scholarly journals Factors Associated With Detection and Survival of T1 Hepatocellular Carcinoma in the United States: National Cancer Database Analysis

2020 ◽  
Vol 18 (9) ◽  
pp. 1210-1220
Author(s):  
Ju Dong Yang ◽  
Michael Luu ◽  
Amit G. Singal ◽  
Mazen Noureddin ◽  
Alexander Kuo ◽  
...  
Keyword(s):  
United States ◽  
The United States ◽  
Meld Score ◽  
Academic Institution ◽  
National Cancer Database ◽  
Factors Associated ◽  
Academic Center ◽  
Pertinent Data ◽  
T1 Stage ◽  
End Stage

Background: It remains unknown to what extent hepatocellular carcinomas (HCCs) are detected very early (T1 stage; ie, unifocal <2 cm) in the United States. The aim of this study was to investigate the trends and factors associated with very early detection of HCC and resultant outcomes. Methods: Patients with HCC diagnosed from 2004 through 2014 were identified from the National Cancer Database. Logistic regression was used to identify factors associated with T1 HCC detection, and Cox proportional hazard analyses identified factors associated with overall survival among patients with T1 HCC. Results: Of 110,182 eligible patients, the proportion with T1 HCC increased from 2.6% in 2004 to 6.8% in 2014 (P<.01). The strongest correlate of T1 HCC detection was receipt of care at an academic institution (odds ratio, 3.51; 95% CI, 2.31–5.34). Older age, lack of insurance, high Model for End-Stage Liver Disease (MELD) score, high alpha-fetoprotein, increased Charlson-Deyo comorbidity score, and nonsurgical treatment were associated with increased mortality, and care at an academic center (hazard ratio [HR], 0.27; 95% CI, 0.15–0.48) was associated with reduced mortality in patients with T1 HCC. Liver transplantation (HR, 0.27; 95% CI, 0.20–0.37) and surgical resection (HR, 0.67; 95% CI, 0.48–0.93) were independently associated with improved survival compared with ablation. This is the first study to examine the trend of T1 HCC using the National Cancer Database, which covers approximately 70% of all cancer diagnoses in the United States, using robust statistical analyses. Limitations of the study include a retrospective study design using administrative data and some pertinent data that were not available. Conclusions: Despite increases over time, <10% of HCCs are detected at T1 stage. The strongest correlates of survival among patients with T1 HCC are receiving care at an academic institution and surgical treatment.

A Critical Review of MELD as a Reliable Tool for Transplant Prioritization

2019 ◽  
Vol 39 (04) ◽  
pp. 403-413 ◽  
Author(s):  
Sophie-Caroline Sacleux ◽  
Didier Samuel
Keyword(s):  
United States ◽  
Serum Creatinine ◽  
International Normalized Ratio ◽  
The United States ◽  
Meld Score ◽  
Waiting List ◽  
Organ Shortage ◽  
Short Term ◽  
Short Term Mortality ◽  
End Stage

AbstractIn a context of global organ shortage, the Model for End-Stage Liver Disease (MELD) score seems to be a fair prioritization tool, with a paradigm: “sickest first.” Since its introduction in the United States in 2002, it has been rapidly adopted by transplant centers and organ sharing agencies around the world. The MELD score showed its effectiveness with a 12% reduction in waiting list mortality in the United States. Its success is linked to its simplicity, the use of basic variables (serum creatinine, serum bilirubin, and international normalized ratio [INR]), and its ability to predict short-term mortality, particularly on the transplant waiting list. However, this score is not perfect: its variables may have disadvantages for some patients, especially women, with serum creatinine and interlaboratory variability of the INR. The MELD score does not take into account some variables associated with poor short-term prognosis in cirrhotic patients. In addition, it is currently capped at 40, which results in the exclusion of sicker patients who could greatly benefit from transplantation. Finally, the MELD score does not accurately reflect the prognosis of several conditions, requiring a MELD exception system. Some solutions have been suggested such as MELD-Na or MELD uncapping, but it has not yet been fully accepted by all transplant centers.

