Predictors and patterns of empirical antibiotic therapy and associated outcomes in COVID-19 patients: a retrospective study in a tertiary care facility in South India.

BACKGROUND: The coronavirus disease (COVID-19) led to a global health crisis. Inappropriate use of antibiotics in COVID-19 patients has been a concern, leading to antimicrobial resistance. This study evaluated the patterns and predictors of empirical antibiotic therapy in COVID-19 patients and associated outcomes. METHODS: A hospital-based retrospective study was conducted with 525 patients admitted to Kasturba Hospital, Manipal, India, with moderate and severe COVID-19 from 1 March to 1 August 2021. They were divided based on empirical therapy, and predictors of antibiotic usage were assessed by logistic regression. RESULTS: Four hundred and eighty (91.4%) COVID-19 patients received at least one course of antibiotics, with 440 (83.8%) initiating empirical therapy. Patients with severe COVID-19 manifestations were more likely to be prescribed empirical antibiotics. Multivariable analysis showed that patients initiated on empirical antibiotics had significantly elevated levels of procalcitonin [OR: 3.91 (95% CI: 1.66-9.16) (p = 0.001)], invasive ventilation [OR: 3.93 (95% CI: 1.70-9.09) (p = 0.001)], shortness of breath [OR: 2.25 (95% CI: 1.30-3.89) (p = 0.003)] and higher CRP levels [OR: 1.01 (95% CI: 1.00-1.01) (p = 0.005)]. Most antibiotics (65.9%) were prescribed from the 'Watch' group, the highest being ceftriaxone. Only 23.8% of the patients had microbiologically confirmed infections. CONCLUSION: The study identified predictors for initiating empirical antibacterial therapy in our setting.

Bioinformatics-guided disproportionality analysis of sevoflurane-induced nephrogenic diabetes insipidus using the FDA Adverse Event Reporting System database.

AIMS: Sevoflurane is an ether-based inhalational anaesthetic that induces and maintains general anaesthesia. Our study aimed to detect sevoflurane-induced nephrogenic diabetes insipidus using data mining algorithms (DMAs) and molecular docking. The FAERS database was analysed using OpenVigil 2.1 for disproportionality analysis. METHODS: We analysed FAERS data from 2004 to 2022 to determine the incidence of nephrogenic diabetes insipidus associated with sevoflurane. Reporting odds ratios (RORs) and proportional reporting ratios (PRRs) with 95% confidence intervals were calculated. We also used molecular docking with AutoDock Vina to examine sevoflurane's binding affinity to relevant receptors. RESULTS: A total of 554 nephrogenic diabetes insipidus cases were reported in FAERS, of which 2.5% (14 cases) were associated with sevoflurane. Positive signals were observed for sevoflurane with ROR of 76.012 (95% CI: 44.67-129.35) and PRR of 75.72 (χ2 : 934.688). Of the 14 cases, 50% required hospitalization, 14% resulted in death, and the remaining cases were categorized as other outcomes. Molecular docking analysis showed that sevoflurane exhibited high binding affinity towards AQP2 (4NEF) and AVPR2 (6U1N) with docking scores of -4.9 and -5.3, respectively. CONCLUSIONS: Sevoflurane use is significantly associated with the incidence of nephrogenic diabetes insipidus. Healthcare professionals should be cautious when using this medication and report any adverse events to regulatory agencies. Further research is needed to validate these findings and identify risk factors while performing statistical adjustments to prevent false-positives. Clinical monitoring is crucial to validate potential adverse effects of sevoflurane.

Purine antimetabolites associated Pneumocystis jirovecii pneumonia.

