{"title":"药物和非药物治疗对成年癌症患者慢性癌症疼痛强度的疗效:一项网络荟萃分析方案。","authors":"Wenhao Su, Xueling Li, Yanru Wang","doi":"10.1371/journal.pone.0322651","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Chronic cancer pain is very common symptom in cancer patients, but this issue has not been satisfactorily resolved by the conventional three-step analgesic therapy. There are multiple non-pharmacological interventions for managing chronic cancer pain, but we haven't reached a consensus on which non pharmacological treatment is the best and these treatments are lack of high-quality evidence. In order to identify the most effective non-pharmaceutical therapy alternatives and investigate further possible medication interventions, this study will use network meta-analysis to assess the therapeutic effects of pharmacological and non-pharmacological treatments on chronic cancer pain patients and support clinical decision-making by prioritizing therapies according to the most valuable clinical outcomes for these patients.</p><p><strong>Methods and analysis: </strong>We will carry out a systematic search of published randomized controlled trials (group, crossover, and parallel) in the PubMed, Web of Science, Cochrane Library, MEDLINE, Embase, and CINAHL databases, without language or date restrictions, in accordance with the PRISMA for Network Meta-Analyses (PRISMA-NMA) guidelines. Included studies must evaluate the effects of pharmacological and non-pharmacological treatments in patients with chronic cancer pain. Adult chronic cancer pain patients (≥ 18 years old) receiving pharmacological or non-pharmacological treatment will be our target participants. Our primary outcomes will be pain intensity, total effective rate of treatment, onset time, and quality of Life (QoL); Adverse reaction will be our secondary outcome. We'll utilize the mean difference (MD) for continuous variables, the odds ratio (OR) for binary variables, and the 95% confidence interval (CI) for interval estimates. The Cochrane Bias Risk Tool (RoB2.0) will be used to assess the bias risk of every RCT trial included in NMA. We will use Review Manager 5.3 software to conduct heterogeneity testing and meta-analysis. The network meta-analysis will be performed by ADDIS1.16.8 software. The Confidence in Network Meta-analysis (CINeMA) framework will be used to evaluate the level of confidence in the NMA results. Besides, we will use SUCRA for ranking the network meta-analysis results, and we will also apply normalized entropy to verify the accuracy of the SUCRA ranking outcomes.</p><p><strong>Discussion: </strong>This network meta-analysis will compare the efficacy of pharmacological versus non-pharmacological treatments for pain intensity in chronic cancer pain patients. The final analysis results may be significantly heterogeneous, because the population with cancerous pain suffers from different types of cancers. Owing to the databases primary reliance on our listed databases for inclusion, potentially valuable research will be overlooked.</p><p><strong>Registration: </strong>This study has been registered in the PROSPERO database (CRD42024505214).</p>","PeriodicalId":20189,"journal":{"name":"PLoS ONE","volume":"20 7","pages":"e0322651"},"PeriodicalIF":2.6000,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12270095/pdf/","citationCount":"0","resultStr":"{\"title\":\"Efficacy of pharmacological and non-pharmacological therapy on chronic cancer pain intensity of adults with cancer: A network meta-analysis protocol.\",\"authors\":\"Wenhao Su, Xueling Li, Yanru Wang\",\"doi\":\"10.1371/journal.pone.0322651\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Chronic cancer pain is very common symptom in cancer patients, but this issue has not been satisfactorily resolved by the conventional three-step analgesic therapy. There are multiple non-pharmacological interventions for managing chronic cancer pain, but we haven't reached a consensus on which non pharmacological treatment is the best and these treatments are lack of high-quality evidence. In order to identify the most effective non-pharmaceutical therapy alternatives and investigate further possible medication interventions, this study will use network meta-analysis to assess the therapeutic effects of pharmacological and non-pharmacological treatments on chronic cancer pain patients and support clinical decision-making by prioritizing therapies according to the most valuable clinical outcomes for these patients.</p><p><strong>Methods and analysis: </strong>We will carry out a systematic search of published randomized controlled trials (group, crossover, and parallel) in the PubMed, Web of Science, Cochrane Library, MEDLINE, Embase, and CINAHL databases, without language or date restrictions, in accordance with the PRISMA for Network Meta-Analyses (PRISMA-NMA) guidelines. Included studies must evaluate the effects of pharmacological and non-pharmacological treatments in patients with chronic cancer pain. 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引用次数: 0
