利用患者论坛讨论和自然语言处理深入了解早期乳腺癌治疗中激素疗法的患者体验。

IF 3.3 Q2 ONCOLOGY
Sameet Sreenivasan, Chao Fang, Emuella M Flood, Natasha Markuzon, Jasmine Y Y Sze
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引用次数: 0

摘要

目的:了解早期乳腺癌(eBC)患者的真实经历对于优化治疗效果和发展患者护理至关重要。然而,由于缺乏患者层面的数据,阻碍了临床开发。本社交聆听研究利用乳腺癌网站(breastcancer.org)患者论坛上的帖子了解患者对激素疗法(HT)治疗早期乳腺癌的症状和影响的见解,为未来的临床研究提供信息:方法:使用自然语言处理 (NLP) 和机器学习技术从 500,000 个帖子样本中识别与 eBC 相关的主题。在对相关数据进行筛选后,保留了 362,074 篇 eBC 帖子,用于进一步分析与 HT 相关的症状和影响,以及对症状严重程度、疼痛部位和使用运动和瑜伽进行症状管理的见解:总的来说,32 种症状和 9 种影响与≥一种高血压有显著关联。潮热(相对风险 [RR],6.70 [95% CI,3.36 至 13.36])、关节痛(RR,6.67 [95% CI,3.53 至 12.59])、体重增加(RR,4.83 [95% CI,3.20 至 7.28])、情绪波动(RR,7.36 [95% CI, 5.75 to 9.42])、失眠(RR, 4.76 [95% CI, 3.14 to 7.22])和抑郁(RR, 3.05 [95% CI, 1.71 to 5.44])显示出最强的关联性。尽管严重头痛、头晕、背痛和肌肉痉挛在 eBC 帖子中的总体发生率较低,但这些症状与≥一种 HT 有显著关联:通过社会聆听方法,可以从一个大型在线乳腺癌论坛的eBC HT帖子中发现真实世界的见解,该论坛收集了来自独特的不同患者群体的经验。使用 NLP 有可能扩大对患者反馈的分析范围,并揭示出患者治疗经历中的可行见解,从而为未来疗法的开发提供依据,并改善对 eBC 患者的护理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Insights Into the Patient Experience of Hormone Therapy for Early Breast Cancer Treatment Using Patient Forum Discussions and Natural Language Processing.

Purpose: Understanding the real-world experience of patients with early breast cancer (eBC) is imperative for optimizing outcomes and evolving patient care. However, there is a lack of patient-level data, hindering clinical development. This social listening study was performed to understand patient insights into symptoms and impacts of hormone therapy (HT) for eBC using posts from patient forums on breastcancer.org to inform future clinical research.

Methods: Natural language processing (NLP) and machine learning techniques were used to identify themes related to eBC from a sample of 500,000 posts. After relevant data selection, 362,074 eBC posts were retained for further analysis of symptoms and impacts related to HT, as well as insights into symptom severity, pain locations, and symptom management using exercise and yoga.

Results: Overall, 32 symptoms and nine impacts had significant associations with ≥one HT. Hot flush (relative risk [RR], 6.70 [95% CI, 3.36 to 13.36]), arthralgia (RR, 6.67 [95% CI, 3.53 to 12.59]), weight increased (RR, 4.83 [95% CI, 3.20 to 7.28]), mood swings (RR, 7.36 [95% CI, 5.75 to 9.42]), insomnia (RR, 4.76 [95% CI, 3.14 to 7.22]), and depression (RR, 3.05 [95% CI, 1.71 to 5.44]) demonstrated the strongest associations. Severe headache, dizziness, back pain, and muscle spasms showed significant associations with ≥one HT despite their low overall prevalence in eBC posts.

Conclusion: The social listening approach allowed the identification of real-world insights from posts specific to eBC HT from a large-scale online breast cancer forum that captured experiences from a uniquely diverse group of patients. Using NLP has a potential to scale analysis of patient feedback and reveal actionable insights into patient experiences of treatment that can inform the development of future therapies and improve the care of patients with eBC.

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来源期刊
CiteScore
6.20
自引率
4.80%
发文量
190
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