Anaplastic thyroid carcinoma: three protocols combining doxorubicin, hyperfractionated radiotherapy and surgery

Patients with anaplastic thyroid carcinoma can rarely be cured, but every effort should be made to prevent death due to suffocation. Between 1984 and 1999, 55 consecutive patients with anaplastic thyroid carcinoma were prospectively treated according to a combined regimen consisting of hyperfractionated radiotherapy, doxorubicin, and when feasible surgery. Radiotherapy was carried out for 5 days a week. The daily fraction until 1988 was 1.0 Gy×2 (A) and 1989–92 1.3 Gy×2 (B) . Thereafter 1.6 Gy×2 (C) was administered. Radiotherapy was administered to a total target dose of 46 Gy; of which 30 Gy was administered preoperatively in the first two protocols (A and B), while the whole dose was given preoperatively in the third protocol (C). The therapy was otherwise identical. Twenty mg doxorubicin was administered intravenously weekly. Surgery was possible in 40 patients. No patient failed to complete the protocol due to toxicity. In only 13 cases (24%) was death attributed to local failure. Five patients (9%) ‘had a survival’ exceeding 2 years. No signs of local recurrence were seen in 33 patients (60%); 5 out of 16 patients in Protocol A, 11 out of 17 patients in Protocol B, 17 out of 22 patients in Protocol C (P=0.017). In the 40 patients undergoing additional surgery, no signs of local recurrence were seen in 5 out of 9 patients, 11 out of 14 patients and 17 out of 17 patients, respectively (P=0.005)

Down-regulation of transcription elogation factor A (SII) like 4 (TCEAL4) in anaplastic thyroid cancer

BACKGROUND: Anaplastic thyroid cancer (ATC) is one of the most aggressive human malignancies and appears to arise mainly from transformation of pre-existing differentiated thyroid cancer (DTC). However, the carcinogenic mechanism of anaplastic transformation remains unclear. Previously, we investigated specific genes related to ATC based on gene expression profiling using cDNA microarray analysis. One of these genes, transcription elongation factor A (SII)-like 4 (TCEAL4), encodes a member of the transcription elongation factor A (SII)-like gene family. The detailed function of TCEAL4 has not been described nor has any association between this gene and human cancers been reported previously. METHODS: To investigate the role of TCEAL4 in ATC carcinogenesis, we examined expression levels of TCEAL4 in ACLs as well as in other types of thyroid cancers and normal human tissue. RESULTS: Expression of TCEAL4 was down-regulated in all 11 ACLs as compared to either normal thyroid tissues or papillary and follicular thyroid cancerous tissues. TCEAL4 was expressed ubiquitously in all normal human tissues tested. CONCLUSION: To our knowledge, this is the first report of altered TCEAL4 expression in human cancers. We suggest that loss of TCEAL4 expression might be associated with development of ATC from DTC. Further functional studies are required

Inferring MicroRNA Activities by Combining Gene Expression with MicroRNA Target Prediction

MicroRNAs (miRNAs) play crucial roles in a variety of biological processes via regulating expression of their target genes at the mRNA level. A number of computational approaches regarding miRNAs have been proposed, but most of them focus on miRNA gene finding or target predictions. Little computational work has been done to investigate the effective regulation of miRNAs.We propose a method to infer the effective regulatory activities of miRNAs by integrating microarray expression data with miRNA target predictions. The method is based on the idea that regulatory activity changes of miRNAs could be reflected by the expression changes of their target transcripts measured by microarray. To validate this method, we apply it to the microarray data sets that measure gene expression changes in cell lines after transfection or inhibition of several specific miRNAs. The results indicate that our method can detect activity enhancement of the transfected miRNAs as well as activity reduction of the inhibited miRNAs with high sensitivity and specificity. Furthermore, we show that our inference is robust with respect to false positives of target prediction.A huge amount of gene expression data sets are available in the literature, but miRNA regulation underlying these data sets is largely unknown. The method is easy to be implemented and can be used to investigate the miRNA effective regulation underlying the expression change profiles obtained from microarray experiments

