There is no consensus on the preferred method for defining the non-inferiority margin in non-inferiority trials, and previous studies showed that the rationale for its choice is often not reported. This study investigated how the non-inferiority margin is defined in the published literature, and whether its reporting has changed over time. A systematic PubMed search was conducted for all published randomized, double-blind, non-inferiority trials from January 1, 1966, to February 6, 2015. The primary outcome was the number of margins that were defined by methods other than the historical evidence of the active comparator. This was evaluated for a time trend. We also assessed the under-reporting of the methods of defining the margin as a secondary outcome, and whether this changed over time. Both outcomes were analyzed using a Poisson log-linear model. Predictors for better reporting of the methods, and the use of the fixed-margin method (one of the historical evidence methods) were also analyzed using logistic regression. Two hundred seventy-three articles were included, which account for 273 non-inferiority margins. There was no statistically significant difference in the number of margins that were defined by other methods compared to those defined based on the historical evidence (ratio 2.17, 95% CI 0.86 to 5.82, p = 0.11), and this did not change over time. The number of margins for which methods were unreported was similar to those with reported methods (ratio 1.35, 95% CI 0.76 to 2.43, p = 0.31), with no change over time. The method of defining the margin was less often reported in journals with low-impact factors compared to journals with high-impact factors (OR 0.20; 95% CI 0.10 to 0.37, p < 0.0001). The publication of the FDA draft guidance in 2010 was associated with increased reporting of the fixed-margin method (after versus before 2010) (OR 3.54; 95% CI 1.12 to 13.35, p = 0.04). Non-inferiority margins are not commonly defined based on the historical evidence of the active comparator, and they are poorly reported. Authors, reviewers, and editors need to take notice of reporting this critical information to allow for better judgment of non-inferiority trials.

Background: The risk of surgical site infections (SSIs), particularly methicillin-resistant Staphylococcus aureus (MRSA) SSIs, after spinal surgeries is one of the most daunting experiences to patients and surgeons. Some authors suggest applying vancomycin powder on the wound before skin closure to minimize the risk of SSIs; however, this practice is not supported by well-established evidence. This study sought to assess the effectiveness of topical (i.e. intra-wound) vancomycin in minimizing the risk of SSIs in patients who underwent spinal surgeries at a Saudi hospital. Methods: A retrospective cohort study was conducted using the hospital database. Patients who underwent spinal surgeries from the period of 09/2013 to 09/2019 were included and followed up (observed from the time of the surgery) to 30 days (surgeries without implants) or 90 days (with implants). The odds ratio (OR) of the primary outcome between vancomycin treated versus non-treated patients was estimated using a logistic regression model adjusting for the measured confounders. A sensitivity analysis was conducted using propensity score analysis (inverse probability of treatment weighting [IPTW] with stabilized weights) to control for confounding by indication. All study analyses were completed using RStudio Version 1.2.5033. Results: We included 81 vancomycin treated vs. 375 untreated patients with 28 infections (8/81 vs. 20/375; respectively). The adjusted OR of SSIs between the two groups was 0.40 (95% confidence interval [CI] 0.11 to 1.34). The result of the propensity score analysis was consistent (OR: 0.97 [95% CI 0.35 to 2.68]). Conclusions: We could not find a lower association of SSIs with intra-wound vancomycin in patients who underwent spinal surgeries. Further studies are needed to assess benefits of using topical vancomycin for this indication vs. the risk of antimicrobial resistance.