scholarly journals Sociodemographic and Clinical Risk Factors Associated With Tuberculosis Mortality in the United States, 2009-2013

2017 ◽  
Vol 132 (3) ◽  
pp. 366-375 ◽  
Author(s):  
Haylea A. Hannah ◽  
Roque Miramontes ◽  
Neel R. Gandhi
Keyword(s):  
United States ◽  
Risk Factors ◽  
Multinomial Logistic Regression ◽  
The United States ◽  
Multidrug Resistant ◽  
Multinomial Logistic Regression Analysis ◽  
Factors Associated ◽  
Specific Mortality ◽  
Stage Renal Disease ◽  
End Stage

Objectives: The objectives of our study were (1) to determine risk factors associated with tuberculosis (TB)–specific and non–TB-specific mortality among patients with TB and (2) to examine whether risk factors for TB-specific mortality differed from those for non–TB-specific mortality. Methods: We obtained data from the National Tuberculosis Surveillance System and included all patients who had TB between 2009 and 2013 in the United States and its territories. We used multinomial logistic regression analysis to determine the adjusted odds ratio (aOR) of each risk factor for TB-specific and non–TB-specific mortality. Results: Of 52 175 eligible patients with TB, 1404 died from TB, and 2413 died from other causes. Some of the risk factors associated with the highest odds of TB-specific mortality were multidrug-resistant TB diagnosis (aOR = 3.42; 95% CI, 1.95-5.99), end-stage renal disease (aOR = 3.02; 95% CI, 2.23-4.08), human immunodeficiency virus infection (aOR = 2.63; 95% CI, 2.02-3.42), age 45-64 years (aOR = 2.57; 95% CI, 2.01-3.30) or age ≥65 years (aOR = 5.76; 95% CI, 4.37-7.61), and immunosuppression (aOR = 2.20; 95% CI, 1.71-2.83). All of these risk factors except multidrug-resistant TB were also associated with increased odds of non–TB-specific mortality. Conclusion: TB patients with certain risk factors have an elevated risk of TB-specific mortality and should be monitored before, during, and after treatment. Identifying the predictors of TB-specific mortality may help public health authorities determine which subpopulations to target and where to allocate resources.

Mass School Shootings in the United States: A Novel Root Cause Analysis Using Lay Press Reports

2019 ◽  
Vol 58 (13) ◽  
pp. 1423-1428 ◽  
Author(s):  
Chris A. Rees ◽  
Lois K. Lee ◽  
Eric W. Fleegler ◽  
Rebekah Mannix
Keyword(s):  
United States ◽  
Environmental Factors ◽  
Root Cause Analysis ◽  
The United States ◽  
School Shootings ◽  
Contributing Factors ◽  
Mass Shootings ◽  
Cause Analysis ◽  
Factors Associated ◽  
Root Cause

School shootings comprise a small proportion of childhood deaths from firearms; however, these shootings receive a disproportionately large share of media attention. We conducted a root cause analysis of 2 recent school shootings in the United States using lay press reports. We reviewed 1760 and analyzed 282 articles from the 10 most trusted news sources. We identified 356 factors associated with the school shootings. Policy-level factors, including a paucity of adequate legislation controlling firearm purchase and ownership, were the most common contributing factors to school shootings. Mental illness was a commonly cited person-level factor, and access to firearms in the home and availability of large-capacity firearms were commonly cited environmental factors. Novel approaches, including root cause analyses using lay media, can identify factors contributing to mass shootings. The policy, person, and environmental factors associated with these school shootings should be addressed as part of a multipronged effort to prevent future mass shootings.

scholarly journals MRI-based radiomic feature analysis of end-stage liver disease for severity stratification

