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      Social Media Surveillance of Multiple Sclerosis Medications Used During Pregnancy and Breastfeeding: Content Analysis

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          Abstract

          Background

          Multiple sclerosis (MS) is a chronic neurological disease occurring mostly in women of childbearing age. Pregnant women with MS are usually excluded from clinical trials; as users of the internet, however, they are actively engaged in threads and forums on social media. Social media provides the potential to explore real-world patient experiences and concerns about the use of medicinal products during pregnancy and breastfeeding.

          Objective

          This study aimed to analyze the content of posts concerning pregnancy and use of medicines in online forums; thus, the study aimed to gain a thorough understanding of patients’ experiences with MS medication.

          Methods

          Using the names of medicinal products as search terms, we collected posts from 21 publicly available pregnancy forums, which were accessed between March 2015 and March 2018. After the identification of relevant posts, we analyzed the content of each post using a content analysis technique and categorized the main topics that users discussed most frequently.

          Results

          We identified 6 main topics in 70 social media posts. These topics were as follows: (1) expressing personal experiences with MS medication use during the reproductive period (55/70, 80%), (2) seeking and sharing advice about the use of medicines (52/70, 74%), (3) progression of MS during and after pregnancy (35/70, 50%), (4) discussing concerns about MS medications during the reproductive period (35/70, 50%), (5) querying the possibility of breastfeeding while taking MS medications (30/70, 42%), and (6) commenting on communications with physicians (26/70, 37%).

          Conclusions

          Overall, many pregnant women or women considering pregnancy shared profound uncertainties and specific concerns about taking medicines during the reproductive period. There is a significant need to provide advice and guidance to MS patients concerning the use of medicines in pregnancy and postpartum as well as during breastfeeding. Advice must be tailored to the circumstances of each patient and, of course, to the individual medicine. Information must be provided by a trusted source with relevant expertise and made publicly available.

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          Most cited references20

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          Internet use in pregnancy informs women's decision making: a web-based survey.

          Internet access and usage is almost ubiquitous, providing new opportunities and increasing challenges for health care practitioners and users. With pregnant women reportedly turning to the Internet for information during pregnancy, a better understanding of this behavior is needed. The objective of this study was to ascertain why and how pregnant women use the Internet as a health information source, and the overall effect it had on their decision making. Kuhlthau's (1993) information-seeking model was adapted to provide the underpinning theoretical framework for the study. The design was exploratory and descriptive. Data were collected using a valid and reliable web-based questionnaire. Over a 12-week period, 613 women from 24 countries who had confirmed that they had used the Internet for pregnancy-related information during their pregnancy completed and submitted a questionnaire. Most women (97%) used search engines such as Google to identify online web pages to access a large variety of pregnancy-related information and to use the Internet for pregnancy-related social networking, support, and electronic commerce (i.e., e-commerce). Almost 94 percent of women used the Internet to supplement information already provided by health professionals and 83 percent used it to influence their pregnancy decision making. Nearly half of the respondents reported dissatisfaction with information given by health professionals (48.6%) and lack of time to ask health professionals questions (46.5%) as key factors influencing them to access the Internet. Statistically, women's confidence levels significantly increased with respect to making decisions about their pregnancy after Internet usage (p < 0.05). In this study, the Internet played a significant part in the respondents' health information seeking and decision making in pregnancy. Health professionals need to be ready to support pregnant women in online data retrieval, interpretation, and application.
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            Evolving knowledge of the teratogenicity of medications in human pregnancy.

