As part of AP&T's peer-review process, a technical check of this meta-analysis was performed by Prof. G. Eslick.
Meta-analysis: underutilisation and disparities of treatment among patients with hepatocellular carcinoma in the United States
Version of Record online: 19 AUG 2013
© 2013 John Wiley & Sons Ltd
Alimentary Pharmacology & Therapeutics
Volume 38, Issue 7, pages 703–712, October 2013
How to Cite
Tan, D., Yopp, A., Beg, M. S., Gopal, P. and Singal, A. G. (2013), Meta-analysis: underutilisation and disparities of treatment among patients with hepatocellular carcinoma in the United States. Alimentary Pharmacology & Therapeutics, 38: 703–712. doi: 10.1111/apt.12450
- Issue online: 3 SEP 2013
- Version of Record online: 19 AUG 2013
- Manuscript Accepted: 21 JUL 2013
- Manuscript Revised: 20 JUL 2013
- Manuscript Revised: 18 JUN 2013
- Manuscript Received: 28 MAY 2013
- Center for Translational Medicine. Grant Number: KL2TR000453
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Despite wide availability of treatment options for hepatocellular carcinoma (HCC), several studies have suggested underutilisation in clinical practice.
To quantify utilisation rates for HCC treatment among patients with HCC in the United States, and to summarise patterns of association between utilisation rates and patient socio-demographic characteristics.
We performed a systematic literature review using the Medline database from January 1989 to March 2013. Two investigators independently extracted data on patient populations, study methods and results using standardised forms. Pooled treatment rates for any treatment and curative treatment, with 95% confidence intervals, were calculated. Prespecified subgroup analysis was performed to identify patient-level correlates of treatment utilisation.
We identified 24 studies that met inclusion criteria. The pooled rates of any treatment and curative treatment were 52.8% (95% CI 52.2–53.4%) and 21.8% (95% CI 21.4–22.1%) respectively. Among patients diagnosed at an early stage, the pooled curative treatment rate was 59.0% (95% CI 58.1–59.9%). Elderly, non-Caucasians and patients of low socioeconomic status had lower treatment rates than their counterparts.
Rates of HCC treatment in the United States, including curative treatment rates among patients detected at an early stage, are disappointingly low. Future efforts should focus on identifying appropriate intervention targets to increase treatment rates and reduce socio-demographic disparities.
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Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related death worldwide and is one of the leading causes of death among patients with cirrhosis. Its incidence in the United States is increasing due to the current epidemic of non-alcoholic fatty liver disease and hepatitis C virus (HCV) infection. Prognosis for patients with HCC depends on tumour stage, degree of underlying liver dysfunction and patient performance status, with curative therapies only available for patients detected at an early stage. Patients detected at an early stage can achieve 5-year survival rates of 70% with transplant or resection, whereas those with advanced HCC are only eligible for palliative treatments and have a median survival of less than 1 year.[2, 3]
Hepatocellular carcinoma disproportionately affects disadvantaged populations, with the highest age-specific incidence occurring among minorities. HCC rates are two times higher in Asian Americans than African Americans, whose rates are two times higher than those in Caucasians. Elderly, African Americans and patients of low socioeconomic status (SES) have poorer survival rates than their counterparts.[4, 5] The reasons for differences in survival are likely multi-factorial, involving a combination of medical, financial and social factors. Several studies have reported lower rates of surveillance, whereas others have postulated biological differences in tumour behaviour, and others have reported differential rates of HCC treatment.[4, 6-8] The aims of our study were to (i) quantify utilisation rates for any treatment and curative treatment among patients with HCC in the United States and (ii) to summarise patterns of association between utilisation rates and patient socio-demographic characteristics.
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We conducted a computer-assisted search with the Ovid interface to Medline to identify relevant published articles. We searched the Medline database from 1 January 1989 to 1 March 2013 with the following keyword combinations: [treatORtherap OR transplantORresect OR surgORablat OR RFA OR chemoORemboliz OR TACE OR nexavar OR sorafenib] AND [hepatocellular caORliverca or HCC]. Given our focus on current utilisation of treatment within the United States, our search was limited to human studies published in English after 1989. Manual searches of references from relevant articles were performed to identify studies that were missed by our computer-assisted search. Finally, consultation with expert hepatologists was performed to identify additional references or unpublished data.