PURPOSE: To detect the possible safety signal of purine antimetabolites associated with Pneumocystis jirovecii pneumonia through disproportionality analysis in the FDA Adverse Event Reporting System (FAERS) Database. METHODS: A case/non-case retrospective disproportionality analysis was performed in the publicly available FAERS database using AERSmine (2004Q1-2021Q3). Four models were developed to explore the signal strength of PAs among different populations with possible confounding factors. Reporting odds ratio (ROR) and Proportional reporting ratio (PRR) was used as the data mining algorithm for the analysis. A value of ROR-1.96SE > 1 and PRR ≥ 2 with an associated X2 value of 4 or more was considered the threshold for a signal. RESULTS: A total of 7073 reports associated with Pneumocystis jirovecii pneumonia were present in the database, of which 899 reports were associated with purine antimetabolites. A crude signal strength of ROR 15.76(14.70-16.91) was obtained for purine antimetabolites associated PJP, with the highest signal strength reported with fludarabine and thioguanine [ROR 19.63(17.42-22.13); 19.45(13.21-28.63)]. Stratifying the cases based on autoimmune disorders and the cancer population revealed an ROR of 3.33(2.46-4.50) and 2.93(2.26-3.79) respectively. The highest risk of PJP with use of PAs was observed amongst children with a higher risk of nearly 2 times than the adult population [ROR 11.57(9.16-14.62)]. CONCLUSIONS: Our study provided evidence on the occurrence of PJP with the use of purine antimetabolites among the autoimmune and cancer population. We identified signals for PJP with azathioprine, mercaptopurine, thioguanine, cladribine, fludarabine, and clofarabine. More research with a superior epidemiological study design of a defined population is required to validate these findings.

Pantoprazole associated dyspepsia hypocalcemia and hyponatremia: A disproportionality analysis in FDA adverse event reporting system (FAERS) database.

BACKGROUND AND STUDY AIM: The study was designed to detect novel Adverse Events (AEs) of pantoprazole by disproportionality analysis in the FDA (Food and Drug Administration) database of Adverse Event Reporting System (FAERS) using Data Mining Algorithms (DMAs). Pantoprazole, the most commonly over-utilized Over The Counter (OTC) medication, was selected to assess any short-term or long-term AEs. The study aimed to analyze the novel adverse events of pantoprazole using the FAERS database. MATERIALS AND METHODS: A retrospective case/non-case disproportionality analysis was performed in the FAERS database. This study was based on AEs reported to FAERS from 2006Q1-2021Q3. Openvigil 2.1 was used for data extraction. Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), and Information Component (IC) were applied to measure the disproportionality in reporting. A value of ROR-1.96SE > 1, PRR ≥ 2, and IC-2SD > 0 were considered as the threshold for a positive signal. RESULTS: A total of 1050 reports of dyspepsia, 7248 reports of hypocalcemia and 995 reports of hyponatremia were identified. A potential positive signal for dyspepsia (ROR-1.96SE = 2.231, PRR = 2.359, IC-2SD = 1.13), hypocalcemia (4.961, 5.45, 2.23) and hyponatremia (3.948, 4.179, 1.92) were identified for pantoprazole. CONCLUSION: Data mining in the FAERS database produced three potential signals associated with pantoprazole. As a result, further clinical surveillance is needed to quantify and validate potential hazards associated with pantoprazole-related adverse events.

Drugs-associated with red man syndrome: An integrative approach using disproportionality analysis and Pharmip.

WHAT IS KNOWN AND OBJECTIVE: Red man syndrome (RMS) is a non-IgE-mediated anaphylactoid adverse event frequently witnessed after a rapid infusion of vancomycin. This study aims to unravel drugs and associated off-label targets that induce RMS by exploiting FDA Adverse Event Reporting System (FAERS) and Pharmacovigilance/Pharmacogenomics Insilico Pipeline (PHARMIP). METHODS: The case/non-case retrospective observational study was conducted in the FAERS database. Reporting odds ratio (ROR) and proportional reporting ratio (PRR) data mining algorithms were used to evaluate the strength of the signal. The off-label targets of the drugs with potential signals were obtained using online servers by applying a similarity ensemble approach and a reverse pharmacophore database, which was further validated by molecular docking studies. RESULTS AND DISCUSSION: Oritavancin exhibited a strong positive signal (PRR:1185.20 and ROR:1256), which suggests a higher risk for causing RMS. The literature search revealed the involvement of the MRGPRX2 gene in the development of RMS. PHARMIP study unearthed Carbonic anhydrase II (CA2) as the common off-label target among the drugs causing RMS. The results obtained from molecular docking studies reinforced the findings as mentioned earlier, wherein the highest docking score was disinterred for oritavancin (-9.4 for MRGPRX2 and - 8.7 for CA2). WHAT IS NEW AND CONCLUSION: Many antibiotics and other classes of medications have been discovered in the quest for drugs that may induce RMS, although a causal relationship could not be established. The implication of MRGPX2 and CA2 in the initial stages of pathogenesis necessitates the development of inhibitors that could be used as potential therapeutic agents against RMS.

Existence of Notoriety Bias in FDA Adverse Event Reporting System Database and Its Impact on Signal Strength.