            A majority of pregnant women take at least one medication during pregnancy, although the safety of such drugs during pregnancy is not always known. We reviewed the safety during pregnancy of 172 drugs approved by the US Food and Drug Administration (FDA) from 2000 to 2010 using the TERIS risk rating system. We also reviewed safety information for 468 drugs approved by the FDA from 1980 to 2000 to determine if revisions in risk categories had been made in the last 10 years. The teratogenic risk in human pregnancy was "undetermined" for 168 (97.7%) of drug treatments approved between 2000 and 2010. Furthermore, the amount of data available regarding safety in pregnancy was rated as "none" for 126 (73.3%) of these drugs. For those drugs approved between 1980 and 2000, only 23 (5%) changed a full risk category or more in the past 10 years. Sources of data that led to a revised risk were derived from exposure cohort studies performed through record linkage studies, teratogen information services, large population-based case-control studies, and pregnancy registries. The mean time for a treatment initially classified as having an "undetermined" risk to be assigned a more precise risk was 27 years (95% confidence interval 26-28 years). The lack of information needed to assess the safety of drug treatments during human pregnancy remains a serious public health problem. A more active approach to post-marketing surveillance for teratogenic effects is necessary. Copyright © 2011 Wiley-Liss, Inc.
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              Digital Drug Safety Surveillance: Monitoring Pharmaceutical Products in Twitter

              Background Traditional adverse event (AE) reporting systems have been slow in adapting to online AE reporting from patients, relying instead on gatekeepers, such as clinicians and drug safety groups, to verify each potential event. In the meantime, increasing numbers of patients have turned to social media to share their experiences with drugs, medical devices, and vaccines. Objective The aim of the study was to evaluate the level of concordance between Twitter posts mentioning AE-like reactions and spontaneous reports received by a regulatory agency. Methods We collected public English-language Twitter posts mentioning 23 medical products from 1 November 2012 through 31 May 2013. Data were filtered using a semi-automated process to identify posts with resemblance to AEs (Proto-AEs). A dictionary was developed to translate Internet vernacular to a standardized regulatory ontology for analysis (MedDRA®). Aggregated frequency of identified product-event pairs was then compared with data from the public FDA Adverse Event Reporting System (FAERS) by System Organ Class (SOC). Results Of the 6.9 million Twitter posts collected, 4,401 Proto-AEs were identified out of 60,000 examined. Automated, dictionary-based symptom classification had 72 % recall and 86 % precision. Similar overall distribution profiles were observed, with Spearman rank correlation rho of 0.75 (p < 0.0001) between Proto-AEs reported in Twitter and FAERS by SOC. Conclusion Patients reporting AEs on Twitter showed a range of sophistication when describing their experience. Despite the public availability of these data, their appropriate role in pharmacovigilance has not been established. Additional work is needed to improve data acquisition and automation.
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                Author and article information

                Contributors
                Journal
                J Med Internet Res
                J. Med. Internet Res
                JMIR
                Journal of Medical Internet Research
                JMIR Publications (Toronto, Canada )
                1439-4456
                1438-8871
                August 2019
                07 August 2019
                : 21
                : 8
                : e13003
                Affiliations
                [1 ] Department of Clinical Research University of Basel Basel Switzerland
                [2 ] Patient Safety Novartis Pharma AG Basel Switzerland
                [3 ] School of Health and Human Sciences University of Hertfordshire Hatfield United Kingdom
                [4 ] Booz Allen Hamilton Inc Boston, MA United States
                [5 ] Department of Cranio-Maxillofacial Surgery University Hospital of Basel Basel Switzerland
                [6 ] Hightech Research Center of Cranio-Maxillofacial Surgery University of Basel Basel Switzerland
                Author notes
                Corresponding Author: Britt-Isabelle Berg isabelle.berg@ 123456usb.ch
                Author information
                http://orcid.org/0000-0001-6351-8235
                http://orcid.org/0000-0001-9576-3489
                http://orcid.org/0000-0002-1276-9250
                http://orcid.org/0000-0003-3256-6108
                http://orcid.org/0000-0002-4267-0761
                Article
                v21i8e13003
                10.2196/13003
                6702799
                31392963
                2e3cd4ef-a8db-489e-b6fb-ba719b966e03
                ©Bita Rezaallah, David John Lewis, Carrie Pierce, Hans-Florian Zeilhofer, Britt-Isabelle Berg. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 07.08.2019.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/.as well as this copyright and license information must be included.

                History
                : 5 December 2018
                : 8 April 2019
                : 2 June 2019
                : 29 June 2019
                Categories
                Original Paper
                Original Paper

                Medicine
                pharmacovigilance,machine learning,pregnancy outcome,postpartum,central nervous system agents,risk assessment,text mining

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