One investigator (D.T.) reviewed all publication titles of citations identified by the search strategy. Potentially relevant studies were retrieved, and selection criteria were applied. The articles were independently checked for inclusion (D.T. and A.S.) and disagreements were resolved through consensus. Inclusion criteria included: (i) cohort studies that described receipt of HCC treatment in patients with HCC (ii) studies from the United States after 1989 so as to be representative of current delivery of care; and (iii) available data regarding socio-demographic information for patients who did and did not receive treatment. We excluded: (i) clinical trials with a protocol and/or extra nursing support as they do not evaluate delivery of care in a real-world clinical setting; (ii) studies conducted outside the United States; and (iii) survey studies because of high rates of over-reporting by physicians. Additional exclusion criteria included non-English language, nonhuman data and lack of original data. If publications used the same patient cohort, data from the most recent manuscript were included.
Two reviewers (D.T. and A.S.) independently extracted required information from eligible studies using standardised forms. A third investigator (A.Y.) was available to resolve any discrepancies. Data were collected on study design, geographical location and date of the study, number of patients with cirrhosis, number of HCC patients and number of patients with early-stage HCC in each study. We recorded definitions of any treatment, curative treatment and early-stage HCC for each study. Finally, data were collected on age, gender, race/ethnicity and SES (insurance status and income) for those who received treatment and those who failed to receive treatment. Authors were contacted as necessary for missing information.
Clinical end point and statistical analysis
Our primary study outcomes were rates of any treatment and rates of curative treatment among patients with HCC. Rates of any treatment included curative treatments (transplant, resection or radiofrequency ablation) and noncurative treatments (chemoembolisation, radiation-based therapy or systemic therapy). Studies that only reported rates of transplantation, resection and/or radiofrequency ablation were included in analyses for receipt of curative treatment but not those for receipt of any treatment.
The proportion of patients who received treatment was derived for each study, and 95% confidence intervals were calculated using the adjusted Wald method. A weighed pooled estimate of treatment rates was computed by multiplying the point estimate for each study by the proportion of individuals in that study relative to the number of individuals in all included studies. Sensitivity analyses were planned for the following predefined variables: (i) the study cohort (single-centre vs. multi-centre administrative database); (ii) the proportion of patients with early-stage HCC; (iii) the definition of curative treatment; and (iv) introduction of the Milan criteria for liver transplantation in 1996. All data analysis was performed using Stata 11 (StataCorp, College Station, TX, USA).
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The computer-assisted search yielded 22 280 potentially relevant articles. After initial review, 264 titles were potentially appropriate, and these abstracts were reviewed. Fifty-seven publications underwent full-text review, and 34 were excluded. Sixteen of these articles were excluded as they were repeat analyses using the same cohort as other studies, eleven were not related to receipt of HCC treatment, four did not have extractable data and three did not have any original data. One additional relevant article was identified through recursive literature searches. The remaining 24 studies met all inclusion criteria[9-32] (Figure S1, Table 1).
|Author, year||Study setting||Mean age (years)||Gender (% male)||Race (% caucasian)||Cirrhosis (%)|
|Altekruse 2012||SEER-Medicare Database||NR||74||49||NR|
|Cance 2000||National Cancer Database||60-69||71||60||NR|
|Harrison 2004||University of Medicine and Dentistry, New Jersey||59||80||61||93|
|Jan 2012||Tulane University||64||76||67||94|
|Jou 2010||Duke University||NR||80||68||100|
|Kanwal 2012||Liver Cancer Research Network||59||76||77||100|
|Kemmer 2008||University of Cincinnati||57||80||64||100|
|Kitisin 2011||University of Pittsburgh||62||75||87||84|
|Kooby 2008||Emory University||60||72||71||82|
|Kozyreva 2011||Tufts University and Massachusetts General Hospital||62||79||77||90|
