title: Analysis of Patient Narratives in Disease Blogs on the Internet: An Exploratory Study of Social Pharmacovigilance.
abstract: BACKGROUND
  Although several reports have suggested that patient-generated data from Internet sources could be used to improve drug safety and pharmacovigilance, few studies have identified such data sources in Japan. We introduce a unique Japanese data source: tōbyōki, which translates literally as "an account of a struggle with disease."
  
  
  OBJECTIVE
  The objective of this study was to evaluate the basic characteristics of the TOBYO database, a collection of tōbyōki blogs on the Internet, and discuss potential applications for pharmacovigilance.
  
  
  METHODS
  We analyzed the overall gender and age distribution of the patient-generated TOBYO database and compared this with other external databases generated by health care professionals. For detailed analysis, we prepared separate datasets for blogs written by patients with depression and blogs written by patients with rheumatoid arthritis (RA), because these conditions were expected to entail subjective patient symptoms such as discomfort, insomnia, and pain. Frequently appearing medical terms were counted, and their variations were compared with those in an external adverse drug reaction (ADR) reporting database. Frequently appearing words regarding patients with depression and patients with RA were visualized using word clouds and word cooccurrence networks.
  
  
  RESULTS
  As of June 4, 2016, the TOBYO database comprised 54,010 blogs representing 1405 disorders. Overall, more entries were written by female bloggers (68.8%) than by male bloggers (30.8%). The most frequently observed disorders were breast cancer (4983 blogs), depression (3556), infertility (2430), RA (1118), and panic disorder (1090). Comparison of medical terms observed in tōbyōki blogs with those in an external ADR reporting database showed that subjective and symptomatic events and general terms tended to be frequently observed in tōbyōki blogs (eg, anxiety, headache, and pain), whereas events using more technical medical terms (eg, syndrome and abnormal laboratory test result) tended to be observed frequently in the ADR database. We also confirmed the feasibility of using visualization techniques to obtain insights from unstructured text-based tōbyōki blog data. Word clouds described the characteristics of each disorder, such as "sleeping" and "anxiety" in depression and "pain" and "painful" in RA.
  
  
  CONCLUSIONS
  Pharmacovigilance should maintain a strong focus on patients' actual experiences, concerns, and outcomes, and this approach can be expected to uncover hidden adverse event signals earlier and to help us understand adverse events in a patient-centered way. Patient-generated tōbyōki blogs in the TOBYO database showed unique characteristics that were different from the data in existing sources generated by health care professionals. Analysis of tōbyōki blogs would add value to the assessment of disorders with a high prevalence in women, psychiatric disorders in which subjective symptoms have important clinical meaning, refractory disorders, and other chronic disorders.
authors.affiliation: Chugai Pharmaceutical Co Ltd, Drug Safety Data Management Department, Tokyo, Japan.
authors.forename: Shinichi
authors.identifier: http://orcid.org/0000-0003-1822-1090
authors.initials: S
authors.lastname: Matsuda
authors.affiliation: Chugai Pharmaceutical Co Ltd, Drug Safety Data Management Department, Tokyo, Japan.
authors.forename: Kotonari
authors.identifier: http://orcid.org/0000-0002-1923-7003
authors.initials: K
authors.lastname: Aoki
authors.affiliation: Chugai Pharmaceutical Co Ltd, Drug Safety Data Management Department, Tokyo, Japan.
authors.forename: Shiho
authors.identifier: http://orcid.org/0000-0002-5354-0583
authors.initials: S
authors.lastname: Tomizawa
authors.affiliation: Chugai Pharmaceutical Co Ltd, Pharmacovigilance Department, Tokyo, Japan.
authors.forename: Masayoshi
authors.identifier: http://orcid.org/0000-0001-6197-8027
authors.initials: M
authors.lastname: Sone
authors.affiliation: Chugai Pharmaceutical Co Ltd, Medical Information Department, Tokyo, Japan.
authors.forename: Riwa
authors.identifier: http://orcid.org/0000-0003-1394-5022
authors.initials: R
authors.lastname: Tanaka
authors.affiliation: Chugai Pharmaceutical Co Ltd, Clinical Science & Strategy Department, Tokyo, Japan.
authors.forename: Hiroshi
authors.identifier: http://orcid.org/0000-0002-3954-9039
authors.initials: H
authors.lastname: Kuriki
authors.affiliation: Chugai Pharmaceutical Co Ltd, Drug Safety Data Management Department, Tokyo, Japan.
authors.forename: Yoichiro
authors.identifier: http://orcid.org/0000-0003-1156-2984
authors.initials: Y
authors.lastname: Takahashi
keywords: Internet; adverse drug reaction; pharmacovigilance; social media; text mining