While medication labels are considered the authoritative resource for medication information, emerging research suggests that patient-generated health data (PGHD) are a valuable tool to understand the ways in which patients experience medications in real world settings. However, the relationship between these two data sources has not been closely examined. To understand how rates of medication side effects compare between a source of PGHD and medication labels, the current study compares adverse drug reaction rates from FDA medication labels with those self-reported by patients from an online patient community, PatientsLikeMe (PLM). The linear association between medication label and PLM nausea rates was evaluated using Spearman correlation, with an associated 95% confidence interval calculated based on 10,000 bootstrap iterations. The reporting ratio of PLM nausea rates to medication label nausea rates was defined for all treatments with non-zero medication label nausea rates. Lognormality of the distribution of this reporting ratio was assessed based on a Kolmogorov-Smirnov test (α = 0.05). Nausea rates for 163 medications were compared between the two data sources. Overall rates ranged from 0 to 60% for medication labels and 0 to 36% for PLM data with median rates of 6.4 and 3.7%, respectively. In general, nausea rates reported by patients in the online community were lower than those found in medication labels. This inconsistency was attributed to a variety of factors, including differences in data collection mechanisms and product use factors. Quantifiable and consistent differences exist between side effect rates reported on medication labels and those self-reported by patients based on real-world use. In general, self-reported rates of nausea associated with medication use were lower than those reported in medication labels. Although considered a definitive resource for medication information, this discrepancy demonstrates that medication labels may not comprehensively describe the patient experience. Results suggest that a combination of information from different sources may provide a more rounded and holistic view on medication safety and tolerability.

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在线患者社区和药物标签上处方药的恶心副作用发生率比较：一项探索性分析

尽管药物标签被视为药物信息的权威资源，但新兴研究表明，患者生成的健康数据（PGHD）是了解患者在现实世界中体验药物使用方式的宝贵工具。但是，这两个数据源之间的关系尚未得到仔细检查。为了了解PGHD来源和药物标签之间药物副作用的发生率如何比较，本研究将FDA药物标签中的药物不良反应率与在线患者社区PatientPikeMe（PLM）的患者自我报告的药物不良反应率进行了比较。使用Spearman相关性评估药物标签和PLM恶心率之间的线性关联，并基于10,000个bootstrap迭代计算关联的95％置信区间。对于所有非零药物标签恶心率的治疗，均定义了PLM恶心率与药物标签恶心率的报告比率。基于Kolmogorov-Smirnov检验（α= 0.05）评估了该报告比率分布的对数正态性。在两个数据源之间比较了163种药物的恶心率。药物标签的总体发生率范围为0至60％，PLM数据的总体发生率范围为0至36％，中位发生率分别为6.4和3.7％。通常，在线社区患者报告的恶心率低于药物标签中的恶心率。这种不一致的原因是多种因素，包括数据收集机制和产品使用因素的差异。药物标签上报告的副作用率与患者根据实际使用情况自行报告的副作用率之间存在可量化且一致的差异。通常，与药物使用相关的自我报告的恶心率低于药物标签中报告的恶心率。尽管被视为药品信息的权威资源，但这种差异表明药品标签可能无法全面描述患者的经历。结果表明，来自不同来源的信息的组合可能会提供关于药物安全性和耐受性的更全面和整体的观点。这种差异表明药物标签可能无法全面描述患者的经历。结果表明，来自不同来源的信息的组合可能会提供关于药物安全性和耐受性的更全面，更全面的观点。这种差异表明药物标签可能无法全面描述患者的经历。结果表明，来自不同来源的信息的组合可能会提供关于药物安全性和耐受性的更全面和整体的观点。