|Leykum 2007||South Texas VA hospitals||55||100||40||79|
|Sanyal, 2010||Marketscan Claims Research Database||63||66||NR||NR|
|Sarkar 2012||University of California, San Francisco||50-64||78||0||100|
|Schwartz, 1995||Mount Sinai Medical Center||NR||NR||NR||100|
|Shah 2011||SEER-Medicare Database||75||67||74||55|
|Stravitz 2008||Virginia Commonwealth University||57||86||63||100|
|Stuart 1996||Deaconess Health System||64||78||NR||68|
|Theodoropoulos 2011||Hahnemann University||55||80||47||83|
|Tong 2010||University of California, Los Angeles||62||78||0||73|
|Wong 2012||Hawaii Medical Center||62||75||19||74|
|Yang 2011||Mayo Clinic||62||72||83||83|
|Yu 2010||Columbia University||60||80||40||NR|
|Zak 2011||California Cancer Registry||55-64||71||37||NR|
|Zaydfudim 2010||Tennessee Cancer Registry||61||74||78||NR|
|Author, year||Study years||Number of HCC patients||Rates of any HCC treatment (%)|
|Cance 2000||1985–1996||6353||3213 (50.6%)|
|Harrison 2004||1997–2003||264||190 (72.0%)|
|Jan 2012||2003–2011||206||145 (70.4%)|
|Jou 2010||2002–2008||319||207 (64.9%)|
|Kitisin 2011||2000–2009||1010||841 (83.3%)|
|Kooby 2008||1990–2004||501||307 (61.3%)|
|Kozyreva 2011||1998–2008||335||245 (73.1%)|
|Leykum 2007||2000–2005||72||20 (27.8%)|
|Sanyal 2010||2002–2008||4406||3757 (85.3%)|
|Shah 2011||1991–2005||8730||2595 (29.7%)|
|Stravitz 2008||1997–2005||297||233 (78.5%)|
|Stuart 1996||1986–1995||314||233 (74.2%)|
|Theodoropoulos 2011||2001–2007||81||63 (77.8%)|
|Tong 2010||2000–2007||278||236 (84.9%)|
|Wong 2012||1992–2009||618||427 (69.1%)|
|Yang 2011||2007–2009||453||271 (55.2%)|
|Zak 2011||1996–2006||12 148||NR|
|Author, year||Number of early HCC||Definition of early HCC||Curative treatment (%)||Definition curative treatment|
|Altekruse 2012||8940 (41.8%)||Localised||4727 (22.1%)||Resection, OLT and RFA|
|Cance 2000||1252 (19.7%)||AJCC stage I–II||1088 (17.1%)||Surgery|
|Harrison 2004||108 (40.9%)||AJCC stage I–II||68 (25.8%)||Resection and OLT|
|Jan 2012||NR||NR||51 (24.8%)||OLT|
|Jou 2010||151 (47.3%)||BCLC stage A||113 (35.4%)||Resection, OLT and RFA|
|Kanwal 2012||76 (28.5%)||BCLC stage A||135 (50.6%)||Resection, OLT and RFA|
|Kemmer 2008||82 (48.5%)||Milan criteria||24 (14.2%)||OLT|
|Kitisin 2011||NR||NR||302 (29.9%)||Resection, OLT and RFA|
|Kooby 2008||232 (46.3%)||Milan criteria||224 (44.7%)||Resection, OLT and RFA|
|Kozyreva 2011||197 (58.8%)||CLIP stage I–II||104 (31.0%)||Resection and OLT|
|Leykum 2007||28 (38.9%)||Milan criteria||16 (22.2%)||Resection, OLT and RFA|
|Sanyal 2010||NR||NR||932 (21.2%)||Resection, OLT and RFA|
|Sarkar 2012||16 (51.6%)||Milan criteria||15 (48.5%)||Resection, OLT and RFA|
|Schwartz 1995||NR||NR||33 (28.7%)||Resection and OLT|
|Shah 2011||3197 (36.6%)||AJCC stage I–II||NR||Resection, OLT and RFA|
|Stravitz 2008||135 (45.5%)||Milan criteria||60 (20.4%)||OLT|
|Stuart 1996||73 (23.2%)||TNM stage I–II||63 (20.1%)||Resection and OLT|
|Theodoropoulos 2011||27 (33.3%)||BCLC stage A||16 (19.8%)||Resection and OLT|
|Tong 2010||158 (56.8%)||Milan criteria||141 (50.7%)||Resection, OLT and RFA|
|Wong 2012||237 (38.3%)||Milan criteria||187 (30.3%)||Resection and OLT|
|Yang 2011||139 (30.7%)||Milan criteria||79 (17.4%)||Resection, OLT and RFA|
|Yu 2010||246 (53.2%)||AJCC stage I–II||130 (28.1%)||OLT|
|Zak 2011||NR||NR||2390 (19.7%)||Resection, OLT and RFA|
|Zaydfudim 2010||358 (52.6%)||AJCC stage I–II||158 (23.2%)||Resection, OLT and RFA|
There were 16 studies, with a total of 24 237 patients, which assessed receipt of any treatment, including both curative and noncurative treatments, among patients with HCC. Rates of treatment ranged from 28% to 85% among studies, with a pooled treatment rate of 52.8% (95% CI 52.2–53.4%) (Figure 1, Table 2). We evaluated potential sources of heterogeneity through preplanned subgroup analysis. The pooled treatment rate was 49.1% (95% CI 48.4–49.8%) among the 19489 patients in the three multi-centre studies, which was significantly lower than the 72.0% (95% CI 70.7–73.3%) treatment rate among the 13 single-centre studies, which contained a total of 4748 HCC patients (P < 0.001). Among the multi-centre studies, the study by Sanyal and colleagues reported substantially higher treatment rates than the other two studies. Given that this study used insurance claims data, untreated patients who did not receive hospice may not have been fully captured. If this study was removed, the pooled treatment rate of the two remaining multi-centre studies was only 38.5% (95% CI 37.7–39.3%).
