Changes in surrogate outcomes can be translated into clinical outcomes using a Monte Carlo model

Drug-drug Interactions with Warfarin: A Systematic Review and Meta-analysis

AIM

The objective of this paper is to systematically review the literature on drug-drug interactions with warfarin, with a focus on patient-important clinical outcomes.

METHODS

MEDLINE, EMBASE, and the International Pharmaceutical Abstract (IPA) databases were searched from January 2004 to August 2019. We included studies describing drug-drug interactions between warfarin and other drugs. Screening and data extraction were conducted independently and in duplicate. We synthesized pooled odds ratios (OR) with 95% confidence intervals (CIs), comparing warfarin plus another medication to warfarin alone. We assessed the risk of bias at the study level and evaluated the overall certainty of evidence using GRADE.

RESULTS

Of 42,013 citations identified, a total of 72 studies reporting on 3,735,775 patients were considered eligible, including 11 randomized clinical trials and 61 observational studies. Increased risk of clinically relevant bleeding when added to warfarin therapy was observed for antiplatelet (AP) regimens (OR=1.74; 95% CI 1.56, 1.94), many antimicrobials (OR=1.63; 95% CI 1.45, 1.83), NSAIDs including COX-2 NSAIDs (OR=1.83; 95% CI 1.29, 2.59), SSRIs (OR=1.62; 95% CI 1.42, 1.85), mirtazapine (OR=1.75; 95% CI 1.30, 2.36), loop diuretics (OR=1.92; 95% CI 1.29, 2.86), and others. We found a protective effect of proton pump inhibitors (PPIs) against warfarin-related gastrointestinal (GI) bleedings (OR=0.69; 95% CI 0.64, 0.73). No significant effect on thromboembolic events or mortality of any drug group used with warfarin was found, including single or dual AP regimens.

CONCLUSIONS

This review found low to moderate certainty evidence supporting the interaction between warfarin and a small group of medications, which result in increased bleeding risk. PPIs are associated with reduced hospitalization for upper GI bleeding for patients taking warfarin. Further studies are required to better understand drug-drug interactions leading to thromboembolic outcomes or death.

Meta-Analysis of Genotype-Guided Versus Standard Dosing of Vitamin K Antagonists

Vitamin K antagonist (VKA) is a commonly prescribed anticoagulant with a narrow therapeutic window. Genetic polymorphisms account for high VKA dosage variability. Hence, we performed an updated meta-analysis of all randomized clinical trials (RCTs) comparing genotype-guided VKA versus standard dosing algorithms. We conducted a systematic search of electronic databases from inception to October 2017 for all RCTs. The primary outcome was the percentage of time in therapeutic range (TTR). Secondary outcomes were international normalized ratio >4, major and all bleeding events, thromboembolism, adverse and serious adverse events, and all-cause mortality. We calculated the weighted mean difference for the primary outcome and risk ratio (RR) for secondary outcomes using a random-effect model. We included 20 RCTs and analyzed a total of 5,980 adult patients. Our pooled analysis showed greater improvement in TTR for the genotype-guided group in comparison with the standard group (mean difference 3.41%, 95% confidence interval [CI] 0.71 to 6.10, p = 0.01). In addition, there were significant reductions in major and all bleeding events ((RR 0.35, 95% CI 0.20 to 0.63, p = 0.0004) and (RR 0.79, 95% CI 0.66 to 0.95, p = 0.01), respectively). However, there were no significant differences between the groups for international normalized ratio >4 (RR 0.89, 95% CI 0.80 to 1.00, p = 0.06), thromboembolism (RR 0.81, 95% CI 0.56 to 1.17, p = 0.25), serious adverse events (RR 0.79, 95% CI 0.61 to 1.03, p = 0.08), any adverse events (RR 0.94, 95% CI 0.88 to 1.01, p = 0.07), or all-cause mortality (RR 0.73, 95% CI 0.32 to 1.66, p = 0.46). In conclusion, genotype-guided VKA dosing can improve the TTR and reduce the risk for bleeding episodes, in comparison with standard dosing algorithms.

Genotype-guided versus standard vitamin K antagonist dosing algorithms in patients initiating anticoagulation

Variability in vitamin K antagonist (VKA) dosing is partially explained by genetic polymorphisms. We performed a meta-analysis to determine whether genotype-guided VKA dosing algorithms decrease a composite of death, thromboembolic events and major bleeding (pri-mary outcome) and improve time in therapeutic range (TTR). We searched MEDLINE, EMBASE, CENTRAL, trial registries and conference proceedings for randomised trials comparing genotype-guided and standard (non genotype-guided) VKA dosing algorithms in adults initiating anticoagulation. Data were pooled using a random effects model. Of the 12 included studies (3,217 patients), six reported all components of the primary outcome of mortality, thromboembolic events and major bleeding (2,223 patients, 87 events). Our meta-analysis found no significant difference between groups for the primary outcome (relative risk 0.85, 95 % confidence interval [CI] 0.54–1.34; heterogeneity X2=4.46, p=0.35, I2=10 %). Based on 10 studies (2,767 patients), TTR was significantly higher in the genotype-guided group (mean difference (MD) 4.31 %; 95 % CI 0.35, 8.26; heterogeneity X2=43.31, p< 0.001, I2=79 %). Pre-specified exploratory analyses demonstrated that TTR was significantly higher when geno-type-guided dosing was compared with fixed VKA dosing (6 trials, 997 patients: MD 8.41 %; 95 % CI 3.50,13.31; heterogeneity X2=15.18, p=0.01, I2=67 %) but not when compared with clinical algorithm-guided dosing (4 trials, 1,770 patients: MD –0.29 %; 95 % CI –2.48,1.90; heterogeneity X2=1.53, p=0.68, I2=0 %; p for interaction=0.002). In conclusion, genotype-guided compared with standard VKA dosing algorithms were not found to decrease a composite of death, thromboembolism and major bleeding, but did result in improved TTR. An improvement in TTR was observed in comparison with fixed VKA dosing algorithms, but not with clinical algorithms.

