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Background: The drug reaction with eosinophilia and systemic symptoms (DRESS) syndrome represents a severe form of drug hypersensitivity reaction characterized by significant morbidity, mortality, and long-term sequelae, coupled with limited therapeutic avenues. Accurate identification of the causative drug(s) is paramount for acute management, exploration of safe therapeutic alternatives, and prevention of future occurrences. However, the absence of a standardized diagnostic test and a specific causality algorithm tailored to DRESS poses a significant challenge in its clinical management. Methods: We conducted a retrospective case-control study involving 37 DRESS patients to validate a novel causality algorithm, the ALDRESS, designed explicitly for this syndrome, comparing it against the current standard algorithm, SEFV. Results: The ALDRESS algorithm showcased superior performance, exhibiting an 85.7% sensitivity and 93% specificity with comparable negative predictive values (80.6% vs. 97%). Notably, the ALDRESS algorithm yielded a substantially higher positive predictive value (75%) compared to SEFV (51.40%), achieving an overall accuracy rate of 92%. Conclusions: Our findings underscore the efficacy of the ALDRESS algorithm in accurately attributing causality to drugs implicated in DRESS syndrome. However, further validation studies involving larger, diverse cohorts are warranted to consolidate its clinical utility and broaden its applicability. This study lays the groundwork for a refined causality assessment tool, promising advancements in the diagnosis and management of DRESS syndrome.
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The field of pharmacogenetics (PGx) holds great promise in advancing personalized medicine by adapting treatments based on individual genetic profiles. Despite its benefits, there are still economic, ethical and institutional barriers that hinder its implementation in our healthcare environment. A retrospective analysis approach of anonymized data sourced from electronic health records was performed, encompassing a diverse patient population and evaluating key parameters such as prescribing patterns and test results, to assess the impact of pharmacogenetic testing. A head-to-head comparison with previously published activity results within the same pharmacogenetic laboratory was also conducted to contrast the progress made after 10 years. The analysis revealed significant utilization of pharmacogenetic testing in daily clinical practice, with 1,145 pharmacogenetic tests performed over a 1-year period and showing a 35% growth rate increase over time. Of the 17 different medical departments that sought PGx tests, the Oncology department accounted for the highest number, representing 58.47% of all genotyped patients. A total of 1,000 PGx tests were requested for individuals susceptible to receive a dose modification based on genotype, and 76 individuals received a genotype-guided dose adjustment. This study presents a comprehensive descriptive analysis of real-world data obtained from a public tertiary hospital laboratory specialized in pharmacogenetic testing, and presents data that strongly endorse the integration of pharmacogenetic testing into everyday clinical practice.
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Background: The Roussel Uclaf Causality Assessment Method (RUCAM) is a validated tool for assessing causality in cases of suspected drug-induced liver injury (DILI). However, RUCAM cannot discriminate between concomitant hepatotoxic drugs with the same temporal sequence. Objective: To analyse the utility of the lymphocyte transformation test (LTT) for assisting updated RUCAM in 45 patients and 40 controls with a clinical diagnosis of DILI. Methods: Suspected DILI cases were detected through the Prospective Pharmacovigilance Program from Laboratory Signals in Hospital (PPLSH) or by consultations. The controls completed the drug therapy with no adverse reactions during the study period. A receiver operating characteristics (ROC) curve analysis was performed to calculate the optimal cut-off value for the stimulation index (SI), corresponding to the largest sum for the specificity and sensitivity values of LTT for true DILI cases. Results: Out of 45 patients diagnosed with DILI, 42 cases were detected by the PPLSH, two cases by consultation and one case by both methods. Most DILI cases (64.4%) arose during hospitalization. According to the biochemical parameters, 24 cases (53.3%) had the hepatocellular phenotype, 14 (31.1%) had the cholestatic phenotype, and 7 cases (15.6%) had the mixed phenotype. Considering the severity criteria, 7 (15.5%) cases were classified as moderate DILI, and 4 (8.9%) were severe DILI; there were no fatal cases. A total of 149 drugs (median/case, 3; IQR, 2-5) were suspected to be involved in the DILI cases (RUCAM score ≥3). In 8 cases, only one drug was suspected, and polypharmacy (≥5 drugs) was identified in 29% of the cases. Of all DILI cases, 46 (30.9%) of the 149 suspected drugs produced positive LTT results, and the LTT was positive in 34 (75.5%) of the 45 patients. No exposed controls produced positive LTT results. The optimal cut-off of 1.95 for the SI was obtained with a sensitivity of 77% and specificity of 100% (area under the curve, 0.91; 95% asymptotic confidence interval 0.84-0.97; p < 0.001). The sensitivity of the hepatocellular phenotype was 92%. Conclusion: Our results demonstrate that LTT is an add on strengthening causality in cases of suspected idiosyncratic DILI, especially for patients with several suspected drugs and a hepatocellular phenotype.