Utilisation of curative treatment
There were 23 studies, with a total of 50 769 patients, which assessed receipt of curative treatment among patients with HCC. Rates of curative treatment ranged from 14% to 51% among studies, with a pooled treatment rate of 21.8% (95% CI 21.4–22.1%) (Figure 2, Table 3). Once again, we found substantial heterogeneity between studies, which was explored through sensitivity and subgroup analyses. We first performed a sensitivity analysis based on introduction of the Milan criteria for liver transplantation. When excluding the studies by Stuart and Cance, which both exclusively included cohorts prior to 1996, the pooled treatment rate was 22.5% (95% CI 22.1–22.9%). We next explored heterogeneity through subgroup analyses. The pooled curative treatment rate was 20.8% (95% CI 20.5–21.2%) among 45 244 patients in the six multi-centre studies, which was significantly lower than the 29.4% (95% CI 28.2–30.7%) curative treatment rate among the 17 single-centre studies, which contained a total of 5525 HCC patients (P < 0.001). We also performed a subset analysis, based on the definition of curative treatment. Studies that included transplant, resection and RFA as curative treatments had a pooled curative treatment rate of 22.2% (95% CI 21.8–22.6%) compared to a pooled rate of 19.8% (95% CI 19.0–20.6%) among studies that only included surgical treatment (liver transplantation and/or resection) (P < 0.001).
Eighteen of the studies reported the number of patients with early HCC. Of the 32 884 HCC patients in these studies, 12 455 (37.9%) had early-stage HCC. The pooled curative treatment rate among patients with early-stage HCC was 59.0% (95% CI 58.1–59.9%) (Figure 3). When excluding the two studies by Stuart and Cance, the pooled treatment rate was 54.9% (95% CI 54.0–55.9%). Only three studies defined early stage with the Barcelona Clinic Liver Cancer (BCLC) staging system, while an additional eight studies used Milan criteria. The other seven studies used a variety of definitions including the American Joint Committee on Cancer (AJCC) or Tumor Node Metastases (TNM) staging systems. The pooled curative treatment rate among studies using the BCLC or Milan criteria was 72.4% (95% CI 69.9–74.8%), which was significantly higher than the pooled curative treatment rate of 56.7% (95% CI 55.8–57.6%) among studies using other definitions (P < 0.001).
Correlates of HCC treatment
Several patient factors are associated with higher utilisation rates for HCC treatment, but heterogeneity in the reporting of these associations precluded pooling of the data.
Older age was a consistent negative predictor of HCC treatment, with five studies reporting higher treatment rates in younger patients.[17, 19, 22, 29, 30] Most studies lacked sufficient data to adjust for potential differences in tumour stage at presentation.[19, 22, 30] However, Kozyreva and colleagues found that patients older than 70 years were significantly less likely to receive any treatment than younger patients (36.8% vs. 22.9%, P = 0.01) despite having similar tumour stage (P = 0.95) and liver function as younger patients (Child A 57.9% vs. 56.7%).
The majority of studies that evaluated the impact of gender found no difference in treatment rates between males and females.[16, 22, 29, 30] The study by Zaydfudim and colleagues was the only that suggested differential treatment rates by gender. They found that females had a 1.78 odds (95% CI 1.15–2.76) of undergoing surgical treatment, after adjusting for age, race, insurance status and tumour stage.