Quality of oral anticoagulation with phenprocoumon in regular medical care and its potential for improvement in a telemedicine-based coagulation service--results from the prospective, multi-center, observational cohort study thrombEVAL

BACKGROUND

The majority of studies on quality of oral anticoagulation (OAC) therapy with vitamin K-antagonists are performed with short-acting warfarin. Data on long-acting phenprocoumon, which is frequently used in Europe for OAC therapy and is considered to enable more stable therapy adjustment, are scarce. In this study, we aimed to assess quality of OAC therapy with phenprocoumon in regular medical care and to evaluate its potential for optimization in a telemedicine-based coagulation service.

METHODS

In the prospective observational cohort study program thrombEVAL we investigated 2,011 patients from regular medical care in a multi-center cohort study and 760 patients from a telemedicine-based coagulation service in a single-center cohort study. Data were obtained from self-reported data, computer-assisted personal interviews, and laboratory measurements according to standard operating procedures with detailed quality control. Time in therapeutic range (TTR) was calculated by linear interpolation method to assess quality of OAC therapy. Study monitoring was carried out by an independent institution.

RESULTS

Overall, 15,377 treatment years and 48,955 international normalized ratio (INR) measurements were analyzed. Quality of anticoagulation, as measured by median TTR, was 66.3% (interquartile range (IQR) 47.8/81.9) in regular medical care and 75.5% (IQR 64.2/84.4) in the coagulation service (P <0.001). Stable anticoagulation control within therapeutic range was achieved in 63.8% of patients in regular medical care with TTR at 72.1% (IQR 58.3/84.7) as compared to 96.4% of patients in the coagulation service with TTR at 76.2% [(IQR 65.6/84.7); P = 0.001)]. Prospective follow-up of coagulation service patients with pretreatment in regular medical care showed an improvement of the TTR from 66.2% (IQR 49.0/83.6) to 74.5% (IQR 62.9/84.2; P <0.0001) in the coagulation service. Treatment in the coagulation service contributed to an optimization of the profile of time outside therapeutic range, a 2.2-fold increase of stabile INR adjustment and a significant decrease in TTR variability by 36% (P <0.001).

CONCLUSIONS

Quality of anticoagulation with phenprocoumon was comparably high in this real-world sample of regular medical care. Treatment in a telemedicine-based coagulation service substantially improved quality of OAC therapy with regard to TTR level, frequency of stable anticoagulation control, and TTR variability.

TRIAL REGISTRATION

ClinicalTrials.gov, unique identifier NCT01809015, March 8, 2013.

A Bayesian prediction model between a biomarker and the clinical endpoint for dichotomous variables

Background

Early biomarkers are helpful for predicting clinical endpoints and for evaluating efficacy in clinical trials even if the biomarker cannot replace clinical outcome as a surrogate. The building and evaluation of an association model between biomarkers and clinical outcomes are two equally important concerns regarding the prediction of clinical outcome. This paper is to address both issues in a Bayesian framework.

Methods

A Bayesian meta-analytic approach is proposed to build a prediction model between the biomarker and clinical endpoint for dichotomous variables. Compared with other Bayesian methods, the proposed model only requires trial-level summary data of historical trials in model building. By using extensive simulations, we evaluate the link function and the application condition of the proposed Bayesian model under scenario (i) equal positive predictive value (PPV) and negative predictive value (NPV) and (ii) higher NPV and lower PPV. In the simulations, the patient-level data is generated to evaluate the meta-analytic model. PPV and NPV are employed to describe the patient-level relationship between the biomarker and the clinical outcome. The minimum number of historical trials to be included in building the model is also considered.

Results

It is seen from the simulations that the logit link function performs better than the odds and cloglog functions under both scenarios. PPV/NPV ≥0.5 for equal PPV and NPV, and PPV + NPV ≥1 for higher NPV and lower PPV are proposed in order to predict clinical outcome accurately and precisely when the proposed model is considered. Twenty historical trials are required to be included in model building when PPV and NPV are equal. For unequal PPV and NPV, the minimum number of historical trials for model building is proposed to be five. A hypothetical example shows an application of the proposed model in global drug development.

Conclusions

The proposed Bayesian model is able to predict well the clinical endpoint from the observed biomarker data for dichotomous variables as long as the conditions are satisfied. It could be applied in drug development. But the practical problems in applications have to be studied in further research.

Electronic supplementary material

The online version of this article (doi:10.1186/1745-6215-15-500) contains supplementary material, which is available to authorized users.