Pediatric Healthcare Professionals’ Views on Autism Spectrum Disorder Screening at 12–18 Months

This study explored North Carolina pediatric healthcare professional’s (PHP) perceptions of screening 12–18 month old infants for Autism Spectrum Disorder (ASD). Eight focus groups (66 PHPs) were conducted across practice settings. The purpose was to explore PHP’s perspectives to: inform development of ASD screening tools and ultimately impact their use in PHP settings. PHPs reported concerns, barriers, and the need for research to support early ASD screening. Additionally, they expressed the need for: (a) clear “red flags” of ASD for 12–18 month olds; (b) socioculturally sensitive and effective screening tools; (c) effective early interventions; (d) systems to handle potential increases in referrals; and (e) continuing education. PHPs also demonstrated preferences about screening tool characteristics and processes for enhancing screening efforts.     

PEER umbrella systematic review of systematic reviews: Management of osteoarthritis in primary care

ObjectiveTo determine how many patients with chronic osteoarthritis pain respond to various non-surgical treatments.Data sourcesPubMed and the Cochrane Library.Study selection Published systematic reviews of randomized controlled trials (RCTs) that included meta-analysis of responder outcomes for at least 1 of the following interventions were included: acetaminophen, oral nonsteroidal anti-inflammatory drugs (NSAIDs), topical NSAIDs, serotonin-norepinephrine reuptake inhibitors (SNRIs), tricyclic antidepressants, cannabinoids, counseling, exercise, platelet-rich plasma, viscosupplementation, glucosamine, chondroitin, intra-articular corticosteroids, rubefacients, or opioids.Synthesis In total, 235 systematic reviews were included. Owing to limited reporting of responder meta-analyses, a post hoc decision was made to evaluate individual RCTs with responder analysis within the included systematic reviews. New meta-analyses were performed where possible. A total of 155 RCTs were included. Interventions that led to more patients attaining meaningful pain relief compared with control included exercise (risk ratio [RR] of 2.36; 95% CI 1.79 to 3.12), intra-articular corticosteroids (RR = 1.74; 95% CI 1.15 to 2.62), SNRIs (RR = 1.53; 95% CI 1.25 to 1.87), oral NSAIDs (RR = 1.44; 95% CI 1.36 to 1.52), glucosamine (RR = 1.33; 95% CI 1.02 to 1.74), topical NSAIDs (RR = 1.27; 95% CI 1.16 to 1.38), chondroitin (RR = 1.26; 95% CI 1.13 to 1.41), viscosupplementation (RR = 1.22; 95% CI 1.12 to 1.33), and opioids (RR = 1.16; 95% CI 1.02 to 1.32). Preplanned subgroup analysis demonstrated no effect with glucosamine, chondroitin, or viscosupplementation in studies that were only publicly funded. When trials longer than 4 weeks were analyzed, the benefits of opioids were not statistically significant.ConclusionInterventions that provide meaningful relief for chronic osteoarthritis pain might include exercise, intra-articular corticosteroids, SNRIs, oral and topical NSAIDs, glucosamine, chondroitin, viscosupplementation, and opioids. However, funding of studies and length of treatment are important considerations in interpreting these data.     

Refined mapping and characterization of the recessive familial amyotrophic lateral sclerosis locus (ALS2) on chromosome 2q33

Amyotrophic lateral sclerosis (ALS) is a progressive degenerative neuromuscular disease that shows familial, autosomal dominant inheritance in 10%–15% of cases. Previous genetic analysis of one large family linked a recessive form of familial ALS (FALS-AR type 3) to the chromosome 2q33–35 region. Using additional polymorphic markers, we have narrowed the size of the linked region to approximately 1.7 cM by linkage and haplotype analysis. We have also established a yeast artificial chromosome contig across the locus that covers an approximate physical distance of 3 million bases. Based on this contig, genes and expressed sequences that map near the 2q33 region have been examined to determine whether they are located within this ALS2 candidate locus. Five identified genes and 34 expressed sequence tags map within the region defined by crossover analysis and merit further consideration as candidate genes for this disease. Accepted: July 15, 1998 / Published online: October 28, 1998     

SELDI-TOF serum profiling for prognostic and diagnostic classification of breast cancers

Surface enhanced laser desorption/ionization (SELDI) time-of-flight mass spectrometry has emerged as a successful tool for serum based detection and differentiation of many cancer types, including breast cancers. In this study, we have applied the SELDI technology to evaluate three potential applications that could extend the effectiveness of established procedures and biomarkers used for prognostication of breast cancers. Paired serum samples obtained from women with breast cancers prior to surgery and post-surgery (6-9 mos.) were examined. In 14/16 post-treatment patients, serum protein profiles could be used to distinguish these samples from the pre-treatment cancer samples. When compared to serum samples from normal healthy women, 11 of these post-treatment samples retained global protein profiles not found in healthy women, including five low-mass proteins that remained elevated in both pre-treatment and post-treatment serum groups. In another pilot study, serum profiles were compared for a group of 30 women who were known BRCA-1 mutation carriers, half of whom subsequently developed breast cancer within three years of the sample procurement. SELDI protein profiling accurately classified 13/15 women with BRCA-1 breast cancers from the 15 non-cancer BRCA-1 carriers. Additionally, the ability of SELDI to distinguish between the serum profiles from sentinel lymph node positive and sentinel lymph node negative patients was evaluated. In sentinel lymph node positive samples, 22/27 samples were correctly classified, in comparison to the correct classification of 55/71 sentinel lymph node negative samples. These initial results indicate the utility of protein profiling approaches for developing new diagnostic and prognostic assays for breast cancers.     

Diagnosis of Ovarian Cancer Using Decision Tree Classification of Mass Spectral Data

Recent reports from our laboratory and others support the SELDI ProteinChip technology as a potential clinical diagnostic tool when combined with $n$ -dimensional analyses algorithms. The objective of this study was to determine if the commercially available classification algorithm biomarker patterns software (BPS), which is based on a classification and regression tree (CART), would be effective in discriminating ovarian cancer from benign diseases and healthy controls. Serum protein mass spectrum profiles from 139 patients with either ovarian cancer, benign pelvic diseases, or healthy women were analyzed using the BPS software. A decision tree, using five protein peaks resulted in an accuracy of 81.5% in the cross-validation analysis and 80%in a blinded set of samples in differentiating the ovarian cancer from the control groups. The potential, advantages, and drawbacks of the BPS system as a bioinformatic tool for the analysis of the SELDI high-dimensional proteomic data are discussed.