Network meta-analysis (NMA), combining direct and indirect comparisons, is increasingly being used to examine the comparative effectiveness of medical interventions. Minimal guidance exists on how to rate the quality of evidence supporting treatment effect estimates obtained from NMA. We present a four-step approach to rate the quality of evidence in each of the direct, indirect, and NMA estimates based on methods developed by the GRADE working group. Using an example of a published NMA, we show that the quality of evidence supporting NMA estimates varies from high to very low across comparisons, and that quality ratings given to a whole network are uninformative and likely to mislead. Network meta-analysis (NMA) that simultaneously addresses the comparative effectiveness and/or safety of multiple interventions through combining direct and indirect estimates of effect is rapidly gaining popularity and influence. 1-6 Although NMA approaches appear attractive, 6-8 application of their results requires understanding the quality of the evidence. By quality of evidence, we mean the degree of confidence or certainty one can place in estimates of treatment effects.NMA is sufficiently new that terminology differs between authors and continues to evolve. Box 1 presents a glossary of terms used in this article.Rationale for an approach to rate the quality of evidence from NMA Recently, several articles have provided guidance regarding identification of the evidence for a NMA, 9 statistical aspects of conducting NMA, 10-17 and critical appraisal and interpretation of published NMA.18 19 Few of these, however, provide explicit guidance on how to rate the quality of the evidence. Reports of NMAs often describe the risk of bias of trials included in a NMA (such as method of randomisation, concealment of random allocation, masking, etc). [22][23][24] For example, a recent NMA compared the effects of coronary artery bypass grafting, various stents, and medical treatment on mortality, myocardial infarction, and the need for revascularisation among patients with stable coronary artery disease. The authors stated that appropriate methods of concealment of random allocation were reported for 71 trials (71%). 25 Fifty six trials (56%) reported blind adjudication of clinical outcomes, and for 69 trials (69%) data from intention to treat analyses were available. Although such an assessment of risk of bias describes the entire body of evidence (that is, all trials contributing evidence to the NMA), it does not acknowledge that the risk of bias is likely to differ across the comparisons of the network.1 For example, the risk of bias of studies comparing sirolimus eluting stents versus medical treatment may be considerably less than the risk of bias of studies comparing coronary artery bypass grafting with medical treatment. In addition, risk of bias is only one determinant of quality of evidence. Our confidence in effect estimates will, for instance, also decrease if there are large differences in results from study to study (for exampl...

Background: Despite the abundant literature on this topic, accurate prevalence estimates of pain in cancer patients are not available. We investigated the prevalence of pain in cancer patients according to the different disease stages and types of cancer.Patients and methods: A systematic review of the literature was conducted. An instrument especially designed for judging prevalence studies on their methodological quality was used. Methodologically acceptable articles were used in the meta-analyses.Results: Fifty-two studies were used in the meta-analysis. Pooled prevalence rates of pain were calculated for four subgroups: (i) studies including patients after curative treatment, 33% [95% confidence interval (CI) 21% to 46%]; (ii) studies including patients under anticancer treatment: 59% (CI 44% to 73%); (iii) studies including patients characterised as advanced/metastatic/terminal disease, 64% (CI 58% to 69%) and (iii) studies including patients at all disease stages, 53% (CI 43% to 63%). Of the patients with pain more than one-third graded their pain as moderate or severe. Pooled prevalence of pain was >50% in all cancer types with the highest prevalence in head/neck cancer patients (70%; 95% CI 51% to 88%). Conclusion:Despite the clear World Health Organisation recommendations, cancer pain still is a major problem.

We conclude that despite an acute pain protocol, postoperative pain treatment was unsatisfactory, especially after intermediate and major surgical procedures on an extremity or on the spine.

OBJECTIVEPainful diabetic peripheral neuropathy (PDPN) is a common complication of diabetes mellitus. Unfortunately, pharmacological treatment is often partially effective or accompanied by unacceptable side effects, and new treatments are urgently needed. Small observational studies suggested that spinal cord stimulation (SCS) may have positive effects. RESEARCH DESIGN AND METHODSWe performed a multicenter randomized clinical trial in 36 PDPN patients with severe lower limb pain not responding to conventional therapy. Twenty-two patients were randomly assigned to SCS in combination with the best medical treatment (BMT) (SCS group) and 14 to BMT only (BMT group). The SCS system was implanted only if trial stimulation was successful. Treatment success was defined as ‡50% pain relief during daytime or nighttime or "(very) much improved" for pain and sleep on the patient global impression of change (PGIC) scale at 6 months. RESULTSTrial stimulation was successful in 77% of the SCS patients. Treatment success was observed in 59% of the SCS and in 7% of the BMT patients (P < 0.01). Pain relief during daytime and during nighttime was reported by 41 and 36% in the SCS group and 0 and 7% in the BMT group, respectively (P < 0.05). Pain and sleep were "(very) much improved" in 55 and 36% in the SCS group, whereas no changes were seen in the BMT group, respectively (P < 0.001 and P < 0.05). One SCS patient died because of a subdural hematoma. CONCLUSIONSTreatment success was shown in 59% of patients with PDPN who were treated with SCS over a 6-month period, although this treatment is not without risks.Painful diabetic peripheral neuropathy (PDPN) is a common complication of diabetes mellitus (DM), and prevalence of PDPN ranges from 10 to 26% (1-3). In many patients, the pain is of such intensity that it has a major impact on patients' health-related quality of life (HRQoL) and functional ability, including interference with general activity, mood, mobility, work, social relations, sleep, and enjoyment of life (4).

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