Model confidence sets and forecast combination: an application to age-specific mortality

Background: Model averaging combines forecasts obtained from a range of models, and it often produces more accurate forecasts than a forecast from a single model. Objective: The crucial part of forecast accuracy improvement in using the model averaging lies in the determination of optimal weights from a finite sample. If the weights are selected sub-optimally, this can affect the accuracy of the model-averaged forecasts. Instead of choosing the optimal weights, we consider trimming a set of models before equally averaging forecasts from the selected superior models. Motivated by Hansen et al. (2011), we apply and evaluate the model confidence set procedure when combining mortality forecasts. Data & Methods: The proposed model averaging procedure is motivated by Samuels and Sekkel (2017) based on the concept of model confidence sets as proposed by Hansen et al. (2011) that incorporates the statistical significance of the forecasting performance. As the model confidence level increases, the set of superior models generally decreases. The proposed model averaging procedure is demonstrated via national and sub-national Japanese mortality for retirement ages between 60 and 100+. Results: Illustrated by national and sub-national Japanese mortality for ages between 60 and 100+, the proposed model-average procedure gives the smallest interval forecast errors, especially for males. Conclusion: We find that robust out-of-sample point and interval forecasts may be obtained from the trimming method. By robust, we mean robustness against model misspecification

Dysregulated Epstein-Barr virus infection in patients with CIDP

Ubiquitous viruses have frequently been proposed as a cause or trigger of chronic immune-mediated diseases. Infections are reported to be temporally associated with clinical exacerbations in patients with chronic inflammatory demyelinating polyneuropathy (CIDP). We examined immunological parameters of herpesvirus infections in untreated patients with CIDP compared to demographically matched controls. Patients with CIDP were uniformly seropositive for EBV-specific IgG and the disease was associated with a moderately enhanced IgG reactivity to EBV-encoded antigens expressed during both B cell transformation and productive viral replication. Moreover, cellular EBV copy numbers were 3-fold increased in patients with CIDP. In contrast, humoral immune responses to other herpesviruses (HCMV, HSV) as well as virus-specific IgM responses were unchanged in CIDP. These data indicate that host-pathogen interactions during chronic EBV infection are dysregulated in treatment-naïve patients with CIDP

Enhanced COMP catabolism detected in serum of patients with arthritis and animal disease models through a novel capture ELISA

Objective: The study aimed determining whether assessment of cartilage oligomeric matrix protein (COMP) degradation products could serve as a serological disease course and therapeutic response predictor in arthritis. Methods: We generated a panel of monoclonal antibodies against COMP fragments and developed a novel capture enzyme-linked immunosorbent assay (ELISA) for detecting COMP fragments in patients with osteoarthritis (OA) and rheumatoid arthritis (RA). This test was also used to monitor COMP fragments in surgically-induced OA, collagen-induced arthritis (CIA), and tumor necrosis factor (TNF) transgenic animal models. Results: Compared with a commercial COMP ELISA kit that detected no significant difference in COMP levels between OA and control groups, a significant increase of the COMP fragments were noted in the serum of OA patients assayed by this newly established ELISA. In addition, serum COMP fragment levels were well correlated with severity in OA patients and the progression of surgically-induced OA in murine models. Furthermore, the serum levels of COMP fragments in RA patients, mice with CIA, and TNF transgenic mice were significantly higher when compared with their controls. Interestingly, treatment with TNFα inhibitors and methotrexate led to a significant decrease of serum COMP fragments in RA patients. Additionally, administration of Atsttrin [Tang, et al., Science 2011;332(6028):478] also resulted in a significant reduction in COMP fragments in arthritis mice models. Conclusion: A novel sandwich ELISA is capable of reproducibly measuring serum COMP fragments in both arthritic patients and rodent arthritis models. This test also provides a valuable means to utilize serum COMP fragments for monitoring the effects of interventions in arthritis. © 2012 Osteoarthritis Research Society International