Text Mining the History of Medicine

Historical text archives constitute a rich and diverse source of information, which is becoming increasingly readily accessible, due to large-scale digitisation efforts. However, it can be difficult for researchers to explore and search such large volumes of data in an efficient manner. Text mining (TM) methods can help, through their ability to recognise various types of semantic information automatically, e.g., instances of concepts (places, medical conditions, drugs, etc.), synonyms/variant forms of concepts, and relationships holding between concepts (which drugs are used to treat which medical conditions, etc.). TM analysis allows search systems to incorporate functionality such as automatic suggestions of synonyms of user-entered query terms, exploration of different concepts mentioned within search results or isolation of documents in which concepts are related in specific ways. However, applying TM methods to historical text can be challenging, according to differences and evolutions in vocabulary, terminology, language structure and style, compared to more modern text. In this article, we present our efforts to overcome the various challenges faced in the semantic analysis of published historical medical text dating back to the mid 19th century. Firstly, we used evidence from diverse historical medical documents from different periods to develop new resources that provide accounts of the multiple, evolving ways in which concepts, their variants and relationships amongst them may be expressed. These resources were employed to support the development of a modular processing pipeline of TM tools for the robust detection of semantic information in historical medical documents with varying characteristics. We applied the pipeline to two large-scale medical document archives covering wide temporal ranges as the basis for the development of a publicly accessible semantically-oriented search system. The novel resources are available for research purposes, while the processing pipeline and its modules may be used and configured within the Argo TM platform

Treatment and Survival Outcomes of Waldenstrom Macroglobulinemia in Latin American Patients: A Multinational Retrospective Cohort Study

PURPOSE: Waldenstrom Macroglobulinemia (WM) is a rare lymphoma with distinct clinical features, and data from Latin American patients are lacking. Therefore, we aim to investigate the clinical, therapy, and outcome patterns of WM in Latin America. METHODS: We retrospectively analyzed patients with WM diagnosed between 1991 and 2019 from 24 centers in seven Latin American countries. The study outcomes were overall survival (OS) and progression-free survival (PFS). RESULTS: We identified 159 cases (median age 67 years, male 62%). Most patients (95%) were symptomatic at diagnosis. The International Prognostic Scoring System for WM (IPSSWM) at diagnosis was available in 141 (89%) patients (high-risk 40%, intermediate-risk 37%, and low-risk 23%). Twenty-seven (17%) patients were tested for MYD88, with 89% (n = 24 of 27) carrying the mutation. First-line and second-line therapies were administered to 142 (89%) and 53 (33%) patients, respectively. Chemoimmunotherapy was the most commonly used first-line (66%) and second-line (45%) approach; only 18 (11%) patients received ibrutinib. With a median follow-up of 69 months, the 5-year OS rate was 81%. In treated patients, the 5-year OS and PFS rates were 78% and 59%, respectively. High-risk IPSSWM at treatment initiation was an independent risk factor for OS (adjusted hazard ratio: 4.73, 95% CI, 1.67 to 13.41, = .003) and PFS (adjusted hazard ratio: 2.43, 95% CI, 1.31 to 4.50, = .005). CONCLUSION: In Latin America, the management of WM is heterogeneous, with limited access to molecular testing and novel agents. However, outcomes were similar to those reported internationally. We validated the IPSSWM score as a prognostic factor for OS and PFS. There is an unmet need to improve access to recommended diagnostic approaches and therapies in Latin America