Purpose: To compare the effectiveness and safety of a drug in daily practice with the outcomes of a target non‐inferiority trial by rigorously mimickingin an observational study the trial's design features.Methods: This cohort study was conducted using the British Clinical Practice Research Datalink (CPRD) to emulate the ROCKET AF (Rivaroxaban Once Daily Oral Direct Factor Xa Inhibition Compared with Vitamin K Antagonism for Prevention of Stroke and Embolism Trial in Atrial Fibrillation) trial. Patients with atrial fibrillation who were newly prescribed (>=12 months of no use) either rivaroxaban or warfarinfrom October 2008 to December 2017 were included. Non‐inferiority of rivaroxaban to warfarin in the prevention of stroke or systemic embolism was assessed in different analysis populations (intention‐to‐treat [ITT], per‐protocol [PP], and as‐treated populations) using a hazardratio (HR) of 1.46 as the non‐inferiority margin. Major bleeding (safety outcome) was also assessed and compared to that of the target trial. All outcomes were analyzed using Cox‐proportional hazard analyses.Results: We included 25,473 incident users of rivaroxaban (n=4,008) or warfarin(n=21,465). Similar to the trial, non‐inferiority in the primary out come was demonstrated in all three analysis populations: HR=1.04 (95%CI 0.84 to 1.30) (ITT), HR=0.98 (95%CI 0.70 to 1.38) (PP), and HR=1.11 (95%CI 0.86 to 1.42) (as‐treated). Risk of major bleeding was also similar to the target trial.Conclusion: The results of this study provide supportive evidence to the effectiveness of rivaroxaban and adds knowledge on the usefulness of emulating a non‐inferiority trial to assess drug effectiveness.

Objectives This study was conducted to assess the validity of recording (and the original diagnostic practice) of type 2 diabetes mellitus at a hospital whose records were integrated to a centralised database (the standardised common data model (CDM) of the Saudi National Pharmacoepidemiologic Database (NPED)). Design A retrospective single-centre validation study. Settings Data of the study participants were extracted from the CDM of the NPED (only records of one tertiary care hospital were integrated at the time of the study) between 1 January 2013 and 1 July 2018. Participants A random sample of patients with type 2 diabetes mellitus (≥18 years old and with a code of type 2 diabetes mellitus) matched with a control group (patients without diabetes) based on age and sex. Outcome measures The standardised coding of type 2 diabetes in the CDM was validated by comparing the presence of diabetes in the CDM versus the original electronic records at the hospital, the recording in paper-based medical records, and the physician re-assessment of diabetes in the included cases and controls, respectively. Sensitivity, specificity, positive predictive value and negative predictive value were estimated for each pairwise comparison using RStudio V.1.4.1103. Results A total of 437 random sample of patients with type 2 diabetes mellitus was identified and matched with 437 controls. Only 190 of 437 (43.0%) had paper-based medical records. All estimates were above 90% except for sensitivity and specificity of CDM versus paper-based records (54%; 95% CI 47% to 61% and 68%; 95% CI 62% to 73%, respectively). Conclusions This study provided an assessment to the extent of which only type 2 diabetes mellitus code can be used to identify patients with this disease at a Saudi centralised database. A future multi-centre study would help adding more emphasis to the study findings.

Previous studies have suggested that drug pricing could contribute to drug shortages; however, there is limited quantitative assessment of this potential causal association. This retrospective database analysis aimed to investigate the association between drug prices and drug shortage incidents in Saudi Arabia. This was a retrospective database analysis study. Drugs with shortage notifications sent to the Saudi Food and Drug Authority (SFDA) between January 2017 and December 2020 were included. Each drug's foreign-to-Saudi price ratio (FTSPR) was calculated by dividing the mean international price by the Saudi price. Drugs were categorized into three groups based on their FTSPR: Group 1 (FTSPR > 1), Group 2 (FTSPR = 1), and Group 3 (FTSPR < 1). The primary outcome was the ratio of mean counts (mCR) between the three groups, with Group 3 serving as the control group. The analysis was adjusted for the measured confounders using a negative binomial regression model. A total of 900 drugs were included in the study, with 348 in Group 1, 345 in Group 2, and 209 in Group 3. The mean count in Group 1 was higher compared to Group 3 (mCR: 1.88; 95% confidence interval [CI] 1.24 to 2.83), while the mean counts between Group 2 and Group 3 were comparable (mCR: 1.39; 95% CI 0.92 to 2.09). Our findings indicate an association between drug shortage incidents and higher prices of drugs outside Saudi Arabia. Further studies are needed to explore this causal relationship in different contexts.