Assessing socioeconomic health care utilization inequity in Israel: impact of alternative approaches to morbidity adjustment

<p/> <p>Background</p> <p>The ability to accurately detect differential resource use between persons of different socioeconomic status relies on the accuracy of health-needs adjustment measures. This study tests different approaches to morbidity adjustment in explanation of health care utilization inequity.</p> <p>Methods</p> <p>A representative sample was selected of 10 percent (~270,000) adult enrolees of Clalit Health Services, Israel's largest health care organization. The Johns-Hopkins University Adjusted Clinical Groups^®were used to assess each person's overall morbidity burden based on one year's (2009) diagnostic information. The odds of above average health care resource use (primary care visits, specialty visits, diagnostic tests, or hospitalizations) were tested using multivariate logistic regression models, separately adjusting for levels of health-need using data on age and gender, comorbidity (using the Charlson Comorbidity Index), or morbidity burden (using the Adjusted Clinical Groups). Model fit was assessed using tests of the Area Under the Receiver Operating Characteristics Curve and the Akaike Information Criteria.</p> <p>Results</p> <p>Low socioeconomic status was associated with higher morbidity burden (1.5-fold difference). Adjusting for health needs using age and gender or the Charlson index, persons of low socioeconomic status had greater odds of above average resource use for all types of services examined (primary care and specialist visits, diagnostic tests, or hospitalizations). In contrast, after adjustment for overall morbidity burden (using Adjusted Clinical Groups), low socioeconomic status was no longer associated with greater odds of specialty care or diagnostic tests (OR: 0.95, CI: 0.94-0.99; and OR: 0.91, CI: 0.86-0.96, for specialty visits and diagnostic respectively). Tests of model fit showed that adjustment using the comprehensive morbidity burden measure provided a better fit than age and gender or the Charlson Index.</p> <p>Conclusions</p> <p>Identification of socioeconomic differences in health care utilization is an important step in disparity reduction efforts. Adjustment for health-needs using a comprehensive morbidity burden diagnoses-based measure, this study showed relative underutilization in use of specialist and diagnostic services, and thus allowed for identification of inequity in health resources use, which could not be detected with less comprehensive forms of health-needs adjustments.</p

Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI): A Prospective Longitudinal Observational Study

BACKGROUND: Current classification of traumatic brain injury (TBI) is suboptimal, and management is based on weak evidence, with little attempt to personalize treatment. A need exists for new precision medicine and stratified management approaches that incorporate emerging technologies. OBJECTIVE: To improve characterization and classification of TBI and to identify best clinical care, using comparative effectiveness research approaches. METHODS: This multicenter, longitudinal, prospective, observational study in 22 countries across Europe and Israel will collect detailed data from 5400 consenting patients, presenting within 24 hours of injury, with a clinical diagnosis of TBI and an indication for computed tomography. Broader registry-level data collection in approximately 20 000 patients will assess generalizability. Cross sectional comprehensive outcome assessments, including quality of life and neuropsychological testing, will be performed at 6 months. Longitudinal assessments will continue up to 24 months post TBI in patient subsets. Advanced neuroimaging and genomic and biomarker data will be used to improve characterization, and analyses will include neuroinformatics approaches to address variations in process and clinical care. Results will be integrated with living systematic reviews in a process of knowledge transfer. The study initiation was from October to December 2014, and the recruitment period was for 18 to 24 months. EXPECTED OUTCOMES: Collaborative European NeuroTrauma Effectiveness Research in TBI should provide novel multidimensional approaches to TBI characterization and classification, evidence to support treatment recommendations, and benchmarks for quality of care. Data and sample repositories will ensure opportunities for legacy research. DISCUSSION: Comparative effectiveness research provides an alternative to reductionistic clinical trials in restricted patient populations by exploiting differences in biology, care, and outcome to support optimal personalized patient management