Simple gravitational particle swarm algorithm for multimodal optimization problems.

In real world situations, decision makers prefer to have multiple optimal solutions before making a final decision. Aiming to help the decision makers even if they are non-experts in optimization algorithms, this study proposes a new and simple multimodal optimization (MMO) algorithm called the gravitational particle swarm algorithm (GPSA). Our GPSA is developed based on the concept of "particle clustering in the absence of clustering procedures". Specifically, it simply replaces the global feedback term in classical particle swarm optimization (PSO) with an inverse-square gravitational force term between the particles. The gravitational force mutually attracts and repels the particles, enabling them to autonomously and dynamically generate sub-swarms in the absence of algorithmic clustering procedures. Most of the sub-swarms gather at the nearby global optima, but a small number of particles reach the distant optima. The niching behavior of our GPSA was tested first on simple MMO problems, and then on twenty MMO benchmark functions. The performance indices (peak ratio and success rate) of our GPSA were compared with those of existing niching PSOs (ring-topology PSO and fitness Euclidean-distance ratio PSO). The basic performance of our GPSA was comparable to that of the existing methods. Furthermore, an improved GPSA with a dynamic parameter delivered significantly superior results to the existing methods on at least 60% of the tested benchmark functions.

Safety and Effectiveness of Lenvatinib in 594 Patients with Unresectable Thyroid Cancer in an All-Case Post-Marketing Observational Study in Japan.

INTRODUCTION: Lenvatinib is approved in Japan for treating patients with all histological subtypes of unresectable thyroid cancer, including differentiated thyroid cancer (DTC), medullary thyroid cancer (MTC), and anaplastic thyroid cancer (ATC). However, safety and effectiveness data are limited in Japanese patients. Therefore, this prospective, post-marketing observational study evaluated, in daily clinical practice, the safety and effectiveness of lenvatinib in Japanese patients with unresectable thyroid cancer. METHODS: All patients with unresectable thyroid cancer first treated with lenvatinib between May and November 2015 were registered. Patients were orally administered lenvatinib and followed up for 12 months. The endpoints included adverse drug reactions (ADRs), overall survival (OS), overall response rate (ORR), and time-to-treatment failure. Post hoc Cox multivariate analyses were performed to assess prognostic factors associated with the 12-month OS rate. RESULTS: Of 629 registered patients, 594 were included in the analysis. A total of 442 patients (74.4%) had DTC, 28 (4.7%) had MTC, and 124 (20.9%) had ATC. Hypertension, proteinuria, and palmar-plantar erythrodysesthesia syndrome were the most frequently reported ADRs across all histological subtypes. The median OS was 101.0 days in patients with ATC which was not reached in patients with DTC and patients with MTC, with 12-month OS rates of 15.6%, 75.7%, and 83.0%, respectively. The ORRs were 59.2%, 45.0%, and 43.8% among 368 patients with DTC, 20 with MTC, and 105 with ATC, respectively. Multivariate analyses revealed that Eastern Cooperative Oncology Group performance status (ECOG PS), tumor size, the presence of tumor invasion, and body weight were baseline prognostic factors affecting OS in patients with DTC, while ECOG PS and the presence of liver metastasis were prognostic factors in patients with ATC. CONCLUSION: Lenvatinib demonstrated an acceptable safety profile for patients with thyroid cancer in a real-world setting in Japan. The safety profile and effectiveness findings for lenvatinib in this study were consistent with those from previous clinical trials, irrespective of histological subtype.