Five included studies demonstrated disparities in HCC treatment utilisation, particularly that of curative treatments, according to race.[11, 22, 27, 29, 30] Studies by Zak and Harrison reported lower treatment rates among African American patients, but lacked sufficient data to adjust for differences in tumour stage and/or liver function.[11, 30] Similarly, Shah and colleagues found higher treatment rates among Asian patients using the SEER-Medicare database, but it is unknown if this is related to differential rates of underlying cirrhosis. Yu and colleagues found that African Americans were significantly less likely to receive a transplant than Caucasian patients (OR 0.03, 95% CI 0.00–0.37) after adjusting for confounders including age, insurance status and tumour stage, but did not find a significant association with Hispanic ethnicity (OR 0.42, 95% CI 0.09–2.08). Similarly, Wong and colleagues found that Pacific Islanders and Filipinos who were detected at an early stage were significantly less likely to undergo liver transplant than Caucasians (10.0% vs. 38.0%).
The impact of SES on HCC treatment utilisation has only been evaluated in four studies.[22, 29-31] Several other studies evaluated patients with insurance or easy access to health care and therefore were unable to determine the impact of SES on treatment utilisation.[9, 18, 19] There was a consistent effect of higher treatment rates among patients with private insurance compared with patients without insurance or those with Medicare/Medicaid. In the Tennessee Cancer Registry, both uninsured patients (OR 0.05, 95% CI 0.01–0.37) and those with Medicaid (OR 0.32, 95% CI 0.15–0.69) were significantly less likely to receive surgical therapy than those with private insurance, after adjusting for age, gender, race and tumour stage. Yu and colleagues reported similar results, with privately insured patients significantly more likely to receive liver transplantation (OR 22.07, 95% CI 2.67–182.34), independent of tumour stage.
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Despite strong evidence demonstrating that HCC treatment significantly improves survival, our meta-analysis highlights that many patients with HCC fail to receive treatment in clinical practice. We found less than one fourth of patients with HCC undergo curative treatment, and nearly 50% do not receive any treatment. The low rates of curative treatment are in part related to diagnoses at an advanced stage; however, more than one third of patients diagnosed at an early stage do not receive curative treatment. Our study also highlights the presence of significant socio-demographic disparities, with the lowest treatment rates among non-Caucasians and patients of low SES.
The transition from diagnosis to treatment is a complex process, involving several steps and interfaces with multiple new providers. Providers must be aware of the cancer diagnosis, complete the staging work-up, determine the optimal treatment and finally refer patients to the appropriate consultants. The complex array of potential treatment options, each delivered by a different type of provider, may make this process even more difficult for HCC. These treatment decisions for HCC have become increasingly complex with the availability of novel therapies and the growing use of multimodal and multi-provider treatments. Patients may be asked to make multiple transitions between several providers as various treatment options are considered. A breakdown at any step can result in treatment underutilisation and/or treatment delays. Even in the setting of optimal processes, patients may choose to forgo therapy, given disinterest, other barriers to care or perceived excess risk from the treatment. Current studies fail to provide an in-depth analysis to clarify which factors mediate or moderate underutilisation of HCC treatment. A multidisciplinary approach involving a team of hepatologists, surgeons, interventional radiologists, radiation oncologists, medical oncologists and radiologists may improve communication and allow better delivery of optimal treatment. Further research is needed to evaluate the benefits of multidisciplinary care and identify other potential intervention strategies to increase appropriate HCC treatment.
Therapeutic choices for HCC are dependent on tumour stage, liver function and performance status. Although there is not one universally accepted staging system, the BCLC staging system has been incorporated into guidelines and is the most widely used, given that it combines all three features.[37, 38] However, it is important to note that most studies, particularly those from large administrative databases, provide limited data regarding liver function or patient performance status. This lack of data precludes an accurate assessment of the appropriateness of lack of treatment. For example, it would be appropriate to not treat a patient with poor functional status, but this would be regarded as treatment underutilisation in several studies included in this meta-analysis. Automated data has been demonstrated to underestimate quality of care in other areas, such as HCV-related care, for similar reasons. It is crucial that future studies provide data regarding liver function and patient performance status to better interpret treatment utilisation rates.
