treatment. As this study shows in Table 1, these patients are more likely to present with features of decompensation such as ascites and hepatic encephalopathy. These complications may require frequent admissions and invasive therapies such as paracentesis [17].

Recognizing this disparity in healthcare is crucial in order to hypothesize ways to minimize or eliminate further inequality in healthcare. All patients with chronic liver disease should be referred to a hepatologist in order to facilitate care, however the patient's primary care physician should also promote screening exams for HCC in order to promote increased compliance with exams. Patient education and understanding of barriers to completing screening exams, such as transportation and cost should also be explored in patients with government funded insurances [18]. This could assist in earlier diagnosis when patients would be more likely to be a candidate for curative treatment. In addition, government funded insurance could consider linking reimbursement to completion of HCC screening as they are doing for other quality metrics in the care of diabetes and other malignancies.

There are multiple limitations in this study. First, the data was collected through the NIS where information can only be obtained from ICD-9 coding. These codes could not be verified by medical charts given privacy issues, and therefore are susceptible to error. It is expected that this error would be randomly spread out equally throughout the dataset and would not singularly impact a certain variable more than others. Given patient privacy, we were not able to perform a chart review on patients to obtain more information about the specific characteristics of a patient's tumor burden such as size number of lesions, or vascular invasion. These factors impact the choice of liver directed therapy, however, the extent of this effect could not determined in this study. The NIS does not include laboratory values, therefore we are unable to include the Model for End Organ Liver Disease (MELD) score or Child's Pugh Score, therefore disease severity was stratified by the number of features of decompensation. However, there are many strengths to this study including the large number of diverse patients with HCC. This number of patients could not be obtained with a single center study.

As the incidence and mortality of HCC continues to rise, it is vital to recognize the impact that treatment can have on patient mortality and quality of life. Given that liver transplantation and surgical resection are considered curative treatments for a disease with limited progress in survival rates thus far, it becomes even more important that all patients receive access to the best evidence-based treatment for their disease stage, regardless of their insurance status. Further research should be conducted to determine ways to reduce this disparity.AbbreviationsHCUP

Healthcare Cost and Utilization Project

HCC

hepatocellular carcinoma

IRB

Institutional Review Board

ICD-9

International Classification of Disease, Ninth Revision, Clinical Modification

NIS

Nationwide Inpatient Sample

TACE

transarterial chemoembolization

Funding

This research did not have grant or other financial support.

Conflict of interest

The authors have no conflicts of interest to declare.

Appendix A
Supplementary data

The following are the supplementary data to this article:

References
[1]
American Cancer Society.
Cancer facts & figures 2016.
American Cancer Society, (2016),
[2]
S. Mittal, H.B. El-Serag.
Epidemiology of HCC: consider the population.
J Clin Gastroenterol, 47 (2013), pp. S2-S6
[3]
S.F. Altekruse, K.A. McGlynn, M.E. Reichman.
Hepatocellular carcinoma incidence, mortality, and survival trends in the United States from 1975 to 2005.
J Clin Oncol, 27 (2009), pp. 1485-1491
[4]
D. Hashim, P. Boffetta, C. La Vecchia, M. Rota, P. Bertuccio, M. Malvezzi, et al.
The global decrease in cancer mortality: trends and disparities.
Ann Oncol, 27 (2016), pp. 926-933
[5]
H. Nathan, D.L. Segev, S.C. Mayo, K. Hirosa, C. Wolfgnang, M. Choti, et al.
National trends in surgical procedures for hepatocellular carcinoma: 1998–2008.
Cancer, 118 (2012), pp. 1838-1844
[6]
J. Smith, C. Medalia.
U.S. Census Bureau, Current Population Reports, P60-253 health insurance coverage in the United States: 2014.
U.S. Government Printing Office, (2015),
[7]
R.S. Hoehn, D.J. Hanseman, P.L. Jernigan, K. Wima, A.E. Ertel, D.E. Abbott, et al.
Cincinnati Research in Outcomes and Safety in Surgery (CROSS) disparities in care for patients with curable hepatocellular carcinoma.
HPB, 17 (2015), pp. 747-752
[8]
Overview of the National (Nationwide) Inpatient Sample (NIS). Available from: https://www.hcup-us.ahrq.gov/nisoverview.jsp [retrieved 31.3.16].
[9]
A. Elixhauser, C. Steiner, D.R. Harris, R.M. Coffey.
Comorbidity measures for use with administrative data.
Med Care, 36 (1998), pp. 8-27
[10]
L.C. Harlan, H.M. Parsons, C.L. Wiggins, J.L. Stevens, Y.Z. Patt.
Treatment of hepatocellular carcinoma in the community: disparities in standard therapy.
Liver Cancer, 4 (2015), pp. 70-83
[11]
H. Bruns, V.J. Lozanovski, D. Schultze, N. Hillebrand, U. Hinz, M. Buchler, et al.
Prediction of postoperative mortality in liver transplantation in the era of MELD-based liver allocation: a multivariate analysis.
[12]
R.G. Roetzheim, N. Pal, C. Tennant, L. Voti, J. Ayanian, A. Schwabe, et al.
Effects of health insurance and race on early detection of cancer.
JNCI, 91 (1999), pp. 1409-1415
[13]
E. Ward, M. Halpern, N. Schrag, V. Cokkinides, C. DeSantis, P. Bandi, et al.
Association of insurance with cancer care utilization and outcomes.
CA: Cancer J Clin, 58 (2008), pp. 9-31
[14]
L.B. Palmer, M.D. Kappelman, R.S. Sandler, P. Hayashi.
Surveillance for hepatocellular carcinoma in a medicaid cirrhotic population.
J Clin Gastroenterol, 47 (2013), pp. 713-718
[15]
C.E. Ray, C. Battaglia, A.M. Libby, A. Prochazka, S. Xu, B. Funaki.
Interventional radiologic treatment of hepatocellular carcinoma—a cost analysis from the payer perspective.
J Vasc Intervent Radiol, 23 (2012), pp. 306-314
[16]
A. Waghray, A.R. Murali, K.N. Menon.
Hepatocellular carcinoma: from diagnosis to treatment.
World J Hepatol, 7 (2015), pp. 1020-1029
[17]
E.G. Giannini, F. Farinati, F. Ciccarese, A. Pecorelli, G.L. Rapaccini, M. Di Marco, et al.
Prognosis of untreated hepatocellular carcinoma.
Hepatology, 61 (2015), pp. 184-190
[18]
S. Farvardin, J. Patel, M. Khambaty, O. Yerokun, H. Mok, J. Tiro, et al.
Patient-reported barriers are associated with lower hepatocellular carcinoma surveillance rates in patients with cirrhosis.
Hepatology, 65 (2017), pp. 875-884
Copyright © 2019. Fundación Clínica Médica Sur, A.C.
Download PDF
Article options
es en pt

¿Es usted profesional sanitario apto para prescribir o dispensar medicamentos?

Are you a health professional able to prescribe or dispense drugs?

Você é um profissional de saúde habilitado a prescrever ou dispensar medicamentos