2021 ◽  
Author(s):  
Jennifer Nitsch ◽  
Jordan Sack ◽  
Michael W. Halle ◽  
Jan H. Moltz ◽  
April Wall ◽  
...  
Keyword(s):  
Disease Severity ◽  
Prediction Models ◽  
Blood Parameters ◽  
Meld Score ◽  
Poor Correlation ◽  
Discrimination Ability ◽  
Random Forest Classification ◽  
Forest Classification ◽  
Academic Center ◽  
End Stage

Abstract Purpose We aimed to develop a predictive model of disease severity for cirrhosis using MRI-derived radiomic features of the liver and spleen and compared it to the existing disease severity metrics of MELD score and clinical decompensation. The MELD score is compiled solely by blood parameters, and so far, it was not investigated if extracted image-based features have the potential to reflect severity to potentially complement the calculated score. Methods This was a retrospective study of eligible patients with cirrhosis ($$n=90$$ n = 90 ) who underwent a contrast-enhanced MR screening protocol for hepatocellular carcinoma (HCC) screening at a tertiary academic center from 2015 to 2018. Radiomic feature analyses were used to train four prediction models for assessing the patient’s condition at time of scan: MELD score, MELD score $$\ge $$ ≥ 9 (median score of the cohort), MELD score $$\ge $$ ≥ 15 (the inflection between the risk and benefit of transplant), and clinical decompensation. Liver and spleen segmentations were used for feature extraction, followed by cross-validated random forest classification. Results Radiomic features of the liver and spleen were most predictive of clinical decompensation (AUC 0.84), which the MELD score could predict with an AUC of 0.78. Using liver or spleen features alone had slightly lower discrimination ability (AUC of 0.82 for liver and AUC of 0.78 for spleen features only), although this was not statistically significant on our cohort. When radiomic prediction models were trained to predict continuous MELD scores, there was poor correlation. When stratifying risk by splitting our cohort at the median MELD 9 or at MELD 15, our models achieved AUCs of 0.78 or 0.66, respectively. Conclusions We demonstrated that MRI-based radiomic features of the liver and spleen have the potential to predict the severity of liver cirrhosis, using decompensation or MELD status as imperfect surrogate measures for disease severity.

scholarly journals Racial Differences in Incident Genitourinary Cancer Cases Captured in the National Cancer Database

Medicina ◽  
2021 ◽  
Vol 57 (7) ◽  
pp. 671
Author(s):  
Dylan T. Wolff ◽  
Thomas F. Monaghan ◽  
Danielle J. Gordon ◽  
Kyle P. Michelson ◽  
Tashzna Jones ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
United States ◽  
Bladder Cancer ◽  
Kidney Cancer ◽  
The United States ◽  
Coverage Rate ◽  
National Cancer Database ◽  
Genitourinary Cancer ◽  
Coverage Rates ◽  
Capture Rates

Background and Objectives: The National Cancer Database (NCDB) captures nearly 70% of all new cancer diagnoses in the United States, but there exists significant variation in this capture rate based on primary tumor location and other patient demographic factors. Prostate cancer has the lowest coverage rate of all major cancers, and other genitourinary malignancies likewise fall below the average NCDB case coverage rate. We aimed to explore NCDB coverage rates for patients with genitourinary cancers as a function of race. Materials and Methods: We compared the incidence of cancer cases in the NCDB with contemporary United States Cancer Statistics data. Results: Across all malignancies, American Indian/Alaskan Natives subjects demonstrated the lowest capture rates, and Asian/Pacific Islander subjects exhibited the second-lowest capture rates. Between White and Black subjects, capture rates were significantly higher for White subjects overall and for prostate cancer and kidney cancer in White males, but significantly higher for bladder cancer in Black versus White females. No significant differences were observed in coverage rates for kidney cancer in females, bladder cancer in males, penile cancer, or testicular cancer in White versus Black patients. Conclusions: Differential access to Commission on Cancer-accredited treatment facilities for racial minorities with genitourinary cancer constitutes a unique avenue for health equity research.

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