Background: Notoriety bias is defined as "a selection bias in which a case has a greater chance of being reported if the subject is exposed to the studied factor known to cause, thought to cause, or likely to cause the event of interest." This study aimed to determine the existence of notoriety bias in the FDA Adverse Event Reporting System (FAERS) database and estimate the impact of potential notoriety bias induced by safety alerts on signal estimation using disproportionality analysis. Methods: Publicly available FAERS data were downloaded and used for analysis. Thirty-one drugs which had label change/safety alert issued by FDA from 2009 to 2013 were considered. These drugs were reviewed 4 quarters before and after the safety alert notification for the existence of notoriety bias. The impact of notoriety bias induced by safety alerts was analyzed by comparing the signal strength using reporting odds ratio (ROR) and proportional reporting ratio (PRR), 2 years before and after the safety alert. Wilcoxon signed rank test was used to determine whether there were a statistically significant difference before and after the safety alert. Results: There was increased reporting for 11 drugs after the safety alert/label change by the FDA. The reporting of 20 drugs decreased or remained unchanged after the safety alert/label change by the FDA. Wilcoxon signed rank test showed that there is no statistically significant difference with respect to the number of reports before and after the safety alert (P = .330, Z = -0.974). Fourteen (45.16%) drugs had an increase in ROR, while 17 (54.83%) drugs had a decrease in ROR after safety alert issued by FDA (P = .953, Z = -0.059). Fourteen (45.16%) drugs had an increase in PRR, while 17 (54.83%) drugs had a decrease in PRR after safety alert issued by the FDA (P = .914, Z = -0.108). Conclusion: Although few FDA safety alert/warnings had a strong and immediate impact, many had no impact on reporting of AE and signal strength. This study found that overreporting due to notoriety bias does not exist in the FAERS database and the overall disproportionality in signal estimates is not altered by the safety alert.

Assessment of sleep quality and its predictors among newly diagnosed psychiatric patients.

OBJECTIVES: Poor sleep is a vital symptom observed in many psychiatric conditions and is the most neglected and underdiagnosed. The current study aims at assessment of sleep quality among psychiatric patients using the Pittsburgh Sleep Quality Index (PSQI) scale and to identify the predictors of sleep quality. METHODS: A hospital-based cross-sectional observational study conducted in the Psychiatry department with a sample size of 256 patients for six months. PSQI scale was used to assess sleep quality and multiple logistic regression was used (to identify) the predictors for poor sleep quality. RESULTS: The mean age of the study population was 37.95 ± 14.11 years, with 148 (58%) male study participants. 192 (75%) of the study population had poor sleep quality with respect to PSQI scale with a mean score of 9.05 ± 4.65 that was well above the expected range (0-5) suggestive of compromised quality of sleep (p=0.001). Poor sleep satisfaction, waking up after the sleep onset, anorexia, day time drowsiness and at least one completely sleepless night in the past one week of admission were identified as good predictors for poor sleep quality. CONCLUSIONS: Our study addresses the importance of assessing sleep quality regardless of the psychiatric conditions. We recommend screening patients if they have Poor sleep satisfaction, waking up after the sleep onset, anorexia, day time drowsiness or at least one completely sleepless night in the past one week of admission predictors for comorbid sleep disorders.

Finding Early Improvement Threshold to Predict Response After 8 Weeks of Treatment Using Risperidone in First-Episode Psychosis.

PURPOSE/BACKGROUND: The study aims to assess whether the early response can predict the outcome at the endpoint for the treatment of first-episode psychosis with risperidone and identify the relationship between initial symptom reduction and late response. METHODS/PROCEDURES: A prospective observational study with 4 points follow-up (weeks 2, 3, 4, and 8) was conducted in 48 adult first-episode psychosis patients. Symptoms were quantified by the Positive and Negative Syndrome Scale (PANSS) score. The initial recommended dose was 2 mg of risperidone once daily before sleep. The PANSS score on day 1 (before initiation of drug therapy) was considered as the baseline score. Treatment responses were considered as a reduction of more than 20%, 25%, 30% and 50% from the baseline score on first, second, third, and final follow-up, respectively. Receiver operating characteristic curves were generated for predicting response at the endpoint. FINDINGS/RESULTS: Thirty-one (65%) patients achieved more than 50% reduction (responders) in PANSS score. The mean total PANSS score of the study population after 8 weeks of therapy was found to be 49.77 (95% confidence interval, 46.10-53.43). The mean percentage reduction in PANSS score after 8 weeks of therapy was found to be 52.92% (95% confidence interval, 48.83-57.01). Week 2 response can be taken as the early response (area under the curve = 81.9, P < 0.001). However, the more accurate prediction was possible with week 4 response (area under the curve = 88.7%, P < 0.001). IMPLICATIONS/CONCLUSIONS: Our study suggests that patients with an early response at week 2 are likely to achieve positive response after 8 weeks.