The low curative treatment rates appear to be related to high rates of late-stage diagnosis, as only 40% of patients are diagnosed at an early stage despite the availability of efficacious surveillance tools. When examining the subgroup of patients detected at an early stage, curative treatment rates are closer to 57–73%, depending on the definition of early-stage HCC. The low rates of early tumour detection are multi-factorial, with surveillance underuse and suboptimal effectiveness of surveillance tools in clinical practice both playing a large role.[41-44] Patients diagnosed incidentally or symptomatically are significantly more likely to be diagnosed at an advanced stage, when curative options are no longer an option.[23, 45] Interventions are needed to improve surveillance rates, which can increase early tumour detection, facilitate higher rates of curative treatment and thereby improve overall survival.[36, 46]
Racial and socioeconomic disparities have been well described in the survival of patients with HCC. Although prior studies have suggested difference in tumour biology and/or surveillance rates, our meta-analysis highlights the importance of socio-demographic disparities in treatment utilisation. Patients who are elderly, non-Caucasian and of low SES suffer from significantly lower HCC treatment rates than their counterparts. Although current studies suggest an association between socio-demographic factors and HCC treatment, none have explored why treatment is not being performed in these subgroups. The roles of patient attitudes, co-morbid conditions and barriers to accessing care have not been clearly evaluated. For example, elderly patients and patients of low SES may have lower treatment rates due to difficulty accessing medical care or a higher rate of co-morbid conditions. Similarly, race and SES are often highly correlated, so independent causal effects can be difficult to identify.
The primary limitation of our meta-analysis was our inability to identify specific reasons for underutilisation of HCC treatment. Current studies did not distinguish cases in which physicians failed to order treatment, cases in which treatment was not appropriate (e.g. patients with significant co-morbidities or those with Child C cirrhosis who were not transplant candidates) and those in which patients were non-adherent after treatment was recommended. Studies evaluating the reasons behind treatment under-utilisation are necessary to identify intervention targets that can increase treatment rates.
Our meta-analysis was also limited by clinical heterogeneity among studies, such as the different operational definitions used for early-stage disease and/or curative treatment. This variability in definitions makes it difficult to compare treatment rates across studies. Clear consistent definitions and measures are necessary to better quantify and interpret HCC treatment rates. This clinical heterogeneity may also relate to other aetiologies such as inter-centre variation in treatment rates, similar to what has been reported for HCC surveillance. Inter-centre variation in treatment rates may be even larger given the selected availability of some treatments, such as liver transplantation. Another possible explanation of clinical heterogeneity is changes in treatment expertise over time; however, we did not see any evidence of a time trend on subgroup analysis.
In summary, HCC treatment is underutilised nationally, with nearly 50% failing to receive any treatment and less than 25% receiving curative treatment. Even among patients diagnosed at an early stage, more than one in three fail to receive curative treatment. There are also significant socio-demographic disparities with the lowest treatment rates in non-Caucasians and patients of low SES. Further studies are needed to explore reasons for the underutilisation of treatment, particularly in these disadvantaged subgroups. These studies will be the first crucial step in identifying appropriate intervention targets to increase HCC treatment rates and reduce socio-demographic disparities.
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Guarantor of the article: Amit Singal.
Author contributions: Debra Tan was involved in acquisition of data, interpretation of data, drafting of the manuscript and critical revision of the manuscript for important intellectual content. Adam Yopp was involved in study concept and design, interpretation of data and critical revision of the manuscript for important intellectual content. Muhammad Beg was involved in critical revision of the manuscript for important intellectual content. Purva Gopal was involved in critical revision of the manuscript for important intellectual content. Amit Singal was involved in study concept and design, acquisition of data, analysis and interpretation of data, drafting of the manuscript, critical revision of the manuscript for important intellectual content, statistical analysis and study supervision.
All authors approved the final version of the manuscript.
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Declaration of personal interests: Amit Singal and Adam Yopp are on the Speaker Bureau for Bayer and Onyx Pharmaceuticals.
Declaration of funding interests: This study was conducted with support from Center for Translational Medicine, NIH/NCATS Grant Number KL2TR000453 and an ACG Junior Faculty Development Award. The content is solely the responsibility of the authors and does not necessarily represent the official views of the Center for Translational Medicine, UT Southwestern Medical Center and its affiliated academic and health care centres, the National Center for Advancing Translational Sciences or the National Institutes of Health.
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|apt12450-sup-0001-FigS1.pdf||application/PDF||98K||Figure S1. Flow diagram of included articles.|
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