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Singal A.G.,Southwestern Medical Center | Singal A.G.,Southwestern University | Singal A.G.,Harold mmons Cancer Center | Nehra M.,Southwestern Medical Center | And 7 more authors.
American Journal of Gastroenterology | Year: 2013

OBJECTIVES:Only 40% of patients with hepatocellular carcinoma (HCC) are diagnosed at an early stage, suggesting breakdowns in the surveillance process. The aim of our study was to assess the reasons behind surveillance process failures among patients in the Hepatitis C Antiviral Long-Term Treatment against Cirrhosis Trial (HALT-C), which prospectively collected HCC surveillance data on a large cohort of patients.METHODS:Binary regression analysis was used to identify predictors of consistent surveillance, which was defined as having an ultrasound and alpha-fetoprotein every 12 months. Surveillance failures among patients who developed HCC were classified into one of three categories: absence of screening, absence of follow-up, or absence of detection.RESULTS:Over a mean follow-up of 6.1 years, 692 (68.9%) of 1,005 patients had consistent surveillance. Study site was the strongest predictor of consistent surveillance (P<0.001). After adjusting for study site, patient-level predictors of consistent surveillance included platelet count >150,000/mm 3 (hazard ratio (HR) 1.28; 95% confidence interval (CI): 1.05-1.56) and complete clinic visit adherence (HR 1.72, 95% CI: 1.11-2.63). Of 83 patients with HCC, 23 (27.7%) were detected beyond Milan criteria. Three (13%) had late-stage HCC due to the absence of screening, 4 (17%) due to the absence of follow-up, and 16 (70%) due to the absence of detection.CONCLUSIONS:Surveillance process failures, including absence of screening or follow-up, are common and potentially contribute to late-stage tumors in one-third of cases. However, the most common reason for finding HCC at a late stage was an absence of detection, suggesting better surveillance strategies are needed. Source

Chivukula R.R.,Johns Hopkins University | Shi G.,Southwestern Medical Center | Acharya A.,Southwestern Medical Center | Mills E.W.,Johns Hopkins University | And 9 more authors.
Cell | Year: 2014

Downregulation of the miR-143/145 microRNA (miRNA) cluster has been repeatedly reported in colon cancer and other epithelial tumors. In addition, overexpression of these miRNAs inhibits tumorigenesis, leading to broad consensus that they function as cell-autonomous epithelial tumor suppressors. We generated mice with deletion of miR-143/145 to investigate the functions of these miRNAs in intestinal physiology and disease in vivo. Although intestinal development proceeded normally in the absence of these miRNAs, epithelial regeneration after injury was dramatically impaired. Surprisingly, we found that miR-143/145 are expressed and function exclusively within the mesenchymal compartment of intestine. Defective epithelial regeneration in miR-143/145-deficient mice resulted from the dysfunction of smooth muscle and myofibroblasts and was associated with derepression of the miR-143 target Igfbp5, which impaired IGF signaling after epithelial injury. These results provide important insights into the regulation of epithelial wound healing and argue against a cell-autonomous tumor suppressor role for miR-143/145 in colon cancer. © 2014 Elsevier Inc. Source

Lee S.C.,University of Texas Southwestern Medical Center | Lee S.C.,Harold mmons Cancer Center | Marks E.G.,University of Texas Southwestern Medical Center | Sanders J.M.,University of Texas Southwestern Medical Center | Wiebe D.J.,University of CaliforniaMerced
Journal of Cancer Survivorship | Year: 2016

Purpose: We explored patient-perceived role in “decision-making” related to active treatment and palliation among African Americans receiving lung cancer care through a county safety-net system. Methods: Drawing from a cohort of over 100 African Americans treated in a safety-net hospital, we invited a subsample of 13 patient-caregiver dyads to participate in a series of dyadic, ethnographic interviews conducted at the patients’ homes. Over 40 h of transcripts were analyzed in an iterative process resulting in reported themes. Results: Findings from ethnographic interviews demonstrated that healthcare communication with physicians is difficult for patients. While caregivers and patients describe a deep engagement in lung cancer care, they expressed a concurrent lack of understanding of their prognosis and outcomes of treatment. Dyads did not discuss their lung cancer experience in terms of decision-making; rather, most articulated their role as following physician guidance. Distinct lack of understanding about disease course, severity, and prognosis may constrain patient perception of the need for informed decision-making over the course of care. Conclusions: Dyadic interviews detailing safety-net patient experiences of lung cancer care raise important questions about how clinicians, as well as researchers, conceptualize processes of informed decision-making in vulnerable populations. Implications for Cancer Survivors: Safety-net patients may not perceive their role as involving informed decision-making and further may lack understanding of disease course and individual prognosis. Safety-net patient dyads expressed high involvement in care and a desire for clarity; clinicians should be prepared to clearly communicate disease stage and prognosis. © 2015, Springer Science+Business Media New York. Source