Vemurafenib Induced Drug Reaction with Eosinophilia and Systemic Symptoms (DRESS): A Disproportionality Analysis in FAERS Database.

BACKGROUND: Signal strength for any drug-event combination can be determined using disproportionality analysis. Vemurafenib is a BRAF inhibitor approved by the US Food and Drug Administration (FDA) in 2011 for the treatment of metastatic melanoma. This study aims to identify the signal strength of Drug Reaction with Eosinophilia and Systemic Symptoms (DRESS) associated with vemurafenib using disproportionality analysis in FDA database of Adverse Event Reporting System (FAERS). METHODS: Data were obtained from the public release of data in FAERS. The case/non-case method was adopted for the analysis of the association between vemurafenib use and DRESS. The data mining algorithm used for the analysis was the Reporting Odds Ratio (ROR) and Proportional Reporting Ratio (PRR). A value of ROR-1.96SE>1, PRR≥2 was considered as positive signal strength. RESULTS: A total of 7,171 reports for DRESS have been reported in the FDA database. Amongst which, 125 reports were associated with vemurafenib. A cumulative ROR of 17.72 (95% CI 14.83; 21.18) and PRR of 17.46 (95% CI 14.65; 20.81) were observed. Combination treatment of vemurafenib with cobimetinib had a higher number of reports (100) with ROR of 103.42 (84.13- 127.14) and PRR of 94.52 (78.26- 114.15). Four deaths were reported and the non-death serious reports included hospitalization, life-threatening, disability, and other serious events with 61, 11, 2 and 39 reports, respectively. CONCLUSION: Positive signal strength was observed for vemurafenib associated DRESS. The signal strength was higher for vemurafenib in combination with cobimetinib than vemurafenib alone. Health care professionals should be cautious about encountering serious adverse events and should report such events to the regulatory authorities.

Evaluation of prescribing practices and drug-related problems in chronic kidney disease patients: A cross-sectional study.

AIM: The primary intent of the study is to analyze the prescribing pattern and to identify the various drug-related problems (DRPs) associated with the therapy in chronic kidney disease (CKD) patients. SUBJECTS AND METHODS: A prospective observational study was conducted in 160 patients diagnosed with any stages of CKD. The prescribing pattern was studied and DRPs were identified, reported, and categorized as per the Pharmaceutical Care Network Europe classification V 5.01. The association between categorical variables was analyzed using the Chi-square test. The predictors of DRPs were identified using binary logistic regression analysis. RESULTS: The mean age of the study population was 50.08 ± 15.32 years with male predominance (71%). The average number of drugs per prescription was found to be 9.16 ± 3.01. The most prescribed drug category was antihypertensives and the most commonly prescribed drugs were diuretics. A total of 337 DRPs were identified, out of which the most common DRP was drug interactions (60%), followed by frequency errors (11.6%). Logistic regression analysis identified comorbidities more than three (odds ratio 2.09), antihypertensives more than two (odds ratio 1.9), alcoholism (odds ratio 1.5), and polypharmacy (odds ratio 1.2) as the predictors of DRPs even though they were not statistically significant at P = 0.01. CONCLUSION: DRPs increase the risk of deterioration of the disease state and increase the length of hospital stay. Identification and resolving of the DRPs will lead to better patient care and proper treatment. Early identification and modification of the above-mentioned predictors could possibly prevent/reduce DRPs.

Early prediction of clinical response in first episode schizophrenia (FES) patients receiving olanzapine.

