Objective: To determine optimal second monotherapy for children with childhood absence epilepsy (CAE) experiencing initial treatment failure.
Methods: Children with CAE experiencing treatment failure during the double-blind phase of a randomized controlled trial comparing ethosuximide, valproic acid, and lamotrigine were randomized to open-label second monotherapy with one of the 2 other study therapies. Primary study outcome was freedom from failure proportion at week 16-20 and month 12 visits after randomization. Secondary study outcome was percentage of participants experiencing attentional dysfunction at these visits.
Results: A total of 208 children were enrolled, randomized, and received second therapy. At both week 16-20 visit and month 12 visit, ethosuximide's (63%, 57%) and valproic acid's (65%, 49%) freedom from failure proportions were similar to each other and higher than lamotrigine's (45%, 36%, p = 0.051 and p = 0.062). At both time points, ethosuximide and valproic acid had superior seizure control compared to lamotrigine (p < 0.0001). At both the week 16-20 and month 12 visits, attentional dysfunction was numerically more common with valproic acid than with ethosuximide or lamotrigine. For each medication, second monotherapy freedom from failure proportions demonstrated noninferiority to initial monotherapy freedom from failure proportions.
Conclusions: As second monotherapy, ethosuximide and valproic acid, demonstrated higher freedom from failure proportions and greater efficacy than lamotrigine; valproic acid was associated with more attentional dysfunction. Ethosuximide is the optimal second monotherapy for children with CAE not responding to initial therapy with other medications.
Clinicaltrialsgov Identifier: NCT00088452.
Classification Of Evidence: This study provides Class III evidence that for children with CAE experiencing initial treatment failure, second monotherapy with ethosuximide or valproic acid is superior to lamotrigine.
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http://dx.doi.org/10.1212/WNL.0000000000003480 | DOI Listing |
Brief Bioinform
November 2024
School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology (GIST), Buk-gu, Gwangju 61005, Republic of Korea.
Combination therapies have emerged as a promising approach for treating complex diseases, particularly cancer. However, predicting the efficacy and safety profiles of these therapies remains a significant challenge, primarily because of the complex interactions among drugs and their wide-ranging effects. To address this issue, we introduce DD-PRiSM (Decomposition of Drug-Pair Response into Synergy and Monotherapy effect), a deep-learning pipeline that predicts the effects of combination therapy.
View Article and Find Full Text PDFJ Immunother Cancer
January 2025
Department of Nuclear Medicine and Minnan PET Center, Xiamen Cancer Center, The First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, Fujian, China
Background: Fibroblast activation protein (FAP)-targeted radioligand therapy, with immunomodulatory effects, has shown efficacy in both preclinical and clinical studies. We recently reported on a novel dimeric FAP-targeting radiopharmaceutical, Ga/Lu-DOTA-2P(FAPI), which demonstrated increased tumor uptake and prolonged retention in various cancers. However, further exploration is required to understand the therapeutic efficacy and underlying mechanisms of combining Ga/Lu-DOTA-2P(FAPI) radioligand therapy with PD-1/PD-L1 immunotherapy.
View Article and Find Full Text PDFClin Gastroenterol Hepatol
January 2025
Inflammatory Bowel Disease Center, Division of Gastroenterology and Hepatology, Mayo Clinic, Jacksonville FL. Electronic address:
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View Article and Find Full Text PDFClin Transl Med
January 2025
Department of Cell Biology, National Translational Science Center for Molecular Medicine, Fourth Military Medical University, Xi'an, China.
Background: Gut microbiome on predicting clinical responses to immune checkpoint inhibitors (ICIs) has been discussed in detail for decades, while microecological features of the lower respiratory tract within advanced non-small-cell lung cancer (NSCLC) are still relatively vague.
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Invest New Drugs
January 2025
Postgraduate Training Base Alliance, Wenzhou Medical University (Zhejiang Cancer Hospital), Hangzhou, 310022, Zhejiang, China.
A novel molecular classification for small cell lung cancer (SCLC) has been established utilizing the transcription factors achaete-scute homologue 1 (ASCL1), neurogenic differentiation factor 1 (NeuroD1), POU class 2 homeobox 3 (POU2F3), and yes-associated protein 1 (YAP1). This classification was predicated on the transcription factors. Conversely, there is a paucity of information regarding the distribution of these markers in other subtypes of pulmonary neuroendocrine tumors (PNET).
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