European Palliative Care Research Centre, Department of Cancer Research and Molecular Medicine, Faculty of Medicine, Norwegian University of Science and Technology, Trondheim, Norway Department of Oncology, Trondheim University Hospital, Trondheim, Norway Palliative Care, Pain Therapy and Rehabilitation Unit, Fondazione IRCCS (Istituto di Ricovero e Cura a Carraterre Scientifico [Italian Research Hospital]), Istituto Nazionale Dei Tumori, Milano, Italy Department of Anesthesiology and Emergency Medicine, Intensive Care Unit, Trondheim University Hospital, Trondheim, Norway Faculty of Medicine, University of Oslo, Oslo, Norway Regional Center for Excellence in Palliative Care, Oslo University Hospital, Oslo, Norway Scientific Directorate, IRCCS Arcispedale Santa Maria Nuova, Reggio-Emilia, Italy Center for the Evaluation and Research on Pain, Department of Oncology, Instituto di Ricerche Farmacologiche 'Mario Negri', Milan, Italy Department of Circulation and Medical Imaging, Faculty of Medicine, Norwegian Univeristy of Science and Technology, Trondheim, Norway.
Pain. 2012 Mar;153(3):696-703. doi: 10.1016/j.pain.2011.12.005. Epub 2012 Jan 20.
The overall aim of the present study was to further develop an evidence-based platform for the content of an international cancer pain classification system. Data from a multicentre, observational longitudinal study of cancer patients were analysed. Analyses were carried out in 2 samples: (A) Cross-sectional data of patients on opioids at inclusion, and (B) patients just admitted to palliative care. Outcome measures in the models we investigated were pain on average, worst pain, and pain relief at inclusion, and at day 14, respectively. Uni- and multivariate regression models were applied to test the explicative power on pain outcomes of a series of known pain domains, including incident pain, psychological distress, neuropathic pain, pain localisation, sleep disturbances, total morphine equivalent daily dose (MEDD), and cancer diagnosis. In the 2 analyses, 1529 (A) and 352 (B) patients were included, respectively. Incident pain, pain localisation, MEDD, use of nonsteroidal antiinflammatory drugs, and sleep were associated with one or more of the pain outcomes in analysis A, while initial pain intensity, initial pain relief, incident pain, localisation of pain, cancer diagnosis, and age were predictors in the longitudinal analysis. Identified domains explained 16% to 24% of the variability of the pain outcome. Initial pain intensity emerged as the strongest predictor of pain outcome after 2 weeks, and incident pain was confirmed to be a relevant domain. The regression models explained only a minor part of the variability of pain outcomes.
本研究的总体目标是进一步为国际癌症疼痛分类系统的内容开发一个基于证据的平台。对一项多中心、观察性纵向癌症患者研究的数据进行了分析。在两个样本中进行了分析：(A)纳入时正在使用阿片类药物的患者的横断面数据，以及 (B)刚刚进入姑息治疗的患者。我们研究的模型中的结局指标分别为纳入时、第 14 天的平均疼痛、最剧烈疼痛和疼痛缓解情况。应用单变量和多变量回归模型来测试一系列已知疼痛领域对疼痛结局的解释能力，包括新发疼痛、心理困扰、神经病理性疼痛、疼痛定位、睡眠障碍、每日吗啡等效剂量 (MEDD) 和癌症诊断。在这两项分析中，分别纳入了 1529 例（A）和 352 例（B）患者。新发疼痛、疼痛定位、MEDD、非甾体抗炎药的使用以及睡眠与分析 A 中一个或多个疼痛结局相关，而初始疼痛强度、初始疼痛缓解、新发疼痛、疼痛定位、癌症诊断和年龄是纵向分析中的预测因素。确定的领域解释了疼痛结局的 16%至 24%的可变性。初始疼痛强度是 2 周后疼痛结局的最强预测因素，新发疼痛被确认为一个相关领域。回归模型仅能解释疼痛结局可变性的一小部分。
