Open Access

Abstract Background Opioid use for chronic non‐cancer pain (CNCP) is under debate. In the absence of pan‐European guidance on this issue, a position paper was commissioned by the European Pain Federation (EFIC). Methods The clinical practice recommendations were developed by eight scientific societies and one patient self‐help organization under the coordination of EFIC. A systematic literature search in MEDLINE (up until January 2020) was performed. Two categories of guidance are given: Evidence‐based recommendations (supported by evidence from systematic reviews of randomized controlled trials or of observational studies) and Good Clinical Practice (GCP) statements (supported either by indirect evidence or by case‐series, case–control studies and clinical experience). The GRADE system was applied to move from evidence to recommendations. The recommendations and GCP statements were developed by a multiprofessional task force (including nursing, service users, physicians, physiotherapy and psychology) and formal multistep procedures to reach a set of consensus recommendations. The clinical practice recommendations were reviewed by five external reviewers from North America and Europe and were also posted for public comment. Results The European Clinical Practice Recommendations give guidance for combination with other medications, the management of frequent (e.g. nausea, constipation) and rare (e.g. hyperalgesia) side effects, for special clinical populations (e.g. children and adolescents, pregnancy) and for special situations (e.g. liver cirrhosis). Conclusion If a trial with opioids for chronic noncancer pain is conducted, detailed knowledge and experience are needed to adapt the opioid treatment to a special patient group and/or clinical situation and to manage side effects effectively. Significance If a trial with opioids for chronic noncancer pain is conducted, detailed knowledge and experience are needed to adapt the opioid treatment to a special patient group and/or clinical situation and to manage side effects effectively. A collaboration of medical specialties and of all health care professionals is needed for some special populations and clinical situations.

Abstract Purpose This study aims to assess the implementation of published research, contraindications, and warnings on the prescription of dual renin‐angiotensin‐hormone system (RAS) blockade in ambulatory care in Germany. Methods Cohort study based on health claims data of 6.7 million subjects from 2008 to 2015. Yearly prevalence and incidence for dual RAS blockade with (a) angiotensin‐converting enzyme inhibitors and angiotensin‐receptor blockers (ACEI + ARB) and (b) aliskiren and ACEI or ARB (aliskiren + ACEI/ARB) were calculated. We assessed prescriber specialty and associations between discontinuing dual RAS blockade with specialist (internal medicine, cardiology, nephrology) visits and hospital discharge in the previous year. Results A total of 2 984 517 patients were included (age 51.4 ± SD 18.4 y, 48.5% male). Prescription rates for ACEI + ARB decreased from 0.6% (n = 17 907) to 0.4% (n = 12 237) and for aliskiren + ACEI/ARB from 0.23% (n = 6634) to 0.03% (n = 818). Incident prescriptions decreased from 0.23% (n = 6705) to 0.19% (n = 5055) (ACE + ARB) and from 0.1% (n = 2796) to 0.005% (n = 142) (aliskiren + ACE/ARB); 59% of ACEI + ARB and 48% of aliskiren + ACE/ARB combinations were prescribed only by one physician. Of those, 73% (ACEI + ARB) and 58% (aliskiren + ACE/ARB) were primary care providers (PCPs). Discontinuing dual RAS blockade was associated with specialist care and hospital discharge in the previous year (specialist care: RR 1.4, 95% CI, 1.3‐1.6; hospital visit: RR 1.5, 95% CI, 1.3‐1.6). Conclusions Our results suggest a delayed uptake of treatment recommendation for ACEI + ARB and a higher impact of Dear Doctor letters addressing PCPs directly compared with published research, contraindications, and warnings. Targeted continuous medical education, practice software alerts, and stronger involvement of pharmacists might improve the implementation of medication safety recommendations in ambulatory care.

(1) Background: Predicting chronic low back pain (LBP) is of clinical and economic interest as LBP leads to disabilities and health service utilization. This study aims to build a competitive and interpretable prediction model; (2) Methods: We used clinical and claims data of 3837 participants of a population-based cohort study to predict future LBP consultations (ICD-10: M40.XX-M54.XX). Best subset selection (BSS) was applied in repeated random samples of training data (75% of data); scoring rules were used to identify the best subset of predictors. The rediction accuracy of BSS was compared to randomforest and support vector machines (SVM) in the validation data (25% of data); (3) Results: The best subset comprised 16 out of 32 predictors. Previous occurrence of LBP increased the odds for future LBP consultations (odds ratio (OR) 6.91 [5.05; 9.45]), while concomitant diseases reduced the odds (1 vs. 0, OR: 0.74 [0.57; 0.98], >1 vs. 0: 0.37 [0.21; 0.67]). The area-under-curve (AUC) of BSS was acceptable (0.78 [0.74; 0.82]) and comparable with SVM (0.78 [0.74; 0.82]) and randomforest (0.79 [0.75; 0.83]); (4) Conclusions: Regarding prediction accuracy, BSS has been considered competitive with established machine-learning approaches. Nonetheless, considerable misclassification is inherent and further refinements are required to improve predictions.