Objective Seizure frequency and seizure freedom are among the most important outcome measures for patients with epilepsy. In this study, we aimed to automatically extract this clinical information from unstructured text in clinical notes. If successful, this could improve clinical decision-making in epilepsy patients and allow for rapid, large-scale retrospective research. Materials and Methods We developed a finetuning pipeline for pretrained neural models to classify patients as being seizure-free and to extract text containing their seizure frequency and date of last seizure from clinical notes. We annotated 1000 notes for use as training and testing data and determined how well 3 pretrained neural models, BERT, RoBERTa, and Bio_ClinicalBERT, could identify and extract the desired information after finetuning. Results The finetuned models (BERTFT, Bio_ClinicalBERTFT, and RoBERTaFT) achieved near-human performance when classifying patients as seizure free, with BERTFT and Bio_ClinicalBERTFT achieving accuracy scores over 80%. All 3 models also achieved human performance when extracting seizure frequency and date of last seizure, with overall F1 scores over 0.80. The best combination of models was Bio_ClinicalBERTFT for classification, and RoBERTaFT for text extraction. Most of the gains in performance due to finetuning required roughly 70 annotated notes. Discussion and Conclusion Our novel machine reading approach to extracting important clinical outcomes performed at or near human performance on several tasks. This approach opens new possibilities to support clinical practice and conduct large-scale retrospective clinical research. Future studies can use our finetuning pipeline with minimal training annotations to answer new clinical questions.

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OBJECTIVEThe choice of treatment modality for optic pathway gliomas (OPGs) is controversial. Chemotherapy is widely regarded as first-line therapy; however, subtotal resections have been reported for decompression or salvage therapy as first- and second-line treatment. The goal of this study was to further investigate the role and efficacy of resection for OPGs.METHODSA retrospective chart review was performed on 83 children who underwent surgical treatment for OPGs between 1986 and 2014. Pathology was reviewed by a neuropathologist. Clinical outcomes, including progression-free survival (PFS), overall survival (OS), and complications, were analyzed.RESULTSThe 5- and 10-year PFS rates were 55% and 46%, respectively. The 5- and 10-year OS rates were 87% and 78%, respectively. The median extent of resection was 80% (range 30%–98%). Age less than 2 years at surgery and pilomyxoid features of the tumor were found to be associated with significantly lower 5-year OS. No difference was seen in PFS or OS of children treated with surgery as a first-line treatment compared with children with surgery as a second- or third-line treatment. Severe complications included new disabling visual deficit in 5%, focal neurological deficit in 8%, and infection in 2%. New hormone deficiency occurred in 22% of the children.CONCLUSIONSApproximately half of all children experience a long-term benefit from resection both as primary treatment and as a second-line therapy after failure of primary treatment. Primary surgery does not appear to have a significant benefit for children younger than 2 years or tumors with pilomyxoid features. Given the risks associated with surgery, an interdisciplinary approach is needed to tailor the treatment plan to the individual characteristics of each child.

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