Background: At present, schizophrenia guidelines recommend waiting for 8 weeks before considering a patient as non-responder. This study aims to detect the optimal early response threshold that best predict the final outcome of olanzapine.Methods: The study was conducted for 8-week, four points follow up (week 2,3,4, and 8) prospective observational study. A reduction of 20, 25, 30% in Positive and Negative Syndrome Scale (PANSS) score from the base line at week 2,3, and 4 respectively were considered as early response. A reduction of 50% at week 8 was considered as responders. Receiver Operating Characteristics (ROC) curves were performed to detect the optimal threshold.Results: Mean total baseline PANSS score was 106.66(95% CI; 100.4, 112.9). Week 2 (AUC = 50.5%, p > 0.964) and week 3 (AUC = 64.9, p > 0.13) responses failed to predict the 8th week response. Week 4 response (AUC = 92%, p < 0.001) can be taken for the prediction of 8th week response (specificity = 72%, sensitivity = 100%, Positive Predictive Value = 61.1%, Negative Predictive Value = 100% and Optimum Early Response (OER) = 29.4%). 25 patients (69%) achieved more than 50% reduction (responders) in PANSS score after 8 weeks of treatment.Conclusions: Our study suggests that patients with early response at week 4 are likely to achieve positive response after 8 weeks. This may help in appropriate clinical decision making for early non-responders.Key PointsThe early response can forecast the outcome at the endpoint for the treatment of FESA reduction of baseline PANSS score by 30% or more after four weeks are likely to have remission after week 8 with olanzapine therapy.

Aromatase inhibitors associated osteonecrosis of jaw: signal refining to identify pseudo safety signals.

Background Signal generation through data mining algorithms is an innovative and emerging field in pharmacovigilance. Early detection of safety signals is important for public health safety. However, the possibility of generating pseudo signals should not be overlooked. Objective Our study aimed to identify potential signals of aromatase inhibitors associated Osteonecrosis of Jaw and assess the possibilities of the safety signal to be a pseudo signal/false positive in FDA Adverse Event Reporting System (FAERS). Setting Spontaneously reported data in FAERS database. Methods Data for this study were obtained from the public release of data in FAERS. OpenVigil, a pharmacovigilance analytical tool was used to access FAERS data. Reporting Odds Ratio (ROR) was used to assess the relation between the drug and adverse event. A value of ROR-1.96SE > 1, (SE-standard error) was considered positive. Main outcome measure Signal strength. Results FAERS database had a total of 15,178 reports for Osteonecrosis of Jaw. Amongst which 617 reports were associated with aromatase inhibitors. Signal strength ROR (lower bound of the 95% CI) for letrozole, anastrozole and exemestane associated Osteonecrosis of Jaw without any background correction was 8.34, 6.64 and 15.14 respectively. Upon removing the reports of concomitantly administered drugs (bisphosphonates and denosumab), signal strength drastically decreased to 0.03, 0.36 and 0.47 for letrozole, anastrozole and exemestane respectively. The signal strength of bisphosphonates and denosumab associated Osteonecrosis of Jaw was not changed significantly upon removal of aromatase inhibitors. Conclusion Our study concluded that the signal generated for aromatase inhibitors associated Osteonecrosis of Jaw in FAERS database can be false positive. Careful background corrections with identification of those risk factors are imperative to exclude false positive results.

Postlicensure surveillance of human papillomavirus vaccine using the Vaccine Adverse Event Reporting System, 2006-2017.

BACKGROUND: The United States Food and Drug Administration (FDA) has licensed three HPV (Human papilloma virus) vaccines. The centers for disease control and prevention (CDC) and advisory committee on immunization practices (ACIP) recommends routine HPV vaccination at age 11 or 12 years. This study aimed to summarize and characterize adverse events following HPV vaccination reported to VAERS database from July 2006 to May 2017. METHODS: A systematic data mining was performed in the VAERS database for reports associated with HPV vaccine. Clinically relevant Vaccine Event Combinations (VEC) were identified in the VAERS database following HPV vaccination. A VEC was considered for analysis only if a minimum of hundred reports were present in database for the given Adverse Event (AE). The data mining algorithm used in this study was reporting odds ratio. A value of ROR-1.96SE >1 was considered as positive signal. RESULTS: VAERS received 49444 reports after receipt of HPV vaccine during the study period. Out of 49444, 2307 unique reactions were identified. A total of 177 death reports and 3526 non death serious reactions were reported to VAERS. ROR showed positive signals for abdominal pain, syncope, dizziness, convulsion, abortion spontaneous, alopecia, amenorrhea, anogenital warts, cervical dysplasia, anaemia, dyskinesia, migrane, blood pressure decreased, fall, head injury, loss of consciousness, pallor, presyncope, seizures. CONCLUSION: The present analysis did not identify any new/unexpected safety concern and was consistent with the safety data from prelicensure trials. Further epidemiological studies are required to systematically validate the data provided by VAERS.

