Applying the Rapid OPPERA Algorithm to Predict Persistent Pain Outcomes Among a Cohort of Women Undergoing Breast Cancer Surgery.
Applying the Rapid OPPERA Algorithm to Predict Persistent Pain Outcomes Among a Cohort of Women Undergoing Breast Cancer Surgery.
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DOI：
10.1016/j.jpain.2022.07.012
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发表时间：
2022-12
期刊：
影响因子：
4
通讯作者：
Schreiber, Kristin L.
中科院分区：
文献类型：
--
作者：
Wilson, Jenna M.;Colebaugh, Carin A.;Flowers, K. Mikayla;Overstreet, Demario;Edwards, Robert R.;Maixner, William;Smith, Shad B.;Schreiber, Kristin L.
乳房手术后持续性乳房切除术后疼痛的持续时间和严重程度在不同患者之间存在差异，部分原因是疼痛处理的个体间差异。快速OPPERA算法（ROPA）根据四个关键的心理物理和心理社会特征，经验性地确定了三组具有不同慢性疼痛风险的患者。我们的目的是在接受乳房手术的围手术期队列中测试这种基于组的聚类类型，以研究术后疼痛结局的差异。计划接受乳腺癌手术的女性（N=228）前瞻性入组了一项纵向观察性研究。术前评估压力疼痛阈值（PPT）、焦虑、抑郁和躯体化。术后2周、3个月、6个月和12个月，患者报告了手术区域疼痛严重程度、疼痛对认知/情感和身体功能的影响以及疼痛灾难性。使用患者术前焦虑、抑郁、躯体化和PPT评分的ROPA聚类将患者分为三组：适应性（低心理社会评分，高PPT）、疼痛敏感性（中等心理社会评分，低PPT）和整体症状（高心理社会评分，中等PPT）。与其他聚类相比，总体症状聚类报告了手术后显著更差的持续性疼痛结局。研究结果表明，基于患者特征的聚类算法，如ROPA，可以概括不同的诊断和临床环境，表明“人的类型”在理解疼痛变异性的重要性。本文介绍了一个实际的翻译以前开发的患者聚类解决方案，基于慢性疼痛队列，围手术期队列的妇女接受乳腺癌手术。这种术前特征可能有助于临床医生根据对术后疼痛的预测应用个性化干预。
Persistent post-mastectomy pain after breast surgery is variable in duration and severity across patients, due in part to interindividual variability in pain processing. The Rapid OPPERA Algorithm (ROPA) empirically identified three clusters of patients with different risk of chronic pain based on four key psychophysical and psychosocial characteristics. We aimed to test this type of group-based clustering within in a perioperative cohort undergoing breast surgery to investigate differences in postsurgical pain outcomes. Women (N=228) scheduled for breast cancer surgery were prospectively enrolled in a longitudinal observational study. Pressure pain threshold (PPT), anxiety, depression, and somatization were assessed preoperatively. At 2-weeks, 3, 6, and 12-months after surgery, patients reported surgical area pain severity, impact of pain on cognitive/emotional and physical functioning, and pain catastrophizing. The ROPA clustering, which used patients’ preoperative anxiety, depression, somatization, and PPT scores, assigned patients to three groups: Adaptive (low psychosocial scores, high PPT), Pain Sensitive (moderate psychosocial scores, low PPT), and Global Symptoms (high psychosocial scores, moderate PPT). The Global Symptoms cluster, compared to other clusters, reported significantly worse persistent pain outcomes following surgery. Findings suggest that patient characteristic-based clustering algorithms, like ROPA, may generalize across diverse diagnoses and clinical settings, indicating the importance of “person type” in understanding pain variability. This article presents the practical translation of a previously developed patient clustering solution, based within a chronic pain cohort, to a perioperative cohort of women undergoing breast cancer surgery. Such preoperative characterization could potentially help clinicians apply personalized interventions based on predictions concerning postsurgical pain.
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DOI：
10.1016/j.jpain.2018.07.001
发表时间：
2018-12
期刊：
The journal of pain
影响因子：
--
作者：
Meints SM;Wang V;Edwards RR
通讯作者：
Edwards RR
影响因子：
120.7
作者：
Gartner, Rune;Jensen, Maj-Britt;Kehlet, Henrik
通讯作者：
Kehlet, Henrik
影响因子：
7.4
作者：
Ruscheweyh, Ruth;Marziniak, Martin;Knecht, Stefan
通讯作者：
Knecht, Stefan
影响因子：
7.4
作者：
Bair, Eric;Gaynor, Sheila;Maixner, William
通讯作者：
Maixner, William
影响因子：
7.4
作者：
Gaynor SM;Bortsov A;Bair E;Fillingim RB;Greenspan JD;Ohrbach R;Diatchenko L;Nackley A;Tchivileva IE;Whitehead W;Alonso AA;Buchheit TE;Boortz-Marx RL;Liedtke W;Park JJ;Maixner W;Smith SB
通讯作者：
Smith SB