Background: Multiple sclerosis (MS) is a chronic inflammatory autoimmune disease of the central nervous system. Pediatric-onset MS (POMS), defined as onset of MS before 18 years of age, is estimated to account for 2% to 5% of the MS population worldwide. Objectives: To conduct a literature review focused on the healthcare resource utilization and cost as well as quality-of-life (QOL) outcomes among patients with POMS. Methods: We conducted a systematic literature review of English-language studies published after September 2010 in MEDLINE and Embase to describe the global economic healthcare resource utilization and costs and humanistic (QOL) burden in patients with POMS. Results: We found 11 studies that reported on healthcare resource utilization, cost, or insurance coverage and 36 studies that reported on QOL outcomes in patients with POMS. Patients with POMS had higher rates of primary care visits (1.41 [1.29-1.54]), hospital visits (10.74 [8.95-12.90]), and admissions (rate ratio, 4.27 [2.92-6.25];OR, 15.2 [12.0-19.1]) compared with healthy controls. Mean per-patient costs in the United States were $5907 across all settings per year of follow-up between 2002 and 2012; mean costs per hospital stay were $38 543 (in 2015 USD) between 2004 and 2013. Three studies reported psychosocial scores between 71.59 and 79.7, and 8 studies reported physical health scores between 74.62 to 82.75 using the Pediatric Quality of Life Measurement Model (PedsQLTM). Twelve studies used the PedsQL™ Multidimensional Fatigue Scale. Mean scores on the self-reported general fatigue scale ranged from 63.15 to 78.5. Quality-of-life scores were lower than those of healthy controls. Discussion: Our review presents a uniquely broad and recent overview of the global economic and humanistic burden of patients with POMS. Additional research on healthcare resource utilization and cost would provide a more robust understanding of the economic burden in this population. Conclusions: Healthcare resource utilization and costs are high in this population, and patients report reduced QOL and significant fatigue compared with healthy children and adolescents.
The goal of this research was to design a solution to detect non-reported incidents of injection. METHODS: We developed methods to process electronic medical records and automatically extract clinical notes describing incidents of injection by using the SVM based technique. First, we manually labeled a training set of clinical notes into two categories based on whether they included an incident report of injection or not, and then the machine learning models were created. This machine learning method arranges data in a vector space, using single words as the axes. For the training process, a few variations were tested: normalized versus non-normalized data. The extracted notes are treated as incident candidates which are shown to the safety management department for further analysis. RESULTS: Using the developed method based on the SVM, we implemented an incident candidate reporting system. To evaluate the system, we asked a staff of the safety management department to judge whether extracted incident candidates were incidents or not. The system used inpatients' clinical notes written from January 8, 2018 to January 14, 2018 in Kyoto University Hospital. As a result, in the case of non-normalized data, 41 out of 364 incident candidates were judged clinical notes describing incidents. Furthermore, 21 of them were nonreported incidents. In the case of normalized data, 23 out of 91 incident candidates were judged clinical notes describing incidents. Moreover, 13 of them were nonreported incidents. CONCLUSIONS: In this research, we aimed to establish a method to extract incident candidates from clinical notes in order to detect nonreported incidents of injection. In addition, we created a reporting system that presents incident candidates extracted by using the developed method. The system successfully detected non-reported incidents to the safety management department, thus our goal was achieved.
