How do others cope?: Extracting coping strategies for adverse drug events from social media

Patients advise their peers on how to cope with their illness in daily life on online support groups. To date, no efforts have been made to automatically extract recommended coping strategies from online patient discussion groups. We introduce this new task, which poses a number of challenges including complex, long entities, a large long-tailed label space, and cross-document relations. We present an initial ontology for coping strategies as a starting point for future research on coping strategies, and the first end-to-end pipeline for extracting coping strategies for side effects. We also compared two possible computational solutions for this novel and highly challenging task; multi-label classification and named entity recognition (NER) with entity linking (EL). We evaluated our methods on the discussion forum from the Facebook group of the worldwide patient support organization 'GIST support international' (GSI); GIST support international donated the data to us. We found that coping strategy extraction is difficult and both methods attain limited performance (measured with F1 score) on held out test sets; multi-label classification outperforms NER+EL (F1=0.220 vs F1=0.155). An inspection of the multi-label classification output revealed that for some of the incorrect predictions, the reference label is close to the predicted label in the ontology (e.g. the predicted label 'juice' instead of the more specific reference label 'grapefruit juice'). Performance increased to F1=0.498 when we evaluated at a coarser level of the ontology. We conclude that our pipeline can be used in a semi-automatic setting, in interaction with domain experts to discover coping strategies for side effects from a patient forum. For example, we found that patients recommend ginger tea for nausea and magnesium and potassium supplements for cramps.This information can be used as input for patient surveys or clinical studies.Algorithms and the Foundations of Software technolog

Automated gathering of real-world data from online patient forums can complement pharmacovigilance for rare cancers

Current methods of pharmacovigilance result in severe under-reporting of adverse drug events (ADEs). Patient forums have the potential to complement current pharmacovigilance practices by providing real-time uncensored and unsolicited information. We are the first to explore the value of patient forums for rare cancers. To this end, we conduct a case study on a patient forum for Gastrointestinal Stromal Tumor patients. We have developed machine learning algorithms to automatically extract and aggregate side effects from messages on open online discussion forums. We show that patient forum data can provide suggestions for which ADEs impact quality of life the most: For many side effects the relative reporting rate differs decidedly from that of the registration trials, including for example cognitive impairment and alopecia as side effects of avapritinib. We also show that our methods can provide real-world data for long-term ADEs, such as osteoporosis and tremors for imatinib, and novel ADEs not found in registration trials, such as dry eyes and muscle cramping for imatinib. We thus posit that automated pharmacovigilance from patient forums can provide real-world data for ADEs and should be employed as input for medical hypotheses for rare cancers.Algorithms and the Foundations of Software technolog

A qualitative research on co-creating care pathways for Sarcoma and GIST by stimulating reflection

Introduction: Care Pathway Management intends to enhance the quality of care by restructuring care services. As recipients of care, patients have relevant experiential knowledge on the provision of care, but they are rarely involved in Care Pathway Management due to various barriers. This study aims to acquire insights into how patients can be meaningfully involved in Care Pathway Management. Methods: A case study was cond

Risk factors for borderline personality disorder in treatment seeking patients with a substance use disorder: An international multicenter study

Borderline personality disorder (BPD) and substance use disorders (SUDs) often co-occur, partly because they share risk factors. In this international multicenter study, risk factors for BPD were examined for SUD patients. In total, 1,205 patients were comprehensively examined by standardized interviews and questionnaires on psychiatric diagnosis and risk factors, and it was found that 1,033 (85.7%) had SUDs without BPD (SUD) and 172 (14.3%) had SUD with BPD (SUD + BPD). SUD + BPD patients were significantly younger, more often females and more often diagnosed with comorbid adult attention deficit/hyperactivity disorder. SUD + BPD patients did not differ from SUD patients on most risk factors typical for SUD such as maternal use of drugs during pregnancy or parents having any SUD. However, SUD + BPD patients did have a higher risk of having experienced emotional and physical abuse, neglect, or family violence in childhood compared to SUD patients, suggesting that child abuse and family violence are BPD-specific risk factors in patients with SUDs