Shen M.J.,Sloan Kettering Cancer Center | Coups E.J.,The New School | Li Y.,Sloan Kettering Cancer Center | Holland J.C.,Sloan Kettering Cancer Center | And 2 more authors.
Psycho-Oncology | Year: 2015

Objective Patients diagnosed with lung cancer report high levels of stigma and psychological distress. This study examined posttraumatic growth among lung cancer survivors as a potential buffer against this relationship between stigma and psychological distress and examined how these relationships differed by the timing of quitting smoking (pre versus post-diagnosis). Methods Stages IA and IB non-small-cell lung cancer survivors (N = 141) who were former smokers, 1-6 years post-treatment, and had no evidence of disease completed standardized questionnaires assessing stigma, posttraumatic growth, timing of quitting smoking history, and psychological distress. Results Hierarchical linear regression and simple slope analyses indicated that among those who quit smoking prior to diagnosis (pre-diagnosis quitters), stigma had a positive association with psychological distress at high levels of posttraumatic growth (p = 0.003) and had a positive (but non-significant) association with psychological distress among those with low levels of posttraumatic growth (p = 0.167). Among those who quit smoking after diagnosis (post-diagnosis quitters), stigma had a positive association with psychological distress among those with low levels of posttraumatic growth (p = 0.004) but had no relationship among those with high levels of posttraumatic growth (p = 0.880). Conclusions Findings indicate that posttraumatic growth buffers against the negative effects of stigma on psychological distress but only among post-diagnosis quitters. Future interventions could focus on fostering posttraumatic growth as a way to decrease the negative effects of stigma. Copyright © 2014 John Wiley & Sons, Ltd. Copyright © 2014 John Wiley & Sons, Ltd. Source

Singal A.G.,Southwestern Medical Center | Singal A.G.,Southwestern University | Singal A.G.,Harold mmons Cancer Center | Mukherjee A.,University of Michigan | And 7 more authors.
American Journal of Gastroenterology | Year: 2013

OBJECTIVES:Predictive models for hepatocellular carcinoma (HCC) have been limited by modest accuracy and lack of validation. Machine-learning algorithms offer a novel methodology, which may improve HCC risk prognostication among patients with cirrhosis. Our study's aim was to develop and compare predictive models for HCC development among cirrhotic patients, using conventional regression analysis and machine-learning algorithms.METHODS:We enrolled 442 patients with Child A or B cirrhosis at the University of Michigan between January 2004 and September 2006 (UM cohort) and prospectively followed them until HCC development, liver transplantation, death, or study termination. Regression analysis and machine-learning algorithms were used to construct predictive models for HCC development, which were tested on an independent validation cohort from the Hepatitis C Antiviral Long-term Treatment against Cirrhosis (HALT-C) Trial. Both models were also compared with the previously published HALT-C model. Discrimination was assessed using receiver operating characteristic curve analysis, and diagnostic accuracy was assessed with net reclassification improvement and integrated discrimination improvement statistics.RESULTS:After a median follow-up of 3.5 years, 41 patients developed HCC. The UM regression model had a c-statistic of 0.61 (95% confidence interval (CI) 0.56-0.67), whereas the machine-learning algorithm had a c-statistic of 0.64 (95% CI 0.60-0.69) in the validation cohort. The HALT-C model had a c-statistic of 0.60 (95% CI 0.50-0.70) in the validation cohort and was outperformed by the machine-learning algorithm. The machine-learning algorithm had significantly better diagnostic accuracy as assessed by net reclassification improvement (P<0.001) and integrated discrimination improvement (P=0.04).CONCLUSIONS:Machine-learning algorithms improve the accuracy of risk stratifying patients with cirrhosis and can be used to accurately identify patients at high-risk for developing HCC. Source

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