Objectives: MG is a debilitating chronic illness characterized by muscle weakness, potentially life-threatening exacerbations and high costs. We sought to further quantify the humanistic and economic burden by reviewing published evidence. Methods: Using PRISMA guidelines, two systematic literature reviews were conducted, one for quality of life (QOL) and one for economic studies, in key biomedical literature databases, Embase, Ovid Medline and Cochrane. Additionally, only studies published between 2009-2019 were identified. Results: A total of 957 abstracts from the QOL search and 521 from the economic search underwent screening. A total of 81 QOL and 41 economic studies were selected. A variety of QOL tools were used, including SF-36, EQ-5D, HADS, MG-ADL, MG-QOL15, QMG and MGC among others. The only study mapping utility values found a range of 0.94-0.20 across MGFA classifications, indicating a major QOL deterioration related to disease severity. Deterioration was further supported in other studies which found increased levels of chronic fatigue, sleep disturbances and anxiety/depression with MG. Refractory patients experienced significantly worse deteriorations across various scales. Employment status and medication adherence were also negatively affected. Of 41 economic studies, 32 were related to cost/healthcare resource use, while 9 described economic models. The average US cost in 2013 was $98,795 per MG hospitalization and the gross hospitalization cost in the HCUP database had risen more than 13-fold since 2003 totalling $546,834,101. Inpatient, outpatient and home costs were found to account for 27%, 23% and 23% of MG healthcare costs. A US claims database found annual costs to be approximately 4 times higher in refractory vs. non-refractory patients ($109,004 vs. $24,196, p,0.001), possibly related to a higher use of IVig/ PLEX, costly therapies according to economic models. Conclusions: Novel treatment strategies are necessitated to help control rising costs and alleviate the humanistic burden associated with MG, especially in refractory patients.
117 (46%) with bisphosphonates and 19 (7%) with Ra-223. Further to this; 79% of these Ra-223 patients were also administered abiraterone or enzalutamide versus 21% who used it alone. Of patients on Ra-223, 11% had only bone metastases while 89% had bone plus one or more additional metastases. The majority of patients on Ra-223 had Gleason scores below 8 (84% ≤ 7). The average (median) PSA level was 114 (110) and 111 (40) at diagnosis and treatment, respectively. The average (median) time from diagnosis to development of CRPC was 375 days (305). ConClusions: Bone-targeted therapy is still dominated by denosumab and bisphosphonates. However, Ra-223 is the first BTA to actually improve survival. The real-world data used in this analysis shows that Ra-223 is not only used in patients whose cancer has spread to the bones but also in those whose cancer has spread to other organs. Though commonly administered with abiraterone or enzalutamide, Ra-223 is also given alone. The majority of patients treated with Ra-223 show a Gleason score of 7 and the average (median) PSA values are lower at treatment than at diagnosis. The analysis of Ra-223 patients has also identified the average time from diagnosis to development of CRPC.
Purpose Multiple sclerosis (MS) is a costly, immune-mediated disease of the central nervous system. Most patients have relapsing-remitting MS (RRMS) for which disease-modifying therapies (DMTs) provide an effective treatment option by reducing relapse rates. However, adherence to DMTs is suboptimal. This study examines the association between adherence to teriflunomide and clinical and healthcare utilization outcomes. Patients and Methods Patients with RRMS who started treatment with teriflunomide between 1/1/2018 and 12/31/2019 were analyzed using IQVIA PharMetrics ® Plus data. RRMS patients were identified via diagnosis codes and treatment types; the first prescription date for teriflunomide was the index date. Highly and poorly adherent patients were identified based on the proportion of days covered (PDC) post-index (PDC ≥0.8 and PDC ≤0.5, respectively). Patient demographics, clinical characteristics, healthcare utilization during the year pre- and post-index, and relapse rate post-index were reported descriptively. Outcomes were compared between highly and poorly adherent patients through logistic regression. Models were adjusted for demographics, comorbidities, and utilization measures during the baseline period. Results Among the 922 RRMS patients identified, 534 (57.9%) were highly adherent to teriflunomide, while 249 (27.0%) had PDC ≤0.5. The two groups were not statistically different in terms of demographic characteristics and comorbidities; however, poorly adherent patients were more likely to have emergency department (ED) or inpatient visits during baseline (36.9% versus 26.8%, P =0.004; 17.3% versus 10.9%, P =0.013, respectively). Unadjusted results suggested lower likelihood of both relapses and utilization during follow-up among highly adherent patients compared to poorly adherent patients. Adjusted results confirmed that high adherence was associated with decreased likelihood of post-index relapses, ED utilization, and inpatient utilization (OR [95% CI]: 0.55 [0.39–0.76], 0.49 [0.34–0.71], and 0.51 [0.27–0.97], respectively) even after controlling for baseline utilization. Conclusion High adherence to teriflunomide was found to be associated with fewer relapses and lower healthcare utilization among patients with RRMS.
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