Deprescribing of benzodiazepines and Z-drugs amongst the psychiatric patients of a tertiary care Hospital.

BACKGROUND: In current clinical practice, regardless of the clinical guidelines, BZDs and Z drugs are used beyond the period of indication, resulting in undesirable effects. This study aimed to assess feasibility of deprescribing amongst patients utilizing BZDs and Z drugs inappropriately for longer duration than the prescribed period. The study also analysed the Quality of Sleep (QoS) and Cost Savings incurred amongst deprescribed patients. METHODS: It was a prospective interventional study conducted in IP and OP settings of Psychiatry Department, Bangalore, India. Based on inclusion criteria, 109 patients were recruited for the study for a period of 7 months. Deprescribing was advised to inappropriate BZD and Z-drug users by clinical pharmacist after discussing with the prescribing psychiatrist. The patients were followed-up twice in a month after deprescribing. QoS was assessed by using Pittsburg Sleep Quality Index (PSQI) scale. The total medications cost incurred per patient/month before and after the intervention among both the groups was measured. RESULTS: Post-intervention, 40(30.69%) BZD users were deprescribed i.e, either dose tapered 6(5.5%), completely ceased 27(24.8%) or on si opus sit (SOS) BZDs prescription 7(6.4%). A majority of 44(40.36%) patients continued BZDs according to the algorithm. Clonazepam 35(87.5%) was the most deprescribed BZD. Deprescribing of BZDs showed an association with QoS of patients, p-value (<0.05). A statistically significant cost reduction was observed after deprescribing BZDs, (Z = 5.465, p=<0.001). DISCUSSION: Deprescribing BZDs was associated with decline in its usage; implementing deprescribing practice amongst the inappropriate BZD users is feasible, provides an improved QoS and an economic benefit.

Predictors of adverse drug reactions in geriatric patients: An exploratory study among cancer patients.

OBJECTIVES: The objective of this study was to study the predictors of adverse drug reactions (ADRs) among geriatric patients in the Department of Medical Oncology. METHODS: A hospital-based prospective observational study was carried out among 153 inpatients in the Department of Medical Oncology for 6 months. Patients above 60 years of age with a confirmed history of malignancy were included in the study. The potential risk factors for ADR were defined in relation to the patient and chemotherapeutic regimen and relationship between them was assessed by univariate and multivariate logistic regression analysis. RESULTS: Among 153 patients, 94 (64.43%) experienced ADRs. The mean ADR per patient was 0.88 ± 1.2. The common ADRs found were alopecia (30.18%) and diarrhea (28.68%). Risk estimates revealed that there was a significant association between smokers (odds ratio [OR] = 10.326; 95% confidence interval [CI] 2.345-45.47, P = 0.001), alcoholics (OR = 10.897; 95% CI 2.479-47.902, P = 0.001), increasing age (OR = 2.22; 95% CI 1.698-2.909, P = 0.001), overweight (OR = 16.68; 95% CI 2.179-127.741, P = 0.001), and male participants (OR = 0.143; 95% CI 0.05-0.390 P = 0.001) with the development of ADRs. The risk of carboplatin (OR = 13.359; 95% CI 3.056-58.406 P = 0.001) and 5-fluorouracil (OR = 1.938 95% CI 1.266-2.935 P = 0.001) use and occurrence of ADRs were also found to be high. CONCLUSION: The study findings showed that smoking, alcohol consumption, age more than 70 years, and overweight had a high risk for developing ADRs in geriatric patients who underwent chemotherapy. The independent risk factors identified should be targeted for preventive measures to improve anticancer agent prescription and reduce the risk of ADRs.

Novel Adverse Events of Iloperidone: A Disproportionality Analysis in US Food and Drug Administration Adverse Event Reporting System (FAERS) Database.