摘要
背景:慢性癌性疼痛是癌症患者非常常见的症状,但传统的三步镇痛疗法并不能很好地解决这一问题。有多种非药物干预治疗慢性癌症疼痛,但我们尚未就哪种非药物治疗是最好的达成共识,这些治疗缺乏高质量的证据。为了确定最有效的非药物治疗方案,并进一步研究可能的药物干预措施,本研究将使用网络荟萃分析来评估药物和非药物治疗对慢性癌症疼痛患者的治疗效果,并根据这些患者最有价值的临床结果来优先考虑治疗方案,从而支持临床决策。方法和分析:我们将在PubMed、Web of Science、Cochrane Library、MEDLINE、Embase和CINAHL数据库中对已发表的随机对照试验(分组、交叉和平行)进行系统检索,不受语言和日期限制,按照PRISMA- nma网络元分析指南进行检索。纳入的研究必须评估药物和非药物治疗对慢性癌症疼痛患者的影响。接受药物或非药物治疗的成人慢性癌性疼痛患者(≥18岁)将成为我们的目标参与者。我们的主要结局是疼痛强度、治疗总有效率、发病时间和生活质量(QoL);不良反应将是我们的次要结果。对于连续变量,我们将使用均值差(MD),对于二元变量,我们将使用比值比(OR),对于区间估计,我们将使用95%置信区间(CI)。将使用Cochrane偏倚风险工具(RoB2.0)评估纳入NMA的每个RCT试验的偏倚风险。我们将使用Review Manager 5.3软件进行异质性测试和meta分析。网络meta分析采用ADDIS1.16.8软件进行。网络信心元分析(CINeMA)框架将用于评估NMA结果的信心水平。此外,我们将使用SUCRA对网络元分析结果进行排序,我们还将使用归一化熵来验证SUCRA排序结果的准确性。讨论:该网络荟萃分析将比较慢性癌症疼痛患者疼痛强度的药物治疗与非药物治疗的疗效。最终的分析结果可能存在显著的异质性,因为患有癌性疼痛的人群患有不同类型的癌症。由于数据库主要依赖于我们列出的数据库进行纳入,潜在的有价值的研究将被忽视。注册:本研究已在PROSPERO数据库中注册(CRD42024505214)。
Efficacy of pharmacological and non-pharmacological therapy on chronic cancer pain intensity of adults with cancer: A network meta-analysis protocol.
Background: Chronic cancer pain is very common symptom in cancer patients, but this issue has not been satisfactorily resolved by the conventional three-step analgesic therapy. There are multiple non-pharmacological interventions for managing chronic cancer pain, but we haven't reached a consensus on which non pharmacological treatment is the best and these treatments are lack of high-quality evidence. In order to identify the most effective non-pharmaceutical therapy alternatives and investigate further possible medication interventions, this study will use network meta-analysis to assess the therapeutic effects of pharmacological and non-pharmacological treatments on chronic cancer pain patients and support clinical decision-making by prioritizing therapies according to the most valuable clinical outcomes for these patients.
Methods and analysis: We will carry out a systematic search of published randomized controlled trials (group, crossover, and parallel) in the PubMed, Web of Science, Cochrane Library, MEDLINE, Embase, and CINAHL databases, without language or date restrictions, in accordance with the PRISMA for Network Meta-Analyses (PRISMA-NMA) guidelines. Included studies must evaluate the effects of pharmacological and non-pharmacological treatments in patients with chronic cancer pain. Adult chronic cancer pain patients (≥ 18 years old) receiving pharmacological or non-pharmacological treatment will be our target participants. Our primary outcomes will be pain intensity, total effective rate of treatment, onset time, and quality of Life (QoL); Adverse reaction will be our secondary outcome. We'll utilize the mean difference (MD) for continuous variables, the odds ratio (OR) for binary variables, and the 95% confidence interval (CI) for interval estimates. The Cochrane Bias Risk Tool (RoB2.0) will be used to assess the bias risk of every RCT trial included in NMA. We will use Review Manager 5.3 software to conduct heterogeneity testing and meta-analysis. The network meta-analysis will be performed by ADDIS1.16.8 software. The Confidence in Network Meta-analysis (CINeMA) framework will be used to evaluate the level of confidence in the NMA results. Besides, we will use SUCRA for ranking the network meta-analysis results, and we will also apply normalized entropy to verify the accuracy of the SUCRA ranking outcomes.
Discussion: This network meta-analysis will compare the efficacy of pharmacological versus non-pharmacological treatments for pain intensity in chronic cancer pain patients. The final analysis results may be significantly heterogeneous, because the population with cancerous pain suffers from different types of cancers. Owing to the databases primary reliance on our listed databases for inclusion, potentially valuable research will be overlooked.
Registration: This study has been registered in the PROSPERO database (CRD42024505214).
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