Symptoms reported by gastrointestinal stromal tumour (GIST) patients on imatinib treatment: combining questionnaire and forum data

Algorithms and the Foundations of Software technolog

Sample bias in web-based patient-generated health data of Dutch patients with gastrointestinal stromal tumor: survey study

BACKGROUND\nOBJECTIVE\nMETHODS\nRESULTS\nCONCLUSIONS\nIncreasingly, social media is being recognized as a potential resource for patient-generated health data, for example, for pharmacovigilance. Although the representativeness of the web-based patient population is often noted as a concern, studies in this field are limited.\nThis study aimed to investigate the sample bias of patient-centered social media in Dutch patients with gastrointestinal stromal tumor (GIST).\nA population-based survey was conducted in the Netherlands among 328 patients with GIST diagnosed 2-13 years ago to investigate their digital communication use with fellow patients. A logistic regression analysis was used to analyze clinical and demographic differences between forum users and nonusers.\nOverall, 17.9% (59/328) of survey respondents reported having contact with fellow patients via social media. Moreover, 78% (46/59) of forum users made use of GIST patient forums. We found no statistically significant differences for age, sex, socioeconomic status, and time since diagnosis between forum users (n=46) and nonusers (n=273). Patient forum users did differ significantly in (self-reported) treatment phase from nonusers (P=.001). Of the 46 forum users, only 2 (4%) were cured and not being monitored; 3 (7%) were on adjuvant, curative treatment; 19 (41%) were being monitored after adjuvant treatment; and 22 (48%) were on palliative treatment. In contrast, of the 273 patients who did not use disease-specific forums to communicate with fellow patients, 56 (20.5%) were cured and not being monitored, 31 (11.3%) were on curative treatment, 139 (50.9%) were being monitored after treatment, and 42 (15.3%) were on palliative treatment. The odds of being on a patient forum were 2.8 times as high for a patient who is being monitored compared with a patient that is considered cured. The odds of being on a patient forum were 1.9 times as high for patients who were on curative (adjuvant) treatment and 10 times as high for patients who were in the palliative phase compared with patients who were considered cured. Forum users also reported a lower level of social functioning (84.8 out of 100) than nonusers (93.8 out of 100; P=.008).\nForum users showed no particular bias on the most important demographic variables of age, sex, socioeconomic status, and time since diagnosis. This may reflect the narrowing digital divide. Overrepresentation and underrepresentation of patients with GIST in different treatment phases on social media should be taken into account when sourcing patient forums for patient-generated health data. A further investigation of the sample bias in other web-based patient populations is warranted.Algorithms and the Foundations of Software technolog

Enithelioid hemangioendothelioma, an ultra-rare cancer : a consensus paper from the community of experts

Epithelioid hemangioendothelioma (EHE) is an ultra-rare, translocated, vascular sarcoma. EHE clinical behavior is variable, ranging from that of a low-grade malignancy to that of a high-grade sarcoma and it is marked by a high propensity for systemic involvement. No active systemic agents are currently approved specifically for EHE, which is typically refractory to the antitumor drugs used in sarcomas. The degree of uncertainty in selecting the most appropriate therapy for EHE patients and the lack of guidelines on the clinical management of the disease make the adoption of new treatments inconsistent across the world, resulting in suboptimal outcomes for many EHE patients. To address the shortcoming, a global consensus meeting was organized in December 2020 under the umbrella of the European Society for Medical Oncology (ESMO) involving >80 experts from several disciplines from Europe, North America and Asia, together with a patient representative from the EHE Group, a global, disease-specific patient advocacy group, and Sarcoma Patient EuroNet (SPAEN). The meeting was aimed at defining, by consensus, evidence-based best practices for the optimal approach to primary and metastatic EHE. The consensus achieved during that meeting is the subject of the present publication.Peer reviewe