BACKGROUND: The signal is defined as "reported information on a possible causal relationship between an adverse event and a drug, of which the relationship is unknown or incompletely documented previously". OBJECTIVE: To detect novel adverse events of iloperidone by disproportionality analysis in FDA database of Adverse Event Reporting System (FAERS) using Data Mining Algorithms (DMAs). METHODOLOGY: The US FAERS database consists of 1028 iloperidone associated Drug Event Combinations (DECs) which were reported from 2010 Q1 to 2016 Q3. We consider DECs for disproportionality analysis only if a minimum of ten reports are present in database for the given adverse event and which were not detected earlier (in clinical trials). Two data mining algorithms, namely, Reporting Odds Ratio (ROR) and Information Component (IC) were applied retrospectively in the aforementioned time period. A value of ROR-1.96SE>1 and IC- 2SD>0 were considered as the threshold for positive signal. RESULTS: The mean age of the patients of iloperidone associated events was found to be 44years [95% CI: 36-51], nevertheless age was not mentioned in twenty-one reports. The data mining algorithms exhibited positive signal for akathisia (ROR-1.96SE=43.15, IC-2SD=2.99), dyskinesia (21.24, 3.06), peripheral oedema (6.67,1.08), priapism (425.7,9.09) and sexual dysfunction (26.6-1.5) upon analysis as those were well above the pre-set threshold. CONCLUSION: Iloperidone associated five potential signals were generated by data mining in the FDA AERS database. The result requires an integration of further clinical surveillance for the quantification and validation of possible risks for the adverse events reported of iloperidone.

Safety Profile of Levonorgestrel: A Disproportionality Analysis of Food and Drug Administration Adverse Event Reporting System (Faers) Database.

BACKGROUND: Levonorgestrel is most commonly utilized as an emergency oral contraceptive. Little is known and/or studied about the adverse effects of levonorgestrel, therefore, current investigation was aimed to generate signal for unreported adverse drug reactions of levonorgestrel using disproportionality analysis in food and drug administration adverse events reporting system database. METHODS: In FDA Adverse Events Reporting System (FAERS) database, all adverse event reports for levonorgestrel between January 2006 to June 2015 were identified and disproportionality analysis was conducted for selected adverse events of levonorgestrel using Reporting Odds Ratio, Proportional Reporting Ratio and Information Component with 95% confidence interval. RESULTS: A disproportionality analysis was done for 15 adverse events of levonorgestrel; out of these, signal for 10 adverse events was found and among them menstruation delayed was reported maximum (1791), followed by pregnancy after post-coital contraception (942), breast tenderness (901), metrorrhagia (899), dysmenorrhea (822), menorrhagia (541), nipple disorder (141), breast enlargement (77), ectopic pregnancy (61) and premenstrual syndrome (35). Pregnancy after post-coital contraception showed the highest signal having the Information Component value of 129.2, Reporting Odds Ratio value of 6.51 and Proportional Reporting Ratio value of 6.49. CONCLUSION: In this paper, ten novel AEs were identified that were disproportionately reported with the use of LNG by using data mining techniques. Although a causal relationship cannot be established, the number of cases reported suggests that there might be an association. If confirmed by epidemiologic studies, the findings from this study would have potential implications for the use of LNG and patient management in clinical practice.

Novel adverse events of vortioxetine: A disproportionality analysis in USFDA adverse event reporting system database.

BACKGROUND: Signal detection is one of the most advanced and emerging field in pharmacovigilance. It is a modern method of detecting new reaction (which can be desired or undesired) of a drug. It facilitates early adverse drug reaction detection which enables health professionals to identify adverse events that may not have been identified in pre-marketing clinical trials. Vortioxetine, the first mixed serotonergic antidepressant was initially approved by the US Food and Drug Administration (USFDA) on September 30, 2013 for the treatment of adults with Major Depressive Disorder (MDD). This study was to identify the signal strength for vortioxetine associated ADRs using data mining technique in USFDA Adverse Event Reporting System (AERS) database. METHODOLOGY: Most commonly used three data mining algorithms, Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR) and Information Component (IC) were selected for the study and they were applied retrospectively in USFDA AERS database from 2015Q1 to 2016Q3. A value of ROR-1.96SE >1, PRR≥2, IC- 2SD>0 were considered as the positive signal. RESULT: A study population of 61,22,000 were reported all over the world. Among which 3481 reactions were associated with vortioxetine which comprised of 632 unique events encompassed with 27 clinically relevant reactions. ROR, PRR and IC showed positive signal for weight loss, agitation, anger, ketoacidosis, insomnia and abnormal dreams. CONCLUSION: The present study suggests that vortioxetine may result in these adverse events. Further pharmacoepidemiologic studies are necessary to confirm this conclusion and to improve the precision of the prevalence and/or the risk factors of this ADRs.